微信小程序页面迁移校验之前 P5任务处理之前

scripts/ops/_diagnose_spi_v2.py

@@ -0,0 +1,120 @@
+"""深入诊断 SPI 数据时间分布"""
+import os
+from pathlib import Path
+from dotenv import load_dotenv
+
+load_dotenv(Path(__file__).resolve().parents[2] / ".env")
+
+PG_DSN = os.environ.get("PG_DSN")
+if not PG_DSN:
+    raise RuntimeError("PG_DSN 未设置")
+
+import psycopg2
+import psycopg2.extras
+
+conn = psycopg2.connect(PG_DSN)
+conn.autocommit = True
+
+def q(sql, params=None):
+    with conn.cursor(cursor_factory=psycopg2.extras.RealDictCursor) as cur:
+        cur.execute(sql, params or ())
+        return cur.fetchall()
+
+print("SPI 数据时间分布深入诊断")
+print("=" * 60)
+
+# 1. dwd_settlement_head 全量时间范围
+rows = q("""
+    SELECT 
+        MIN(pay_time) AS min_pay, MAX(pay_time) AS max_pay,
+        COUNT(*) AS total,
+        COUNT(*) FILTER (WHERE settle_type IN (1, 3)) AS consume_cnt,
+        COUNT(*) FILTER (WHERE settle_type = 2) AS recharge_cnt
+    FROM dwd.dwd_settlement_head
+""")
+r = rows[0]
+print(f"dwd_settlement_head 全量:")
+print(f"  总记录: {r['total']}, 消费(1,3): {r['consume_cnt']}, 充值(2): {r['recharge_cnt']}")
+print(f"  pay_time 范围: {r['min_pay']} ~ {r['max_pay']}")
+
+# 2. settle_type IN (1,3) 的最近数据
+rows2 = q("""
+    SELECT pay_time::date AS pay_date, COUNT(*) AS cnt
+    FROM dwd.dwd_settlement_head
+    WHERE settle_type IN (1, 3)
+    GROUP BY pay_time::date
+    ORDER BY pay_date DESC
+    LIMIT 20
+""")
+print(f"\n消费记录(settle_type IN 1,3) 最近 20 天:")
+for r in rows2:
+    print(f"  {r['pay_date']}: {r['cnt']} 条")
+
+# 3. SPI 用 NOW() - 90 days 作为截止，检查实际截止时间
+rows3 = q("SELECT NOW() AS now_ts, NOW() - INTERVAL '90 days' AS cutoff_90, NOW() - INTERVAL '30 days' AS cutoff_30")
+r = rows3[0]
+print(f"\n时间窗口:")
+print(f"  NOW(): {r['now_ts']}")
+print(f"  90天截止: {r['cutoff_90']}")
+print(f"  30天截止: {r['cutoff_30']}")
+
+# 4. 在 90 天窗口内，按月统计消费记录
+rows4 = q("""
+    SELECT 
+        DATE_TRUNC('month', pay_time)::date AS month,
+        COUNT(*) AS cnt,
+        COUNT(DISTINCT member_id) AS members,
+        SUM(COALESCE(pay_amount, 0)) AS total_amount
+    FROM dwd.dwd_settlement_head
+    WHERE settle_type IN (1, 3)
+      AND pay_time >= NOW() - INTERVAL '90 days'
+    GROUP BY month
+    ORDER BY month
+""")
+print(f"\n90天窗口内消费记录按月分布:")
+for r in rows4:
+    print(f"  {r['month']}: {r['cnt']} 条, {r['members']} 会员, 金额 {r['total_amount']}")
+
+# 5. 在 30 天窗口内的消费记录
+rows5 = q("""
+    SELECT 
+        COUNT(*) AS cnt,
+        COUNT(DISTINCT member_id) AS members,
+        SUM(COALESCE(pay_amount, 0)) AS total_amount,
+        MIN(pay_time) AS min_pay,
+        MAX(pay_time) AS max_pay
+    FROM dwd.dwd_settlement_head
+    WHERE settle_type IN (1, 3)
+      AND pay_time >= NOW() - INTERVAL '30 days'
+""")
+r = rows5[0]
+print(f"\n30天窗口内消费记录:")
+print(f"  记录数: {r['cnt']}, 会员数: {r['members']}, 总金额: {r['total_amount']}")
+print(f"  时间范围: {r['min_pay']} ~ {r['max_pay']}")
+
+# 6. 检查 ODS 层最新数据时间
+rows6 = q("""
+    SELECT 
+        MIN(pay_time) AS min_pay, MAX(pay_time) AS max_pay, COUNT(*) AS cnt
+    FROM ods.ods_settlement_records
+""")
+r = rows6[0]
+print(f"\nods_settlement_records:")
+print(f"  记录数: {r['cnt']}, pay_time 范围: {r['min_pay']} ~ {r['max_pay']}")
+
+# 7. 检查 DWD 层是否有 2 月中旬之后的数据
+rows7 = q("""
+    SELECT pay_time::date AS pay_date, COUNT(*) AS cnt
+    FROM dwd.dwd_settlement_head
+    WHERE pay_time >= '2026-02-10'
+    ORDER BY pay_date
+""")
+print(f"\nDWD 2026-02-10 之后的数据:")
+for r in rows7:
+    print(f"  {r['pay_date']}: {r['cnt']} 条")
+
+if not rows7:
+    print("  无数据!")
+
+conn.close()
+print("\n诊断完成。")