diff --git a/collect_env_report.ps1 b/collect_env_report.ps1
new file mode 100644
index 0000000..f45f4a6
--- /dev/null
+++ b/collect_env_report.ps1
@@ -0,0 +1,60 @@
+$ErrorActionPreference = "Stop"
+
+Write-Host "[1/6] Collecting environment info..." -ForegroundColor Cyan
+$report = @()
+$report += "# ETL Manager Environment Report"
+$report += "Timestamp: $(Get-Date -Format 'yyyy-MM-dd HH:mm:ss')"
+$report += ""
+
+Write-Host "[2/6] Resolving python/pip..." -ForegroundColor Cyan
+$report += "## Executables"
+$py = (Get-Command python -ErrorAction SilentlyContinue)
+$pip = (Get-Command pip -ErrorAction SilentlyContinue)
+if ($py) { $report += "python: $($py.Source)" } else { $report += "python: NOT FOUND" }
+if ($pip) { $report += "pip: $($pip.Source)" } else { $report += "pip: NOT FOUND" }
+$report += ""
+
+Write-Host "[3/6] Python details..." -ForegroundColor Cyan
+$report += "## Python info"
+$report += (python -c "import sys, platform; print('version='+sys.version.replace('\n',' ')); print('executable='+sys.executable); print('prefix='+sys.prefix); print('base_prefix='+sys.base_prefix); print('arch='+platform.architecture()[0]); print('platform='+platform.platform())" 2>&1)
+$report += ""
+
+Write-Host "[4/6] pip details..." -ForegroundColor Cyan
+$report += "## pip"
+$report += (python -m pip --version 2>&1)
+$report += ""
+
+Write-Host "[5/6] PySide6 details..." -ForegroundColor Cyan
+$report += "## PySide6"
+$pyside = @'
+try:
+ import PySide6
+ from PySide6 import QtCore
+ print('PySide6='+PySide6.__version__)
+ print('Qt='+QtCore.qVersion())
+ print('PySide6_path='+PySide6.__file__)
+ print('Qt_plugins_path='+QtCore.QLibraryInfo.path(QtCore.QLibraryInfo.PluginsPath))
+except Exception as e:
+ print('PySide6_import_error='+repr(e))
+'@
+$report += ($pyside | python - 2>&1)
+$report += ""
+
+Write-Host "[6/6] Installed packages..." -ForegroundColor Cyan
+$report += "## Installed packages (freeze)"
+$report += (python -m pip list --format=freeze 2>&1)
+
+$reportPath = "D:\env_report_local.txt"
+if (-not (Test-Path "D:\")) {
+  Write-Host "[WARN] D: not found, fallback to current directory." -ForegroundColor Yellow
+  $reportPath = ".\env_report_local.txt"
+}
+$reportDir = Split-Path $reportPath
+if ($reportDir -and -not (Test-Path $reportDir)) {
+  New-Item -ItemType Directory -Path $reportDir -Force | Out-Null
+}
+
+Write-Host "[WRITE] $reportPath" -ForegroundColor Green
+$report -join "`n" | Set-Content -Path $reportPath -Encoding UTF8
+Write-Host "[DONE]" -ForegroundColor Green
+Write-Output $reportPath
diff --git a/env_report_local.txt b/env_report_local.txt
new file mode 100644
index 0000000..8a311dc
--- /dev/null
+++ b/env_report_local.txt
@@ -0,0 +1,121 @@
+# ETL Manager Environment Report
+Timestamp: 2026-01-28 00:56:34
+
+## Executables
+python: C:\ProgramData\miniconda3\python.exe
+pip: C:\ProgramData\miniconda3\Scripts\pip.exe
+
+## Python info
+version=3.13.9 | packaged by Anaconda, Inc. | (main, Oct 21 2025, 19:09:58) [MSC v.1929 64 bit (AMD64)]
+executable=C:\ProgramData\miniconda3\python.exe
+prefix=C:\ProgramData\miniconda3
+base_prefix=C:\ProgramData\miniconda3
+arch=64bit
+platform=Windows-10-10.0.17763-SP0
+
+## pip
+pip 25.3 from C:\ProgramData\miniconda3\Lib\site-packages\pip (python 3.13)
+
+
+## PySide6
+PySide6=6.10.1
+Qt=6.10.1
+PySide6_path=C:\ProgramData\miniconda3\Lib\site-packages\PySide6\__init__.py
+Qt_plugins_path=C:/ProgramData/miniconda3/Lib/site-packages/PySide6/plugins
+
+## Installed packages (freeze)
+altgraph==0.17.5
+anaconda-anon-usage==0.7.4
+annotated-types==0.6.0
+archspec==0.2.5
+beautifulsoup4==4.13.4
+boltons==25.0.0
+brotlicffi==1.1.0.0
+certifi==2025.11.12
+cffi==2.0.0
+chardet==3.0.4
+charset-normalizer==3.4.4
+colorama==0.4.6
+conda==25.9.1
+conda-anaconda-telemetry==0.3.0
+conda-anaconda-tos==0.2.2
+conda-content-trust==0.2.0
+conda-libmamba-solver==25.4.0
+conda-package-handling==2.4.0
+conda_package_streaming==0.12.0
+coverage==7.12.0
+cryptography==46.0.3
+distro==1.9.0
+et_xmlfile==2.0.0
+frozendict==2.4.6
+ftfy==6.3.1
+googletrans==4.0.0rc1
+h11==0.9.0
+h2==3.2.0
+hpack==3.0.0
+hstspreload==2025.1.1
+httpcore==0.9.1
+httpx==0.13.3
+hyperframe==5.2.0
+idna==2.10
+iniconfig==2.3.0
+jsonpatch==1.33
+jsonpointer==3.0.0
+libmambapy==2.3.2
+lxml==6.0.2
+markdown-it-py==4.0.0
+mdurl==0.1.2
+menuinst==2.4.1
+numpy==2.3.2
+openpyxl==3.1.5
+packaging==25.0
+pandas==2.3.1
+pefile==2024.8.26
+pip==25.2
+platformdirs==4.5.0
+pluggy==1.5.0
+psycopg2==2.9.10
+psycopg2-binary==2.9.11
+pyaes==1.6.1
+pyasn1==0.6.1
+pycosat==0.6.6
+pycparser==2.23
+pydantic==2.12.3
+pydantic_core==2.41.4
+Pygments==2.19.2
+pyinstaller==6.18.0
+pyinstaller-hooks-contrib==2025.11
+PySide6==6.10.1
+PySide6_Addons==6.10.1
+PySide6_Essentials==6.10.1
+PySocks==1.7.1
+pytest==9.0.1
+pytest-cov==7.0.0
+python-dateutil==2.9.0.post0
+python-docx==1.2.0
+python-dotenv==1.2.1
+pytz==2025.2
+pywin32-ctypes==0.2.3
+requests==2.32.5
+rfc3986==1.5.0
+rich==14.2.0
+rsa==4.9.1
+ruamel.yaml==0.18.16
+ruamel.yaml.clib==0.2.14
+setuptools==80.9.0
+shiboken6==6.10.1
+six==1.17.0
+sniffio==1.3.1
+soupsieve==2.7
+Telethon==1.40.0
+tqdm==4.67.1
+truststore==0.10.1
+typing_extensions==4.15.0
+typing-inspection==0.4.2
+tzdata==2025.2
+urllib3==2.5.0
+wcwidth==0.2.14
+wheel==0.45.1
+win_inet_pton==1.1.0
+xlsxwriter==3.2.9
+zstandard==0.24.0
diff --git a/etl_billiards/1.zip b/etl_billiards/1.zip
deleted file mode 100644
index 1b03012..0000000
Binary files a/etl_billiards/1.zip and /dev/null differ
diff --git a/etl_billiards/docs/dwd_main_tables_dictionary.md b/etl_billiards/docs/dwd_main_tables_dictionary.md
index ea88118..bce8375 100644
--- a/etl_billiards/docs/dwd_main_tables_dictionary.md
+++ b/etl_billiards/docs/dwd_main_tables_dictionary.md
@@ -104,9 +104,9 @@
 
 | `entry_time` | TIMESTAMPTZ |  |  | 入职时间。 | assistant_accounts_master - entry_time。 | assistant_accounts_master.json - data.assistantInfos - entry_time。 |
 
-| `resign_time` | TIMESTAMPTZ |  |  | 离职日期；使用“远未来日期”作为“未离职”的占位。 | assistant_accounts_master - resign_time。 | assistant_accounts_master.json - data.assistantInfos - resign_time。 |
+| `resign_time` | TIMESTAMPTZ |  |  | 离职日期；使用“远未来日期（大于2200年）”作为“未离职”的占位。 | assistant_accounts_master - resign_time。 | assistant_accounts_master.json - data.assistantInfos - resign_time。 |
 
-| `leave_status` | INTEGER |  |  | 业务状态/类型字段，用于过滤、分类与统计口径区分。 | assistant_accounts_master - leave_status。 | assistant_accounts_master.json - data.assistantInfos - leave_status。 |
+| `leave_status` | INTEGER |  |  | 业务状态/类型字段，是否离职的状态，0在职，1离职。 | assistant_accounts_master - leave_status。 | assistant_accounts_master.json - data.assistantInfos - leave_status。 |
 
 | `assistant_status` | INTEGER |  |  | 账号启用状态：。 | assistant_accounts_master - assistant_status。 | assistant_accounts_master.json - data.assistantInfos - assistant_status。 |
 
diff --git a/etl_billiards/docs/table_2025-12-19/助教_基础课时长排行_2025年10-12月.csv b/etl_billiards/docs/table_2025-12-19/助教_基础课时长排行_2025年10-12月.csv
deleted file mode 100644
index 3032bdc..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教_基础课时长排行_2025年10-12月.csv
+++ /dev/null
@@ -1,73 +0,0 @@
-2025年10-12月 助教基础课时长排行榜
-口径：order_assistant_type=1，时长=income_seconds/3600（小时），按月排名。
-
-月份,排名,助教昵称,指标
-2025-10,1,佳怡,139.55h
-2025-10,2,璇子,120.20h
-2025-10,3,婉婉,90.68h
-2025-10,4,七七,64.70h
-2025-10,5,小柔,63.87h
-2025-10,6,球球,57.45h
-2025-10,7,小敌,55.82h
-2025-10,8,涛涛,50.13h
-2025-10,9,周周,41.33h
-2025-10,10,素素,40.45h
-2025-10,11,乔西,32.60h
-2025-10,12,苏苏,25.15h
-2025-10,13,奈千,23.62h
-2025-10,14,年糕,21.23h
-2025-10,15,欣怡,19.50h
-2025-10,16,饭团,16.00h
-2025-10,17,Amy,11.97h
-2025-10,18,姜姜,6.60h
-2025-10,19,希希,5.02h
-2025-10,20,悦悦,2.30h
-2025-11,1,佳怡,176.25h
-2025-11,2,璇子,147.92h
-2025-11,3,小燕,109.28h
-2025-11,4,Amy,93.53h
-2025-11,5,七七,91.90h
-2025-11,6,小柔,88.65h
-2025-11,7,涛涛,74.40h
-2025-11,8,阿清,73.48h
-2025-11,9,小敌,72.90h
-2025-11,10,周周,71.27h
-2025-11,11,球球,66.50h
-2025-11,12,婉婉,46.03h
-2025-11,13,小侯,42.58h
-2025-11,14,千千,38.88h
-2025-11,15,年糕,35.80h
-2025-11,16,柚子,35.40h
-2025-11,17,素素,35.03h
-2025-11,18,瑶瑶,34.25h
-2025-11,19,奈千,32.83h
-2025-11,20,乔西,30.57h
-2025-11,21,泡芙,21.38h
-2025-11,22,梦梦,19.60h
-2025-11,23,苏苏,13.52h
-2025-11,24,欣怡,10.33h
-2025-11,25,QQ,5.17h
-2025-11,26,西子,1.82h
-2025-11,27,希希,1.58h
-2025-12,1,小燕,159.02h
-2025-12,2,佳怡,109.40h
-2025-12,3,璇子,90.75h
-2025-12,4,七七,77.72h
-2025-12,5,阿清,66.45h
-2025-12,6,周周,60.02h
-2025-12,7,小柔,54.93h
-2025-12,8,小侯,49.57h
-2025-12,9,球球,48.58h
-2025-12,10,涛涛,44.08h
-2025-12,11,苏苏,43.90h
-2025-12,12,千千,38.28h
-2025-12,13,乔西,25.82h
-2025-12,14,年糕,25.62h
-2025-12,15,瑶瑶,19.48h
-2025-12,16,Amy,18.08h
-2025-12,17,婉婉,17.83h
-2025-12,18,梦梦,16.08h
-2025-12,19,素素,9.98h
-2025-12,20,小敌,6.40h
-2025-12,21,奈千,2.58h
-2025-12,22,QQ,1.22h
diff --git a/etl_billiards/docs/table_2025-12-19/助教_基础课时长排行_2025年10-12月.md b/etl_billiards/docs/table_2025-12-19/助教_基础课时长排行_2025年10-12月.md
deleted file mode 100644
index 0cfa257..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教_基础课时长排行_2025年10-12月.md
+++ /dev/null
@@ -1,31 +0,0 @@
-# 2025年10-12月 助教基础课时长排行榜
-## 思考过程
-按月汇总助教基础课时长，并用 dense_rank 做排名。
-
-## 查询说明
-口径：order_assistant_type=1；时长=income_seconds/3600（小时）。
-
-## SQL
-
-### 基础课时长（助教+月份汇总）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0)=0
-    and asl.order_assistant_type=1
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-)
-select
-  assistant,
-  month_key,
-  sum(income_seconds)/3600.0 as hours
-from raw
-where month_key is not null
-group by assistant, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教_客户充值归因排行_2025年10-12月.csv b/etl_billiards/docs/table_2025-12-19/助教_客户充值归因排行_2025年10-12月.csv
deleted file mode 100644
index cc075d5..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教_客户充值归因排行_2025年10-12月.csv
+++ /dev/null
@@ -1,35 +0,0 @@
-2025年10-12月 助教客户充值归因排行榜（全额复制口径）
-口径：充值支付(dwd_payment.relate_type=5)在消费窗口±30分钟内命中且订单有助教，则全额计入助教；多助教/多订单命中会重复计入。
-
-月份,排名,助教昵称,指标
-2025-10,1,璇子,34700.00
-2025-10,2,小柔,31700.00
-2025-10,3,佳怡,27000.00
-2025-10,4,婉婉,24000.00
-2025-10,5,小敌,21000.00
-2025-10,5,涛涛,21000.00
-2025-10,6,奈千,18000.00
-2025-10,7,乔西,17000.00
-2025-10,8,球球,15000.00
-2025-10,9,周周,11000.00
-2025-10,10,年糕,9000.00
-2025-10,11,七七,6000.00
-2025-10,11,素素,6000.00
-2025-10,11,苏苏,6000.00
-2025-10,12,姜姜,4000.00
-2025-10,13,Amy,3000.00
-2025-10,13,悦悦,3000.00
-2025-10,13,欣怡,3000.00
-2025-11,1,佳怡,20000.00
-2025-11,2,小柔,11000.00
-2025-11,3,璇子,10000.00
-2025-11,4,Amy,9000.00
-2025-11,4,周周,9000.00
-2025-11,4,婉婉,9000.00
-2025-11,4,球球,9000.00
-2025-11,5,小敌,8000.00
-2025-11,6,涛涛,5000.00
-2025-11,7,欣怡,4000.00
-2025-11,8,乔西,3000.00
-2025-11,8,柚子,3000.00
-2025-11,9,素素,1000.00
diff --git a/etl_billiards/docs/table_2025-12-19/助教_客户充值归因排行_2025年10-12月.md b/etl_billiards/docs/table_2025-12-19/助教_客户充值归因排行_2025年10-12月.md
deleted file mode 100644
index 1050c8c..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教_客户充值归因排行_2025年10-12月.md
+++ /dev/null
@@ -1,85 +0,0 @@
-# 2025年10-12月 助教客户充值归因排行榜（全额复制口径）
-## 思考过程
-按“消费窗口±30分钟”把充值支付命中到订单，再全额计入订单内助教，并按月排名。
-
-## 查询说明
-注意：多助教/多订单命中按全额复制，充值会重复计入，故助教汇总可能大于门店总额。
-
-## SQL
-
-### 充值归因（助教+月份汇总，全额复制）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select rp.pay_time, ow.order_settle_id, rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select assistant, month_key, sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教_客户流水排行_2025年10-12月.csv b/etl_billiards/docs/table_2025-12-19/助教_客户流水排行_2025年10-12月.csv
deleted file mode 100644
index 204968c..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教_客户流水排行_2025年10-12月.csv
+++ /dev/null
@@ -1,51 +0,0 @@
-2025年10-12月 助教客户流水排行榜（全额复制口径）
-口径：客户流水=台费+助教+商品应付金额按订单归集后，全额计入订单内每位助教；多助教会导致汇总>门店总额。
-
-月份,排名,助教昵称,指标
-2025-10,1,璇子,80804.14
-2025-10,2,婉婉,62187.64
-2025-10,3,小柔,52623.85
-2025-10,4,小敌,44510.29
-2025-10,5,佳怡,44466.03
-2025-10,6,七七,38810.44
-2025-10,7,奈千,38653.58
-2025-10,8,涛涛,35940.84
-2025-10,9,素素,34135.89
-2025-10,10,球球,33923.75
-2025-10,11,周周,27375.91
-2025-10,12,年糕,26289.89
-2025-10,13,乔西,17649.50
-2025-10,14,Amy,15810.80
-2025-10,15,苏苏,11236.84
-2025-10,16,饭团,7955.28
-2025-10,17,欣怡,4824.69
-2025-10,18,希希,3086.34
-2025-10,19,悦悦,2970.96
-2025-10,20,姜姜,2333.94
-2025-11,1,璇子,154486.83
-2025-11,2,Amy,121568.32
-2025-11,3,小柔,110137.94
-2025-11,4,涛涛,88677.55
-2025-11,5,七七,84500.79
-2025-11,6,佳怡,79249.31
-2025-11,7,奈千,68543.08
-2025-11,8,瑶瑶,65924.36
-2025-11,9,小敌,47986.57
-2025-11,10,球球,41907.39
-2025-11,11,梦梦,39768.09
-2025-11,12,小燕,39426.42
-2025-11,13,阿清,37302.04
-2025-11,14,婉婉,33326.32
-2025-11,15,周周,31436.74
-2025-11,16,小侯,27313.21
-2025-11,17,千千,24684.71
-2025-11,18,柚子,23234.98
-2025-11,19,素素,18707.30
-2025-11,20,年糕,15696.08
-2025-11,21,乔西,15536.78
-2025-11,22,苏苏,10254.59
-2025-11,23,泡芙,8323.03
-2025-11,24,欣怡,5157.29
-2025-11,25,QQ,1134.18
-2025-11,26,西子,303.51
-2025-11,27,希希,281.22
diff --git a/etl_billiards/docs/table_2025-12-19/助教_客户流水排行_2025年10-12月.md b/etl_billiards/docs/table_2025-12-19/助教_客户流水排行_2025年10-12月.md
deleted file mode 100644
index 8d68e7c..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教_客户流水排行_2025年10-12月.md
+++ /dev/null
@@ -1,73 +0,0 @@
-# 2025年10-12月 助教客户流水排行榜（全额复制口径）
-## 思考过程
-先把订单应付金额汇总为 order_amount，再把该订单全额计入订单内每位助教，并按月排名。
-
-## 查询说明
-注意：多助教按全额复制计入，导致助教汇总>门店总额，这是刻意口径。
-
-## SQL
-
-### 客户流水（助教+月份汇总，全额复制）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id=g.order_settle_id
-  where g.site_id=%(site_id)s and coalesce(g.is_delete,0)=0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    coalesce(bo.table_amount,0)+coalesce(a.assistant_amount,0)+coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id=bo.order_settle_id
-  left join goods_amount g on g.order_settle_id=bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-)
-select assistant, month_key, sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教_附加课时长排行_2025年10-12月.csv b/etl_billiards/docs/table_2025-12-19/助教_附加课时长排行_2025年10-12月.csv
deleted file mode 100644
index 902ea41..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教_附加课时长排行_2025年10-12月.csv
+++ /dev/null
@@ -1,37 +0,0 @@
-2025年10-12月 助教附加课(超休)时长排行榜
-口径：order_assistant_type=2，超休时长=income_seconds/3600（小时），按月排名。
-
-月份,排名,助教昵称,指标
-2025-10,1,球球,11.00h
-2025-10,2,佳怡,9.00h
-2025-10,3,璇子,8.00h
-2025-10,3,苏苏,8.00h
-2025-10,4,婉婉,4.00h
-2025-10,5,姜姜,3.00h
-2025-10,5,小敌,3.00h
-2025-11,1,周周,25.00h
-2025-11,1,球球,25.00h
-2025-11,2,婉婉,15.00h
-2025-11,3,佳怡,10.00h
-2025-11,3,柚子,10.00h
-2025-11,3,璇子,10.00h
-2025-11,3,素素,10.00h
-2025-11,4,小柔,7.00h
-2025-11,4,年糕,7.00h
-2025-11,5,泡芙,3.00h
-2025-11,5,涛涛,3.00h
-2025-11,5,瑶瑶,3.00h
-2025-11,6,小燕,2.00h
-2025-11,7,乔西,1.00h
-2025-11,7,梦梦,1.00h
-2025-12,1,七七,22.00h
-2025-12,2,小燕,21.00h
-2025-12,3,婉婉,15.00h
-2025-12,3,小柔,15.00h
-2025-12,4,璇子,14.00h
-2025-12,5,周周,8.00h
-2025-12,6,千千,5.00h
-2025-12,6,球球,5.00h
-2025-12,7,佳怡,4.00h
-2025-12,8,QQ,3.00h
-2025-12,9,苏苏,1.00h
diff --git a/etl_billiards/docs/table_2025-12-19/助教_附加课时长排行_2025年10-12月.md b/etl_billiards/docs/table_2025-12-19/助教_附加课时长排行_2025年10-12月.md
deleted file mode 100644
index e8986cb..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教_附加课时长排行_2025年10-12月.md
+++ /dev/null
@@ -1,31 +0,0 @@
-# 2025年10-12月 助教附加课(超休)时长排行榜
-## 思考过程
-按月汇总助教附加课时长，并用 dense_rank 做排名。
-
-## 查询说明
-口径：order_assistant_type=2；时长=income_seconds/3600（小时）。
-
-## SQL
-
-### 附加课时长（助教+月份汇总）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0)=0
-    and asl.order_assistant_type=2
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-)
-select
-  assistant,
-  month_key,
-  sum(income_seconds)/3600.0 as hours
-from raw
-where month_key is not null
-group by assistant, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_Amy.csv b/etl_billiards/docs/table_2025-12-19/助教详情_Amy.csv
deleted file mode 100644
index bad2eac..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_Amy.csv
+++ /dev/null
@@ -1,56 +0,0 @@
-助教详情：Amy（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础123.6h，附加0.0h；客户流水¥150692.64，充值归因¥12000.00；头部客户(12月)Top3：轩哥、明哥、江先生。
-
-一、基础课业绩
-说明：评价：基础123.6h，附加0.0h；客户流水¥150692.64，充值归因¥12000.00；头部客户(12月)Top3：轩哥、明哥、江先生。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,11.97h,17,-32.44h,-24.56h
-11月,93.53h,4,39.06h,54.65h
-12月,18.08h,16,-26.73h,-23.01h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,0.00h,,0.00h,0.00h
-12月,0.00h,,0.00h,0.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,15810.80,14,-13468.73,-14839.03
-11月,121568.32,2,77313.93,88242.00
-12月,13313.52,12,-7417.01,-327.12
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,3000.00,13,-11466.67,-10000.00
-11月,9000.00,4,1230.77,0.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
-1,轩哥,8.8h / 0.0h,4500.95,0.00,36.0h / 0.0h,38175.17,0.00,4.6h / 0.0h,8281.61,0.00
-2,明哥,0.1h / 0.0h,4190.45,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-3,江先生,2.2h / 0.0h,3202.78,0.00,4.5h / 0.0h,1719.24,0.00,0.0h / 0.0h,0.00,0.00
-4,amy,4.8h / 0.0h,1105.90,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-5,小燕,1.0h / 0.0h,313.44,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-6,叶先生,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,7.4h / 0.0h,7529.19,3000.00
-7,羊,0.0h / 0.0h,0.00,0.00,4.1h / 0.0h,1017.50,1000.00,0.0h / 0.0h,0.00,0.00
-8,葛先生,0.0h / 0.0h,0.00,0.00,1.6h / 0.0h,1585.38,0.00,0.0h / 0.0h,0.00,0.00
-9,陈先生,0.0h / 0.0h,0.00,0.00,4.2h / 0.0h,2566.75,3000.00,0.0h / 0.0h,0.00,0.00
-10,李先生,0.0h / 0.0h,0.00,0.00,1.0h / 0.0h,816.28,0.00,0.0h / 0.0h,0.00,0.00
-11,蔡总,1.2h / 0.0h,0.00,0.00,40.2h / 0.0h,75063.98,5000.00,0.0h / 0.0h,0.00,0.00
-12,昌哥,0.0h / 0.0h,0.00,0.00,2.0h / 0.0h,624.02,0.00,0.0h / 0.0h,0.00,0.00
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_Amy.md b/etl_billiards/docs/table_2025-12-19/助教详情_Amy.md
deleted file mode 100644
index dda6894..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_Amy.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：Amy（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础123.6h，附加0.0h；客户流水¥150692.64，充值归因¥12000.00；头部客户(12月)Top3：轩哥、明哥、江先生。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_QQ.csv b/etl_billiards/docs/table_2025-12-19/助教详情_QQ.csv
deleted file mode 100644
index af1c043..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_QQ.csv
+++ /dev/null
@@ -1,47 +0,0 @@
-助教详情：QQ（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础6.4h，附加3.0h；客户流水¥1517.46，充值归因¥0.00；头部客户(12月)Top3：游、张先生、黄先生。
-
-一、基础课业绩
-说明：评价：基础6.4h，附加3.0h；客户流水¥1517.46，充值归因¥0.00；头部客户(12月)Top3：游、张先生、黄先生。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,5.17h,25,-49.31h,-33.72h
-12月,1.22h,22,-43.59h,-39.88h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,0.00h,,0.00h,0.00h
-12月,3.00h,8,-7.27h,-5.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,0.00,,0.00,0.00
-11月,1134.18,25,-43120.21,-32192.14
-12月,383.28,21,-20347.25,-13257.36
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,0.00,,0.00,0.00
-11月,0.00,,0.00,0.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
-1,游,1.2h / 0.0h,383.28,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-2,张先生,0.0h / 0.0h,0.00,0.00,2.8h / 0.0h,502.16,0.00,0.0h / 0.0h,0.00,0.00
-3,黄先生,0.0h / 3.0h,0.00,0.00,2.4h / 0.0h,632.02,0.00,0.0h / 0.0h,0.00,0.00
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_QQ.md b/etl_billiards/docs/table_2025-12-19/助教详情_QQ.md
deleted file mode 100644
index 040c778..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_QQ.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：QQ（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础6.4h，附加3.0h；客户流水¥1517.46，充值归因¥0.00；头部客户(12月)Top3：游、张先生、黄先生。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_七七.csv b/etl_billiards/docs/table_2025-12-19/助教详情_七七.csv
deleted file mode 100644
index 47420c2..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_七七.csv
+++ /dev/null
@@ -1,56 +0,0 @@
-助教详情：七七（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础234.3h，附加22.0h；客户流水¥187346.62，充值归因¥6000.00；头部客户(12月)Top3：蔡总、轩哥、林先生。
-
-一、基础课业绩
-说明：评价：基础234.3h，附加22.0h；客户流水¥187346.62，充值归因¥6000.00；头部客户(12月)Top3：蔡总、轩哥、林先生。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,64.70h,4,20.29h,28.17h
-11月,91.90h,5,37.42h,53.02h
-12月,77.72h,4,32.91h,36.62h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,0.00h,,0.00h,0.00h
-12月,22.00h,1,11.73h,14.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,38810.44,6,9530.91,8160.61
-11月,84500.79,5,40246.40,51174.47
-12月,64035.39,2,43304.86,50394.74
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,6000.00,11,-8466.67,-7000.00
-11月,0.00,,0.00,0.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
-1,蔡总,26.6h / 0.0h,29660.33,0.00,45.7h / 0.0h,52373.96,0.00,0.0h / 0.0h,0.00,0.00
-2,轩哥,32.8h / 22.0h,27236.57,0.00,24.2h / 0.0h,21849.91,0.00,39.5h / 0.0h,29630.52,3000.00
-3,林先生,14.0h / 0.0h,3808.56,0.00,5.4h / 0.0h,1623.92,0.00,0.0h / 0.0h,0.00,0.00
-4,江先生,3.2h / 0.0h,3042.99,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-5,张先生,1.0h / 0.0h,286.94,0.00,10.9h / 0.0h,3995.10,0.00,13.2h / 0.0h,5315.81,0.00
-6,游,0.0h / 0.0h,0.00,0.00,0.2h / 0.0h,3544.42,0.00,0.0h / 0.0h,0.00,0.00
-7,罗先生,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,1.1h / 0.0h,545.55,0.00
-8,小熊,0.0h / 0.0h,0.00,0.00,1.3h / 0.0h,314.44,0.00,0.0h / 0.0h,0.00,0.00
-9,叶总,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,3.0h / 0.0h,862.68,0.00
-10,陶,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,4.2h / 0.0h,1278.72,0.00
-11,T,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,3.8h / 0.0h,1177.16,3000.00
-12,胡先生,0.0h / 0.0h,0.00,0.00,4.2h / 0.0h,799.04,0.00,0.0h / 0.0h,0.00,0.00
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_七七.md b/etl_billiards/docs/table_2025-12-19/助教详情_七七.md
deleted file mode 100644
index 4cb7dde..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_七七.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：七七（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础234.3h，附加22.0h；客户流水¥187346.62，充值归因¥6000.00；头部客户(12月)Top3：蔡总、轩哥、林先生。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_乔西.csv b/etl_billiards/docs/table_2025-12-19/助教详情_乔西.csv
deleted file mode 100644
index cbd3b25..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_乔西.csv
+++ /dev/null
@@ -1,59 +0,0 @@
-助教详情：乔西（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础89.0h，附加1.0h；客户流水¥46219.50，充值归因¥20000.00；头部客户(12月)Top3：轩哥、T、林先生。
-
-一、基础课业绩
-说明：评价：基础89.0h，附加1.0h；客户流水¥46219.50，充值归因¥20000.00；头部客户(12月)Top3：轩哥、T、林先生。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,32.60h,11,-11.81h,-3.93h
-11月,30.57h,20,-23.91h,-8.32h
-12月,25.82h,13,-18.99h,-15.28h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,1.00h,7,-7.80h,-6.00h
-12月,0.00h,,0.00h,0.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,17649.50,13,-11630.03,-13000.33
-11月,15536.78,21,-28717.61,-17789.54
-12月,13033.22,13,-7697.31,-607.42
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,17000.00,7,2533.33,4000.00
-11月,3000.00,8,-4769.23,-6000.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
-1,轩哥,8.2h / 0.0h,8244.84,0.00,8.3h / 0.0h,7623.25,0.00,9.3h / 0.0h,11503.53,8000.00
-2,T,6.8h / 0.0h,1789.02,0.00,4.4h / 0.0h,1100.80,0.00,0.0h / 0.0h,0.00,0.00
-3,林先生,4.6h / 0.0h,1369.51,0.00,5.0h / 0.0h,1645.89,0.00,0.0h / 0.0h,0.00,0.00
-4,张先生,3.3h / 0.0h,1066.81,0.00,0.0h / 0.0h,0.00,0.00,2.5h / 0.0h,489.66,0.00
-5,候,2.9h / 0.0h,563.04,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-6,罗先生,0.0h / 0.0h,0.00,0.00,1.4h / 0.0h,454.46,0.00,0.0h / 0.0h,0.00,0.00
-7,陈腾鑫,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,0.9h / 0.0h,162.29,3000.00
-8,葛先生,0.0h / 0.0h,0.00,0.00,2.2h / 0.0h,707.97,0.00,0.0h / 0.0h,0.00,0.00
-9,陈先生,0.0h / 0.0h,0.00,0.00,4.2h / 0.0h,2566.75,3000.00,0.0h / 0.0h,0.00,0.00
-10,陈淑涛,0.0h / 0.0h,0.00,0.00,3.4h / 0.0h,1021.49,0.00,0.0h / 0.0h,0.00,0.00
-11,周先生,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,7.5h / 0.0h,2726.01,0.00
-12,陈德韩,0.0h / 0.0h,0.00,0.00,0.0h / 1.0h,0.00,0.00,7.6h / 0.0h,1568.91,5000.00
-13,黄先生,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,1.6h / 0.0h,300.37,0.00
-14,陈先生,0.0h / 0.0h,0.00,0.00,1.8h / 0.0h,416.17,0.00,0.0h / 0.0h,0.00,0.00
-15,方先生,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,3.2h / 0.0h,898.73,1000.00
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_乔西.md b/etl_billiards/docs/table_2025-12-19/助教详情_乔西.md
deleted file mode 100644
index 1d4e6a0..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_乔西.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：乔西（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础89.0h，附加1.0h；客户流水¥46219.50，充值归因¥20000.00；头部客户(12月)Top3：轩哥、T、林先生。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_佳怡.csv b/etl_billiards/docs/table_2025-12-19/助教详情_佳怡.csv
deleted file mode 100644
index f62f7b6..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_佳怡.csv
+++ /dev/null
@@ -1,63 +0,0 @@
-助教详情：佳怡（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础425.2h，附加23.0h；客户流水¥156229.68，充值归因¥47000.00；头部客户(12月)Top3：罗先生、周周、轩哥。
-
-一、基础课业绩
-说明：评价：基础425.2h，附加23.0h；客户流水¥156229.68，充值归因¥47000.00；头部客户(12月)Top3：罗先生、周周、轩哥。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,139.55h,1,95.14h,103.02h
-11月,176.25h,1,121.77h,137.37h
-12月,109.40h,2,64.59h,68.31h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,9.00h,2,2.43h,1.00h
-11月,10.00h,3,1.20h,3.00h
-12月,4.00h,7,-6.27h,-4.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,44466.03,5,15186.50,13816.20
-11月,79249.31,6,34994.92,45922.99
-12月,32514.34,6,11783.81,18873.70
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,27000.00,3,12533.33,14000.00
-11月,20000.00,1,12230.77,11000.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
-1,罗先生,67.8h / 4.0h,16680.01,0.00,57.5h / 10.0h,12309.26,0.00,46.9h / 8.0h,12047.56,7000.00
-2,周周,13.2h / 0.0h,3866.19,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-3,轩哥,6.4h / 0.0h,3741.42,0.00,18.0h / 0.0h,24036.03,0.00,24.6h / 1.0h,17999.86,3000.00
-4,大G,9.5h / 0.0h,2623.97,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-5,T,1.9h / 0.0h,2053.02,0.00,5.0h / 0.0h,2490.70,0.00,8.1h / 0.0h,1323.17,3000.00
-6,林先生,4.5h / 0.0h,1720.12,0.00,10.4h / 0.0h,3269.81,0.00,0.0h / 0.0h,0.00,0.00
-7,游,3.2h / 0.0h,1307.16,0.00,10.3h / 0.0h,4754.69,0.00,0.0h / 0.0h,0.00,0.00
-8,胡先生,3.0h / 0.0h,522.45,0.00,26.4h / 0.0h,9712.14,13000.00,0.0h / 0.0h,0.00,0.00
-9,江先生,0.0h / 0.0h,0.00,0.00,3.8h / 0.0h,1374.85,0.00,0.0h / 0.0h,0.00,0.00
-10,陈先生,0.0h / 0.0h,0.00,0.00,7.6h / 0.0h,2566.75,3000.00,0.0h / 0.0h,0.00,0.00
-11,陈腾鑫,0.0h / 0.0h,0.00,0.00,19.2h / 0.0h,4276.97,1000.00,38.5h / 0.0h,7626.75,12000.00
-12,张先生,0.0h / 0.0h,0.00,0.00,4.9h / 0.0h,2233.65,0.00,0.0h / 0.0h,0.00,0.00
-13,歌神,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,2.0h / 0.0h,361.38,0.00
-14,夏,0.0h / 0.0h,0.00,0.00,2.0h / 0.0h,455.03,0.00,5.8h / 0.0h,2595.54,1000.00
-15,小熊,0.0h / 0.0h,0.00,0.00,6.4h / 0.0h,2072.54,3000.00,6.8h / 0.0h,1213.06,1000.00
-16,蔡总,0.0h / 0.0h,0.00,0.00,4.5h / 0.0h,9696.89,0.00,0.0h / 0.0h,0.00,0.00
-17,吕先生,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,1.7h / 0.0h,337.17,0.00
-18,贺斌,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,1.0h / 0.0h,247.34,0.00
-19,陶,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,4.1h / 0.0h,714.20,0.00
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_佳怡.md b/etl_billiards/docs/table_2025-12-19/助教详情_佳怡.md
deleted file mode 100644
index a524aa2..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_佳怡.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：佳怡（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础425.2h，附加23.0h；客户流水¥156229.68，充值归因¥47000.00；头部客户(12月)Top3：罗先生、周周、轩哥。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_千千.csv b/etl_billiards/docs/table_2025-12-19/助教详情_千千.csv
deleted file mode 100644
index a3f43c0..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_千千.csv
+++ /dev/null
@@ -1,55 +0,0 @@
-助教详情：千千（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础77.2h，附加5.0h；客户流水¥34297.90，充值归因¥0.00；头部客户(12月)Top3：张先生、周先生、陈腾鑫。
-
-一、基础课业绩
-说明：评价：基础77.2h，附加5.0h；客户流水¥34297.90，充值归因¥0.00；头部客户(12月)Top3：张先生、周先生、陈腾鑫。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,38.88h,14,-15.59h,0.00h
-12月,38.28h,12,-6.53h,-2.81h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,0.00h,,0.00h,0.00h
-12月,5.00h,6,-5.27h,-3.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,0.00,,0.00,0.00
-11月,24684.71,17,-19569.68,-8641.61
-12月,9613.19,16,-11117.34,-4027.46
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,0.00,,0.00,0.00
-11月,0.00,,0.00,0.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
-1,张先生,10.0h / 0.0h,2622.05,0.00,4.4h / 0.0h,1623.68,0.00,0.0h / 0.0h,0.00,0.00
-2,周先生,8.6h / 0.0h,1577.94,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-3,陈腾鑫,4.8h / 0.0h,1375.20,0.00,2.9h / 0.0h,2418.94,0.00,0.0h / 0.0h,0.00,0.00
-4,梅,3.3h / 5.0h,1356.34,0.00,5.8h / 0.0h,2007.81,0.00,0.0h / 0.0h,0.00,0.00
-5,清,3.0h / 0.0h,1128.06,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-6,黄先生,6.2h / 0.0h,1048.14,0.00,6.8h / 0.0h,1251.92,0.00,0.0h / 0.0h,0.00,0.00
-7,游,2.2h / 0.0h,505.46,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-8,葛先生,0.0h / 0.0h,0.00,0.00,14.4h / 0.0h,7500.34,0.00,0.0h / 0.0h,0.00,0.00
-9,林先生,0.0h / 0.0h,0.00,0.00,2.7h / 0.0h,499.11,0.00,0.0h / 0.0h,0.00,0.00
-10,轩哥,0.0h / 0.0h,0.00,0.00,1.2h / 0.0h,415.60,0.00,0.0h / 0.0h,0.00,0.00
-11,蔡总,0.0h / 0.0h,0.00,0.00,0.7h / 0.0h,8967.31,0.00,0.0h / 0.0h,0.00,0.00
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_千千.md b/etl_billiards/docs/table_2025-12-19/助教详情_千千.md
deleted file mode 100644
index 07dd33f..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_千千.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：千千（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础77.2h，附加5.0h；客户流水¥34297.90，充值归因¥0.00；头部客户(12月)Top3：张先生、周先生、陈腾鑫。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_周周.csv b/etl_billiards/docs/table_2025-12-19/助教详情_周周.csv
deleted file mode 100644
index c5ba351..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_周周.csv
+++ /dev/null
@@ -1,66 +0,0 @@
-助教详情：周周（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础172.6h，附加33.0h；客户流水¥80429.10，充值归因¥20000.00；头部客户(12月)Top3：周周、明哥、T。
-
-一、基础课业绩
-说明：评价：基础172.6h，附加33.0h；客户流水¥80429.10，充值归因¥20000.00；头部客户(12月)Top3：周周、明哥、T。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,41.33h,9,-3.08h,4.81h
-11月,71.27h,10,16.79h,32.38h
-12月,60.02h,6,15.21h,18.92h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,25.00h,1,16.20h,18.00h
-12月,8.00h,5,-2.27h,0.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,27375.91,11,-1903.62,-3273.92
-11月,31436.74,15,-12817.65,-1889.58
-12月,21616.45,7,885.92,7975.80
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,11000.00,9,-3466.67,-2000.00
-11月,9000.00,4,1230.77,0.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
-1,周周,28.8h / 8.0h,8105.19,0.00,0.0h / 20.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-2,明哥,0.4h / 0.0h,4190.45,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-3,T,10.1h / 0.0h,2968.13,0.00,0.0h / 0.0h,0.00,0.00,4.5h / 0.0h,1300.23,0.00
-4,大G,14.8h / 0.0h,2724.15,0.00,2.8h / 0.0h,1783.61,0.00,0.0h / 0.0h,0.00,0.00
-5,罗先生,2.6h / 0.0h,1584.22,0.00,9.0h / 0.0h,2415.09,0.00,0.0h / 0.0h,0.00,0.00
-6,游,2.4h / 0.0h,1307.16,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-7,张先生,0.0h / 0.0h,449.03,0.00,6.3h / 0.0h,2092.46,0.00,4.1h / 0.0h,1650.08,0.00
-8,轩哥,0.7h / 0.0h,288.12,0.00,5.0h / 3.0h,2175.94,5000.00,20.2h / 0.0h,16154.38,10000.00
-9,江先生,0.0h / 0.0h,0.00,0.00,4.3h / 0.0h,3588.88,0.00,0.0h / 0.0h,0.00,0.00
-10,罗超杰,0.0h / 0.0h,0.00,0.00,1.2h / 0.0h,255.63,0.00,0.0h / 0.0h,0.00,0.00
-11,陈腾鑫,0.0h / 0.0h,0.00,0.00,4.6h / 0.0h,1210.78,0.00,0.0h / 0.0h,197.60,1000.00
-12,林总,0.0h / 0.0h,0.00,0.00,2.2h / 0.0h,439.96,0.00,0.0h / 0.0h,0.00,0.00
-13,林先生,0.0h / 0.0h,0.00,0.00,0.7h / 0.0h,747.44,0.00,0.0h / 0.0h,0.00,0.00
-14,葛先生,0.0h / 0.0h,0.00,0.00,11.0h / 0.0h,3073.27,0.00,0.0h / 0.0h,0.00,0.00
-15,羊,0.0h / 0.0h,0.00,0.00,1.4h / 0.0h,602.50,0.00,0.0h / 0.0h,0.00,0.00
-16,小熊,0.0h / 0.0h,0.00,0.00,10.7h / 0.0h,2612.37,4000.00,0.0h / 0.0h,0.00,0.00
-17,陈德韩,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,4.3h / 0.0h,5714.01,0.00
-18,蔡总,0.0h / 0.0h,0.00,0.00,8.2h / 0.0h,9385.22,0.00,0.0h / 0.0h,0.00,0.00
-19,万先生,0.0h / 0.0h,0.00,0.00,0.0h / 2.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-20,吕先生,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,3.7h / 0.0h,1080.89,0.00
-21,林先生,0.0h / 0.0h,0.00,0.00,4.0h / 0.0h,1053.59,0.00,0.0h / 0.0h,0.00,0.00
-22,陶,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,4.4h / 0.0h,1278.72,0.00
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_周周.md b/etl_billiards/docs/table_2025-12-19/助教详情_周周.md
deleted file mode 100644
index 68ef417..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_周周.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：周周（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础172.6h，附加33.0h；客户流水¥80429.10，充值归因¥20000.00；头部客户(12月)Top3：周周、明哥、T。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_奈千.csv b/etl_billiards/docs/table_2025-12-19/助教详情_奈千.csv
deleted file mode 100644
index 55b648d..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_奈千.csv
+++ /dev/null
@@ -1,58 +0,0 @@
-助教详情：奈千（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础59.0h，附加0.0h；客户流水¥107484.78，充值归因¥18000.00；头部客户(12月)Top3：轩哥、黎先生、陈先生。
-
-一、基础课业绩
-说明：评价：基础59.0h，附加0.0h；客户流水¥107484.78，充值归因¥18000.00；头部客户(12月)Top3：轩哥、黎先生、陈先生。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,23.62h,13,-20.79h,-12.91h
-11月,32.83h,19,-21.64h,-6.05h
-12月,2.58h,21,-42.23h,-38.51h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,0.00h,,0.00h,0.00h
-12月,0.00h,,0.00h,0.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,38653.58,7,9374.05,8003.75
-11月,68543.08,7,24288.69,35216.76
-12月,288.12,22,-20442.41,-13352.52
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,18000.00,6,3533.33,5000.00
-11月,0.00,,0.00,0.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
-1,轩哥,0.7h / 0.0h,288.12,0.00,4.3h / 0.0h,14349.45,0.00,6.2h / 0.0h,22341.76,13000.00
-2,黎先生,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,1.7h / 0.0h,470.19,0.00
-3,陈先生,0.0h / 0.0h,0.00,0.00,5.1h / 0.0h,1150.83,0.00,0.0h / 0.0h,0.00,0.00
-4,羊,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,1.4h / 0.0h,3620.75,0.00
-5,陈腾鑫,0.0h / 0.0h,0.00,0.00,2.6h / 0.0h,441.39,0.00,2.1h / 0.0h,1084.69,1000.00
-6,张先生,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,2.2h / 0.0h,474.93,0.00
-7,夏,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,2.0h / 0.0h,2595.54,1000.00
-8,罗超,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,2.5h / 0.0h,1013.51,0.00
-9,罗先生,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,1143.87,3000.00
-10,陈德韩,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,4.4h / 0.0h,5714.01,0.00
-11,阿亮,0.0h / 0.0h,0.00,0.00,2.9h / 0.0h,493.02,0.00,0.0h / 0.0h,0.00,0.00
-12,曾先生,0.0h / 0.0h,0.00,0.00,1.0h / 0.0h,206.16,0.00,0.0h / 0.0h,0.00,0.00
-13,蔡总,1.8h / 0.0h,0.00,0.00,17.0h / 0.0h,51902.23,0.00,0.0h / 0.0h,0.00,0.00
-14,T,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,1.2h / 0.0h,194.33,0.00
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_奈千.md b/etl_billiards/docs/table_2025-12-19/助教详情_奈千.md
deleted file mode 100644
index 25e397f..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_奈千.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：奈千（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础59.0h，附加0.0h；客户流水¥107484.78，充值归因¥18000.00；头部客户(12月)Top3：轩哥、黎先生、陈先生。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_姜姜.csv b/etl_billiards/docs/table_2025-12-19/助教详情_姜姜.csv
deleted file mode 100644
index c91de92..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_姜姜.csv
+++ /dev/null
@@ -1,46 +0,0 @@
-助教详情：姜姜（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础6.6h，附加3.0h；客户流水¥2333.94，充值归因¥4000.00；头部客户(12月)Top3：罗先生、汪先生。
-
-一、基础课业绩
-说明：评价：基础6.6h，附加3.0h；客户流水¥2333.94，充值归因¥4000.00；头部客户(12月)Top3：罗先生、汪先生。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,6.60h,18,-37.81h,-29.93h
-11月,0.00h,,0.00h,0.00h
-12月,0.00h,,0.00h,0.00h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,3.00h,5,-3.57h,-5.00h
-11月,0.00h,,0.00h,0.00h
-12月,0.00h,,0.00h,0.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,2333.94,20,-26945.59,-28315.89
-11月,0.00,,0.00,0.00
-12月,0.00,,0.00,0.00
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,4000.00,12,-10466.67,-9000.00
-11月,0.00,,0.00,0.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
-1,罗先生,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,1.5h / 0.0h,1143.87,3000.00
-2,汪先生,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,5.1h / 3.0h,1190.07,1000.00
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_姜姜.md b/etl_billiards/docs/table_2025-12-19/助教详情_姜姜.md
deleted file mode 100644
index 3b5c045..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_姜姜.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：姜姜（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础6.6h，附加3.0h；客户流水¥2333.94，充值归因¥4000.00；头部客户(12月)Top3：罗先生、汪先生。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_婉婉.csv b/etl_billiards/docs/table_2025-12-19/助教详情_婉婉.csv
deleted file mode 100644
index ece6ca8..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_婉婉.csv
+++ /dev/null
@@ -1,65 +0,0 @@
-助教详情：婉婉（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础154.6h，附加34.0h；客户流水¥106476.37，充值归因¥33000.00；头部客户(12月)Top3：江先生、明哥、候。
-
-一、基础课业绩
-说明：评价：基础154.6h，附加34.0h；客户流水¥106476.37，充值归因¥33000.00；头部客户(12月)Top3：江先生、明哥、候。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,90.68h,3,46.27h,54.16h
-11月,46.03h,12,-8.44h,7.15h
-12月,17.83h,17,-26.98h,-23.26h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,4.00h,4,-2.57h,-4.00h
-11月,15.00h,2,6.20h,8.00h
-12月,15.00h,3,4.73h,7.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,62187.64,2,32908.11,31537.81
-11月,33326.32,14,-10928.07,0.00
-12月,10962.41,15,-9768.12,-2678.24
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,24000.00,4,9533.33,11000.00
-11月,9000.00,4,1230.77,0.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
-1,江先生,4.7h / 0.0h,5889.30,0.00,9.4h / 0.0h,6947.07,5000.00,2.7h / 0.0h,1538.09,0.00
-2,明哥,11.7h / 10.0h,4822.90,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-3,候,1.1h / 0.0h,195.75,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-4,刘哥,0.3h / 0.0h,54.46,0.00,5.0h / 0.0h,2982.34,0.00,0.0h / 0.0h,0.00,0.00
-5,林总,0.0h / 0.0h,0.00,0.00,0.9h / 0.0h,244.48,0.00,0.0h / 0.0h,0.00,0.00
-6,羊,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,4.3h / 0.0h,3620.75,0.00
-7,叶先生,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,3.7h / 0.0h,1278.01,0.00
-8,邓飛,0.0h / 0.0h,0.00,0.00,0.8h / 0.0h,925.47,1000.00,0.0h / 4.0h,0.00,0.00
-9,歌神,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,6.7h / 0.0h,4718.40,0.00
-10,夏,0.0h / 0.0h,0.00,0.00,5.4h / 4.0h,2991.13,0.00,18.2h / 0.0h,11826.32,1000.00
-11,轩哥,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,45.2h / 0.0h,33043.15,16000.00
-12,罗先生,0.0h / 5.0h,0.00,0.00,7.9h / 0.0h,2086.94,0.00,3.4h / 0.0h,1143.87,3000.00
-13,蔡总,0.0h / 0.0h,0.00,0.00,0.0h / 3.0h,6196.43,0.00,0.0h / 0.0h,0.00,0.00
-14,吕先生,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,2.8h / 0.0h,3924.18,3000.00
-15,万先生,0.0h / 0.0h,0.00,0.00,0.0h / 4.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-16,老宋,0.0h / 0.0h,0.00,0.00,1.0h / 0.0h,465.98,0.00,0.0h / 0.0h,0.00,0.00
-17,黎先生,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,0.8h / 0.0h,470.19,0.00
-18,君姐,0.0h / 0.0h,0.00,0.00,4.2h / 0.0h,1864.86,0.00,0.0h / 0.0h,0.00,0.00
-19,林先生,0.0h / 0.0h,0.00,0.00,6.0h / 4.0h,2690.52,0.00,0.0h / 0.0h,0.00,0.00
-20,婉婉,0.0h / 0.0h,0.00,0.00,1.6h / 0.0h,242.81,0.00,2.8h / 0.0h,624.68,1000.00
-21,胡先生,0.0h / 0.0h,0.00,0.00,3.8h / 0.0h,5688.29,3000.00,0.0h / 0.0h,0.00,0.00
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_婉婉.md b/etl_billiards/docs/table_2025-12-19/助教详情_婉婉.md
deleted file mode 100644
index 09efb40..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_婉婉.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：婉婉（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础154.6h，附加34.0h；客户流水¥106476.37，充值归因¥33000.00；头部客户(12月)Top3：江先生、明哥、候。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_小侯.csv b/etl_billiards/docs/table_2025-12-19/助教详情_小侯.csv
deleted file mode 100644
index 27942ed..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_小侯.csv
+++ /dev/null
@@ -1,57 +0,0 @@
-助教详情：小侯（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础92.2h，附加0.0h；客户流水¥41280.98，充值归因¥0.00；头部客户(12月)Top3：张先生、陈腾鑫、李先生。
-
-一、基础课业绩
-说明：评价：基础92.2h，附加0.0h；客户流水¥41280.98，充值归因¥0.00；头部客户(12月)Top3：张先生、陈腾鑫、李先生。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,42.58h,13,-11.89h,3.70h
-12月,49.57h,8,4.76h,8.47h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,0.00h,,0.00h,0.00h
-12月,0.00h,,0.00h,0.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,0.00,,0.00,0.00
-11月,27313.21,16,-16941.18,-6013.11
-12月,13967.77,11,-6762.76,327.12
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,0.00,,0.00,0.00
-11月,0.00,,0.00,0.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
-1,张先生,14.4h / 0.0h,4161.57,0.00,5.8h / 0.0h,1583.86,0.00,0.0h / 0.0h,0.00,0.00
-2,陈腾鑫,12.1h / 0.0h,3984.45,0.00,7.0h / 0.0h,2965.62,0.00,0.0h / 0.0h,0.00,0.00
-3,李先生,9.3h / 0.0h,1729.57,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-4,梅,3.3h / 0.0h,1356.34,0.00,1.4h / 0.0h,1573.10,0.00,0.0h / 0.0h,0.00,0.00
-5,清,3.0h / 0.0h,1128.06,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-6,T,3.9h / 0.0h,938.16,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-7,候,3.4h / 0.0h,669.62,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-8,林志铭,0.0h / 0.0h,0.00,0.00,1.2h / 0.0h,220.15,0.00,0.0h / 0.0h,0.00,0.00
-9,林先生,0.0h / 0.0h,0.00,0.00,9.7h / 0.0h,3619.37,0.00,0.0h / 0.0h,0.00,0.00
-10,艾宇民,0.0h / 0.0h,0.00,0.00,7.6h / 0.0h,3872.24,0.00,0.0h / 0.0h,0.00,0.00
-11,蔡总,0.0h / 0.0h,0.00,0.00,2.6h / 0.0h,10419.30,0.00,0.0h / 0.0h,0.00,0.00
-12,钟智豪,0.0h / 0.0h,0.00,0.00,1.8h / 0.0h,274.34,0.00,0.0h / 0.0h,0.00,0.00
-13,李先生,0.0h / 0.0h,0.00,0.00,5.6h / 0.0h,2785.23,0.00,0.0h / 0.0h,0.00,0.00
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_小侯.md b/etl_billiards/docs/table_2025-12-19/助教详情_小侯.md
deleted file mode 100644
index b71681b..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_小侯.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：小侯（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础92.2h，附加0.0h；客户流水¥41280.98，充值归因¥0.00；头部客户(12月)Top3：张先生、陈腾鑫、李先生。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_小敌.csv b/etl_billiards/docs/table_2025-12-19/助教详情_小敌.csv
deleted file mode 100644
index 659a0d4..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_小敌.csv
+++ /dev/null
@@ -1,55 +0,0 @@
-助教详情：小敌（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础135.1h，附加3.0h；客户流水¥93760.82，充值归因¥29000.00；头部客户(12月)Top3：郑先生、张先生、轩哥。
-
-一、基础课业绩
-说明：评价：基础135.1h，附加3.0h；客户流水¥93760.82，充值归因¥29000.00；头部客户(12月)Top3：郑先生、张先生、轩哥。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,55.82h,7,11.41h,19.29h
-11月,72.90h,9,18.42h,34.02h
-12月,6.40h,20,-38.41h,-34.69h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,3.00h,5,-3.57h,-5.00h
-11月,0.00h,,0.00h,0.00h
-12月,0.00h,,0.00h,0.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,44510.29,4,15230.76,13860.46
-11月,47986.57,9,3732.18,14660.25
-12月,1263.96,20,-19466.57,-12376.68
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,21000.00,5,6533.33,8000.00
-11月,8000.00,5,230.77,-1000.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
-1,郑先生,4.9h / 0.0h,814.93,0.00,27.3h / 0.0h,4745.90,0.00,0.0h / 0.0h,0.00,0.00
-2,张先生,1.5h / 0.0h,449.03,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-3,轩哥,0.0h / 0.0h,0.00,0.00,11.2h / 0.0h,15962.93,0.00,43.1h / 0.0h,32148.10,21000.00
-4,游,0.0h / 0.0h,0.00,0.00,3.6h / 0.0h,3791.20,0.00,0.0h / 0.0h,0.00,0.00
-5,叶先生,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,2.1h / 0.0h,3922.17,0.00
-6,李先生,0.0h / 0.0h,0.00,0.00,11.8h / 0.0h,2997.53,3000.00,0.0h / 0.0h,0.00,0.00
-7,周先生,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,6.6h / 0.0h,2726.01,0.00
-8,陈德韩,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,4.0h / 0.0h,5714.01,0.00
-9,蔡总,0.0h / 0.0h,0.00,0.00,17.2h / 0.0h,19881.95,5000.00,0.0h / 0.0h,0.00,0.00
-10,林先生,0.0h / 0.0h,0.00,0.00,1.9h / 0.0h,607.06,0.00,0.0h / 0.0h,0.00,0.00
-11,邓飛,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 3.0h,0.00,0.00
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_小敌.md b/etl_billiards/docs/table_2025-12-19/助教详情_小敌.md
deleted file mode 100644
index e1078be..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_小敌.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：小敌（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础135.1h，附加3.0h；客户流水¥93760.82，充值归因¥29000.00；头部客户(12月)Top3：郑先生、张先生、轩哥。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_小柔.csv b/etl_billiards/docs/table_2025-12-19/助教详情_小柔.csv
deleted file mode 100644
index 384edcd..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_小柔.csv
+++ /dev/null
@@ -1,66 +0,0 @@
-助教详情：小柔（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础207.4h，附加22.0h；客户流水¥209918.77，充值归因¥42700.00；头部客户(12月)Top3：蔡总、轩哥、明哥。
-
-一、基础课业绩
-说明：评价：基础207.4h，附加22.0h；客户流水¥209918.77，充值归因¥42700.00；头部客户(12月)Top3：蔡总、轩哥、明哥。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,63.87h,5,19.46h,27.34h
-11月,88.65h,6,34.17h,49.77h
-12月,54.93h,7,10.12h,13.84h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,7.00h,4,-1.80h,0.00h
-12月,15.00h,3,4.73h,7.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,52623.85,3,23344.32,21974.02
-11月,110137.94,3,65883.55,76811.62
-12月,47156.98,3,26426.45,33516.34
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,31700.00,2,17233.33,18700.00
-11月,11000.00,2,3230.77,2000.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
-1,蔡总,30.2h / 0.0h,25658.77,0.00,62.2h / 3.0h,88451.79,5000.00,0.0h / 0.0h,0.00,0.00
-2,轩哥,8.4h / 0.0h,13202.16,0.00,2.0h / 0.0h,4130.37,0.00,35.2h / 0.0h,33211.31,23000.00
-3,明哥,7.7h / 12.0h,4190.45,0.00,5.8h / 0.0h,2258.14,0.00,0.0h / 0.0h,0.00,0.00
-4,江先生,3.2h / 0.0h,3042.99,0.00,6.1h / 0.0h,7578.00,5000.00,2.7h / 0.0h,1538.09,0.00
-5,T,2.0h / 0.0h,434.21,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-6,昌哥,1.8h / 0.0h,318.40,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-7,陈腾鑫,1.6h / 0.0h,310.00,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-8,罗先生,0.0h / 0.0h,0.00,0.00,4.1h / 0.0h,722.25,0.00,0.0h / 0.0h,0.00,0.00
-9,邓飛,0.0h / 0.0h,0.00,0.00,1.2h / 0.0h,925.47,1000.00,0.0h / 0.0h,0.00,0.00
-10,吴生,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,2.8h / 0.0h,685.89,0.00
-11,歌神,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,3.8h / 0.0h,2789.21,0.00
-12,羊,0.0h / 0.0h,0.00,0.00,1.6h / 0.0h,383.40,0.00,0.0h / 0.0h,0.00,0.00
-13,张先生,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,3.3h / 0.0h,568.87,0.00
-14,游,0.0h / 0.0h,0.00,0.00,2.2h / 0.0h,935.84,0.00,0.0h / 0.0h,0.00,0.00
-15,陈德韩,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,3.0h / 0.0h,5714.01,0.00
-16,吕先生,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,7.5h / 0.0h,2750.70,3000.00
-17,罗先生,0.0h / 3.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-18,万先生,0.0h / 0.0h,0.00,0.00,0.0h / 4.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-19,林先生,0.0h / 0.0h,0.00,0.00,3.2h / 0.0h,2398.29,0.00,0.0h / 0.0h,0.00,0.00
-20,陶,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,1.7h / 0.0h,362.17,0.00
-21,叶总,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,3.8h / 0.0h,5003.60,5700.00
-22,胡先生,0.0h / 0.0h,0.00,0.00,0.1h / 0.0h,2354.39,0.00,0.0h / 0.0h,0.00,0.00
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_小柔.md b/etl_billiards/docs/table_2025-12-19/助教详情_小柔.md
deleted file mode 100644
index 9247805..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_小柔.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：小柔（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础207.4h，附加22.0h；客户流水¥209918.77，充值归因¥42700.00；头部客户(12月)Top3：蔡总、轩哥、明哥。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_小柳.csv b/etl_billiards/docs/table_2025-12-19/助教详情_小柳.csv
deleted file mode 100644
index 0a44a03..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_小柳.csv
+++ /dev/null
@@ -1,44 +0,0 @@
-助教详情：小柳（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础0.0h，附加0.0h；客户流水¥0.00，充值归因¥0.00；头部客户(12月)Top3：无。
-
-一、基础课业绩
-说明：评价：基础0.0h，附加0.0h；客户流水¥0.00，充值归因¥0.00；头部客户(12月)Top3：无。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,0.00h,,0.00h,0.00h
-12月,0.00h,,0.00h,0.00h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,0.00h,,0.00h,0.00h
-12月,0.00h,,0.00h,0.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,0.00,,0.00,0.00
-11月,0.00,,0.00,0.00
-12月,0.00,,0.00,0.00
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,0.00,,0.00,0.00
-11月,0.00,,0.00,0.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_小柳.md b/etl_billiards/docs/table_2025-12-19/助教详情_小柳.md
deleted file mode 100644
index 8872c16..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_小柳.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：小柳（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础0.0h，附加0.0h；客户流水¥0.00，充值归因¥0.00；头部客户(12月)Top3：无。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_小燕.csv b/etl_billiards/docs/table_2025-12-19/助教详情_小燕.csv
deleted file mode 100644
index eca0b93..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_小燕.csv
+++ /dev/null
@@ -1,48 +0,0 @@
-助教详情：小燕（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础268.3h，附加23.0h；客户流水¥77172.28，充值归因¥0.00；头部客户(12月)Top3：葛先生、小燕、梅。
-
-一、基础课业绩
-说明：评价：基础268.3h，附加23.0h；客户流水¥77172.28，充值归因¥0.00；头部客户(12月)Top3：葛先生、小燕、梅。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,109.28h,3,54.81h,70.40h
-12月,159.02h,1,114.21h,117.92h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,2.00h,6,-6.80h,-5.00h
-12月,21.00h,2,10.73h,13.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,0.00,,0.00,0.00
-11月,39426.42,12,-4827.97,6100.10
-12月,37745.86,5,17015.33,24105.22
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,0.00,,0.00,0.00
-11月,0.00,,0.00,0.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
-1,葛先生,80.8h / 16.0h,22323.38,0.00,53.5h / 0.0h,17941.19,0.00,0.0h / 0.0h,0.00,0.00
-2,小燕,78.2h / 5.0h,15422.48,0.00,51.4h / 2.0h,10944.82,0.00,0.0h / 0.0h,0.00,0.00
-3,梅,0.0h / 0.0h,0.00,0.00,3.8h / 0.0h,1573.10,0.00,0.0h / 0.0h,0.00,0.00
-4,蔡总,0.0h / 0.0h,0.00,0.00,0.7h / 0.0h,8967.31,0.00,0.0h / 0.0h,0.00,0.00
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_小燕.md b/etl_billiards/docs/table_2025-12-19/助教详情_小燕.md
deleted file mode 100644
index af5c276..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_小燕.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：小燕（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础268.3h，附加23.0h；客户流水¥77172.28，充值归因¥0.00；头部客户(12月)Top3：葛先生、小燕、梅。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_希希.csv b/etl_billiards/docs/table_2025-12-19/助教详情_希希.csv
deleted file mode 100644
index bc73ed6..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_希希.csv
+++ /dev/null
@@ -1,47 +0,0 @@
-助教详情：希希（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础6.6h，附加0.0h；客户流水¥3367.56，充值归因¥0.00；头部客户(12月)Top3：陈腾鑫、歌神、郭先生。
-
-一、基础课业绩
-说明：评价：基础6.6h，附加0.0h；客户流水¥3367.56，充值归因¥0.00；头部客户(12月)Top3：陈腾鑫、歌神、郭先生。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,5.02h,19,-39.39h,-31.51h
-11月,1.58h,27,-52.89h,-37.30h
-12月,0.00h,,0.00h,0.00h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,0.00h,,0.00h,0.00h
-12月,0.00h,,0.00h,0.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,3086.34,18,-26193.19,-27563.49
-11月,281.22,27,-43973.17,-33045.10
-12月,0.00,,0.00,0.00
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,0.00,,0.00,0.00
-11月,0.00,,0.00,0.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
-1,陈腾鑫,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,1.0h / 0.0h,359.28,0.00
-2,歌神,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,4.0h / 0.0h,2727.06,0.00
-3,郭先生,0.0h / 0.0h,0.00,0.00,1.6h / 0.0h,281.22,0.00,0.0h / 0.0h,0.00,0.00
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_希希.md b/etl_billiards/docs/table_2025-12-19/助教详情_希希.md
deleted file mode 100644
index 7a68a55..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_希希.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：希希（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础6.6h，附加0.0h；客户流水¥3367.56，充值归因¥0.00；头部客户(12月)Top3：陈腾鑫、歌神、郭先生。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_年糕.csv b/etl_billiards/docs/table_2025-12-19/助教详情_年糕.csv
deleted file mode 100644
index e37cfbe..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_年糕.csv
+++ /dev/null
@@ -1,63 +0,0 @@
-助教详情：年糕（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础82.6h，附加7.0h；客户流水¥59830.16，充值归因¥9000.00；头部客户(12月)Top3：葛先生、明哥、蔡总。
-
-一、基础课业绩
-说明：评价：基础82.6h，附加7.0h；客户流水¥59830.16，充值归因¥9000.00；头部客户(12月)Top3：葛先生、明哥、蔡总。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,21.23h,14,-23.18h,-15.29h
-11月,35.80h,15,-18.68h,-3.08h
-12月,25.62h,14,-19.19h,-15.48h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,7.00h,4,-1.80h,0.00h
-12月,0.00h,,0.00h,0.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,26289.89,12,-2989.64,-4359.94
-11月,15696.08,20,-28558.31,-17630.24
-12月,17844.19,9,-2886.34,4203.54
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,9000.00,10,-5466.67,-4000.00
-11月,0.00,,0.00,0.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
-1,葛先生,2.6h / 0.0h,5551.79,0.00,6.7h / 0.0h,3777.09,0.00,0.0h / 0.0h,0.00,0.00
-2,明哥,4.6h / 0.0h,4190.45,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-3,蔡总,6.0h / 0.0h,2130.39,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-4,叶先生,2.6h / 0.0h,1558.40,0.00,1.8h / 0.0h,711.79,0.00,5.3h / 0.0h,3607.02,3000.00
-5,君姐,2.2h / 0.0h,1414.23,0.00,6.0h / 0.0h,1864.86,0.00,0.0h / 0.0h,0.00,0.00
-6,林先生,0.9h / 0.0h,1369.51,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-7,张先生,2.5h / 0.0h,540.07,0.00,4.2h / 0.0h,1007.52,0.00,2.1h / 0.0h,596.24,0.00
-8,潘先生,2.0h / 0.0h,516.93,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-9,常总,1.7h / 0.0h,460.52,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-10,小燕,0.5h / 0.0h,111.90,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-11,谢俊,0.0h / 0.0h,0.00,0.00,4.5h / 0.0h,794.53,0.00,0.0h / 0.0h,0.00,0.00
-12,歌神,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,2.6h / 0.0h,1929.19,0.00
-13,夏,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,1.2h / 0.0h,4670.88,0.00
-14,轩哥,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,7.2h / 0.0h,12643.27,3000.00
-15,罗先生,0.0h / 0.0h,0.00,0.00,7.6h / 0.0h,2400.67,0.00,0.0h / 0.0h,0.00,0.00
-16,吕先生,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,2.8h / 0.0h,2843.29,3000.00
-17,万先生,0.0h / 0.0h,0.00,0.00,0.0h / 7.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-18,胡先生,0.0h / 0.0h,0.00,0.00,0.8h / 0.0h,2354.39,0.00,0.0h / 0.0h,0.00,0.00
-19,李先生,0.0h / 0.0h,0.00,0.00,4.2h / 0.0h,2785.23,0.00,0.0h / 0.0h,0.00,0.00
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_年糕.md b/etl_billiards/docs/table_2025-12-19/助教详情_年糕.md
deleted file mode 100644
index 6d5df8b..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_年糕.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：年糕（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础82.6h，附加7.0h；客户流水¥59830.16，充值归因¥9000.00；头部客户(12月)Top3：葛先生、明哥、蔡总。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_悦悦.csv b/etl_billiards/docs/table_2025-12-19/助教详情_悦悦.csv
deleted file mode 100644
index 4787f35..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_悦悦.csv
+++ /dev/null
@@ -1,46 +0,0 @@
-助教详情：悦悦（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础2.3h，附加0.0h；客户流水¥2970.96，充值归因¥3000.00；头部客户(12月)Top3：小宇、轩哥。
-
-一、基础课业绩
-说明：评价：基础2.3h，附加0.0h；客户流水¥2970.96，充值归因¥3000.00；头部客户(12月)Top3：小宇、轩哥。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,2.30h,20,-42.11h,-34.23h
-11月,0.00h,,0.00h,0.00h
-12月,0.00h,,0.00h,0.00h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,0.00h,,0.00h,0.00h
-12月,0.00h,,0.00h,0.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,2970.96,19,-26308.57,-27678.87
-11月,0.00,,0.00,0.00
-12月,0.00,,0.00,0.00
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,3000.00,13,-11466.67,-10000.00
-11月,0.00,,0.00,0.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
-1,小宇,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,0.4h / 0.0h,78.52,0.00
-2,轩哥,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,1.9h / 0.0h,2892.44,3000.00
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_悦悦.md b/etl_billiards/docs/table_2025-12-19/助教详情_悦悦.md
deleted file mode 100644
index ef5b8b0..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_悦悦.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：悦悦（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础2.3h，附加0.0h；客户流水¥2970.96，充值归因¥3000.00；头部客户(12月)Top3：小宇、轩哥。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_柚子.csv b/etl_billiards/docs/table_2025-12-19/助教详情_柚子.csv
deleted file mode 100644
index 546d754..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_柚子.csv
+++ /dev/null
@@ -1,56 +0,0 @@
-助教详情：柚子（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础35.4h，附加10.0h；客户流水¥23234.98，充值归因¥3000.00；头部客户(12月)Top3：陈先生、羊、葛先生。
-
-一、基础课业绩
-说明：评价：基础35.4h，附加10.0h；客户流水¥23234.98，充值归因¥3000.00；头部客户(12月)Top3：陈先生、羊、葛先生。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,35.40h,16,-19.08h,-3.48h
-12月,0.00h,,0.00h,0.00h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,10.00h,3,1.20h,3.00h
-12月,0.00h,,0.00h,0.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,0.00,,0.00,0.00
-11月,23234.98,18,-21019.41,-10091.34
-12月,0.00,,0.00,0.00
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,0.00,,0.00,0.00
-11月,3000.00,8,-4769.23,-6000.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
-1,陈先生,0.0h / 0.0h,0.00,0.00,4.4h / 0.0h,1150.83,0.00,0.0h / 0.0h,0.00,0.00
-2,羊,0.0h / 0.0h,0.00,0.00,1.6h / 0.0h,429.33,0.00,0.0h / 0.0h,0.00,0.00
-3,葛先生,0.0h / 0.0h,0.00,0.00,3.4h / 0.0h,3052.28,0.00,0.0h / 0.0h,0.00,0.00
-4,陈腾鑫,0.0h / 0.0h,0.00,0.00,0.8h / 0.0h,472.03,0.00,0.0h / 0.0h,0.00,0.00
-5,张先生,0.0h / 0.0h,0.00,0.00,3.2h / 0.0h,941.37,0.00,0.0h / 0.0h,0.00,0.00
-6,夏,0.0h / 0.0h,0.00,0.00,0.2h / 7.0h,2991.13,0.00,0.0h / 0.0h,0.00,0.00
-7,轩哥,0.0h / 0.0h,0.00,0.00,0.2h / 0.0h,4484.68,0.00,0.0h / 0.0h,0.00,0.00
-8,胡先生,0.0h / 0.0h,0.00,0.00,1.0h / 0.0h,5688.29,3000.00,0.0h / 0.0h,0.00,0.00
-9,李先生,0.0h / 0.0h,0.00,0.00,7.8h / 0.0h,1712.78,0.00,0.0h / 0.0h,0.00,0.00
-10,牛先生,0.0h / 0.0h,0.00,0.00,10.4h / 0.0h,1887.48,0.00,0.0h / 0.0h,0.00,0.00
-11,阿亮,0.0h / 0.0h,0.00,0.00,2.4h / 0.0h,424.78,0.00,0.0h / 0.0h,0.00,0.00
-12,万先生,0.0h / 0.0h,0.00,0.00,0.0h / 3.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_柚子.md b/etl_billiards/docs/table_2025-12-19/助教详情_柚子.md
deleted file mode 100644
index 15b80ae..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_柚子.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：柚子（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础35.4h，附加10.0h；客户流水¥23234.98，充值归因¥3000.00；头部客户(12月)Top3：陈先生、羊、葛先生。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_梦梦.csv b/etl_billiards/docs/table_2025-12-19/助教详情_梦梦.csv
deleted file mode 100644
index 068ad17..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_梦梦.csv
+++ /dev/null
@@ -1,51 +0,0 @@
-助教详情：梦梦（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础35.7h，附加1.0h；客户流水¥45991.89，充值归因¥0.00；头部客户(12月)Top3：葛先生、阿亮、蔡总。
-
-一、基础课业绩
-说明：评价：基础35.7h，附加1.0h；客户流水¥45991.89，充值归因¥0.00；头部客户(12月)Top3：葛先生、阿亮、蔡总。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,19.60h,22,-34.88h,-19.28h
-12月,16.08h,18,-28.73h,-25.01h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,1.00h,7,-7.80h,-6.00h
-12月,0.00h,,0.00h,0.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,0.00,,0.00,0.00
-11月,39768.09,11,-4486.30,6441.77
-12月,6223.80,18,-14506.73,-7416.84
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,0.00,,0.00,0.00
-11月,0.00,,0.00,0.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
-1,葛先生,2.9h / 0.0h,5551.79,0.00,4.4h / 0.0h,1884.66,0.00,0.0h / 0.0h,0.00,0.00
-2,阿亮,2.7h / 0.0h,495.46,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-3,蔡总,10.5h / 0.0h,176.55,0.00,7.0h / 1.0h,34274.25,0.00,0.0h / 0.0h,0.00,0.00
-4,轩哥,0.0h / 0.0h,0.00,0.00,1.0h / 0.0h,363.25,0.00,0.0h / 0.0h,0.00,0.00
-5,羊,0.0h / 0.0h,0.00,0.00,0.6h / 0.0h,104.77,0.00,0.0h / 0.0h,0.00,0.00
-6,林先生,0.0h / 0.0h,0.00,0.00,4.3h / 0.0h,2461.85,0.00,0.0h / 0.0h,0.00,0.00
-7,张先生,0.0h / 0.0h,0.00,0.00,2.3h / 0.0h,679.31,0.00,0.0h / 0.0h,0.00,0.00
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_梦梦.md b/etl_billiards/docs/table_2025-12-19/助教详情_梦梦.md
deleted file mode 100644
index 0068571..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_梦梦.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：梦梦（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础35.7h，附加1.0h；客户流水¥45991.89，充值归因¥0.00；头部客户(12月)Top3：葛先生、阿亮、蔡总。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_楚楚.csv b/etl_billiards/docs/table_2025-12-19/助教详情_楚楚.csv
deleted file mode 100644
index 6b3c3fa..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_楚楚.csv
+++ /dev/null
@@ -1,44 +0,0 @@
-助教详情：楚楚（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础0.0h，附加0.0h；客户流水¥0.00，充值归因¥0.00；头部客户(12月)Top3：无。
-
-一、基础课业绩
-说明：评价：基础0.0h，附加0.0h；客户流水¥0.00，充值归因¥0.00；头部客户(12月)Top3：无。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,0.00h,,0.00h,0.00h
-12月,0.00h,,0.00h,0.00h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,0.00h,,0.00h,0.00h
-12月,0.00h,,0.00h,0.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,0.00,,0.00,0.00
-11月,0.00,,0.00,0.00
-12月,0.00,,0.00,0.00
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,0.00,,0.00,0.00
-11月,0.00,,0.00,0.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_楚楚.md b/etl_billiards/docs/table_2025-12-19/助教详情_楚楚.md
deleted file mode 100644
index d1aacfc..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_楚楚.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：楚楚（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础0.0h，附加0.0h；客户流水¥0.00，充值归因¥0.00；头部客户(12月)Top3：无。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_欣怡.csv b/etl_billiards/docs/table_2025-12-19/助教详情_欣怡.csv
deleted file mode 100644
index 312e2b0..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_欣怡.csv
+++ /dev/null
@@ -1,52 +0,0 @@
-助教详情：欣怡（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础29.8h，附加0.0h；客户流水¥9981.98，充值归因¥7000.00；头部客户(12月)Top3：老宋、张先生、轩哥。
-
-一、基础课业绩
-说明：评价：基础29.8h，附加0.0h；客户流水¥9981.98，充值归因¥7000.00；头部客户(12月)Top3：老宋、张先生、轩哥。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,19.50h,15,-24.91h,-17.03h
-11月,10.33h,24,-44.14h,-28.55h
-12月,0.00h,,0.00h,0.00h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,0.00h,,0.00h,0.00h
-12月,0.00h,,0.00h,0.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,4824.69,17,-24454.84,-25825.14
-11月,5157.29,24,-39097.10,-28169.03
-12月,0.00,,0.00,0.00
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,3000.00,13,-11466.67,-10000.00
-11月,4000.00,7,-3769.23,-5000.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
-1,老宋,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,0.5h / 0.0h,75.99,0.00
-2,张先生,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,2.4h / 0.0h,570.76,0.00
-3,轩哥,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,1.4h / 0.0h,408.24,0.00
-4,羊,0.0h / 0.0h,0.00,0.00,2.0h / 0.0h,364.70,0.00,0.0h / 0.0h,0.00,0.00
-5,小熊,0.0h / 0.0h,0.00,0.00,7.8h / 0.0h,2438.20,4000.00,0.0h / 0.0h,0.00,0.00
-6,陶,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,4.9h / 0.0h,904.50,0.00
-7,T,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,10.3h / 0.0h,2865.20,3000.00
-8,胡先生,0.0h / 0.0h,0.00,0.00,0.4h / 0.0h,2354.39,0.00,0.0h / 0.0h,0.00,0.00
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_欣怡.md b/etl_billiards/docs/table_2025-12-19/助教详情_欣怡.md
deleted file mode 100644
index 55c8a47..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_欣怡.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：欣怡（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础29.8h，附加0.0h；客户流水¥9981.98，充值归因¥7000.00；头部客户(12月)Top3：老宋、张先生、轩哥。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_泡芙.csv b/etl_billiards/docs/table_2025-12-19/助教详情_泡芙.csv
deleted file mode 100644
index 29e1380..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_泡芙.csv
+++ /dev/null
@@ -1,48 +0,0 @@
-助教详情：泡芙（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础21.4h，附加3.0h；客户流水¥8323.03，充值归因¥0.00；头部客户(12月)Top3：夏、艾宇民、羊。
-
-一、基础课业绩
-说明：评价：基础21.4h，附加3.0h；客户流水¥8323.03，充值归因¥0.00；头部客户(12月)Top3：夏、艾宇民、羊。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,21.38h,21,-33.09h,-17.50h
-12月,0.00h,,0.00h,0.00h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,3.00h,5,-5.80h,-4.00h
-12月,0.00h,,0.00h,0.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,0.00,,0.00,0.00
-11月,8323.03,23,-35931.36,-25003.29
-12月,0.00,,0.00,0.00
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,0.00,,0.00,0.00
-11月,0.00,,0.00,0.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
-1,夏,0.0h / 0.0h,0.00,0.00,2.4h / 0.0h,501.87,0.00,0.0h / 0.0h,0.00,0.00
-2,艾宇民,0.0h / 0.0h,0.00,0.00,17.5h / 3.0h,5037.44,0.00,0.0h / 0.0h,0.00,0.00
-3,羊,0.0h / 0.0h,0.00,0.00,0.8h / 0.0h,429.33,0.00,0.0h / 0.0h,0.00,0.00
-4,胡先生,0.0h / 0.0h,0.00,0.00,0.8h / 0.0h,2354.39,0.00,0.0h / 0.0h,0.00,0.00
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_泡芙.md b/etl_billiards/docs/table_2025-12-19/助教详情_泡芙.md
deleted file mode 100644
index f47a20a..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_泡芙.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：泡芙（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础21.4h，附加3.0h；客户流水¥8323.03，充值归因¥0.00；头部客户(12月)Top3：夏、艾宇民、羊。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_涛涛.csv b/etl_billiards/docs/table_2025-12-19/助教详情_涛涛.csv
deleted file mode 100644
index e365ba9..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_涛涛.csv
+++ /dev/null
@@ -1,60 +0,0 @@
-助教详情：涛涛（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础168.6h，附加3.0h；客户流水¥166962.41，充值归因¥26000.00；头部客户(12月)Top3：蔡总、轩哥、葛先生。
-
-一、基础课业绩
-说明：评价：基础168.6h，附加3.0h；客户流水¥166962.41，充值归因¥26000.00；头部客户(12月)Top3：蔡总、轩哥、葛先生。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,50.13h,8,5.72h,13.61h
-11月,74.40h,7,19.92h,35.52h
-12月,44.08h,10,-0.73h,2.99h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,3.00h,5,-5.80h,-4.00h
-12月,0.00h,,0.00h,0.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,35940.84,8,6661.31,5291.01
-11月,88677.55,4,44423.16,55351.23
-12月,42344.02,4,21613.49,28703.38
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,21000.00,5,6533.33,8000.00
-11月,5000.00,6,-2769.23,-4000.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
-1,蔡总,15.1h / 0.0h,18914.63,0.00,28.4h / 0.0h,57785.21,0.00,0.0h / 0.0h,0.00,0.00
-2,轩哥,10.8h / 0.0h,14490.25,0.00,21.8h / 0.0h,22186.78,0.00,40.1h / 0.0h,30415.18,15000.00
-3,葛先生,5.8h / 0.0h,5551.79,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-4,君姐,2.2h / 0.0h,1414.23,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-5,候,3.1h / 0.0h,563.70,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-6,阿亮,2.9h / 0.0h,538.07,0.00,1.7h / 3.0h,300.53,0.00,0.0h / 0.0h,0.00,0.00
-7,罗先生,2.3h / 0.0h,524.41,0.00,2.3h / 0.0h,844.76,0.00,6.0h / 0.0h,1773.80,3000.00
-8,张先生,1.9h / 0.0h,346.94,0.00,1.8h / 0.0h,325.27,0.00,0.0h / 0.0h,0.00,0.00
-9,江先生,0.0h / 0.0h,0.00,0.00,1.8h / 0.0h,2095.41,5000.00,0.0h / 0.0h,0.00,0.00
-10,叶先生,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,3.1h / 0.0h,3607.02,3000.00
-11,吴生,0.0h / 0.0h,0.00,0.00,2.2h / 0.0h,537.96,0.00,0.0h / 0.0h,0.00,0.00
-12,陈淑涛,0.0h / 0.0h,0.00,0.00,4.4h / 0.0h,1176.77,0.00,0.0h / 0.0h,0.00,0.00
-13,李先生,0.0h / 0.0h,0.00,0.00,2.0h / 0.0h,779.48,0.00,0.0h / 0.0h,0.00,0.00
-14,明哥,0.0h / 0.0h,0.00,0.00,5.4h / 0.0h,2258.14,0.00,0.0h / 0.0h,0.00,0.00
-15,冯先生,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,0.9h / 0.0h,144.84,0.00
-16,胡先生,0.0h / 0.0h,0.00,0.00,2.7h / 0.0h,387.24,0.00,0.0h / 0.0h,0.00,0.00
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_涛涛.md b/etl_billiards/docs/table_2025-12-19/助教详情_涛涛.md
deleted file mode 100644
index cc57443..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_涛涛.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：涛涛（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础168.6h，附加3.0h；客户流水¥166962.41，充值归因¥26000.00；头部客户(12月)Top3：蔡总、轩哥、葛先生。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_球球.csv b/etl_billiards/docs/table_2025-12-19/助教详情_球球.csv
deleted file mode 100644
index ae1ce76..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_球球.csv
+++ /dev/null
@@ -1,74 +0,0 @@
-助教详情：球球（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础172.5h，附加41.0h；客户流水¥95647.82，充值归因¥24000.00；头部客户(12月)Top3：葛先生、周周、T。
-
-一、基础课业绩
-说明：评价：基础172.5h，附加41.0h；客户流水¥95647.82，充值归因¥24000.00；头部客户(12月)Top3：葛先生、周周、T。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,57.45h,6,13.04h,20.92h
-11月,66.50h,11,12.02h,27.62h
-12月,48.58h,9,3.77h,7.49h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,11.00h,1,4.43h,3.00h
-11月,25.00h,1,16.20h,18.00h
-12月,5.00h,6,-5.27h,-3.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,33923.75,10,4644.22,3273.92
-11月,41907.39,10,-2347.00,8581.07
-12月,19816.68,8,-913.85,6176.04
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,15000.00,8,533.33,2000.00
-11月,9000.00,4,1230.77,0.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
-1,葛先生,1.1h / 0.0h,5551.79,0.00,0.9h / 0.0h,3052.28,0.00,0.0h / 0.0h,0.00,0.00
-2,周周,15.2h / 0.0h,4161.75,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-3,T,10.7h / 0.0h,3327.26,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-4,蔡总,8.5h / 0.0h,2130.39,0.00,3.4h / 0.0h,6196.43,0.00,0.0h / 0.0h,0.00,0.00
-5,罗先生,2.3h / 0.0h,1584.22,0.00,0.0h / 0.0h,0.00,0.00,1.4h / 0.0h,514.68,0.00
-6,候,5.3h / 0.0h,926.59,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-7,张先生,3.0h / 0.0h,876.46,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-8,李先生,0.0h / 0.0h,703.83,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-9,大G,1.8h / 0.0h,467.10,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-10,黄先生,0.6h / 5.0h,87.29,0.00,4.4h / 18.0h,828.62,0.00,11.0h / 9.0h,1608.13,0.00
-11,邓飛,0.0h / 0.0h,0.00,0.00,0.8h / 0.0h,925.47,1000.00,0.0h / 0.0h,0.00,0.00
-12,罗超杰,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,0.8h / 0.0h,176.14,0.00
-13,陈腾鑫,0.0h / 0.0h,0.00,0.00,25.1h / 0.0h,5150.83,0.00,6.1h / 2.0h,980.14,0.00
-14,叶先生,0.0h / 0.0h,0.00,0.00,6.7h / 0.0h,3013.86,0.00,0.0h / 0.0h,0.00,0.00
-15,歌神,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,2.6h / 0.0h,1929.19,0.00
-16,羊,0.0h / 0.0h,0.00,0.00,2.2h / 0.0h,383.40,0.00,3.1h / 0.0h,3620.75,0.00
-17,夏,0.0h / 0.0h,0.00,0.00,2.0h / 4.0h,370.12,0.00,2.5h / 0.0h,455.12,0.00
-18,轩哥,0.0h / 0.0h,0.00,0.00,11.2h / 0.0h,12063.93,5000.00,9.1h / 0.0h,9207.48,6000.00
-19,罗超,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,2.9h / 0.0h,2385.30,3000.00
-20,小熊,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,4.4h / 0.0h,709.18,0.00
-21,陈德韩,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,1.8h / 0.0h,5714.01,0.00
-22,刘哥,0.0h / 0.0h,0.00,0.00,2.0h / 0.0h,2982.34,0.00,0.0h / 0.0h,0.00,0.00
-23,桂先生,0.0h / 0.0h,0.00,0.00,2.6h / 0.0h,826.02,0.00,0.0h / 0.0h,0.00,0.00
-24,万先生,0.0h / 0.0h,0.00,0.00,0.0h / 3.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-25,吕先生,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,2.8h / 0.0h,2843.29,3000.00
-26,胡先生,0.0h / 0.0h,0.00,0.00,3.9h / 0.0h,5688.29,3000.00,0.0h / 0.0h,0.00,0.00
-27,江先生,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,2.7h / 0.0h,2740.35,3000.00
-28,小宇,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,1.5h / 0.0h,318.98,0.00
-29,陶,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,4.7h / 0.0h,721.01,0.00
-30,小燕,0.0h / 0.0h,0.00,0.00,1.4h / 0.0h,425.80,0.00,0.0h / 0.0h,0.00,0.00
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_球球.md b/etl_billiards/docs/table_2025-12-19/助教详情_球球.md
deleted file mode 100644
index de1e3ee..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_球球.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：球球（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础172.5h，附加41.0h；客户流水¥95647.82，充值归因¥24000.00；头部客户(12月)Top3：葛先生、周周、T。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_瑶瑶.csv b/etl_billiards/docs/table_2025-12-19/助教详情_瑶瑶.csv
deleted file mode 100644
index aef2879..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_瑶瑶.csv
+++ /dev/null
@@ -1,49 +0,0 @@
-助教详情：瑶瑶（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础53.7h，附加3.0h；客户流水¥72216.91，充值归因¥0.00；头部客户(12月)Top3：蔡总、轩哥、陈世。
-
-一、基础课业绩
-说明：评价：基础53.7h，附加3.0h；客户流水¥72216.91，充值归因¥0.00；头部客户(12月)Top3：蔡总、轩哥、陈世。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,34.25h,18,-20.23h,-4.63h
-12月,19.48h,15,-25.33h,-21.61h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,3.00h,5,-5.80h,-4.00h
-12月,0.00h,,0.00h,0.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,0.00,,0.00,0.00
-11月,65924.36,8,21669.97,32598.04
-12月,6292.55,17,-14437.98,-7348.10
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,0.00,,0.00,0.00
-11月,0.00,,0.00,0.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
-1,蔡总,19.5h / 0.0h,6292.55,0.00,20.3h / 2.0h,53735.58,0.00,0.0h / 0.0h,0.00,0.00
-2,轩哥,0.0h / 0.0h,0.00,0.00,9.3h / 1.0h,8137.22,0.00,0.0h / 0.0h,0.00,0.00
-3,陈世,0.0h / 0.0h,0.00,0.00,0.8h / 0.0h,139.15,0.00,0.0h / 0.0h,0.00,0.00
-4,游,0.0h / 0.0h,0.00,0.00,2.0h / 0.0h,3544.42,0.00,0.0h / 0.0h,0.00,0.00
-5,林先生,0.0h / 0.0h,0.00,0.00,1.9h / 0.0h,367.99,0.00,0.0h / 0.0h,0.00,0.00
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_瑶瑶.md b/etl_billiards/docs/table_2025-12-19/助教详情_瑶瑶.md
deleted file mode 100644
index 5a7271b..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_瑶瑶.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：瑶瑶（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础53.7h，附加3.0h；客户流水¥72216.91，充值归因¥0.00；头部客户(12月)Top3：蔡总、轩哥、陈世。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_璇子.csv b/etl_billiards/docs/table_2025-12-19/助教详情_璇子.csv
deleted file mode 100644
index cead2b0..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_璇子.csv
+++ /dev/null
@@ -1,56 +0,0 @@
-助教详情：璇子（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础358.9h，附加32.0h；客户流水¥301070.23，充值归因¥44700.00；头部客户(12月)Top3：轩哥、蔡总、江先生。
-
-一、基础课业绩
-说明：评价：基础358.9h，附加32.0h；客户流水¥301070.23，充值归因¥44700.00；头部客户(12月)Top3：轩哥、蔡总、江先生。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,120.20h,2,75.79h,83.67h
-11月,147.92h,2,93.44h,109.03h
-12月,90.75h,3,45.94h,49.66h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,8.00h,3,1.43h,0.00h
-11月,10.00h,3,1.20h,3.00h
-12月,14.00h,4,3.73h,6.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,80804.14,1,51524.61,50154.31
-11月,154486.83,1,110232.44,121160.51
-12月,65779.26,1,45048.73,52138.62
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,34700.00,1,20233.33,21700.00
-11月,10000.00,3,2230.77,1000.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
-1,轩哥,37.7h / 0.0h,28122.15,0.00,50.3h / 0.0h,46514.85,0.00,64.6h / 0.0h,53866.23,23000.00
-2,蔡总,18.3h / 0.0h,21216.97,0.00,49.9h / 0.0h,84757.28,5000.00,0.0h / 0.0h,0.00,0.00
-3,江先生,17.7h / 14.0h,10018.73,0.00,29.6h / 10.0h,14700.83,5000.00,15.2h / 8.0h,5637.50,3000.00
-4,林先生,9.6h / 0.0h,3351.61,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-5,罗先生,5.2h / 0.0h,1655.57,0.00,5.1h / 0.0h,1718.68,0.00,2.8h / 0.0h,1087.21,0.00
-6,君姐,2.2h / 0.0h,1414.23,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-7,游,0.0h / 0.0h,0.00,0.00,3.1h / 0.0h,3544.42,0.00,0.0h / 0.0h,0.00,0.00
-8,羊,0.0h / 0.0h,0.00,0.00,5.0h / 0.0h,1017.12,0.00,0.0h / 0.0h,0.00,0.00
-9,张先生,0.0h / 0.0h,0.00,0.00,4.9h / 0.0h,2233.65,0.00,5.4h / 0.0h,3211.91,0.00
-10,夏,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,7.6h / 0.0h,6452.71,0.00
-11,罗超,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,2.6h / 0.0h,2385.30,3000.00
-12,叶总,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,22.0h / 0.0h,8163.28,5700.00
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_璇子.md b/etl_billiards/docs/table_2025-12-19/助教详情_璇子.md
deleted file mode 100644
index 30e4c11..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_璇子.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：璇子（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础358.9h，附加32.0h；客户流水¥301070.23，充值归因¥44700.00；头部客户(12月)Top3：轩哥、蔡总、江先生。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_素素.csv b/etl_billiards/docs/table_2025-12-19/助教详情_素素.csv
deleted file mode 100644
index ce40957..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_素素.csv
+++ /dev/null
@@ -1,64 +0,0 @@
-助教详情：素素（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础85.5h，附加10.0h；客户流水¥55755.41，充值归因¥7000.00；头部客户(12月)Top3：叶先生、周先生、轩哥。
-
-一、基础课业绩
-说明：评价：基础85.5h，附加10.0h；客户流水¥55755.41，充值归因¥7000.00；头部客户(12月)Top3：叶先生、周先生、轩哥。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,40.45h,10,-3.96h,3.92h
-11月,35.03h,17,-19.44h,-3.85h
-12月,9.98h,19,-34.83h,-31.11h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,10.00h,3,1.20h,3.00h
-12月,0.00h,,0.00h,0.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,34135.89,9,4856.36,3486.06
-11月,18707.30,19,-25547.09,-14619.02
-12月,2912.22,19,-17818.31,-10728.42
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,6000.00,11,-8466.67,-7000.00
-11月,1000.00,9,-6769.23,-8000.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
-1,叶先生,3.0h / 0.0h,1558.40,0.00,7.0h / 3.0h,3725.65,0.00,15.1h / 0.0h,8807.20,3000.00
-2,周先生,6.2h / 0.0h,1065.70,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-3,轩哥,0.8h / 0.0h,288.12,0.00,0.0h / 0.0h,0.00,0.00,3.6h / 0.0h,8972.50,0.00
-4,邓飛,0.0h / 0.0h,0.00,0.00,0.8h / 0.0h,925.47,1000.00,0.0h / 0.0h,0.00,0.00
-5,罗超杰,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,1.9h / 0.0h,396.94,0.00
-6,陈腾鑫,0.0h / 0.0h,0.00,0.00,0.4h / 0.0h,152.18,0.00,2.1h / 0.0h,542.06,0.00
-7,谢俊,0.0h / 0.0h,0.00,0.00,2.4h / 0.0h,417.75,0.00,0.0h / 0.0h,0.00,0.00
-8,罗先生,0.0h / 0.0h,0.00,0.00,4.7h / 0.0h,861.57,0.00,0.0h / 0.0h,0.00,0.00
-9,葛先生,0.0h / 0.0h,0.00,0.00,9.1h / 0.0h,4668.26,0.00,0.0h / 0.0h,0.00,0.00
-10,歌神,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,3.9h / 0.0h,2789.21,0.00
-11,羊,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,4.3h / 0.0h,3620.75,0.00
-12,张先生,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,1.1h / 0.0h,449.93,0.00
-13,都先生,0.0h / 0.0h,0.00,0.00,1.6h / 0.0h,269.64,0.00,0.0h / 0.0h,0.00,0.00
-14,夏,0.0h / 0.0h,0.00,0.00,0.8h / 4.0h,2991.13,0.00,0.0h / 0.0h,0.00,0.00
-15,罗先生,0.0h / 0.0h,0.00,0.00,4.3h / 0.0h,1856.86,0.00,0.0h / 0.0h,0.00,0.00
-16,陈德韩,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,5.5h / 0.0h,5714.01,0.00
-17,吕先生,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,2.8h / 0.0h,2843.29,3000.00
-18,万先生,0.0h / 0.0h,0.00,0.00,0.0h / 3.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-19,阿亮,0.0h / 0.0h,0.00,0.00,3.1h / 0.0h,484.40,0.00,0.0h / 0.0h,0.00,0.00
-20,胡先生,0.0h / 0.0h,0.00,0.00,0.8h / 0.0h,2354.39,0.00,0.0h / 0.0h,0.00,0.00
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_素素.md b/etl_billiards/docs/table_2025-12-19/助教详情_素素.md
deleted file mode 100644
index 5480ae0..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_素素.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：素素（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础85.5h，附加10.0h；客户流水¥55755.41，充值归因¥7000.00；头部客户(12月)Top3：叶先生、周先生、轩哥。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_苏苏.csv b/etl_billiards/docs/table_2025-12-19/助教详情_苏苏.csv
deleted file mode 100644
index 07c011a..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_苏苏.csv
+++ /dev/null
@@ -1,58 +0,0 @@
-助教详情：苏苏（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础82.6h，附加9.0h；客户流水¥33952.79，充值归因¥6000.00；头部客户(12月)Top3：罗先生、T、林先生。
-
-一、基础课业绩
-说明：评价：基础82.6h，附加9.0h；客户流水¥33952.79，充值归因¥6000.00；头部客户(12月)Top3：罗先生、T、林先生。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,25.15h,12,-19.26h,-11.38h
-11月,13.52h,23,-40.96h,-25.37h
-12月,43.90h,11,-0.91h,2.81h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,8.00h,3,1.43h,0.00h
-11月,0.00h,,0.00h,0.00h
-12月,1.00h,9,-9.27h,-7.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,11236.84,15,-18042.69,-19412.99
-11月,10254.59,22,-33999.80,-23071.73
-12月,12461.36,14,-8269.17,-1179.28
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,6000.00,11,-8466.67,-7000.00
-11月,0.00,,0.00,0.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
-1,罗先生,19.6h / 0.0h,6061.87,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-2,T,4.5h / 0.0h,1429.89,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-3,林先生,4.9h / 0.0h,1369.86,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-4,黄先生,8.1h / 1.0h,1357.90,0.00,4.0h / 0.0h,674.36,0.00,11.2h / 4.0h,1960.96,0.00
-5,张先生,3.9h / 0.0h,1163.40,0.00,0.0h / 0.0h,0.00,0.00,6.4h / 0.0h,3604.02,0.00
-6,葛先生,2.5h / 0.0h,1004.77,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-7,候,0.4h / 0.0h,73.67,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-8,罗超,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,2.6h / 0.0h,2385.30,3000.00
-9,罗超杰,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,2.1h / 0.0h,443.27,0.00
-10,蔡总,0.0h / 0.0h,0.00,0.00,4.7h / 0.0h,6557.92,0.00,0.0h / 0.0h,0.00,0.00
-11,吕先生,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,2.8h / 0.0h,2843.29,3000.00
-12,林先生,0.0h / 0.0h,0.00,0.00,3.1h / 0.0h,2398.29,0.00,0.0h / 0.0h,0.00,0.00
-13,邓飛,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 4.0h,0.00,0.00
-14,昌哥,0.0h / 0.0h,0.00,0.00,1.6h / 0.0h,624.02,0.00,0.0h / 0.0h,0.00,0.00
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_苏苏.md b/etl_billiards/docs/table_2025-12-19/助教详情_苏苏.md
deleted file mode 100644
index 3d21174..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_苏苏.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：苏苏（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础82.6h，附加9.0h；客户流水¥33952.79，充值归因¥6000.00；头部客户(12月)Top3：罗先生、T、林先生。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_西子.csv b/etl_billiards/docs/table_2025-12-19/助教详情_西子.csv
deleted file mode 100644
index 2e02cd3..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_西子.csv
+++ /dev/null
@@ -1,45 +0,0 @@
-助教详情：西子（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础1.8h，附加0.0h；客户流水¥303.51，充值归因¥0.00；头部客户(12月)Top3：张先生。
-
-一、基础课业绩
-说明：评价：基础1.8h，附加0.0h；客户流水¥303.51，充值归因¥0.00；头部客户(12月)Top3：张先生。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,1.82h,26,-52.66h,-37.07h
-12月,0.00h,,0.00h,0.00h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,0.00h,,0.00h,0.00h
-12月,0.00h,,0.00h,0.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,0.00,,0.00,0.00
-11月,303.51,26,-43950.88,-33022.81
-12月,0.00,,0.00,0.00
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,0.00,,0.00,0.00
-11月,0.00,,0.00,0.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
-1,张先生,0.0h / 0.0h,0.00,0.00,1.8h / 0.0h,303.51,0.00,0.0h / 0.0h,0.00,0.00
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_西子.md b/etl_billiards/docs/table_2025-12-19/助教详情_西子.md
deleted file mode 100644
index 43e0809..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_西子.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：西子（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础1.8h，附加0.0h；客户流水¥303.51，充值归因¥0.00；头部客户(12月)Top3：张先生。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_阿清.csv b/etl_billiards/docs/table_2025-12-19/助教详情_阿清.csv
deleted file mode 100644
index 3c1cd86..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_阿清.csv
+++ /dev/null
@@ -1,55 +0,0 @@
-助教详情：阿清（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础139.9h，附加0.0h；客户流水¥53805.04，充值归因¥0.00；头部客户(12月)Top3：陈腾鑫、葛先生、梅。
-
-一、基础课业绩
-说明：评价：基础139.9h，附加0.0h；客户流水¥53805.04，充值归因¥0.00；头部客户(12月)Top3：陈腾鑫、葛先生、梅。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,73.48h,8,19.01h,34.60h
-12月,66.45h,5,21.64h,25.36h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,0.00h,,0.00h,0.00h
-12月,0.00h,,0.00h,0.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,0.00,,0.00,0.00
-11月,37302.04,13,-6952.35,3975.72
-12月,16503.00,10,-4227.53,2862.36
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,0.00,,0.00,0.00
-11月,0.00,,0.00,0.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
-1,陈腾鑫,34.9h / 0.0h,7428.12,0.00,44.4h / 0.0h,10029.58,0.00,0.0h / 0.0h,0.00,0.00
-2,葛先生,7.9h / 0.0h,2831.40,0.00,19.7h / 0.0h,7141.04,0.00,0.0h / 0.0h,0.00,0.00
-3,梅,7.5h / 0.0h,2086.99,0.00,3.3h / 0.0h,1573.10,0.00,0.0h / 0.0h,0.00,0.00
-4,张先生,7.2h / 0.0h,1794.40,0.00,1.0h / 0.0h,679.31,0.00,0.0h / 0.0h,0.00,0.00
-5,清,3.0h / 0.0h,1128.06,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-6,候,4.2h / 0.0h,773.51,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-7,常总,1.7h / 0.0h,460.52,0.00,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00
-8,轩哥,0.0h / 0.0h,0.00,0.00,1.0h / 0.0h,10078.85,0.00,0.0h / 0.0h,0.00,0.00
-9,黄先生,0.0h / 0.0h,0.00,0.00,0.7h / 0.0h,382.08,0.00,0.0h / 0.0h,0.00,0.00
-10,蔡总,0.0h / 0.0h,0.00,0.00,1.5h / 0.0h,6557.92,0.00,0.0h / 0.0h,0.00,0.00
-11,小燕,0.0h / 0.0h,0.00,0.00,2.0h / 0.0h,860.16,0.00,0.0h / 0.0h,0.00,0.00
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_阿清.md b/etl_billiards/docs/table_2025-12-19/助教详情_阿清.md
deleted file mode 100644
index 0c79f34..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_阿清.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：阿清（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础139.9h，附加0.0h；客户流水¥53805.04，充值归因¥0.00；头部客户(12月)Top3：陈腾鑫、葛先生、梅。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_饭团.csv b/etl_billiards/docs/table_2025-12-19/助教详情_饭团.csv
deleted file mode 100644
index 4a01a9e..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_饭团.csv
+++ /dev/null
@@ -1,46 +0,0 @@
-助教详情：饭团（2025年10-12月）
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。评价：基础16.0h，附加0.0h；客户流水¥7955.28，充值归因¥0.00；头部客户(12月)Top3：轩哥、张先生。
-
-一、基础课业绩
-说明：评价：基础16.0h，附加0.0h；客户流水¥7955.28，充值归因¥0.00；头部客户(12月)Top3：轩哥、张先生。
-
-月份,基础课业绩,基础课业绩,基础课业绩,基础课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,16.00h,16,-28.41h,-20.53h
-11月,0.00h,,0.00h,0.00h
-12月,0.00h,,0.00h,0.00h
-
-二、附加课业绩
-说明：附加课=order_assistant_type=2。
-
-月份,附加课业绩,附加课业绩,附加课业绩,附加课业绩
-月份,小时数,排名,平均值差值小时数,中位数值差值小时数
-10月,0.00h,,0.00h,0.00h
-11月,0.00h,,0.00h,0.00h
-12月,0.00h,,0.00h,0.00h
-
-三、客户消费业绩
-说明：订单台费+助教+商品应付金额全额计入订单内助教。
-
-月份,客户消费业绩,客户消费业绩,客户消费业绩,客户消费业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,7955.28,16,-21324.25,-22694.55
-11月,0.00,,0.00,0.00
-12月,0.00,,0.00,0.00
-
-四、客户充值业绩
-说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。
-
-月份,客户充值业绩,客户充值业绩,客户充值业绩,客户充值业绩
-月份,合计元,排名,平均值差值元,中位数值差值元
-10月,0.00,,0.00,0.00
-11月,0.00,,0.00,0.00
-12月,0.00,,0.00,0.00
-
-五、头部客户（按12月消费业绩排序，Top100）
-说明：基础/附加课时=基础h/附加h。
-
-排名,客户名称,12月,12月,12月,11月,11月,11月,10月,10月,10月
-排名,客户名称,基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元),基础/附加课时,消费业绩(元),客户充值(元)
-1,轩哥,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,6.9h / 0.0h,5089.50,0.00
-2,张先生,0.0h / 0.0h,0.00,0.00,0.0h / 0.0h,0.00,0.00,9.1h / 0.0h,2865.78,0.00
diff --git a/etl_billiards/docs/table_2025-12-19/助教详情_饭团.md b/etl_billiards/docs/table_2025-12-19/助教详情_饭团.md
deleted file mode 100644
index e47ee2e..0000000
--- a/etl_billiards/docs/table_2025-12-19/助教详情_饭团.md
+++ /dev/null
@@ -1,196 +0,0 @@
-# 助教详情：饭团（2025年10-12月）
-## 思考过程
-按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。
-
-## 查询说明
-本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。均值/中位数差值对比集合为当月该指标>0的助教。充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。
-评价：基础16.0h，附加0.0h；客户流水¥7955.28，充值归因¥0.00；头部客户(12月)Top3：轩哥、张先生。
-
-## SQL
-
-### 服务时长（助教-客户-月份）
-```sql
-with raw as (
-  select
-    asl.nickname as assistant,
-    asl.tenant_member_id as member_id,
-    case when asl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when asl.start_use_time >= '2025-11-01 00:00:00+08'::timestamptz and asl.start_use_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz and asl.start_use_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    asl.order_assistant_type,
-    asl.income_seconds
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-    and asl.tenant_member_id is not null and asl.tenant_member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
-  sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 客户流水（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_amount as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    bo.order_start_time,
-    bo.order_end_time,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_amount a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-raw as (
-  select
-    ao.assistant,
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  join assistant_orders ao on ao.order_settle_id=o.order_settle_id
-  where o.member_id is not null and o.member_id<>0
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(order_amount) as revenue_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
-
-### 充值归因（助教-客户-月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as table_start_time,
-    max(tfl.ledger_end_time) as table_end_time
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_time as (
-  select
-    asl.order_settle_id,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id=asl.order_settle_id
-  where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
-  group by asl.order_settle_id
-),
-order_windows as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
-    greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
-  from base_orders bo
-  left join assistant_time at on at.order_settle_id=bo.order_settle_id
-  where bo.member_id is not null and bo.member_id<>0
-),
-assistant_orders as (
-  select distinct order_settle_id, nickname as assistant
-  from billiards_dwd.dwd_assistant_service_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz
-    and start_use_time <  %(window_end)s::timestamptz
-),
-recharge_pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
-  where p.site_id=%(site_id)s
-    and p.relate_type=5
-    and p.pay_status=2
-    and p.pay_amount>0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-),
-matched as (
-  select
-    rp.pay_time,
-    ow.order_settle_id,
-    ow.member_id,
-    rp.pay_amount
-  from recharge_pay rp
-  join order_windows ow
-    on ow.member_id=rp.member_id
-   and rp.pay_time >= ow.win_start - interval '30 minutes'
-   and rp.pay_time <= ow.win_end   + interval '30 minutes'
-),
-raw as (
-  select
-    ao.assistant,
-    m.member_id,
-    case when m.pay_time >= '2025-10-01 00:00:00+08'::timestamptz and m.pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when m.pay_time >= '2025-11-01 00:00:00+08'::timestamptz and m.pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when m.pay_time >= '2025-12-01 00:00:00+08'::timestamptz and m.pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    m.pay_amount
-  from matched m
-  join assistant_orders ao on ao.order_settle_id=m.order_settle_id
-)
-select
-  assistant,
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_amount
-from raw
-where month_key is not null
-group by assistant, member_id, month_key;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/客户_Top100_2025年10-12月_分表.csv b/etl_billiards/docs/table_2025-12-19/客户_Top100_2025年10-12月_分表.csv
deleted file mode 100644
index d0a15d3..0000000
--- a/etl_billiards/docs/table_2025-12-19/客户_Top100_2025年10-12月_分表.csv
+++ /dev/null
@@ -1,105 +0,0 @@
-2025年10-12月 客户消费能力Top100（分表）
-与总表同口径；分表仅计算12月喜爱助教Top5，并展示10-12月各月消费/充值。
-
-排名,客户名称,电话号码,12月,12月,12月,11月,11月,10月,10月
-排名,客户名称,电话号码,喜爱助教昵称,消费(元),充值(元),消费(元),充值(元),消费(元),充值(元)
-    1,轩哥,188****7530,七七(65.8h)、璇子(37.7h)、涛涛(10.8h)、Amy(8.8h)、小柔(8.4h),29170.33,0.00,51318.11,13000.00,72647.61,53000.00
-    2,蔡总,159****8893,小柔(30.2h)、七七(26.7h)、瑶瑶(19.5h)、璇子(18.3h)、涛涛(15.1h),34327.09,0.00,115512.37,5000.00,0.00,0.00
-    3,葛先生,138****8071,小燕(104.8h)、阿清(7.9h)、涛涛(5.9h)、梦梦(2.9h)、年糕(2.6h),23237.78,0.00,24991.55,0.00,0.00,0.00
-    4,罗先生,139****6996,佳怡(73.8h)、苏苏(19.6h)、璇子(5.3h)、周周(2.6h)、球球(2.3h),17515.75,0.00,16177.44,0.00,12880.69,10000.00
-    5,陈腾鑫,178****8218,阿清(34.9h)、小侯(12.1h)、千千(4.9h)、小柔(1.7h),10701.83,0.00,19428.27,1000.00,9945.66,8000.00
-    6,江先生,188****4838,璇子(38.7h)、婉婉(4.7h)、小柔(3.2h)、七七(3.2h)、Amy(2.2h),10050.26,0.00,14700.83,5000.00,5721.32,6000.00
-    7,小燕,178****1334,小燕(85.7h)、Amy(1.0h)、年糕(0.5h),17306.66,0.00,12582.23,0.00,0.00,0.00
-    8,张先生,139****8852,小侯(14.5h)、千千(10.0h)、阿清(7.2h)、苏苏(3.9h)、乔西(3.3h),7533.67,0.00,8692.62,0.00,9878.04,0.00
-    9,曾巧明,186****1488,,6331.51,0.00,8821.59,0.00,9677.06,0.00
-    10,黄生,136****9719,,4181.24,0.00,6353.05,0.00,7871.94,0.00
-    11,夏,191****2851,,0.00,0.00,4318.15,6000.00,12281.44,11000.00
-    12,叶先生,138****9539,素素(3.1h)、年糕(2.6h),1658.40,0.00,3725.65,0.00,9107.20,6307.00
-    13,T,180****9962,球球(10.7h)、周周(10.1h)、乔西(6.9h)、苏苏(4.5h)、小侯(3.9h),6777.66,0.00,2490.70,0.00,4382.70,3000.00
-    14,林先生,133****1070,七七(14.0h)、璇子(9.6h)、苏苏(4.9h)、乔西(4.6h)、佳怡(4.5h),9468.05,0.00,3469.81,0.00,0.00,0.00
-    15,曾丹烨,139****3242,,2485.41,0.00,5168.56,0.00,4702.36,3000.00
-    16,胡先生,186****3391,佳怡(3.0h),522.45,0.00,10898.42,8000.00,0.00,0.00
-    17,艾宇民,150****9958,,1179.56,0.00,7185.78,0.00,2397.73,0.00
-    18,谢俊,186****5198,,969.66,0.00,4819.27,0.00,4193.93,0.00
-    19,周周,198****8725,周周(40.8h)、球球(15.2h)、佳怡(13.2h),8905.19,0.00,0.00,0.00,0.00,0.00
-    20,叶总,137****3287,,0.00,0.00,0.00,0.00,8163.28,5700.00
-    21,羊,187****5094,,0.00,0.00,4534.79,16000.00,3620.75,48000.00
-    22,游,172****6666,佳怡(3.2h)、周周(2.4h)、千千(2.2h)、QQ(1.2h),2795.90,0.00,5001.47,0.00,0.00,0.00
-    23,桂先生,166****7275,,606.24,0.00,4788.94,0.00,2283.11,985.00
-    24,明哥,166****0999,婉婉(26.7h)、小柔(25.7h)、年糕(4.6h)、周周(0.4h)、Amy(0.1h),5322.90,0.00,2258.14,0.00,0.00,0.00
-    25,陈德韩,134****7864,,20.00,0.00,0.00,0.00,7282.92,5000.00
-    26,小熊,139****0145,,0.00,0.00,5213.64,4000.00,1922.24,1000.00
-    27,黄先生,135****3507,苏苏(9.6h)、千千(6.2h),2506.04,0.00,1926.28,0.00,2620.40,3000.00
-    28,吕先生,155****0663,,0.00,0.00,0.00,0.00,7012.05,6000.00
-    29,郑先生,159****4331,小敌(4.9h),1614.93,0.00,4823.14,0.00,0.00,0.00
-    30,歌神,188****2164,,0.00,0.00,0.00,0.00,5877.65,5000.00
-    31,罗先生,139****9222,婉婉(7.5h)、小柔(4.5h),0.00,0.00,4687.61,0.00,1143.87,3000.00
-    32,大G,186****4598,周周(14.9h)、佳怡(9.5h)、球球(1.9h),3591.07,0.00,1783.61,0.00,0.00,0.00
-    33,林先生,137****8785,,480.91,0.00,4486.47,0.00,0.00,0.00
-    34,梅,136****4552,千千(10.8h)、阿清(7.5h)、小侯(3.3h),2483.11,0.00,2107.81,0.00,0.00,0.00
-    35,李先生,134****4343,小侯(9.3h)、球球(0.0h),2395.25,0.00,2084.52,0.00,0.00,0.00
-    36,陶,189****2151,,0.00,0.00,0.00,0.00,4096.07,6000.00
-    37,陈先生,159****2829,,0.00,0.00,3717.58,3000.00,100.00,0.00
-    38,候,131****0323,球球(5.3h)、阿清(4.3h)、小侯(3.4h)、涛涛(3.1h)、乔西(2.9h),3765.88,0.00,0.00,0.00,0.00,0.00
-    39,黄先生,158****2109,球球(8.1h)、QQ(4.5h),300.15,0.00,1660.64,0.00,1608.13,3000.00
-    40,孟紫龙,176****3741,,2888.95,0.00,603.78,0.00,0.00,0.00
-    41,罗超,137****0990,,0.00,0.00,0.00,0.00,3398.81,3000.00
-    42,君姐,166****4594,璇子(2.3h)、涛涛(2.2h)、年糕(2.2h),1414.23,0.00,1947.72,0.00,0.00,0.00
-    43,吴生,136****3341,,368.03,0.00,1721.17,0.00,1164.50,0.00
-    44,刘哥,135****0020,婉婉(0.3h),54.46,0.00,2982.34,0.00,0.00,0.00
-    45,李先生,131****4000,,0.00,0.00,2997.53,3000.00,0.00,0.00
-    46,阿亮,159****2628,涛涛(2.9h)、梦梦(2.7h),1133.53,0.00,1802.73,0.00,0.00,0.00
-    47,李先生,186****8308,,0.00,0.00,2785.23,0.00,0.00,0.00
-    48,周先生,173****7775,,0.00,0.00,0.00,0.00,2726.01,0.00
-    49,林先生,159****0021,,0.00,0.00,2690.52,0.00,0.00,0.00
-    50,周先生,193****6822,千千(8.6h)、素素(6.2h),2643.64,0.00,0.00,0.00,0.00,0.00
-    51,林先生,188****0332,,0.00,0.00,2612.01,0.00,0.00,0.00
-    52,牛先生,152****5159,,0.00,0.00,2187.48,0.00,0.00,0.00
-    53,孟紫龙（该会员已注销）,176****37411,,0.00,0.00,300.00,0.00,1831.72,0.00
-    54,罗超杰,137****8012,,0.00,0.00,423.70,0.00,1160.35,0.00
-    55,汪先生,139****6339,,0.00,0.00,0.00,0.00,1390.07,1000.00
-    56,桂先生（该会员已注销）,166****72751,,0.00,0.00,0.00,0.00,1370.81,0.00
-    57,方先生,153****3185,,0.00,0.00,414.57,0.00,898.73,1000.00
-    58,陈淑涛,132****5485,,0.00,0.00,1276.77,0.00,0.00,0.00
-    59,清,130****3087,阿清(3.0h)、千千(3.0h)、小侯(3.0h),1128.06,0.00,0.00,0.00,0.00,0.00
-    60,amy,137****8221,Amy(4.8h),1105.90,0.00,0.00,0.00,0.00,0.00
-    61,曾先生,133****1235,,193.90,0.00,700.09,0.00,97.35,0.00
-    62,昌哥,137****1229,小柔(1.8h),318.40,0.00,624.02,0.00,0.00,0.00
-    63,李,131****9882,,0.00,0.00,320.99,0.00,606.45,0.00
-    64,邓飛,136****9597,,0.00,0.00,925.47,1000.00,0.00,1345.00
-    65,陈世,134****1938,,0.00,0.00,502.07,0.00,419.02,0.00
-    66,婉婉,183****2742,,0.00,0.00,242.81,0.00,624.68,1000.00
-    67,贺斌,150****0885,,0.00,0.00,108.29,0.00,662.27,0.00
-    68,陈泽斌,132****6060,,100.00,0.00,500.00,0.00,100.00,0.00
-    69,林总,138****1180,,0.00,0.00,684.44,0.00,0.00,0.00
-    70,卢广贤,186****6220,,128.86,0.00,288.51,0.00,263.07,0.00
-    71,王龙,186****8011,,669.58,0.00,0.00,0.00,0.00,0.00
-    72,王先生,185****1125,,183.75,0.00,416.93,0.00,0.00,0.00
-    73,潘先生,186****0511,年糕(2.0h),564.93,0.00,0.00,0.00,0.00,0.00
-    74,老宋,138****4554,,0.00,0.00,465.98,0.00,75.99,0.00
-    75,郭先生,156****5001,,0.00,0.00,281.22,0.00,237.13,0.00
-    76,孙启明,137****6325,,0.00,0.00,200.00,0.00,300.00,0.00
-    77,王先生,136****0168,,100.00,0.00,400.00,0.00,0.00,0.00
-    78,黎先生,133****0983,,0.00,0.00,0.00,0.00,470.19,0.00
-    79,常总,185****7188,阿清(1.7h)、年糕(1.7h),460.52,0.00,0.00,0.00,0.00,0.00
-    80,张丹逸,136****6637,,100.00,0.00,0.00,0.00,339.36,0.00
-    81,陈先生,186****8238,,0.00,0.00,416.17,0.00,0.00,0.00
-    82,陈先生,138****3964,,100.00,0.00,0.00,0.00,300.00,0.00
-    83,张先生,136****4528,,298.35,0.00,100.00,0.00,0.00,0.00
-    84,小宇,187****8077,,0.00,0.00,0.00,0.00,397.50,0.00
-    85,黄先生,191****8219,,0.00,0.00,364.33,0.00,0.00,0.00
-    86,刘女士,177****7538,,0.00,0.00,0.00,0.00,362.58,0.00
-    87,魏先生,137****6862,,319.39,0.00,0.00,0.00,0.00,0.00
-    88,杜先生,188****4705,,0.00,0.00,207.47,0.00,100.00,0.00
-    89,刘先生,137****2930,,300.00,0.00,0.00,0.00,0.00,0.00
-    90,陈先生,133****6117,,0.00,0.00,300.00,0.00,0.00,0.00
-    91,潘先生,176****7964,,300.00,0.00,0.00,0.00,0.00,0.00
-    92,钟智豪,188****2803,,0.00,0.00,274.34,0.00,0.00,0.00
-    93,都先生,138****7796,,0.00,0.00,269.64,0.00,0.00,0.00
-    94,林志铭,135****4233,,0.00,0.00,267.96,0.00,0.00,0.00
-    95,方先生,158****6447,,148.00,0.00,100.00,0.00,0.00,0.00
-    96,李先生,176****5124,,0.00,0.00,0.00,0.00,244.00,0.00
-    97,钟先生,132****3438,,0.00,0.00,0.00,0.00,239.37,0.00
-    98,杨,130****5960,,232.00,0.00,0.00,0.00,0.00,0.00
-    99,黄国磊,131****3045,,100.00,0.00,100.00,0.00,25.33,0.00
-    100,周先生,159****9997,,100.00,0.00,100.00,0.00,0.00,0.00
diff --git a/etl_billiards/docs/table_2025-12-19/客户_Top100_2025年10-12月_分表.md b/etl_billiards/docs/table_2025-12-19/客户_Top100_2025年10-12月_分表.md
deleted file mode 100644
index 8c2578b..0000000
--- a/etl_billiards/docs/table_2025-12-19/客户_Top100_2025年10-12月_分表.md
+++ /dev/null
@@ -1,199 +0,0 @@
-# 2025年10-12月 客户消费能力Top100（分表）
-## 思考过程
-以台费订单为基准汇总三类明细，满足应付金额口径，并输出Top100客户的消费/充值/助教偏好。按你的要求，先生成评价为空的版本，再在脚本末尾回填评价。
-
-## 查询说明
-与总表同口径；分表仅计算12月喜爱助教Top5，并展示10-12月各月消费/充值。
-
-## SQL
-
-### Top100（按消费总额）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount,
-    sum(tfl.real_table_use_seconds) as table_use_seconds
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_info as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.order_start_time, coalesce(a.assistant_start_time, bo.order_start_time)) as order_start_time,
-    greatest(bo.order_end_time, coalesce(a.assistant_end_time, bo.order_end_time)) as order_end_time,
-    bo.table_use_seconds,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_info a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-select
-  o.member_id,
-  sum(o.order_amount) as consume_total,
-  count(*) as order_cnt
-from orders o
-where o.member_id is not null and o.member_id <> 0
-group by o.member_id
-order by consume_total desc
-limit 100;
-```
-
-### 按月消费汇总
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount,
-    sum(tfl.real_table_use_seconds) as table_use_seconds
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_info as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.order_start_time, coalesce(a.assistant_start_time, bo.order_start_time)) as order_start_time,
-    greatest(bo.order_end_time, coalesce(a.assistant_end_time, bo.order_end_time)) as order_end_time,
-    bo.table_use_seconds,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_info a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, x as (
-  select
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  where o.member_id is not null and o.member_id <> 0
-)
-select
-  member_id,
-  month_key,
-  sum(order_amount) as consume_sum
-from x
-where month_key is not null
-group by member_id, month_key;
-```
-
-### 按月充值汇总
-```sql
-with pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id = p.relate_id
-  where p.site_id = %(site_id)s
-    and p.relate_type = 5
-    and p.pay_status = 2
-    and p.pay_amount > 0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-)
-, x as (
-  select
-    member_id,
-    case when pay_time >= '2025-10-01 00:00:00+08'::timestamptz and pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when pay_time >= '2025-11-01 00:00:00+08'::timestamptz and pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when pay_time >= '2025-12-01 00:00:00+08'::timestamptz and pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    pay_amount
-  from pay
-)
-select
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_sum
-from x
-where month_key is not null
-group by member_id, month_key;
-```
-
-### 喜爱助教Top5（仅12月）
-```sql
-with x as (
-  select
-    asl.tenant_member_id as member_id,
-    asl.nickname as assistant_nickname,
-    sum(case when asl.order_assistant_type=1 then asl.income_seconds else asl.income_seconds*1.5 end) / 3600.0 as weighted_hours
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0)=0
-    and asl.tenant_member_id is not null and asl.tenant_member_id <> 0
-    and asl.start_use_time >= '2025-12-01 00:00:00+08'::timestamptz
-    and asl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by asl.tenant_member_id, asl.nickname
-),
-ranked as (
-  select *, row_number() over(partition by member_id order by weighted_hours desc) as rn
-  from x
-)
-select
-  member_id,
-  string_agg(assistant_nickname || '(' || to_char(round(weighted_hours::numeric, 1), 'FM999999990.0') || 'h)', '、' order by weighted_hours desc) as fav5
-from ranked
-where rn <= 5
-group by member_id;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/客户_Top100_2025年10-12月_总表.csv b/etl_billiards/docs/table_2025-12-19/客户_Top100_2025年10-12月_总表.csv
deleted file mode 100644
index eea0105..0000000
--- a/etl_billiards/docs/table_2025-12-19/客户_Top100_2025年10-12月_总表.csv
+++ /dev/null
@@ -1,105 +0,0 @@
-2025年10-12月 客户消费能力Top100（总表）
-"消费=台费(dwd_table_fee_log.ledger_amount)+助教(dwd_assistant_service_log.ledger_amount)+商品(dwd_store_goods_sale.ledger_amount)，均为应付金额（不扣优惠），以台费订单为基准串联；充值=充值支付流水(dwd_payment.relate_type=5, pay_status=2, pay_amount>0)按支付时间切月；储值卡未使用金额=当前有效储值卡余额之和(dim_member_card_account.balance, member_card_type_name='储值卡')；喜爱助教=基础课时长+附加课时长*1.5（income_seconds换算小时），总表按10-12月汇总Top5。"
-
-排名,客户名称,电话号码,10月-12月,10月-12月,10月-12月,当前,评价
-排名,客户名称,电话号码,喜爱助教昵称,总消费(元),总充值(元),储值卡未使用金额(元),评价
-1,轩哥,188****7530,璇子(152.6h)、七七(129.6h)、涛涛(72.7h)、小敌(54.3h)、佳怡(50.6h),153136.05,66000.00,6050.80,订单：53单，平均单次¥2889.36；打球：279.0h，平均单次5.3h；偏好：666(54.4%)、发财(13.7%)、包厢(6.5%)、A区(5.9%)；时间：到店均值16:43 中位19:21；离店均值22:31 中位次日01:03；商品：荷花双中支×56(¥3808.00)、细和天下×21(¥2625.00)、100  和成天下×13(¥1495.00)、农夫山泉苏打水×211(¥1266.00)、红牛×101(¥1010.00)、双中支中华×14(¥1008.00)（商品合计¥26812.00 占比17.5%）；综合：10-12月到店消费40天/53次，到店周期中位#1，消费排名#1，在店时长#3；12月到店消费8天/9次，到店周期中位#1，消费排名#1，在店时长#7；最近到店2025-12-18；趋势：10-12月到店频次下降，建议重点唤醒；围客与客户运营建议：重点维护包厢/团建需求，提前锁档与套餐化；商品贡献高，可做常购商品补货提醒与组合促销
-2,蔡总,159****8893,小柔(97.0h)、七七(72.4h)、璇子(68.2h)、涛涛(43.5h)、瑶瑶(42.8h),149839.46,5000.00,2016.18,订单：23单，平均单次¥6514.76；打球：180.4h，平均单次7.8h；偏好：发财(79.2%)、666(6.5%)、A区(4.3%)、补时长(2.8%)；时间：到店均值18:05 中位20:12；离店均值次日02:58 中位次日04:48；商品：钻石荷花×100(¥4685.00)、细和天下×30(¥3750.00)、粗和天下×24(¥3000.00)、100  和成天下×20(¥2300.00)、双中支中华×31(¥2232.00)、荷花双中支×29(¥2008.00)（商品合计¥37968.00 占比25.3%）；综合：10-12月到店消费22天/23次，到店周期中位#2，消费排名#2，在店时长#8；12月到店消费8天/8次，到店周期中位#1，消费排名#2，在店时长#10；最近到店2025-12-15；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：商品贡献高，可做常购商品补货提醒与组合促销
-3,葛先生,138****8071,小燕(158.3h)、阿清(27.6h)、千千(14.4h)、周周(11.0h)、年糕(9.4h),48229.33,0.00,9011.19,订单：42单，平均单次¥1148.32；打球：180.6h，平均单次4.3h；偏好：TV台(43.8%)、A区(21.2%)、包厢(20.6%)、S区/斯诺克(6.7%)；时间：到店均值14:01 中位19:40；离店均值18:19 中位21:54；商品：百威235毫升×72(¥1080.00)、卡士×33(¥726.00)、风花雪月×36(¥576.00)、细荷花×7(¥370.00)、蜂蜜水×36(¥360.00)、东方树叶×39(¥312.00)（商品合计¥5432.00 占比11.3%）；综合：10-12月到店消费25天/42次，到店周期中位#1，消费排名#3，在店时长#7；12月到店消费11天/24次，到店周期中位#1，消费排名#3，在店时长#2；最近到店2025-12-19；趋势：10-12月到店频次上升，12月更活跃；围客与客户运营建议：重点维护包厢/团建需求，提前锁档与套餐化；商品贡献高，可做常购商品补货提醒与组合促销
-4,罗先生,139****6996,佳怡(205.2h)、苏苏(19.6h)、璇子(13.2h)、周周(11.6h)、涛涛(10.5h),46573.88,10000.00,585.35,订单：86单，平均单次¥541.56；打球：212.7h，平均单次2.5h；偏好：TV台(39.2%)、C区(31.8%)、M7(7.8%)、麻将(5.8%)；时间：到店均值15:24 中位18:18；离店均值18:05 中位20:27；商品：百威235毫升×94(¥1410.00)、东方树叶×39(¥312.00)、细荷花×6(¥300.00)、荷花双中支×4(¥276.00)、中支芙蓉王×6(¥228.00)、哇哈哈矿泉水×38(¥190.00)（商品合计¥4390.00 占比9.4%）；综合：10-12月到店消费59天/86次，到店周期中位#1，消费排名#4，在店时长#5；12月到店消费17天/25次，到店周期中位#1，消费排名#4，在店时长#5；最近到店2025-12-18；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：商品贡献高，可做常购商品补货提醒与组合促销
-5,陈腾鑫,178****8218,阿清(79.2h)、佳怡(57.7h)、球球(34.2h)、小侯(19.1h)、千千(7.7h),40075.76,9000.00,0.00,订单：93单，平均单次¥430.92；打球：207.0h，平均单次2.2h；偏好：麻将(25.0%)、C区(18.7%)、TV台(13.6%)、包厢(11.4%)；时间：到店均值17:33 中位20:09；离店均值19:45 中位22:28；商品：百威235毫升×27(¥405.00)、东方树叶×50(¥400.00)、哇哈哈矿泉水×41(¥205.00)、荷花双中支×2(¥144.00)、地道肠×27(¥135.00)、哈啤×12(¥120.00)（商品合计¥2468.00 占比6.2%）；综合：10-12月到店消费49天/93次，到店周期中位#1，消费排名#5，在店时长#6；12月到店消费11天/20次，到店周期中位#1，消费排名#5，在店时长#8；最近到店2025-12-13；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：关注是否为临时充值型，建议引导储值梯度与权益；重点维护包厢/团建需求，提前锁档与套餐化；商品贡献高，可做常购商品补货提醒与组合促销
-6,江先生,188****4838,璇子(110.5h)、婉婉(16.8h)、小柔(12.0h)、Amy(6.7h)、周周(4.3h),30472.41,11000.00,0.00,订单：24单，平均单次¥1269.68；打球：65.6h，平均单次2.7h；偏好：包厢(44.5%)、888(15.3%)、M8(12.8%)、B区(10.3%)；时间：到店均值16:05 中位19:47；离店均值18:53 中位21:24；商品：百威235毫升×480(¥7200.00)、风花雪月×28(¥448.00)、钻石荷花×7(¥330.00)、东方树叶×11(¥88.00)、双中支中华×1(¥72.00)、荷花双中支×1(¥68.00)（商品合计¥8943.00 占比29.3%）；综合：10-12月到店消费21天/24次，到店周期中位#3，消费排名#6，在店时长#14；12月到店消费5天/6次，到店周期中位#3，消费排名#6，在店时长#18；最近到店2025-12-13；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：关注是否为临时充值型，建议引导储值梯度与权益；重点维护包厢/团建需求，提前锁档与套餐化；商品贡献高，可做常购商品补货提醒与组合促销
-7,小燕,178****1334,小燕(140.1h)、阿清(2.0h)、球球(1.4h)、Amy(1.0h)、年糕(0.5h),29888.89,0.00,1802.64,订单：62单，平均单次¥482.08；打球：148.0h，平均单次2.4h；偏好：A区(55.2%)、麻将(20.7%)、S区/斯诺克(14.7%)、补时长(4.3%)；时间：到店均值15:22 中位19:05；离店均值17:50 中位21:43；商品：东方树叶×28(¥224.00)、双中支中华×2(¥144.00)、钻石荷花×2(¥90.00)、荷花双中支×1(¥68.00)、蜂蜜水×6(¥60.00)、百威235毫升×3(¥45.00)（商品合计¥863.00 占比2.9%）；综合：10-12月到店消费27天/62次，到店周期中位#1，消费排名#7，在店时长#10；12月到店消费15天/30次，到店周期中位#1，消费排名#7，在店时长#3；最近到店2025-12-18；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-8,张先生,139****8852,七七(25.1h)、小侯(20.2h)、千千(14.4h)、周周(10.4h)、璇子(10.3h),26104.33,0.00,1942.41,订单：46单，平均单次¥567.49；打球：105.7h，平均单次2.3h；偏好：C区(76.3%)、666(8.8%)、麻将(5.7%)、补时长(4.8%)；时间：到店均值18:43 中位18:47；离店均值21:25 中位21:12；商品：东方树叶×28(¥224.00)、哇哈哈矿泉水×41(¥205.00)、钻石荷花×3(¥135.00)、细和天下×1(¥125.00)、双中支中华×1(¥72.00)、农夫山泉苏打水×11(¥66.00)（商品合计¥1205.00 占比4.6%）；综合：10-12月到店消费40天/46次，到店周期中位#1，消费排名#8，在店时长#13；12月到店消费13天/13次，到店周期中位#1，消费排名#8，在店时长#13；最近到店2025-12-18；趋势：10-12月到店频次下降，建议重点唤醒；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-9,曾巧明,186****1488,,24830.16,0.00,0.00,订单：59单，平均单次¥420.85；打球：404.3h，平均单次6.9h；偏好：B区(66.4%)、C区(32.8%)、A区(0.8%)；时间：到店均值17:01 中位16:13；离店均值23:52 中位次日00:12；商品：跨越贵烟×1(¥30.00)、地道肠×4(¥20.00)、东方树叶×2(¥16.00)、可乐×2(¥10.00)、哇哈哈矿泉水×2(¥10.00)（商品合计¥86.00 占比0.3%）；综合：10-12月到店消费54天/59次，到店周期中位#1，消费排名#9，在店时长#1；12月到店消费15天/16次，到店周期中位#1，消费排名#9，在店时长#1；最近到店2025-12-18；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-10,黄生,136****9719,,18406.23,0.00,0.00,订单：36单，平均单次¥511.28；打球：298.2h，平均单次8.3h；偏好：B区(64.4%)、C区(35.6%)；时间：到店均值13:13 中位12:53；离店均值21:30 中位22:04；商品：地道肠×8(¥40.00)、可乐×2(¥10.00)（商品合计¥50.00 占比0.3%）；综合：10-12月到店消费36天/36次，到店周期中位#1，消费排名#10，在店时长#2；12月到店消费7天/7次，到店周期中位#3，消费排名#10，在店时长#4；最近到店2025-12-18；趋势：10-12月到店频次下降，建议重点唤醒；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-11,夏,191****2851,婉婉(29.7h)、柚子(10.7h)、球球(10.6h)、佳怡(7.8h)、璇子(7.6h),16599.59,17000.00,0.00,订单：10单，平均单次¥1659.96；打球：40.5h，平均单次4.1h；偏好：888(72.1%)、TV台(22.1%)、包厢(5.8%)、补时长(0.0%)；时间：到店均值18:28 中位20:36；离店均值22:43 中位次日01:10；商品：百威235毫升×247(¥3705.00)、细荷花×5(¥250.00)、荷花双中支×3(¥204.00)、清洁费150×1(¥150.00)、三只松鼠开心果×4(¥120.00)、鸡翅三个一份×6(¥108.00)（商品合计¥5162.90 占比31.1%）；综合：10-12月到店消费9天/10次，到店周期中位#5，消费排名#11，在店时长#19；12月到店消费0天/0次，到店周期中位—，消费排名#11，在店时长—；最近到店2025-11-06；趋势：10-12月到店频次下降，建议重点唤醒；围客与客户运营建议：关注是否为临时充值型，建议引导储值梯度与权益；重点维护包厢/团建需求，提前锁档与套餐化；商品贡献高，可做常购商品补货提醒与组合促销
-12,叶先生,138****9539,素素(29.7h)、年糕(9.7h)、Amy(7.4h)、球球(6.7h)、婉婉(3.7h),14491.25,6307.00,0.00,订单：8单，平均单次¥1811.41；打球：27.2h，平均单次3.4h；偏好：B区(30.9%)、888(24.0%)、C区(17.8%)、包厢(16.3%)；时间：到店均值18:38 中位20:59；离店均值次日00:04 中位次日02:12；商品：蓝妹×96(¥1728.00)、钻石荷花×9(¥405.00)、50  和成天下×6(¥390.00)、鸡翅三个一份×14(¥252.00)、100  和成天下×2(¥230.00)、透明袋无穷鸡翅×10(¥200.00)（商品合计¥4880.00 占比33.7%）；综合：10-12月到店消费8天/8次，到店周期中位#2，消费排名#12，在店时长#27；12月到店消费2天/2次，到店周期中位#1，消费排名#12，在店时长#37；最近到店2025-12-06；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：关注是否为临时充值型，建议引导储值梯度与权益；重点维护包厢/团建需求，提前锁档与套餐化；商品贡献高，可做常购商品补货提醒与组合促销
-13,T,180****9962,佳怡(15.0h)、周周(14.7h)、乔西(11.2h)、球球(10.7h)、欣怡(10.3h),13651.06,3000.00,849.68,订单：16单，平均单次¥853.19；打球：55.6h，平均单次3.5h；偏好：麻将(50.8%)、M8(17.0%)、包厢(16.0%)、A区(9.2%)；时间：到店均值18:05 中位19:34；离店均值21:23 中位22:01；商品：荷花双中支×4(¥288.00)、钻石荷花×4(¥190.00)、软荷花×3(¥174.00)、哇哈哈矿泉水×26(¥130.00)、红牛×10(¥100.00)、跨越贵烟×3(¥86.00)（商品合计¥1689.00 占比12.4%）；综合：10-12月到店消费12天/16次，到店周期中位#1，消费排名#13，在店时长#16；12月到店消费5天/8次，到店周期中位#1，消费排名#13，在店时长#14；最近到店2025-12-17；趋势：12月为高峰月，具备加深运营空间；围客与客户运营建议：重点维护包厢/团建需求，提前锁档与套餐化
-14,林先生,133****1070,七七(19.4h)、佳怡(14.9h)、璇子(9.6h)、乔西(9.6h)、苏苏(4.9h),12937.86,0.00,158.79,订单：14单，平均单次¥924.13；打球：44.4h，平均单次3.2h；偏好：麻将(33.6%)、M8(31.5%)、M7(21.5%)、补时长(11.4%)；时间：到店均值12:18 中位17:34；离店均值15:50 中位次日01:15；商品：荷花双中支×5(¥360.00)、细荷花×5(¥260.00)、细和天下×2(¥250.00)、钻石荷花×5(¥250.00)、双中支中华×3(¥216.00)、粗和天下×1(¥125.00)（商品合计¥2246.00 占比17.4%）；综合：10-12月到店消费13天/14次，到店周期中位#1，消费排名#14，在店时长#17；12月到店消费10天/11次，到店周期中位#1，消费排名#14，在店时长#12；最近到店2025-12-13；趋势：10-12月到店频次上升，12月更活跃；围客与客户运营建议：储值余额偏低，建议在其常用时段做补能引导；商品贡献高，可做常购商品补货提醒与组合促销
-15,曾丹烨,139****3242,,12356.33,3000.00,6639.14,订单：54单，平均单次¥228.82；打球：256.7h，平均单次4.8h；偏好：麻将(100.0%)；时间：到店均值16:05 中位17:32；离店均值20:29 中位22:06；商品：合味道泡面×1(¥12.00)、地道肠×2(¥10.00)、东鹏特饮×1(¥7.00)、喜之郎果冻×1(¥5.00)（商品合计¥34.00 占比0.3%）；综合：10-12月到店消费44天/54次，到店周期中位#1，消费排名#15，在店时长#4；12月到店消费9天/11次，到店周期中位#2，消费排名#15，在店时长#6；最近到店2025-12-16；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-16,胡先生,186****3391,佳怡(29.4h)、七七(4.2h)、球球(3.9h)、婉婉(3.9h)、涛涛(2.7h),11420.87,8000.00,0.00,订单：9单，平均单次¥1268.99；打球：39.8h，平均单次4.4h；偏好：包厢(44.2%)、A区(23.1%)、888(11.9%)、麻将(10.7%)；时间：到店均值13:36 中位17:09；离店均值17:14 中位20:36；商品：百威235毫升×70(¥1050.00)、钻石荷花×5(¥225.00)、鸡翅三个一份×4(¥72.00)、蜂蜜水×7(¥70.00)、50  和成天下×1(¥65.00)、软荷花×1(¥58.00)（商品合计¥1900.00 占比16.6%）；综合：10-12月到店消费5天/9次，到店周期中位#6，消费排名#16，在店时长#20；12月到店消费1天/1次，到店周期中位—，消费排名#16，在店时长#41；最近到店2025-12-01；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：关注是否为临时充值型，建议引导储值梯度与权益；重点维护包厢/团建需求，提前锁档与套餐化
-17,艾宇民,150****9958,泡芙(22.0h)、小侯(7.6h),10763.07,0.00,0.00,订单：44单，平均单次¥244.62；打球：112.4h，平均单次2.6h；偏好：B区(82.1%)、C区(12.7%)、包厢(5.2%)；时间：到店均值16:20 中位16:06；离店均值18:50 中位18:03；商品：百威235毫升×30(¥450.00)、地道肠×13(¥65.00)、细荷花×1(¥50.00)、中支芙蓉王×1(¥38.00)、乖媳妇山椒泡爪×1(¥25.00)、哇哈哈矿泉水×5(¥25.00)（商品合计¥808.00 占比7.5%）；综合：10-12月到店消费41天/44次，到店周期中位#1，消费排名#17，在店时长#12；12月到店消费8天/10次，到店周期中位#2，消费排名#17，在店时长#16；最近到店2025-12-17；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：重点维护包厢/团建需求，提前锁档与套餐化
-18,谢俊,186****5198,年糕(4.5h)、素素(2.4h),9982.86,0.00,0.00,订单：46单，平均单次¥217.02；打球：159.5h，平均单次3.5h；偏好：B区(100.0%)；时间：到店均值19:31 中位20:12；离店均值22:59 中位23:48；商品：钻石荷花×1(¥45.00)（商品合计¥45.00 占比0.5%）；综合：10-12月到店消费43天/46次，到店周期中位#1，消费排名#18，在店时长#9；12月到店消费4天/6次，到店周期中位#5，消费排名#18，在店时长#19；最近到店2025-12-17；趋势：10-12月到店频次下降，建议重点唤醒；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-19,周周,198****8725,周周(70.8h)、球球(15.2h)、佳怡(13.2h),8905.19,0.00,0.00,订单：10单，平均单次¥890.52；打球：35.9h，平均单次3.6h；偏好：麻将(59.3%)、M7(19.6%)、补时长(19.6%)、A区(1.5%)；时间：到店均值11:40 中位14:30；离店均值17:04 中位次日00:34；商品：哇哈哈AD钙奶×13(¥104.00)、跨越贵烟×3(¥90.00)、细荷花×1(¥55.00)、红利群×2(¥52.00)、钻石荷花×1(¥50.00)、哇哈哈矿泉水×7(¥35.00)（商品合计¥685.00 占比7.7%）；综合：10-12月到店消费8天/10次，到店周期中位#1，消费排名#19，在店时长#22；12月到店消费8天/10次，到店周期中位#1，消费排名#19，在店时长#11；最近到店2025-12-17；趋势：10-12月到店频次上升，12月更活跃；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-20,叶总,137****3287,璇子(22.0h)、小柔(3.8h)、七七(3.0h),8163.28,5700.00,0.00,订单：5单，平均单次¥1632.66；打球：23.4h，平均单次4.7h；偏好：包厢(53.5%)、888(25.5%)、麻将(12.9%)、B区(8.2%)；时间：到店均值21:36 中位21:10；离店均值次日02:18 中位次日02:08；商品：百威235毫升×132(¥1980.00)、荷花双中支×3(¥204.00)、软荷花×1(¥58.00)、跨越贵烟×2(¥56.00)、细荷花×1(¥50.00)、钻石荷花×1(¥45.00)（商品合计¥2487.00 占比30.5%）；综合：10-12月到店消费5天/5次，到店周期中位#2，消费排名#20，在店时长#31；12月到店消费0天/0次，到店周期中位—，消费排名#20，在店时长—；最近到店2025-10-27；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：关注是否为临时充值型，建议引导储值梯度与权益；重点维护包厢/团建需求，提前锁档与套餐化；商品贡献高，可做常购商品补货提醒与组合促销
-21,羊,187****5094,球球(5.3h)、璇子(5.0h)、素素(4.3h)、婉婉(4.3h)、Amy(4.1h),8155.54,64000.00,0.00,订单：13单，平均单次¥627.35；打球：35.7h，平均单次2.7h；偏好：麻将(64.8%)、TV台(14.7%)、B区(10.3%)、888(9.7%)；时间：到店均值18:13 中位19:52；离店均值21:16 中位22:36；商品：蓝妹×54(¥972.00)、钻石荷花×4(¥180.00)、中支芙蓉王×2(¥76.00)、无穷烤小腿×3(¥60.00)、跨越贵烟×2(¥56.00)、鸡翅三个一份×3(¥54.00)（商品合计¥2072.00 占比25.4%）；综合：10-12月到店消费10天/13次，到店周期中位#1，消费排名#21，在店时长#23；12月到店消费0天/0次，到店周期中位—，消费排名#21，在店时长—；最近到店2025-11-23；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：关注是否为临时充值型，建议引导储值梯度与权益；商品贡献高，可做常购商品补货提醒与组合促销
-22,游,172****6666,佳怡(13.5h)、小敌(3.6h)、璇子(3.1h)、周周(2.4h)、千千(2.2h),7797.37,0.00,0.00,订单：13单，平均单次¥599.80；打球：24.1h，平均单次1.9h；偏好：包厢(52.1%)、666(31.7%)、补时长(8.5%)、S区/斯诺克(7.7%)；时间：到店均值19:13 中位18:51；离店均值21:14 中位20:36；商品：双中支中华×3(¥216.00)、红牛×17(¥170.00)、跨越贵烟×5(¥140.00)、荷花双中支×2(¥136.00)、50枸杞槟榔×2(¥130.00)、100  和成天下×1(¥115.00)（商品合计¥1406.00 占比18.0%）；综合：10-12月到店消费9天/13次，到店周期中位#2，消费排名#22，在店时长#29；12月到店消费6天/9次，到店周期中位#1，消费排名#22，在店时长#27；最近到店2025-12-13；趋势：10-12月到店频次上升，12月更活跃；围客与客户运营建议：重点维护包厢/团建需求，提前锁档与套餐化
-23,桂先生,166****7275,球球(2.6h),7678.29,985.00,0.00,订单：21单，平均单次¥365.63；打球：117.4h，平均单次5.6h；偏好：B区(79.3%)、C区(20.7%)；时间：到店均值18:37 中位19:01；离店均值次日00:12 中位次日00:13；商品：地道肠×17(¥85.00)、哇哈哈矿泉水×15(¥75.00)、可乐×13(¥65.00)、红牛×4(¥40.00)、蜂蜜水×3(¥30.00)、东方树叶×3(¥24.00)（商品合计¥373.00 占比4.9%）；综合：10-12月到店消费21天/21次，到店周期中位#2，消费排名#23，在店时长#11；12月到店消费2天/2次，到店周期中位#9，消费排名#23，在店时长#26；最近到店2025-12-16；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：关注是否为临时充值型，建议引导储值梯度与权益
-24,明哥,166****0999,小柔(31.6h)、婉婉(26.7h)、涛涛(5.4h)、年糕(4.6h)、周周(0.4h),7581.04,0.00,954.64,订单：4单，平均单次¥1895.26；打球：21.1h，平均单次5.3h；偏好：包厢(43.0%)、A区(26.0%)、补时长(23.8%)、C区(5.2%)；时间：到店均值10:22 中位10:15；离店均值13:40 中位13:49；商品：百威235毫升×78(¥1170.00)、硬中华×2(¥100.00)、地道肠×9(¥45.00)、东方树叶×4(¥32.00)、鱼蛋×6(¥30.00)、蜂蜜水×2(¥20.00)（商品合计¥1447.00 占比19.1%）；综合：10-12月到店消费4天/4次，到店周期中位#5，消费排名#24，在店时长#35；12月到店消费3天/3次，到店周期中位#5，消费排名#24，在店时长#20；最近到店2025-12-10；趋势：10-12月到店频次上升，12月更活跃；围客与客户运营建议：重点维护包厢/团建需求，提前锁档与套餐化
-25,陈德韩,134****7864,乔西(9.1h)、素素(5.5h)、奈千(4.4h)、周周(4.3h)、小敌(4.0h),7302.92,5000.00,20.11,订单：4单，平均单次¥1825.73；打球：19.6h，平均单次4.9h；偏好：包厢(66.6%)、888(21.3%)、麻将(12.1%)、补时长(0.0%)；时间：到店均值18:53 中位18:48；离店均值21:23 中位21:56；商品：百威235毫升×85(¥1275.00)、卡士×9(¥198.00)、无穷爱辣烤鸡爪×3(¥60.00)、鸡翅三个一份×2(¥36.00)、鱼蛋×6(¥30.00)、鱼豆腐×2(¥30.00)（商品合计¥1898.00 占比26.0%）；综合：10-12月到店消费4天/4次，到店周期中位#15，消费排名#25，在店时长#38；12月到店消费1天/1次，到店周期中位—，消费排名#25，在店时长—；最近到店2025-12-01；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：储值余额偏低，建议在其常用时段做补能引导；重点维护包厢/团建需求，提前锁档与套餐化
-26,小熊,139****0145,佳怡(13.2h)、周周(10.7h)、欣怡(7.9h)、球球(4.4h)、七七(1.3h),7135.88,5000.00,0.00,订单：9单，平均单次¥792.88；打球：32.7h，平均单次3.6h；偏好：麻将(82.3%)、包厢(9.2%)、TV台(8.5%)、补时长(0.0%)；时间：到店均值14:59 中位18:25；离店均值19:25 中位23:36；商品：软荷花×3(¥174.00)、100  和成天下×1(¥115.00)、中支芙蓉王×3(¥114.00)、钻石荷花×2(¥90.00)、炫赫门小南京×3(¥78.00)、荷花双中支×1(¥68.00)（商品合计¥1223.00 占比17.1%）；综合：10-12月到店消费6天/9次，到店周期中位#2，消费排名#26，在店时长#25；12月到店消费0天/0次，到店周期中位—，消费排名#26，在店时长—；最近到店2025-11-05；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：关注是否为临时充值型，建议引导储值梯度与权益；重点维护包厢/团建需求，提前锁档与套餐化
-27,黄先生,135****3507,苏苏(30.8h)、千千(13.1h)、乔西(1.6h)、阿清(0.7h),7052.72,3000.00,1639.43,订单：22单，平均单次¥320.58；打球：39.4h，平均单次1.8h；偏好：B区(80.5%)、A区(17.0%)、C区(2.2%)、补时长(0.4%)；时间：到店均值18:32 中位19:27；离店均值20:30 中位21:28；商品：东方树叶×6(¥48.00)、钻石荷花×1(¥45.00)、哇哈哈AD钙奶×4(¥32.00)、东鹏特饮×3(¥21.00)、无穷烤小腿×1(¥20.00)、综合蔬果干×1(¥15.00)（商品合计¥225.00 占比3.2%）；综合：10-12月到店消费20天/22次，到店周期中位#3，消费排名#27，在店时长#21；12月到店消费7天/7次，到店周期中位#2，消费排名#27，在店时长#22；最近到店2025-12-16；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-28,吕先生,155****0663,小柔(7.5h)、周周(3.7h)、素素(2.8h)、婉婉(2.8h)、苏苏(2.8h),7012.05,6000.00,0.00,订单：4单，平均单次¥1753.01；打球：17.0h，平均单次4.2h；偏好：666(66.5%)、888(18.2%)、麻将(15.3%)；时间：到店均值14:20 中位18:05；离店均值18:34 中位21:28；商品：蓝妹×35(¥630.00)、软中华×3(¥210.00)、红牛×17(¥170.00)、软荷花×2(¥116.00)、鸡翅三个一份×4(¥72.00)、地道肠×10(¥50.00)（商品合计¥1819.00 占比25.9%）；综合：10-12月到店消费4天/4次，到店周期中位#1，消费排名#28，在店时长#41；12月到店消费0天/0次，到店周期中位—，消费排名#28，在店时长—；最近到店2025-10-20；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：关注是否为临时充值型，建议引导储值梯度与权益
-29,郑先生,159****4331,小敌(32.1h),6438.07,0.00,0.00,订单：16单，平均单次¥402.38；打球：42.2h，平均单次2.6h；偏好：C区(63.7%)、补时长(14.4%)、B区(12.9%)、A区(9.0%)；时间：到店均值15:29 中位20:24；离店均值19:22 中位次日00:03；商品：农夫山泉苏打水×8(¥48.00)、蜂蜜水×4(¥40.00)、地道肠×7(¥35.00)、一次性手套×5(¥10.00)、东方树叶×1(¥8.00)、哇哈哈矿泉水×1(¥5.00)（商品合计¥156.00 占比2.4%）；综合：10-12月到店消费13天/16次，到店周期中位#1，消费排名#29，在店时长#18；12月到店消费5天/7次，到店周期中位#1，消费排名#29，在店时长#25；最近到店2025-12-12；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-30,歌神,188****2164,婉婉(6.7h)、希希(4.0h)、素素(3.9h)、小柔(3.8h)、年糕(2.6h),5877.65,5000.00,0.00,订单：4单，平均单次¥1469.41；打球：12.8h，平均单次3.2h；偏好：888(43.0%)、包厢(41.0%)、麻将(16.0%)；时间：到店均值22:20 中位22:39；离店均值次日01:34 中位次日01:19；商品：百威235毫升×90(¥1350.00)、鸡翅三个一份×5(¥90.00)、焦糖瓜子×3(¥45.00)、鱼蛋×9(¥45.00)、三只松鼠开心果×1(¥30.00)、地道肠×6(¥30.00)（商品合计¥1687.00 占比28.7%）；综合：10-12月到店消费4天/4次，到店周期中位#4，消费排名#30，在店时长#46；12月到店消费0天/0次，到店周期中位—，消费排名#30，在店时长—；最近到店2025-10-24；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：关注是否为临时充值型，建议引导储值梯度与权益；重点维护包厢/团建需求，提前锁档与套餐化
-31,罗先生,139****9222,婉婉(18.8h)、年糕(7.7h)、小柔(4.5h)、素素(4.3h)、姜姜(1.5h),5831.48,3000.00,310.31,订单：5单，平均单次¥1166.30；打球：20.0h，平均单次4.0h；偏好：包厢(72.1%)、888(17.8%)、补时长(10.2%)；时间：到店均值16:46 中位21:04；离店均值次日01:10 中位次日00:07；商品：科罗娜啤酒275ml×26(¥468.00)、蓝妹×18(¥324.00)、鸡翅三个一份×2(¥36.00)、三只松鼠开心果×1(¥30.00)、地道肠×5(¥25.00)、焦糖瓜子×1(¥15.00)（商品合计¥924.00 占比15.8%）；综合：10-12月到店消费5天/5次，到店周期中位#14，消费排名#31，在店时长#37；12月到店消费0天/0次，到店周期中位—，消费排名#31，在店时长—；最近到店2025-11-27；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：储值余额偏低，建议在其常用时段做补能引导；重点维护包厢/团建需求，提前锁档与套餐化
-32,大G,186****4598,周周(17.7h)、佳怡(9.5h)、球球(1.9h),5374.68,0.00,0.00,订单：5单，平均单次¥1074.94；打球：21.6h，平均单次4.3h；偏好：麻将(47.3%)、M7(33.2%)、A区(19.4%)、补时长(0.1%)；时间：到店均值17:16 中位20:28；离店均值21:48 中位次日00:04；商品：荷花双中支×2(¥144.00)、哇哈哈AD钙奶×9(¥72.00)、无穷烤小腿×3(¥60.00)、芙蓉王×2(¥56.00)、红利群×2(¥52.00)、蜂蜜水×4(¥40.00)（商品合计¥748.00 占比13.9%）；综合：10-12月到店消费5天/5次，到店周期中位#1，消费排名#32，在店时长#34；12月到店消费4天/4次，到店周期中位#1，消费排名#32，在店时长#24；最近到店2025-12-07；趋势：10-12月到店频次上升，12月更活跃；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-33,林先生,137****8785,小侯(9.7h)、梦梦(4.3h)、千千(2.7h)、瑶瑶(1.9h)、周周(0.7h),4967.38,0.00,0.00,订单：7单，平均单次¥709.63；打球：18.7h，平均单次2.7h；偏好：C区(76.5%)、包厢(23.4%)、补时长(0.0%)；时间：到店均值17:58 中位19:48；离店均值20:49 中位23:39；商品：百威235毫升×30(¥450.00)、50枸杞槟榔×1(¥65.00)、东方树叶×5(¥40.00)、蜂蜜水×4(¥40.00)、哇哈哈矿泉水×7(¥35.00)、酒鬼花生×4(¥32.00)（商品合计¥887.00 占比17.9%）；综合：10-12月到店消费6天/7次，到店周期中位#3，消费排名#33，在店时长#40；12月到店消费2天/2次，到店周期中位#4，消费排名#33，在店时长#34；最近到店2025-12-06；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：重点维护包厢/团建需求，提前锁档与套餐化
-34,梅,136****4552,千千(16.6h)、阿清(10.8h)、小侯(4.7h)、小燕(3.8h),4590.92,0.00,2050.00,订单：8单，平均单次¥573.86；打球：20.4h，平均单次2.5h；偏好：麻将(77.0%)、C区(12.1%)、补时长(10.8%)；时间：到店均值14:47 中位20:54；离店均值20:02 中位23:31；商品：硬中华×1(¥50.00)、轻上椰子水×2(¥24.00)、哇哈哈矿泉水×2(¥10.00)（商品合计¥84.00 占比1.8%）；综合：10-12月到店消费7天/8次，到店周期中位#5，消费排名#34，在店时长#36；12月到店消费5天/5次，到店周期中位#5，消费排名#34，在店时长#23；最近到店2025-12-19；趋势：10-12月到店频次上升，12月更活跃；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-35,李先生,134****4343,小侯(9.3h)、柚子(7.8h)、球球(0.0h),4479.77,0.00,2433.01,订单：8单，平均单次¥559.97；打球：32.1h，平均单次4.0h；偏好：C区(73.4%)、包厢(26.6%)；时间：到店均值19:34 中位20:19；离店均值23:35 中位23:13；商品：热水可续杯×13(¥39.00)、农夫山泉苏打水×5(¥30.00)、水果脆×1(¥30.00)、跨越贵烟×1(¥30.00)、哇哈哈矿泉水×4(¥20.00)、水溶C×1(¥8.00)（商品合计¥185.00 占比4.1%）；综合：10-12月到店消费8天/8次，到店周期中位#3，消费排名#35，在店时长#26；12月到店消费5天/5次，到店周期中位#3，消费排名#35，在店时长#17；最近到店2025-12-18；趋势：10-12月到店频次上升，12月更活跃；围客与客户运营建议：重点维护包厢/团建需求，提前锁档与套餐化
-36,陶,189****2151,欣怡(4.9h)、球球(4.7h)、周周(4.4h)、七七(4.2h)、佳怡(4.1h),4096.07,6000.00,8.82,订单：7单，平均单次¥585.15；打球：21.7h，平均单次3.1h；偏好：麻将(61.0%)、A区(13.3%)、包厢(9.7%)、C区(8.1%)；时间：到店均值20:49 中位21:49；离店均值23:55 中位次日01:19；商品：荷花双中支×1(¥68.00)、红牛×5(¥50.00)、轻上椰子水×4(¥48.00)、哇哈哈矿泉水×8(¥40.00)、软玉溪×1(¥28.00)、炫赫门小南京×1(¥26.00)（商品合计¥399.00 占比9.7%）；综合：10-12月到店消费6天/7次，到店周期中位#2，消费排名#36，在店时长#33；12月到店消费0天/0次，到店周期中位—，消费排名#36，在店时长—；最近到店2025-10-26；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：储值余额偏低，建议在其常用时段做补能引导；重点维护包厢/团建需求，提前锁档与套餐化
-37,陈先生,159****2829,佳怡(7.6h)、奈千(5.1h)、柚子(4.4h)、乔西(4.2h)、Amy(4.2h),3817.58,3000.00,0.55,订单：3单，平均单次¥1272.53；打球：7.6h，平均单次2.5h；偏好：麻将(54.5%)、TV台(45.4%)、补时长(0.1%)、A区(0.0%)；时间：到店均值13:21 中位19:06；离店均值18:07 中位次日00:40；商品：百威235毫升×10(¥150.00)、钻石荷花×1(¥45.00)、跨越贵烟×1(¥28.00)、无穷爱辣烤鸡爪×1(¥20.00)、白桦树汁×1(¥12.00)、椰汁×1(¥8.00)（商品合计¥277.00 占比7.3%）；综合：10-12月到店消费3天/3次，到店周期中位#19，消费排名#37，在店时长#57；12月到店消费0天/0次，到店周期中位—，消费排名#37，在店时长—；最近到店2025-11-07；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：储值余额偏低，建议在其常用时段做补能引导
-38,候,131****0323,球球(5.3h)、阿清(4.3h)、小侯(3.4h)、涛涛(3.1h)、乔西(2.9h),3765.88,0.00,0.00,订单：8单，平均单次¥470.74；打球：22.0h，平均单次2.7h；偏好：TV台(66.3%)、A区(28.3%)、C区(5.4%)；时间：到店均值20:08 中位19:43；离店均值22:53 中位22:54；商品：冰红茶×8(¥48.00)、地道肠×4(¥20.00)、鱼蛋×4(¥20.00)、可乐×2(¥10.00)、哇米诺豆奶×1(¥10.00)、红牛×1(¥10.00)（商品合计¥161.00 占比4.3%）；综合：10-12月到店消费5天/8次，到店周期中位#1，消费排名#38，在店时长#32；12月到店消费5天/8次，到店周期中位#1，消费排名#38，在店时长#15；最近到店2025-12-17；趋势：10-12月到店频次上升，12月更活跃；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-39,黄先生,158****2109,球球(64.0h)、QQ(6.9h),3568.92,3000.00,420.01,订单：10单，平均单次¥356.89；打球：23.4h，平均单次2.3h；偏好：A区(60.1%)、包厢(27.0%)、补时长(12.9%)；时间：到店均值04:58 中位01:43；离店均值06:06 中位03:20；商品：蓝妹×4(¥72.00)、跨越贵烟×1(¥28.00)、火腿肠×2(¥10.00)、东方树叶×1(¥8.00)、卫龙魔芋爽×1(¥8.00)、农夫山泉苏打水×1(¥6.00)（商品合计¥142.00 占比4.0%）；综合：10-12月到店消费8天/10次，到店周期中位#4，消费排名#39，在店时长#30；12月到店消费3天/4次，到店周期中位#8，消费排名#39，在店时长#45；最近到店2025-12-17；趋势：12月为高峰月，具备加深运营空间；围客与客户运营建议：储值余额偏低，建议在其常用时段做补能引导；重点维护包厢/团建需求，提前锁档与套餐化
-40,孟紫龙,176****3741,,3492.73,0.00,0.00,订单：13单，平均单次¥268.67；打球：57.6h，平均单次4.4h；偏好：B区(100.0%)；时间：到店均值18:44 中位18:50；离店均值23:10 中位23:35；商品：哇哈哈矿泉水×9(¥45.00)、东方树叶×5(¥40.00)、地道肠×7(¥35.00)、可乐×2(¥10.00)、维他柠檬茶×1(¥8.00)、脉动×1(¥8.00)（商品合计¥153.00 占比4.4%）；综合：10-12月到店消费12天/13次，到店周期中位#1，消费排名#40，在店时长#15；12月到店消费10天/11次，到店周期中位#1，消费排名#40，在店时长#9；最近到店2025-12-18；趋势：10-12月到店频次上升，12月更活跃；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-41,罗超,137****0990,球球(2.9h)、璇子(2.7h)、苏苏(2.6h)、奈千(2.5h),3398.81,3000.00,101.19,订单：2单，平均单次¥1699.40；打球：7.3h，平均单次3.7h；偏好：888(78.8%)、麻将(21.2%)；时间：到店均值20:57 中位20:57；离店均值次日00:37 中位次日00:37；商品：科罗娜啤酒275ml×49(¥882.00)、荷花双中支×1(¥68.00)、百威235毫升×3(¥45.00)、掼蛋扑克×4(¥32.00)、跨越贵烟×1(¥28.00)、东方树叶×3(¥24.00)（商品合计¥1115.00 占比32.8%）；综合：10-12月到店消费2天/2次，到店周期中位#16，消费排名#41，在店时长#59；12月到店消费0天/0次，到店周期中位—，消费排名#41，在店时长—；最近到店2025-10-24；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：储值余额偏低，建议在其常用时段做补能引导
-42,君姐,166****4594,年糕(8.2h)、婉婉(4.3h)、璇子(2.3h)、涛涛(2.2h),3361.95,0.00,272.15,订单：3单，平均单次¥1120.65；打球：12.5h，平均单次4.2h；偏好：666(30.5%)、M8(25.3%)、M7(17.7%)、包厢(13.9%)；时间：到店均值15:38 中位16:21；离店均值20:33 中位21:15；商品：哇哈哈矿泉水×20(¥100.00)、卡士×2(¥44.00)、东方树叶×5(¥40.00)、麻将房茶位费×1(¥40.00)、小果盘×1(¥37.90)、软玉溪×1(¥28.00)（商品合计¥319.90 占比9.5%）；综合：10-12月到店消费3天/3次，到店周期中位#5，消费排名#42，在店时长#47；12月到店消费1天/1次，到店周期中位—，消费排名#42，在店时长#31；最近到店2025-12-02；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：储值余额偏低，建议在其常用时段做补能引导；重点维护包厢/团建需求，提前锁档与套餐化
-43,吴生,136****3341,小柔(2.8h)、涛涛(2.2h),3253.70,0.00,3680.65,订单：15单，平均单次¥216.91；打球：34.3h，平均单次2.3h；偏好：C区(86.1%)、B区(7.0%)、包厢(6.7%)、补时长(0.1%)；时间：到店均值19:01 中位18:43；离店均值21:14 中位21:25；商品：哇哈哈矿泉水×18(¥90.00)、双中支中华×1(¥72.00)、阿萨姆×1(¥8.00)（商品合计¥170.00 占比5.2%）；综合：10-12月到店消费12天/15次，到店周期中位#6，消费排名#43，在店时长#24；12月到店消费2天/3次，到店周期中位#5，消费排名#43，在店时长#35；最近到店2025-12-16；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：重点维护包厢/团建需求，提前锁档与套餐化
-44,刘哥,135****0020,婉婉(5.3h)、球球(2.1h),3036.80,0.00,371.51,订单：2单，平均单次¥1518.40；打球：5.0h，平均单次2.5h；偏好：包厢(93.4%)、S区/斯诺克(6.6%)、补时长(0.0%)；时间：到店均值11:33 中位11:33；离店均值12:15 中位12:15；商品：百威235毫升×79(¥1185.00)、中支芙蓉王×2(¥76.00)、地道肠×6(¥30.00)、鱼蛋×6(¥30.00)、红利群×1(¥26.00)、红烧牛肉面×2(¥24.00)（商品合计¥1417.00 占比46.7%）；综合：10-12月到店消费2天/2次，到店周期中位#20，消费排名#44，在店时长#66；12月到店消费1天/1次，到店周期中位—，消费排名#44，在店时长#49；最近到店2025-12-17；趋势：12月为高峰月，具备加深运营空间；围客与客户运营建议：储值余额偏低，建议在其常用时段做补能引导；重点维护包厢/团建需求，提前锁档与套餐化
-45,李先生,131****4000,小敌(11.8h)、涛涛(2.1h)、Amy(1.1h),2997.53,3000.00,563.47,订单：4单，平均单次¥749.38；打球：11.8h，平均单次3.0h；偏好：包厢(100.0%)；时间：到店均值16:24 中位20:21；离店均值19:21 中位23:11；商品：轻上椰子水×10(¥120.00)、科罗娜啤酒275ml×6(¥108.00)、跨越贵烟×1(¥28.00)、地道肠×2(¥10.00)、海之言×1(¥8.00)、茶兀×1(¥8.00)（商品合计¥298.00 占比9.9%）；综合：10-12月到店消费3天/4次，到店周期中位#5，消费排名#45，在店时长#48；12月到店消费0天/0次，到店周期中位—，消费排名#45，在店时长—；最近到店2025-11-07；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：重点维护包厢/团建需求，提前锁档与套餐化
-46,阿亮,159****2628,涛涛(9.1h)、素素(3.1h)、奈千(2.9h)、梦梦(2.7h)、柚子(2.4h),2936.26,0.00,612.33,订单：8单，平均单次¥367.03；打球：16.8h，平均单次2.1h；偏好：B区(65.3%)、S区/斯诺克(34.5%)、补时长(0.2%)；时间：到店均值21:06 中位20:32；离店均值23:26 中位23:29；商品：哇哈哈矿泉水×4(¥20.00)、香飘飘果汁茶×1(¥10.00)、茶兀×1(¥8.00)（商品合计¥38.00 占比1.3%）；综合：10-12月到店消费6天/8次，到店周期中位#1，消费排名#46，在店时长#43；12月到店消费2天/3次，到店周期中位#1，消费排名#46，在店时长#29；最近到店2025-12-04；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-47,李先生,186****8308,小侯(5.6h)、年糕(4.2h),2785.23,0.00,0.00,订单：1单，平均单次¥2785.23；打球：8.3h，平均单次8.3h；偏好：包厢(100.0%)；时间：到店均值23:15 中位23:15；离店均值次日07:32 中位次日07:32；商品：清洁费150×1(¥150.00)、卡士×1(¥22.00)、合味道泡面×1(¥12.00)、轻上椰子水×1(¥12.00)、雪碧×2(¥10.00)、哇哈哈矿泉水×1(¥5.00)（商品合计¥216.00 占比7.8%）；综合：10-12月到店消费1天/1次，到店周期中位—，消费排名#47，在店时长#55；12月到店消费0天/0次，到店周期中位—，消费排名#47，在店时长—；最近到店2025-11-28；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：重点维护包厢/团建需求，提前锁档与套餐化
-48,周先生,173****7775,乔西(7.5h)、小敌(6.6h),2726.01,0.00,0.00,订单：1单，平均单次¥2726.01；打球：7.5h，平均单次7.5h；偏好：666(100.0%)；时间：到店均值15:40 中位15:40；离店均值23:11 中位23:11；商品：哇哈哈矿泉水×1(¥5.00)（商品合计¥5.00 占比0.2%）；综合：10-12月到店消费1天/1次，到店周期中位—，消费排名#48，在店时长#58；12月到店消费0天/0次，到店周期中位—，消费排名#48，在店时长—；最近到店2025-10-25；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-49,林先生,159****0021,婉婉(12.0h)、小柔(3.2h)、苏苏(3.1h),2690.52,0.00,49.48,订单：2单，平均单次¥1345.26；打球：6.0h，平均单次3.0h；偏好：包厢(66.7%)、A区(33.3%)；时间：到店均值10:13 中位10:13；离店均值12:14 中位12:14；商品：百威235毫升×24(¥360.00)、中支芙蓉王×2(¥76.00)、绿茶×4(¥24.00)、无穷爱辣烤鸡爪×1(¥20.00)、透明袋无穷鸡翅×1(¥20.00)、益达×1(¥18.00)（商品合计¥597.00 占比22.2%）；综合：10-12月到店消费2天/2次，到店周期中位#6，消费排名#49，在店时长#62；12月到店消费0天/0次，到店周期中位—，消费排名#49，在店时长—；最近到店2025-11-25；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：储值余额偏低，建议在其常用时段做补能引导；重点维护包厢/团建需求，提前锁档与套餐化
-50,周先生,193****6822,千千(8.6h)、素素(6.2h),2643.64,0.00,2092.01,订单：3单，平均单次¥881.21；打球：14.9h，平均单次5.0h；偏好：C区(100.0%)；时间：到店均值21:06 中位22:21；离店均值次日02:04 中位次日02:07；商品：哇哈哈矿泉水×5(¥25.00)、卡士×1(¥22.00)、东方树叶×2(¥16.00)、王老吉×1(¥8.00)、美汁源果粒橙×1(¥8.00)、一次性拖鞋×1(¥5.00)（商品合计¥89.00 占比3.4%）；综合：10-12月到店消费3天/3次，到店周期中位#4，消费排名#50，在店时长#44；12月到店消费3天/3次，到店周期中位#4，消费排名#50，在店时长#21；最近到店2025-12-13；趋势：10-12月到店频次上升，12月更活跃；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-51,林先生,188****0332,周周(4.0h)、小敌(1.9h),2612.01,0.00,0.00,订单：8单，平均单次¥326.50；打球：16.9h，平均单次2.1h；偏好：666(25.1%)、麻将(22.3%)、M7(20.7%)、S区/斯诺克(12.8%)；时间：到店均值14:55 中位17:06；离店均值17:17 中位19:13；商品：钻石荷花×3(¥135.00)、50枸杞槟榔×1(¥65.00)、跨越贵烟×1(¥28.00)、哇哈哈矿泉水×5(¥25.00)、红牛×2(¥20.00)、蜂蜜水×2(¥20.00)（商品合计¥330.00 占比12.6%）；综合：10-12月到店消费6天/8次，到店周期中位#1，消费排名#51，在店时长#42；12月到店消费0天/0次，到店周期中位—，消费排名#51，在店时长—；最近到店2025-11-28；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-52,牛先生,152****5159,柚子(10.4h),2187.48,0.00,0.00,订单：5单，平均单次¥437.50；打球：10.4h，平均单次2.1h；偏好：C区(99.8%)、补时长(0.2%)、A区(0.0%)、B区(0.0%)；时间：到店均值19:00 中位19:37；离店均值21:29 中位20:52；商品：地道肠×6(¥30.00)、东方树叶×2(¥16.00)、美汁源果粒橙×2(¥16.00)（商品合计¥62.00 占比2.8%）；综合：10-12月到店消费3天/5次，到店周期中位#1，消费排名#52，在店时长#51；12月到店消费0天/0次，到店周期中位—，消费排名#52，在店时长—；最近到店2025-11-24；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-53,孟紫龙（该会员已注销）,176****37411,,2131.72,0.00,0.00,订单：7单，平均单次¥304.53；打球：26.3h，平均单次3.8h；偏好：C区(99.9%)、补时长(0.1%)；时间：到店均值19:17 中位19:34；离店均值23:32 中位23:56；商品：可乐×5(¥25.00)、东鹏特饮×2(¥14.00)、鱼蛋×1(¥5.00)、一次性手套×1(¥2.00)（商品合计¥46.00 占比2.2%）；综合：10-12月到店消费7天/7次，到店周期中位#4，消费排名#53，在店时长#28；12月到店消费0天/0次，到店周期中位—，消费排名#53，在店时长—；最近到店2025-11-28；趋势：10-12月到店频次下降，建议重点唤醒；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-54,罗超杰,137****8012,苏苏(2.1h)、素素(1.9h)、周周(1.2h)、球球(0.8h),1584.05,0.00,3037.00,订单：8单，平均单次¥198.01；打球：8.4h，平均单次1.0h；偏好：包厢(74.8%)、B区(14.0%)、A区(10.9%)、补时长(0.2%)；时间：到店均值18:55 中位22:56；离店均值20:06 中位23:23；商品：雪碧×4(¥20.00)、可乐×3(¥15.00)、维他柠檬茶×1(¥8.00)、打火机×1(¥2.00)（商品合计¥45.00 占比2.8%）；综合：10-12月到店消费6天/8次，到店周期中位#3，消费排名#54，在店时长#54；12月到店消费0天/0次，到店周期中位—，消费排名#54，在店时长—；最近到店2025-11-05；趋势：10-12月到店频次下降，建议重点唤醒；围客与客户运营建议：重点维护包厢/团建需求，提前锁档与套餐化
-55,汪先生,139****6339,姜姜(9.6h),1390.07,1000.00,11.99,订单：4单，平均单次¥347.52；打球：5.1h，平均单次1.3h；偏好：包厢(82.3%)、A区(17.4%)、补时长(0.4%)；时间：到店均值21:16 中位22:01；离店均值23:26 中位23:25；商品：轻上椰子水×1(¥12.00)、三得利×1(¥8.00)、巧乐兹伊利×1(¥8.00)（商品合计¥28.00 占比2.0%）；综合：10-12月到店消费3天/4次，到店周期中位#1，消费排名#55，在店时长#65；12月到店消费0天/0次，到店周期中位—，消费排名#55，在店时长—；最近到店2025-10-09；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：储值余额偏低，建议在其常用时段做补能引导；重点维护包厢/团建需求，提前锁档与套餐化
-56,桂先生（该会员已注销）,166****72751,,1370.81,0.00,0.00,订单：5单，平均单次¥274.16；打球：19.0h，平均单次3.8h；偏好：C区(100.0%)；时间：到店均值19:20 中位19:37；离店均值23:08 中位23:57；商品：红牛×4(¥40.00)、东鹏特饮×2(¥14.00)、可乐×2(¥10.00)、地道肠×2(¥10.00)、普通扑克×1(¥5.00)（商品合计¥79.00 占比5.8%）；综合：10-12月到店消费5天/5次，到店周期中位#2，消费排名#56，在店时长#39；12月到店消费0天/0次，到店周期中位—，消费排名#56，在店时长—；最近到店2025-10-16；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-57,方先生,153****3185,乔西(3.2h),1313.30,1000.00,0.00,订单：3单，平均单次¥437.77；打球：10.2h，平均单次3.4h；偏好：麻将(69.0%)、666(31.0%)；时间：到店均值17:32 中位17:19；离店均值21:01 中位20:30；商品：农夫山泉苏打水×5(¥30.00)、掼蛋扑克×2(¥16.00)、可乐×3(¥15.00)、普通扑克×2(¥10.00)、红牛×1(¥10.00)、椰汁×1(¥8.00)（商品合计¥100.00 占比7.6%）；综合：10-12月到店消费3天/3次，到店周期中位#10，消费排名#57，在店时长#52；12月到店消费0天/0次，到店周期中位—，消费排名#57，在店时长—；最近到店2025-11-17；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：关注是否为临时充值型，建议引导储值梯度与权益
-58,陈淑涛,132****5485,涛涛(4.4h)、乔西(3.4h),1276.77,0.00,0.00,订单：3单，平均单次¥425.59；打球：4.4h，平均单次1.5h；偏好：麻将(77.1%)、A区(22.9%)、补时长(0.0%)；时间：到店均值12:52 中位09:40；离店均值14:39 中位10:40；商品：细荷花×1(¥50.00)、轻上椰子水×1(¥12.00)、哇哈哈矿泉水×2(¥10.00)、火鸡面×1(¥10.00)、茶兀×1(¥8.00)、火腿肠×1(¥5.00)（商品合计¥99.00 占比7.8%）；综合：10-12月到店消费2天/3次，到店周期中位#7，消费排名#58，在店时长#69；12月到店消费0天/0次，到店周期中位—，消费排名#58，在店时长—；最近到店2025-11-22；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-59,清,130****3087,小侯(3.0h)、阿清(3.0h)、千千(3.0h),1128.06,0.00,1944.76,订单：1单，平均单次¥1128.06；打球：3.0h，平均单次3.0h；偏好：麻将(100.0%)；时间：到店均值21:18 中位21:18；离店均值次日02:00 中位次日02:00；综合：10-12月到店消费1天/1次，到店周期中位—，消费排名#59，在店时长#73；12月到店消费1天/1次，到店周期中位—，消费排名#59，在店时长#38；最近到店2025-12-08；趋势：10-12月到店频次上升，12月更活跃；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-60,amy,137****8221,Amy(4.8h),1105.90,0.00,0.38,订单：1单，平均单次¥1105.90；打球：4.8h，平均单次4.8h；偏好：麻将(100.0%)；时间：到店均值22:47 中位22:47；离店均值次日03:37 中位次日03:37；商品：跨越贵烟×2(¥60.00)、掼蛋扑克×2(¥16.00)、热水可续杯×4(¥12.00)、可乐×2(¥10.00)、蜂蜜水×1(¥10.00)（商品合计¥108.00 占比9.8%）；综合：10-12月到店消费1天/1次，到店周期中位—，消费排名#60，在店时长#67；12月到店消费1天/1次，到店周期中位—，消费排名#60，在店时长#32；最近到店2025-12-06；趋势：10-12月到店频次上升，12月更活跃；围客与客户运营建议：储值余额偏低，建议在其常用时段做补能引导
-61,曾先生,133****1235,奈千(1.0h),991.34,0.00,303.19,订单：7单，平均单次¥141.62；打球：13.0h，平均单次1.9h；偏好：S区/斯诺克(63.2%)、A区(36.8%)；时间：到店均值13:58 中位12:19；离店均值15:49 中位14:10；商品：咖啡代购×3(¥45.00)、东方树叶×3(¥24.00)、屈臣氏苏打水×1(¥8.00)、阿萨姆×1(¥8.00)、绿茶×1(¥6.00)、哇哈哈矿泉水×1(¥5.00)（商品合计¥98.00 占比9.9%）；综合：10-12月到店消费7天/7次，到店周期中位#6，消费排名#61，在店时长#45；12月到店消费2天/2次，到店周期中位#6，消费排名#61，在店时长#36；最近到店2025-12-10；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：储值余额偏低，建议在其常用时段做补能引导
-62,昌哥,137****1229,Amy(2.0h)、小柔(1.8h)、苏苏(1.7h),942.42,0.00,2471.98,订单：2单，平均单次¥471.21；打球：4.5h，平均单次2.3h；偏好：A区(100.0%)；时间：到店均值20:05 中位20:05；离店均值22:21 中位22:21；商品：农夫山泉苏打水×3(¥18.00)、麻辣王子×1(¥12.00)、哇哈哈矿泉水×2(¥10.00)、营养快线×1(¥8.00)、阿萨姆×1(¥8.00)（商品合计¥56.00 占比5.9%）；综合：10-12月到店消费2天/2次，到店周期中位#15，消费排名#62，在店时长#68；12月到店消费1天/1次，到店周期中位—，消费排名#62，在店时长#44；最近到店2025-12-07；趋势：12月为高峰月，具备加深运营空间；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-63,李,131****9882,,927.44,0.00,0.00,订单：11单，平均单次¥84.31；打球：11.1h，平均单次1.0h；偏好：B区(68.7%)、A区(30.9%)、补时长(0.4%)；时间：到店均值13:13 中位13:14；离店均值14:13 中位14:00；商品：哇哈哈矿泉水×4(¥20.00)（商品合计¥20.00 占比2.2%）；综合：10-12月到店消费6天/11次，到店周期中位#8，消费排名#63，在店时长#49；12月到店消费0天/0次，到店周期中位—，消费排名#63，在店时长—；最近到店2025-11-24；趋势：10-12月到店频次下降，建议重点唤醒；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-64,邓飛,136****9597,婉婉(6.8h)、苏苏(6.0h)、小敌(4.5h)、小柔(1.2h)、球球(0.8h),925.47,2345.00,74.77,订单：1单，平均单次¥925.47；打球：1.9h，平均单次1.9h；偏好：包厢(100.0%)；时间：到店均值01:56 中位01:56；离店均值03:48 中位03:48；商品：百威235毫升×12(¥180.00)、卡士×1(¥22.00)、农夫山泉苏打水×3(¥18.00)、一次性拖鞋×1(¥5.00)、哇哈哈矿泉水×1(¥5.00)（商品合计¥230.00 占比24.9%）；综合：10-12月到店消费1天/1次，到店周期中位—，消费排名#64，在店时长#85；12月到店消费0天/0次，到店周期中位—，消费排名#64，在店时长—；最近到店2025-11-09；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：储值余额偏低，建议在其常用时段做补能引导；重点维护包厢/团建需求，提前锁档与套餐化
-65,陈世,134****1938,瑶瑶(0.8h),921.09,0.00,0.00,订单：6单，平均单次¥153.52；打球：6.5h，平均单次1.1h；偏好：C区(49.7%)、S区/斯诺克(49.6%)、补时长(0.7%)；时间：到店均值20:42 中位21:08；离店均值22:16 中位22:24；综合：10-12月到店消费3天/6次，到店周期中位#24，消费排名#65，在店时长#61；12月到店消费0天/0次，到店周期中位—，消费排名#65，在店时长—；最近到店2025-11-20；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-66,婉婉,183****2742,婉婉(4.3h),867.49,1000.00,514.08,订单：2单，平均单次¥433.74；打球：4.4h，平均单次2.2h；偏好：B区(36.5%)、A区(35.9%)、888(27.6%)；时间：到店均值15:41 中位15:41；离店均值18:01 中位18:01；商品：旺仔牛奶×2(¥20.00)、红牛×1(¥10.00)、王老吉×1(¥8.00)、哇哈哈矿泉水×1(¥5.00)、喜之郎果冻×1(¥5.00)（商品合计¥48.00 占比5.5%）；综合：10-12月到店消费2天/2次，到店周期中位#23，消费排名#66，在店时长#70；12月到店消费0天/0次，到店周期中位—，消费排名#66，在店时长—；最近到店2025-11-21；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-67,贺斌,150****0885,佳怡(1.0h),770.56,0.00,0.00,订单：4单，平均单次¥192.64；打球：9.6h，平均单次2.4h；偏好：A区(50.1%)、C区(49.9%)；时间：到店均值17:30 中位17:55；离店均值19:53 中位19:54；商品：细荷花×1(¥50.00)、可乐×5(¥25.00)、哇哈哈矿泉水×2(¥10.00)、地道肠×2(¥10.00)、东方树叶×1(¥8.00)（商品合计¥103.00 占比13.4%）；综合：10-12月到店消费3天/4次，到店周期中位#4，消费排名#67，在店时长#53；12月到店消费0天/0次，到店周期中位—，消费排名#67，在店时长—；最近到店2025-11-03；趋势：10-12月到店频次下降，建议重点唤醒；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-68,陈泽斌,132****6060,,700.00,0.00,0.00,订单：6单，平均单次¥116.67；打球：0.1h，平均单次0.0h；偏好：补时长(100.0%)；时间：到店均值17:51 中位20:40；离店均值18:50 中位21:39；综合：10-12月到店消费6天/6次，到店周期中位#10，消费排名#68，在店时长#97；12月到店消费1天/1次，到店周期中位—，消费排名#68，在店时长#51；最近到店2025-12-11；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-69,林总,138****1180,周周(2.2h)、婉婉(0.9h),684.44,0.00,16729.21,订单：2单，平均单次¥342.22；打球：3.7h，平均单次1.9h；偏好：包厢(100.0%)；时间：到店均值18:28 中位18:28；离店均值20:20 中位20:20；商品：东方树叶×1(¥8.00)、哇哈哈AD钙奶×1(¥8.00)（商品合计¥16.00 占比2.3%）；综合：10-12月到店消费2天/2次，到店周期中位#2，消费排名#69，在店时长#72；12月到店消费0天/0次，到店周期中位—，消费排名#69，在店时长—；最近到店2025-11-25；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：储值余额充足，可提供包厢/团建档期与专属权益；重点维护包厢/团建需求，提前锁档与套餐化
-70,卢广贤,186****6220,,680.44,0.00,0.00,订单：4单，平均单次¥170.11；打球：10.4h，平均单次2.6h；偏好：B区(62.8%)、C区(37.2%)；时间：到店均值18:15 中位18:45；离店均值20:51 中位20:41；商品：轻上椰子水×1(¥12.00)、三得利×1(¥8.00)、东鹏特饮×1(¥7.00)、冰红茶×1(¥6.00)、普通扑克×1(¥5.00)（商品合计¥38.00 占比5.6%）；综合：10-12月到店消费4天/4次，到店周期中位#18，消费排名#70，在店时长#50；12月到店消费1天/1次，到店周期中位—，消费排名#70，在店时长#46；最近到店2025-12-13；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-71,王龙,186****8011,,669.58,0.00,95.20,订单：4单，平均单次¥167.40；打球：7.8h，平均单次2.0h；偏好：麻将(99.7%)、补时长(0.3%)；时间：到店均值20:56 中位21:02；离店均值23:28 中位23:28；商品：麻将房茶位费×2(¥80.00)、东方树叶×2(¥16.00)（商品合计¥96.00 占比14.3%）；综合：10-12月到店消费2天/4次，到店周期中位#9，消费排名#71，在店时长#56；12月到店消费2天/4次，到店周期中位#7，消费排名#71，在店时长#28；最近到店2025-12-12；趋势：10-12月到店频次上升，12月更活跃；围客与客户运营建议：储值余额偏低，建议在其常用时段做补能引导
-72,王先生,185****1125,,600.68,0.00,0.00,订单：4单，平均单次¥150.17；打球：5.9h，平均单次1.5h；偏好：S区/斯诺克(99.4%)、补时长(0.6%)；时间：到店均值18:13 中位18:31；离店均值20:09 中位19:30；商品：哇哈哈矿泉水×1(¥5.00)（商品合计¥5.00 占比0.8%）；综合：10-12月到店消费4天/4次，到店周期中位#6，消费排名#72，在店时长#63；12月到店消费1天/1次，到店周期中位—，消费排名#72，在店时长#43；最近到店2025-12-02；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-73,潘先生,186****0511,年糕(2.0h),564.93,0.00,0.00,订单：2单，平均单次¥282.46；打球：3.0h，平均单次1.5h；偏好：666(66.7%)、A区(33.3%)；时间：到店均值18:28 中位18:28；离店均值19:29 中位19:29；商品：农夫山泉苏打水×1(¥6.00)（商品合计¥6.00 占比1.1%）；综合：10-12月到店消费2天/2次，到店周期中位#11，消费排名#73，在店时长#75；12月到店消费2天/2次，到店周期中位#8，消费排名#73，在店时长#40；最近到店2025-12-13；趋势：10-12月到店频次上升，12月更活跃；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-74,老宋,138****4554,婉婉(1.0h)、欣怡(0.5h),541.97,0.00,2126.14,订单：2单，平均单次¥270.98；打球：1.5h，平均单次0.7h；偏好：888(66.9%)、A区(33.1%)；时间：到店均值19:24 中位19:24；离店均值20:02 中位20:02；商品：百威235毫升×12(¥180.00)（商品合计¥180.00 占比33.2%）；综合：10-12月到店消费2天/2次，到店周期中位#13，消费排名#74，在店时长#91；12月到店消费0天/0次，到店周期中位—，消费排名#74，在店时长—；最近到店2025-11-07；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-75,郭先生,156****5001,希希(1.6h),518.35,0.00,2.57,订单：2单，平均单次¥259.18；打球：7.1h，平均单次3.5h；偏好：A区(100.0%)；时间：到店均值20:53 中位20:53；离店均值次日00:32 中位次日00:32；商品：可乐×2(¥10.00)、普通扑克×2(¥10.00)、一次性手套×2(¥4.00)（商品合计¥24.00 占比4.6%）；综合：10-12月到店消费2天/2次，到店周期中位#7，消费排名#75，在店时长#60；12月到店消费0天/0次，到店周期中位—，消费排名#75，在店时长—；最近到店2025-11-01；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：储值余额偏低，建议在其常用时段做补能引导
-76,孙启明,137****6325,,500.00,0.00,0.00,订单：4单，平均单次¥125.00；打球：2.0h，平均单次0.5h；偏好：补时长(100.0%)；时间：到店均值10:50 中位09:58；离店均值11:49 中位10:57；综合：10-12月到店消费4天/4次，到店周期中位#16，消费排名#76，在店时长#83；12月到店消费0天/0次，到店周期中位—，消费排名#76，在店时长—；最近到店2025-11-19；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-77,王先生,136****0168,,500.00,0.00,0.00,订单：5单，平均单次¥100.00；打球：0.1h，平均单次0.0h；偏好：补时长(100.0%)；时间：到店均值19:45 中位19:22；离店均值20:44 中位20:21；综合：10-12月到店消费4天/5次，到店周期中位#5，消费排名#77，在店时长#98；12月到店消费1天/1次，到店周期中位—，消费排名#77，在店时长#53；最近到店2025-12-03；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-78,黎先生,133****0983,奈千(1.7h)、婉婉(0.8h),470.19,0.00,0.00,订单：1单，平均单次¥470.19；打球：1.7h，平均单次1.7h；偏好：包厢(100.0%)；时间：到店均值19:17 中位19:17；离店均值21:01 中位21:01；商品：王老吉×2(¥16.00)、普通茶位×1(¥10.00)、香飘飘果汁茶×1(¥10.00)（商品合计¥36.00 占比7.7%）；综合：10-12月到店消费1天/1次，到店周期中位—，消费排名#78，在店时长#89；12月到店消费0天/0次，到店周期中位—，消费排名#78，在店时长—；最近到店2025-10-10；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：重点维护包厢/团建需求，提前锁档与套餐化
-79,常总,185****7188,年糕(1.7h)、阿清(1.7h),460.52,0.00,5000.00,订单：1单，平均单次¥460.52；打球：1.8h，平均单次1.8h；偏好：A区(100.0%)；时间：到店均值19:13 中位19:13；离店均值20:58 中位20:58；商品：哇哈哈矿泉水×2(¥10.00)、脉动×1(¥8.00)（商品合计¥18.00 占比3.9%）；综合：10-12月到店消费1天/1次，到店周期中位—，消费排名#79，在店时长#88；12月到店消费1天/1次，到店周期中位—，消费排名#79，在店时长#47；最近到店2025-12-14；趋势：10-12月到店频次上升，12月更活跃；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-80,张丹逸,136****6637,,439.36,0.00,0.00,订单：4单，平均单次¥109.84；打球：2.4h，平均单次0.6h；偏好：B区(99.0%)、补时长(1.0%)；时间：到店均值11:15 中位10:29；离店均值12:36 中位11:29；综合：10-12月到店消费4天/4次，到店周期中位#1，消费排名#80，在店时长#80；12月到店消费1天/1次，到店周期中位—，消费排名#80，在店时长#55；最近到店2025-12-03；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-81,陈先生,186****8238,乔西(1.8h),416.17,0.00,497.83,订单：1单，平均单次¥416.17；打球：1.8h，平均单次1.8h；偏好：包厢(100.0%)；时间：到店均值21:15 中位21:15；离店均值23:04 中位23:04；商品：普通茶位×3(¥30.00)（商品合计¥30.00 占比7.2%）；综合：10-12月到店消费1天/1次，到店周期中位—，消费排名#81，在店时长#86；12月到店消费0天/0次，到店周期中位—，消费排名#81，在店时长—；最近到店2025-11-20；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：储值余额偏低，建议在其常用时段做补能引导；重点维护包厢/团建需求，提前锁档与套餐化
-82,陈先生,138****3964,,400.00,0.00,0.00,订单：3单，平均单次¥133.33；打球：2.5h，平均单次0.8h；偏好：补时长(100.0%)；时间：到店均值15:17 中位21:41；离店均值15:57 中位22:40；综合：10-12月到店消费3天/3次，到店周期中位#24，消费排名#82，在店时长#79；12月到店消费1天/1次，到店周期中位—，消费排名#82，在店时长#52；最近到店2025-12-04；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-83,张先生,136****4528,,398.35,0.00,0.00,订单：3单，平均单次¥132.78；打球：2.9h，平均单次1.0h；偏好：S区/斯诺克(98.8%)、补时长(1.2%)；时间：到店均值21:05 中位20:51；离店均值22:41 中位22:13；商品：农夫山泉苏打水×1(¥6.00)（商品合计¥6.00 占比1.5%）；综合：10-12月到店消费3天/3次，到店周期中位#15，消费排名#83，在店时长#76；12月到店消费2天/2次，到店周期中位#10，消费排名#83，在店时长#42；最近到店2025-12-17；趋势：10-12月到店频次上升，12月更活跃；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-84,小宇,187****8077,球球(1.5h)、悦悦(0.4h),397.50,0.00,936.07,订单：2单，平均单次¥198.75；打球：2.1h，平均单次1.0h；偏好：包厢(80.9%)、TV台(19.1%)；时间：到店均值18:07 中位18:07；离店均值19:09 中位19:09；商品：哇哈哈AD钙奶×1(¥8.00)、农夫山泉苏打水×1(¥6.00)、哇哈哈矿泉水×1(¥5.00)（商品合计¥19.00 占比4.8%）；综合：10-12月到店消费2天/2次，到店周期中位#9，消费排名#84，在店时长#82；12月到店消费0天/0次，到店周期中位—，消费排名#84，在店时长—；最近到店2025-10-13；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：重点维护包厢/团建需求，提前锁档与套餐化
-85,黄先生,191****8219,,364.33,0.00,0.00,订单：4单，平均单次¥91.08；打球：1.2h，平均单次0.3h；偏好：B区(95.4%)、补时长(4.6%)；时间：到店均值22:45 中位22:43；离店均值23:46 中位23:45；综合：10-12月到店消费3天/4次，到店周期中位#4，消费排名#85，在店时长#93；12月到店消费0天/0次，到店周期中位—，消费排名#85，在店时长—；最近到店2025-11-29；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-86,刘女士,177****7538,,362.58,0.00,0.00,订单：4单，平均单次¥90.64；打球：2.8h，平均单次0.7h；偏好：B区(99.3%)、补时长(0.7%)；时间：到店均值15:53 中位15:44；离店均值17:04 中位17:04；综合：10-12月到店消费1天/4次，到店周期中位—，消费排名#86，在店时长#77；12月到店消费0天/0次，到店周期中位—，消费排名#86，在店时长—；最近到店2025-10-14；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-87,魏先生,137****6862,,319.39,0.00,84.51,订单：1单，平均单次¥319.39；打球：5.4h，平均单次5.4h；偏好：A区(66.1%)、S区/斯诺克(33.9%)、B区(0.0%)；时间：到店均值18:44 中位18:44；离店均值次日00:08 中位次日00:08；商品：维他柠檬茶×2(¥16.00)、东方树叶×1(¥8.00)（商品合计¥24.00 占比7.5%）；综合：10-12月到店消费1天/1次，到店周期中位—，消费排名#87，在店时长#64；12月到店消费1天/1次，到店周期中位—，消费排名#87，在店时长#30；最近到店2025-12-05；趋势：10-12月到店频次上升，12月更活跃；围客与客户运营建议：储值余额偏低，建议在其常用时段做补能引导
-88,杜先生,188****4705,,307.47,0.00,0.00,订单：3单，平均单次¥102.49；打球：2.1h，平均单次0.7h；偏好：A区(98.3%)、补时长(1.7%)；时间：到店均值21:25 中位21:44；离店均值22:45 中位22:43；商品：哇哈哈矿泉水×2(¥10.00)（商品合计¥10.00 占比3.3%）；综合：10-12月到店消费2天/3次，到店周期中位#21，消费排名#88，在店时长#81；12月到店消费0天/0次，到店周期中位—，消费排名#88，在店时长—；最近到店2025-11-02；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-89,刘先生,137****2930,,300.00,0.00,1.27,订单：1单，平均单次¥300.00；打球：0.0h，平均单次0.0h；偏好：补时长(100.0%)；时间：到店均值23:47 中位23:47；离店均值次日00:48 中位次日00:48；综合：10-12月到店消费1天/1次，到店周期中位—，消费排名#89，在店时长#100；12月到店消费1天/1次，到店周期中位—，消费排名#89，在店时长#54；最近到店2025-12-07；趋势：10-12月到店频次上升，12月更活跃；围客与客户运营建议：储值余额偏低，建议在其常用时段做补能引导
-90,陈先生,133****6117,,300.00,0.00,0.00,订单：2单，平均单次¥150.00；打球：0.0h，平均单次0.0h；偏好：补时长(100.0%)；时间：到店均值20:50 中位20:50；离店均值21:49 中位21:49；综合：10-12月到店消费2天/2次，到店周期中位#2，消费排名#90，在店时长#99；12月到店消费0天/0次，到店周期中位—，消费排名#90，在店时长—；最近到店2025-11-21；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-91,潘先生,176****7964,,300.00,0.00,0.00,订单：1单，平均单次¥300.00；打球：3.0h，平均单次3.0h；偏好：补时长(100.0%)；时间：到店均值00:03 中位00:03；离店均值00:03 中位00:03；综合：10-12月到店消费1天/1次，到店周期中位—，消费排名#91，在店时长#74；12月到店消费1天/1次，到店周期中位—，消费排名#91，在店时长#39；最近到店2025-12-19；趋势：10-12月到店频次上升，12月更活跃；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-92,钟智豪,188****2803,小侯(1.8h),274.34,0.00,0.00,订单：1单，平均单次¥274.34；打球：1.8h，平均单次1.8h；偏好：A区(100.0%)；时间：到店均值23:50 中位23:50；离店均值次日01:36 中位次日01:36；综合：10-12月到店消费1天/1次，到店周期中位—，消费排名#92，在店时长#87；12月到店消费0天/0次，到店周期中位—，消费排名#92，在店时长—；最近到店2025-11-28；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-93,都先生,138****7796,素素(1.6h),269.64,0.00,0.00,订单：1单，平均单次¥269.64；打球：1.6h，平均单次1.6h；偏好：B区(100.0%)；时间：到店均值15:17 中位15:17；离店均值16:56 中位16:56；商品：东方树叶×1(¥8.00)、哇哈哈AD钙奶×1(¥8.00)（商品合计¥16.00 占比5.9%）；综合：10-12月到店消费1天/1次，到店周期中位—，消费排名#93，在店时长#90；12月到店消费0天/0次，到店周期中位—，消费排名#93，在店时长—；最近到店2025-11-13；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-94,林志铭,135****4233,小侯(1.2h),267.96,0.00,795.66,订单：3单，平均单次¥89.32；打球：2.0h，平均单次0.7h；偏好：TV台(75.2%)、S区/斯诺克(24.8%)；时间：到店均值19:45 中位20:54；离店均值20:24 中位21:40；综合：10-12月到店消费2天/3次，到店周期中位#12，消费排名#94，在店时长#84；12月到店消费0天/0次，到店周期中位—，消费排名#94，在店时长—；最近到店2025-11-30；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-95,方先生,158****6447,,248.00,0.00,0.00,订单：3单，平均单次¥82.67；打球：1.0h，平均单次0.3h；偏好：A区(97.2%)、补时长(2.8%)；时间：到店均值15:35 中位22:11；离店均值16:15 中位23:11；综合：10-12月到店消费3天/3次，到店周期中位#17，消费排名#95，在店时长#94；12月到店消费2天/2次，到店周期中位#2，消费排名#95，在店时长#48；最近到店2025-12-18；趋势：10-12月到店频次上升，12月更活跃；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-96,李先生,176****5124,,244.00,0.00,0.00,订单：3单，平均单次¥81.33；打球：0.9h，平均单次0.3h；偏好：A区(97.8%)、补时长(2.2%)；时间：到店均值20:59 中位21:28；离店均值21:39 中位21:28；综合：10-12月到店消费3天/3次，到店周期中位#5，消费排名#96，在店时长#95；12月到店消费0天/0次，到店周期中位—，消费排名#96，在店时长—；最近到店2025-10-13；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-97,钟先生,132****3438,,239.37,0.00,0.00,订单：1单，平均单次¥239.37；打球：2.6h，平均单次2.6h；偏好：麻将(100.0%)；时间：到店均值19:32 中位19:32；离店均值22:10 中位22:10；商品：50枸杞槟榔×1(¥65.00)、地道肠×3(¥15.00)、哇哈哈矿泉水×2(¥10.00)、蜂蜜水×1(¥10.00)、屈臣氏苏打水×1(¥8.00)、芬达×1(¥5.00)（商品合计¥113.00 占比47.2%）；综合：10-12月到店消费1天/1次，到店周期中位—，消费排名#97，在店时长#78；12月到店消费0天/0次，到店周期中位—，消费排名#97，在店时长—；最近到店2025-10-20；趋势：到店频次波动，建议按常用时段做稳定触达；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
-98,杨,130****5960,,232.00,0.00,287.50,订单：2单，平均单次¥116.00；打球：4.0h，平均单次2.0h；偏好：B区(100.0%)；时间：到店均值18:09 中位18:09；离店均值20:11 中位20:11；综合：10-12月到店消费2天/2次，到店周期中位#2，消费排名#98，在店时长#71；12月到店消费2天/2次，到店周期中位#2，消费排名#98，在店时长#33；最近到店2025-12-05；趋势：10-12月到店频次上升，12月更活跃；围客与客户运营建议：储值余额偏低，建议在其常用时段做补能引导
-99,黄国磊,131****3045,,225.33,0.00,0.22,订单：3单，平均单次¥75.11；打球：0.1h，平均单次0.0h；偏好：A区(85.5%)、补时长(14.5%)；时间：到店均值17:56 中位18:02；离店均值18:36 中位18:19；商品：蜂蜜水×2(¥20.00)（商品合计¥20.00 占比8.9%）；综合：10-12月到店消费3天/3次，到店周期中位#22，消费排名#99，在店时长#96；12月到店消费1天/1次，到店周期中位—，消费排名#99，在店时长#55；最近到店2025-12-12；趋势：12月为高峰月，具备加深运营空间；围客与客户运营建议：储值余额偏低，建议在其常用时段做补能引导
-100,周先生,159****9997,,200.00,0.00,0.00,订单：2单，平均单次¥100.00；打球：1.2h，平均单次0.6h；偏好：补时长(100.0%)；时间：到店均值02:54 中位02:54；离店均值03:19 中位03:19；综合：10-12月到店消费2天/2次，到店周期中位#2，消费排名#100，在店时长#92；12月到店消费1天/1次，到店周期中位—，消费排名#100，在店时长#50；最近到店2025-12-01；趋势：12月为高峰月，具备加深运营空间；围客与客户运营建议：保持常用时段的稳定服务供给，提升复购粘性
diff --git a/etl_billiards/docs/table_2025-12-19/客户_Top100_2025年10-12月_总表.md b/etl_billiards/docs/table_2025-12-19/客户_Top100_2025年10-12月_总表.md
deleted file mode 100644
index 826151c..0000000
--- a/etl_billiards/docs/table_2025-12-19/客户_Top100_2025年10-12月_总表.md
+++ /dev/null
@@ -1,459 +0,0 @@
-# 2025年10-12月 客户消费能力Top100（总表）
-## 思考过程
-以台费订单为基准汇总三类明细，满足应付金额口径，并输出Top100客户的消费/充值/助教偏好。按你的要求，先生成评价为空的版本，再在脚本末尾回填评价。
-
-## 查询说明
-消费=台费(dwd_table_fee_log.ledger_amount)+助教(dwd_assistant_service_log.ledger_amount)+商品(dwd_store_goods_sale.ledger_amount)，均为应付金额（不扣优惠），以台费订单为基准串联；充值=充值支付流水(dwd_payment.relate_type=5, pay_status=2, pay_amount>0)按支付时间切月；储值卡未使用金额=当前有效储值卡余额之和(dim_member_card_account.balance, member_card_type_name='储值卡')；喜爱助教=基础课时长+附加课时长*1.5（income_seconds换算小时），总表按10-12月汇总Top5。
-
-## SQL
-
-### Top100（按消费总额）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount,
-    sum(tfl.real_table_use_seconds) as table_use_seconds
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_info as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.order_start_time, coalesce(a.assistant_start_time, bo.order_start_time)) as order_start_time,
-    greatest(bo.order_end_time, coalesce(a.assistant_end_time, bo.order_end_time)) as order_end_time,
-    bo.table_use_seconds,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_info a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-select
-  o.member_id,
-  sum(o.order_amount) as consume_total,
-  count(*) as order_cnt
-from orders o
-where o.member_id is not null and o.member_id <> 0
-group by o.member_id
-order by consume_total desc
-limit 100;
-```
-
-### 按月消费汇总
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount,
-    sum(tfl.real_table_use_seconds) as table_use_seconds
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_info as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.order_start_time, coalesce(a.assistant_start_time, bo.order_start_time)) as order_start_time,
-    greatest(bo.order_end_time, coalesce(a.assistant_end_time, bo.order_end_time)) as order_end_time,
-    bo.table_use_seconds,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_info a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, x as (
-  select
-    o.member_id,
-    case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    o.order_amount
-  from orders o
-  where o.member_id is not null and o.member_id <> 0
-)
-select
-  member_id,
-  month_key,
-  sum(order_amount) as consume_sum
-from x
-where month_key is not null
-group by member_id, month_key;
-```
-
-### 按月充值汇总
-```sql
-with pay as (
-  select
-    p.pay_time,
-    r.member_id,
-    p.pay_amount
-  from billiards_dwd.dwd_payment p
-  join billiards_dwd.dwd_recharge_order r on r.recharge_order_id = p.relate_id
-  where p.site_id = %(site_id)s
-    and p.relate_type = 5
-    and p.pay_status = 2
-    and p.pay_amount > 0
-    and p.pay_time >= %(window_start)s::timestamptz
-    and p.pay_time <  %(window_end)s::timestamptz
-)
-, x as (
-  select
-    member_id,
-    case when pay_time >= '2025-10-01 00:00:00+08'::timestamptz and pay_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when pay_time >= '2025-11-01 00:00:00+08'::timestamptz and pay_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when pay_time >= '2025-12-01 00:00:00+08'::timestamptz and pay_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    pay_amount
-  from pay
-)
-select
-  member_id,
-  month_key,
-  sum(pay_amount) as recharge_sum
-from x
-where month_key is not null
-group by member_id, month_key;
-```
-
-### 储值卡未使用金额（当前余额汇总）
-```sql
-select
-  tenant_member_id as member_id,
-  sum(balance) as stored_value_balance
-from billiards_dwd.dim_member_card_account
-where scd2_is_current=1
-  and coalesce(is_delete,0)=0
-  and member_card_type_name='储值卡'
-  and tenant_member_id = any(%(ids)s)
-group by tenant_member_id;
-```
-
-### 喜爱助教Top5（10-12月）
-```sql
-with x as (
-  select
-    asl.tenant_member_id as member_id,
-    asl.nickname as assistant_nickname,
-    sum(case when asl.order_assistant_type=1 then asl.income_seconds else asl.income_seconds*1.5 end) / 3600.0 as weighted_hours
-  from billiards_dwd.dwd_assistant_service_log asl
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0)=0
-    and asl.tenant_member_id is not null and asl.tenant_member_id <> 0
-    and asl.start_use_time >= %(window_start)s::timestamptz
-    and asl.start_use_time <  %(window_end)s::timestamptz
-  group by asl.tenant_member_id, asl.nickname
-),
-ranked as (
-  select *, row_number() over(partition by member_id order by weighted_hours desc) as rn
-  from x
-)
-select
-  member_id,
-  string_agg(assistant_nickname || '(' || to_char(round(weighted_hours::numeric, 1), 'FM999999990.0') || 'h)', '、' order by weighted_hours desc) as fav5
-from ranked
-where rn <= 5
-group by member_id;
-```
-
-### 评价画像：订单/时长/到店日期
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount,
-    sum(tfl.real_table_use_seconds) as table_use_seconds
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_info as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.order_start_time, coalesce(a.assistant_start_time, bo.order_start_time)) as order_start_time,
-    greatest(bo.order_end_time, coalesce(a.assistant_end_time, bo.order_end_time)) as order_end_time,
-    bo.table_use_seconds,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_info a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-select
-  o.member_id,
-  count(*) as orders,
-  avg(o.order_amount) as avg_order,
-  sum(o.table_use_seconds)/3600.0 as play_hours,
-  avg(o.table_use_seconds)/3600.0 as avg_play_hours,
-  min((o.order_start_time at time zone 'Asia/Shanghai')::date) as first_visit_day,
-  max((o.order_start_time at time zone 'Asia/Shanghai')::date) as last_visit_day,
-  count(distinct (o.order_start_time at time zone 'Asia/Shanghai')::date) as visit_days,
-  sum(case when o.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then 1 else 0 end) as orders_oct,
-  sum(case when o.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and o.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then 1 else 0 end) as orders_nov,
-  sum(case when o.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and o.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then 1 else 0 end) as orders_dec
-from orders o
-where o.member_id = any(%(ids)s)
-group by o.member_id;
-```
-
-### 评价画像：到店/离店时间（小时）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount,
-    sum(tfl.real_table_use_seconds) as table_use_seconds
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_info as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.order_start_time, coalesce(a.assistant_start_time, bo.order_start_time)) as order_start_time,
-    greatest(bo.order_end_time, coalesce(a.assistant_end_time, bo.order_end_time)) as order_end_time,
-    bo.table_use_seconds,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_info a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-, t as (
-  select
-    o.member_id,
-    extract(hour from (o.order_start_time at time zone 'Asia/Shanghai'))
-      + extract(minute from (o.order_start_time at time zone 'Asia/Shanghai'))/60.0
-      + extract(second from (o.order_start_time at time zone 'Asia/Shanghai'))/3600.0 as arrive_h,
-    extract(hour from (o.order_end_time at time zone 'Asia/Shanghai'))
-      + extract(minute from (o.order_end_time at time zone 'Asia/Shanghai'))/60.0
-      + extract(second from (o.order_end_time at time zone 'Asia/Shanghai'))/3600.0 as leave_h_raw
-  from orders o
-  where o.member_id = any(%(ids)s)
-),
-tt as (
-  select
-    member_id,
-    arrive_h,
-    case when leave_h_raw < arrive_h then leave_h_raw + 24 else leave_h_raw end as leave_h
-  from t
-)
-select
-  member_id,
-  avg(arrive_h) as arrive_avg_h,
-  percentile_cont(0.5) within group (order by arrive_h) as arrive_med_h,
-  avg(leave_h) as leave_avg_h,
-  percentile_cont(0.5) within group (order by leave_h) as leave_med_h
-from tt
-group by member_id;
-```
-
-### 评价画像：球台分区偏好（按时长）
-```sql
-select
-  tfl.member_id,
-  coalesce(tfl.site_table_area_name,'') as site_table_area_name,
-  sum(tfl.real_table_use_seconds)/3600.0 as hours
-from billiards_dwd.dwd_table_fee_log tfl
-where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
-  and tfl.start_use_time >= %(window_start)s::timestamptz and tfl.start_use_time < %(window_end)s::timestamptz
-  and tfl.member_id = any(%(ids)s)
-group by tfl.member_id, site_table_area_name;
-```
-
-### 评价画像：商品明细（名称+数量）
-```sql
-with base_orders as (
-  select order_settle_id, max(member_id) as member_id
-  from billiards_dwd.dwd_table_fee_log
-  where site_id=%(site_id)s and coalesce(is_delete,0)=0
-    and start_use_time >= %(window_start)s::timestamptz and start_use_time < %(window_end)s::timestamptz
-  group by order_settle_id
-)
-select
-  bo.member_id,
-  g.ledger_name,
-  sum(g.ledger_count) as qty,
-  sum(g.ledger_amount) as amount
-from base_orders bo
-join billiards_dwd.dwd_store_goods_sale g on g.order_settle_id = bo.order_settle_id
-where g.site_id=%(site_id)s and coalesce(g.is_delete,0)=0
-  and bo.member_id = any(%(ids)s)
-group by bo.member_id, g.ledger_name;
-```
-
-### 评价画像：到店日期明细（用于周期/近期分析）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    max(tfl.ledger_end_time) as order_end_time,
-    sum(tfl.ledger_amount) as table_amount,
-    sum(tfl.real_table_use_seconds) as table_use_seconds
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= '2025-10-01 00:00:00+08'::timestamptz
-    and tfl.start_use_time <  '2026-01-01 00:00:00+08'::timestamptz
-  group by tfl.order_settle_id
-),
-assistant_info as (
-  select
-    asl.order_settle_id,
-    sum(asl.ledger_amount) as assistant_amount,
-    min(asl.start_use_time) as assistant_start_time,
-    max(asl.last_use_time) as assistant_end_time
-  from billiards_dwd.dwd_assistant_service_log asl
-  join base_orders bo on bo.order_settle_id = asl.order_settle_id
-  where asl.site_id = %(site_id)s
-    and coalesce(asl.is_delete,0) = 0
-  group by asl.order_settle_id
-),
-goods_amount as (
-  select
-    g.order_settle_id,
-    sum(g.ledger_amount) as goods_amount
-  from billiards_dwd.dwd_store_goods_sale g
-  join base_orders bo on bo.order_settle_id = g.order_settle_id
-  where g.site_id = %(site_id)s
-    and coalesce(g.is_delete,0) = 0
-  group by g.order_settle_id
-),
-orders as (
-  select
-    bo.order_settle_id,
-    bo.member_id,
-    least(bo.order_start_time, coalesce(a.assistant_start_time, bo.order_start_time)) as order_start_time,
-    greatest(bo.order_end_time, coalesce(a.assistant_end_time, bo.order_end_time)) as order_end_time,
-    bo.table_use_seconds,
-    coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
-  from base_orders bo
-  left join assistant_info a on a.order_settle_id = bo.order_settle_id
-  left join goods_amount g on g.order_settle_id = bo.order_settle_id
-)
-
-select
-  o.member_id,
-  (o.order_start_time at time zone 'Asia/Shanghai')::date as visit_date,
-  count(*) as orders,
-  sum(o.order_amount) as amount
-from orders o
-where o.member_id = any(%(ids)s)
-group by o.member_id, visit_date
-order by o.member_id, visit_date;
-```
diff --git a/etl_billiards/docs/table_2025-12-19/财务_优惠分布_2025年10-12月.csv b/etl_billiards/docs/table_2025-12-19/财务_优惠分布_2025年10-12月.csv
deleted file mode 100644
index 24f1db7..0000000
--- a/etl_billiards/docs/table_2025-12-19/财务_优惠分布_2025年10-12月.csv
+++ /dev/null
@@ -1,119 +0,0 @@
-2025年10-12月 财务优惠（会员折扣+台费调账）分布
-优惠=会员折扣(dwd_table_fee_log.member_discount_amount)+台费调账(dwd_table_fee_adjust.ledger_amount)，按订单归集后汇总到客户(member_id)，按订单最早开台时间切月；不含团购抵扣等其它优惠。
-
-客户名称,手机号(脱敏),VIP卡/等级,10月,10月,10月,11月,11月,11月,12月,12月,12月,10-12月
-客户名称,手机号(脱敏),VIP卡/等级,会员折扣(元),台费调账(元),合计优惠(元),会员折扣(元),台费调账(元),合计优惠(元),会员折扣(元),台费调账(元),合计优惠(元),合计优惠(元)
-轩哥,188****7530,储值卡,0.00,9212.40,9212.40,0.00,10685.47,10685.47,0.00,5331.76,5331.76,25229.63
-曾巧明,186****1488,年卡,9649.06,0.00,9649.06,8811.59,0.00,8811.59,6283.51,0.00,6283.51,24744.16
-黄生,136****9719,年卡,7821.94,0.00,7821.94,6353.05,0.00,6353.05,4181.24,0.00,4181.24,18356.23
-蔡总,159****8893,台费卡,0.00,0.00,0.00,0.00,12274.20,12274.20,0.00,2587.28,2587.28,14861.48
-罗先生,139****6996,年卡,3315.05,566.48,3881.53,4474.12,460.59,4934.71,2087.14,1320.22,3407.36,12223.60
-陈腾鑫,178****8218,台费卡,0.00,2843.20,2843.20,0.00,4913.52,4913.52,0.00,1935.78,1935.78,9692.50
-谢俊,186****5198,年卡,4193.93,0.00,4193.93,4089.12,0.00,4089.12,969.66,0.00,969.66,9252.71
-桂先生,166****7275,月卡,2175.11,0.00,2175.11,4009.66,301.18,4310.84,0.00,568.24,568.24,7054.19
-张先生,139****8852,年卡,1317.04,1307.13,2624.17,2114.89,168.51,2283.40,2007.34,0.00,2007.34,6914.91
-艾宇民,150****9958,年卡,2342.73,0.00,2342.73,2543.78,545.12,3088.90,1179.56,0.00,1179.56,6611.19
-曾丹烨,139****3242,储值卡,0.00,2348.26,2348.26,0.00,2573.25,2573.25,0.00,1240.20,1240.20,6161.71
-葛先生,138****8071,储值卡,0.00,0.00,0.00,0.00,3548.54,3548.54,0.00,2593.02,2593.02,6141.56
-小燕,178****1334,储值卡,0.00,0.00,0.00,0.00,2250.36,2250.36,0.00,2228.54,2228.54,4478.90
-孟紫龙,176****3741,月卡,0.00,0.00,0.00,576.78,0.00,576.78,2762.95,0.00,2762.95,3339.73
-江先生,188****4838,储值卡,0.00,344.54,344.54,0.00,1454.41,1454.41,0.00,405.54,405.54,2204.49
-郑先生,159****4331,储值卡,0.00,0.00,0.00,0.00,1659.16,1659.16,0.00,463.02,463.02,2122.18
-黄先生,135****3507,台费卡,0.00,631.08,631.08,0.00,631.56,631.56,0.00,810.48,810.48,2073.12
-孟紫龙（该会员已注销）,176****37411,月卡,1785.72,0.00,1785.72,0.00,164.00,164.00,0.00,0.00,0.00,1949.72
-T,180****9962,储值卡,0.00,578.93,578.93,0.00,461.72,461.72,0.00,839.34,839.34,1879.99
-林先生,133****1070,储值卡,0.00,0.00,0.00,0.00,199.95,199.95,0.00,1417.70,1417.70,1617.65
-游,172****6666,储值卡,0.00,0.00,0.00,0.00,921.43,921.43,0.00,600.85,600.85,1522.28
-林先生,137****8785,储值卡,0.00,0.00,0.00,0.00,1114.20,1114.20,0.00,186.45,186.45,1300.65
-桂先生（该会员已注销）,166****72751,月卡,988.04,303.77,1291.81,0.00,0.00,0.00,0.00,0.00,0.00,1291.81
-叶先生,138****9539,储值卡,0.00,703.64,703.64,0.00,341.29,341.29,0.00,99.41,99.41,1144.34
-陈德韩,134****7864,台费卡,0.00,1091.02,1091.02,0.00,0.00,0.00,0.00,0.00,0.00,1091.02
-周周,198****8725,储值卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,1061.95,1061.95,1061.95
-胡先生,186****3391,储值卡,0.00,0.00,0.00,0.00,785.20,785.20,0.00,100.59,100.59,885.79
-小熊,139****0145,台费卡,0.00,297.01,297.01,0.00,530.45,530.45,0.00,0.00,0.00,827.46
-夏,191****2851,储值卡,0.00,659.78,659.78,0.00,137.90,137.90,0.00,0.00,0.00,797.68
-李先生,186****8308,储值卡,0.00,0.00,0.00,0.00,777.27,777.27,0.00,0.00,0.00,777.27
-叶总,137****3287,储值卡,0.00,737.12,737.12,0.00,0.00,0.00,0.00,0.00,0.00,737.12
-羊,187****5094,储值卡,0.00,38.64,38.64,0.00,647.57,647.57,0.00,0.00,0.00,686.21
-黄先生,158****2109,储值卡,0.00,240.00,240.00,0.00,326.90,326.90,0.00,100.06,100.06,666.96
-卢广贤,186****6220,年卡,263.07,0.00,263.07,250.51,0.00,250.51,128.86,0.00,128.86,642.44
-陶,189****2151,储值卡,0.00,604.89,604.89,0.00,0.00,0.00,0.00,0.00,0.00,604.89
-大G,186****4598,台费卡,0.00,0.00,0.00,0.00,245.70,245.70,0.00,356.31,356.31,602.01
-明哥,166****0999,储值卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,547.68,547.68,547.68
-梅,136****4552,储值卡,0.00,0.00,0.00,0.00,99.02,99.02,0.00,372.66,372.66,471.68
-阿亮,159****2628,储值卡,0.00,0.00,0.00,0.00,361.34,361.34,0.00,100.86,100.86,462.20
-牛先生,152****5159,台费卡,0.00,0.00,0.00,0.00,424.31,424.31,0.00,0.00,0.00,424.31
-罗超杰,137****8012,储值卡,0.00,245.95,245.95,0.00,164.54,164.54,0.00,0.00,0.00,410.49
-陈世,134****1938,储值卡,0.00,199.51,199.51,0.00,198.89,198.89,0.00,0.00,0.00,398.40
-曾先生,133****1235,储值卡,0.00,36.67,36.67,0.00,265.71,265.71,0.00,90.45,90.45,392.83
-李,131****9882,储值卡,0.00,254.13,254.13,0.00,138.12,138.12,0.00,0.00,0.00,392.25
-陈泽斌,132****6060,储值卡,0.00,77.00,77.00,0.00,222.00,222.00,0.00,78.00,78.00,377.00
-王先生,136****0168,台费卡,0.00,0.00,0.00,0.00,235.00,235.00,0.00,65.00,65.00,300.00
-林先生,188****0332,储值卡,0.00,0.00,0.00,0.00,252.11,252.11,0.00,0.00,0.00,252.11
-歌神,188****2164,储值卡,0.00,246.28,246.28,0.00,0.00,0.00,0.00,0.00,0.00,246.28
-陈先生,159****2829,台费卡,0.00,21.00,21.00,0.00,218.13,218.13,0.00,0.00,0.00,239.13
-黄先生,191****8219,台费卡,0.00,0.00,0.00,0.00,229.16,229.16,0.00,0.00,0.00,229.16
-汪先生,139****6339,储值卡,0.00,228.07,228.07,0.00,0.00,0.00,0.00,0.00,0.00,228.07
-王龙,186****8011,储值卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,200.78,200.78,200.78
-罗先生,139****9222,储值卡,0.00,0.00,0.00,0.00,199.17,199.17,0.00,0.00,0.00,199.17
-吴生,136****3341,储值卡,0.00,0.00,0.00,0.00,99.23,99.23,0.00,99.92,99.92,199.15
-刘女士,177****7538,储值卡,0.00,193.29,193.29,0.00,0.00,0.00,0.00,0.00,0.00,193.29
-林总,138****1180,储值卡,0.00,0.00,0.00,0.00,183.25,183.25,0.00,0.00,0.00,183.25
-陈淑涛,132****5485,储值卡,0.00,0.00,0.00,0.00,180.86,180.86,0.00,0.00,0.00,180.86
-张丹逸,136****6637,储值卡,0.00,133.68,133.68,0.00,0.00,0.00,0.00,45.00,45.00,178.68
-孙启明,137****6325,台费卡,0.00,90.00,90.00,0.00,85.00,85.00,0.00,0.00,0.00,175.00
-陈先生,138****3964,储值卡,0.00,98.00,98.00,0.00,0.00,0.00,0.00,60.00,60.00,158.00
-杜先生,188****4705,台费卡,0.00,48.00,48.00,0.00,99.73,99.73,0.00,0.00,0.00,147.73
-周先生,193****6822,储值卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,135.65,135.65,135.65
-君姐,166****4594,储值卡,0.00,0.00,0.00,0.00,134.10,134.10,0.00,0.00,0.00,134.10
-昌哥,137****1229,储值卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,122.03,122.03,122.03
-amy,137****8221,储值卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,116.28,116.28,116.28
-杨,130****5960,储值卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,116.00,116.00,116.00
-方先生,153****3185,储值卡,0.00,100.27,100.27,0.00,0.00,0.00,0.00,0.00,0.00,100.27
-方先生,158****6447,台费卡,0.00,0.00,0.00,0.00,72.00,72.00,0.00,28.00,28.00,100.00
-陈先生,133****6117,台费卡,0.00,0.00,0.00,0.00,100.00,100.00,0.00,0.00,0.00,100.00
-周先生,159****9997,台费卡,0.00,0.00,0.00,0.00,61.00,61.00,0.00,37.00,37.00,98.00
-王姐,158****8819,储值卡,0.00,97.40,97.40,0.00,0.00,0.00,0.00,0.00,0.00,97.40
-老宋,138****4554,储值卡,0.00,0.00,0.00,0.00,93.95,93.95,0.00,0.00,0.00,93.95
-李先生,176****5124,储值卡,0.00,90.00,90.00,0.00,0.00,0.00,0.00,0.00,0.00,90.00
-曾先生,159****0492,储值卡,0.00,88.00,88.00,0.00,0.00,0.00,0.00,0.00,0.00,88.00
-张先生,136****4528,台费卡,0.00,0.00,0.00,0.00,37.00,37.00,0.00,45.00,45.00,82.00
-刘先生,137****2930,储值卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,82.00,82.00,82.00
-潘先生,176****7964,储值卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,74.00,74.00,74.00
-王先生,183****9763,台费卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,74.00,74.00,74.00
-王先生,185****1125,台费卡,0.00,0.00,0.00,0.00,73.00,73.00,0.00,0.00,0.00,73.00
-清,130****3087,储值卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,72.82,72.82,72.82
-贺斌,150****0885,活动抵用券,0.00,71.27,71.27,0.00,0.00,0.00,0.00,0.00,0.00,71.27
-李先生,186****9266,储值卡,0.00,0.00,0.00,0.00,69.00,69.00,0.00,0.00,0.00,69.00
-林志铭,135****4233,储值卡,0.00,0.00,0.00,0.00,66.50,66.50,0.00,0.00,0.00,66.50
-候,131****0323,储值卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,62.79,62.79,62.79
-吕先生,155****0663,储值卡,0.00,62.54,62.54,0.00,0.00,0.00,0.00,0.00,0.00,62.54
-梁先生,134****2609,台费卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,59.00,59.00,59.00
-肖先生,156****6427,台费卡,0.00,0.00,0.00,0.00,7.00,7.00,0.00,50.00,50.00,57.00
-婉婉,183****2742,储值卡,0.00,0.00,0.00,0.00,37.47,37.47,0.00,0.00,0.00,37.47
-陈小姐,138****0778,储值卡,0.00,32.49,32.49,0.00,0.00,0.00,0.00,0.00,0.00,32.49
-黄国磊,131****3045,台费卡,0.00,0.30,0.30,0.00,19.00,19.00,0.00,0.00,0.00,19.30
-小宇,187****8077,储值卡,0.00,13.42,13.42,0.00,0.00,0.00,0.00,0.00,0.00,13.42
-胡总,133****3091,储值卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,1.00,1.00,1.00
-李先生,131****4000,储值卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00
-周先生,173****7775,台费卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00
-林先生,159****0021,储值卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00
-魏先生,137****6862,台费卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00
-都先生,138****7796,活动抵用券,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00
-陈先生,188****8626,储值卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00
-冯先生,155****0348,储值卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00
-常总,185****7188,储值卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00
-邓飛,136****9597,储值卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00
-李先生,134****4343,储值卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00
-谭先生,138****3185,储值卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00
-黎先生,133****0983,储值卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00
-刘哥,135****0020,台费卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00
-孙先生,135****3191,储值卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00
-钟智豪,188****2803,活动抵用券,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00
-陈先生,186****8238,储值卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00
-郭先生,156****5001,储值卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00
-钟先生,132****3438,储值卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00
-唐先生,135****0785,储值卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00
-陈先生,139****0419,储值卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00
-潘先生,186****0511,台费卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00
-罗超,137****0990,台费卡,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00
diff --git a/etl_billiards/docs/table_2025-12-19/财务_优惠分布_2025年10-12月.md b/etl_billiards/docs/table_2025-12-19/财务_优惠分布_2025年10-12月.md
deleted file mode 100644
index afba5bd..0000000
--- a/etl_billiards/docs/table_2025-12-19/财务_优惠分布_2025年10-12月.md
+++ /dev/null
@@ -1,52 +0,0 @@
-# 2025年10-12月 财务优惠（会员折扣+台费调账）分布
-## 思考过程
-用台费订单为基准关联调账表，再按客户+月份汇总，输出“谁享受了优惠”及金额分布。
-
-## 查询说明
-优惠=会员折扣(dwd_table_fee_log.member_discount_amount)+台费调账(dwd_table_fee_adjust.ledger_amount)，按订单归集后汇总到客户(member_id)，按订单最早开台时间切月；不含团购抵扣等其它优惠。
-
-## SQL
-
-### 优惠分布（客户+月份）
-```sql
-with base_orders as (
-  select
-    tfl.order_settle_id,
-    max(tfl.member_id) as member_id,
-    min(tfl.start_use_time) as order_start_time,
-    sum(tfl.member_discount_amount) as member_discount_amount
-  from billiards_dwd.dwd_table_fee_log tfl
-  where tfl.site_id = %(site_id)s
-    and coalesce(tfl.is_delete,0) = 0
-    and tfl.start_use_time >= %(window_start)s::timestamptz
-    and tfl.start_use_time <  %(window_end)s::timestamptz
-  group by tfl.order_settle_id
-),
-adjusts as (
-  select
-    tfa.order_settle_id,
-    sum(tfa.ledger_amount) as adjust_amount
-  from billiards_dwd.dwd_table_fee_adjust tfa
-  join base_orders bo on bo.order_settle_id = tfa.order_settle_id
-  where tfa.site_id = %(site_id)s
-    and coalesce(tfa.is_delete,0) = 0
-  group by tfa.order_settle_id
-)
-, x as (
-  select
-    bo.member_id,
-    case when bo.order_start_time >= '2025-10-01 00:00:00+08'::timestamptz and bo.order_start_time < '2025-11-01 00:00:00+08'::timestamptz then '2025-10' when bo.order_start_time >= '2025-11-01 00:00:00+08'::timestamptz and bo.order_start_time < '2025-12-01 00:00:00+08'::timestamptz then '2025-11' when bo.order_start_time >= '2025-12-01 00:00:00+08'::timestamptz and bo.order_start_time < '2026-01-01 00:00:00+08'::timestamptz then '2025-12' else null end as month_key,
-    coalesce(bo.member_discount_amount,0) as member_discount_amount,
-    coalesce(a.adjust_amount,0) as adjust_amount
-  from base_orders bo
-  left join adjusts a on a.order_settle_id = bo.order_settle_id
-)
-select
-  member_id,
-  month_key,
-  sum(member_discount_amount) as member_discount_sum,
-  sum(adjust_amount) as adjust_sum
-from x
-where month_key is not null
-group by member_id, month_key;
-```
diff --git a/tmp/env_report_local.txt b/tmp/env_report_local.txt
new file mode 100644
index 0000000..2bc51b1
--- /dev/null
+++ b/tmp/env_report_local.txt
@@ -0,0 +1,121 @@
+# ETL Manager Environment Report
+Timestamp: 2026-01-28 00:43:50
+
+## Executables
+python: C:\ProgramData\miniconda3\python.exe
+pip: C:\ProgramData\miniconda3\Scripts\pip.exe
+
+## Python info
+version=3.13.9 | packaged by Anaconda, Inc. | (main, Oct 21 2025, 19:09:58) [MSC v.1929 64 bit (AMD64)]
+executable=C:\ProgramData\miniconda3\python.exe
+prefix=C:\ProgramData\miniconda3
+base_prefix=C:\ProgramData\miniconda3
+arch=64bit
+platform=Windows-10-10.0.17763-SP0
+
+## pip
+pip 25.3 from C:\ProgramData\miniconda3\Lib\site-packages\pip (python 3.13)
+
+
+## PySide6
+  File "<string>", line 1
+    try:\n import PySide6\n from PySide6 import QtCore\n print('PySide6='+PySide6.__version__)\n print('Qt='+QtCore.qVersion())\n print('PySide6_path='+PySide6.__file__)\n print('Qt_plugins_path='+QtCore.QLibraryInfo.path(QtCore.QLibraryInfo.PluginsPath))\n except Exception as e:\n  print('PySide6_import_error='+repr(e))
+         ^
+SyntaxError: unexpected character after line continuation character
+
+## Installed packages (freeze)
+altgraph==0.17.5
+anaconda-anon-usage==0.7.4
+annotated-types==0.6.0
+archspec==0.2.5
+beautifulsoup4==4.13.4
+boltons==25.0.0
+brotlicffi==1.1.0.0
+certifi==2025.11.12
+cffi==2.0.0
+chardet==3.0.4
+charset-normalizer==3.4.4
+colorama==0.4.6
+conda==25.9.1
+conda-anaconda-telemetry==0.3.0
+conda-anaconda-tos==0.2.2
+conda-content-trust==0.2.0
+conda-libmamba-solver==25.4.0
+conda-package-handling==2.4.0
+conda_package_streaming==0.12.0
+coverage==7.12.0
+cryptography==46.0.3
+distro==1.9.0
+et_xmlfile==2.0.0
+frozendict==2.4.6
+ftfy==6.3.1
+googletrans==4.0.0rc1
+h11==0.9.0
+h2==3.2.0
+hpack==3.0.0
+hstspreload==2025.1.1
+httpcore==0.9.1
+httpx==0.13.3
+hyperframe==5.2.0
+idna==2.10
+iniconfig==2.3.0
+jsonpatch==1.33
+jsonpointer==3.0.0
+libmambapy==2.3.2
+lxml==6.0.2
+markdown-it-py==4.0.0
+mdurl==0.1.2
+menuinst==2.4.1
+numpy==2.3.2
+openpyxl==3.1.5
+packaging==25.0
+pandas==2.3.1
+pefile==2024.8.26
+pip==25.2
+platformdirs==4.5.0
+pluggy==1.5.0
+psycopg2==2.9.10
+psycopg2-binary==2.9.11
+pyaes==1.6.1
+pyasn1==0.6.1
+pycosat==0.6.6
+pycparser==2.23
+pydantic==2.12.3
+pydantic_core==2.41.4
+Pygments==2.19.2
+pyinstaller==6.18.0
+pyinstaller-hooks-contrib==2025.11
+PySide6==6.10.1
+PySide6_Addons==6.10.1
+PySide6_Essentials==6.10.1
+PySocks==1.7.1
+pytest==9.0.1
+pytest-cov==7.0.0
+python-dateutil==2.9.0.post0
+python-docx==1.2.0
+python-dotenv==1.2.1
+pytz==2025.2
+pywin32-ctypes==0.2.3
+requests==2.32.5
+rfc3986==1.5.0
+rich==14.2.0
+rsa==4.9.1
+ruamel.yaml==0.18.16
+ruamel.yaml.clib==0.2.14
+setuptools==80.9.0
+shiboken6==6.10.1
+six==1.17.0
+sniffio==1.3.1
+soupsieve==2.7
+Telethon==1.40.0
+tqdm==4.67.1
+truststore==0.10.1
+typing_extensions==4.15.0
+typing-inspection==0.4.2
+tzdata==2025.2
+urllib3==2.5.0
+wcwidth==0.2.14
+wheel==0.45.1
+win_inet_pton==1.1.0
+xlsxwriter==3.2.9
+zstandard==0.24.0