月收入与累计收入

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  "assumptions": [],
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  "comparison": {
    "abs_tolerance": "0.005",
    "decimal_scale": 2,
    "duplicate_policy": "multiset",
    "max_rows": 10000,
    "rel_tolerance": "0",
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  "difficulty": "medium",
  "error_code": null,
  "error_message": null,
  "execution_ms": 192.44816599530168,
  "expected_digest": "fc4ade5a003f54c15eec904e5102d2c563cfcb21cee67f4a8fc2b5a16d07a99f",
  "expected_result_preview": {
    "columns": [
      {
        "name": "month",
        "type": "VARCHAR"
      },
      {
        "name": "monthly_revenue",
        "type": "DECIMAL(38,2)"
      },
      {
        "name": "cumulative_revenue",
        "type": "DECIMAL(38,2)"
      }
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    "rows": [
      [
        "2025-01",
        "41876.75",
        "41876.75"
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      [
        "2025-02",
        "31673.25",
        "73550.00"
      ],
      [
        "2025-03",
        "34373.25",
        "107923.25"
      ],
      [
        "2025-04",
        "25069.00",
        "132992.25"
      ],
      [
        "2025-05",
        "30064.50",
        "163056.75"
      ],
      [
        "2025-06",
        "31993.75",
        "195050.50"
      ],
      [
        "2025-07",
        "36093.75",
        "231144.25"
      ],
      [
        "2025-08",
        "29252.75",
        "260397.00"
      ],
      [
        "2025-09",
        "26246.25",
        "286643.25"
      ],
      [
        "2025-10",
        "21555.25",
        "308198.50"
      ],
      [
        "2025-11",
        "34944.25",
        "343142.75"
      ],
      [
        "2025-12",
        "20373.00",
        "363515.75"
      ]
    ]
  },
  "finished_at": "2026-08-29T22:57:00.425207",
  "formatted_sql": "WITH monthly AS (\n  SELECT\n    STRFTIME(o.order_date, '%Y-%m') AS month,\n    SUM(i.quantity * i.unit_price - i.discount_amount) AS monthly_revenue\n  FROM fact_orders AS o\n  JOIN fact_order_items AS i\n    ON i.order_id = o.order_id\n  WHERE\n    o.status = 'completed'\n    AND o.order_date >= CAST('2025-01-01' AS DATE)\n    AND o.order_date < CAST('2026-01-01' AS DATE)\n  GROUP BY\n    1\n)\nSELECT\n  month,\n  monthly_revenue,\n  SUM(monthly_revenue) OVER (ORDER BY month ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS cumulative_revenue\nFROM monthly\nORDER BY\n  month",
  "generated_sql": "WITH monthly AS (\n    SELECT\n        strftime(o.order_date, '%Y-%m') AS month,\n        SUM(i.quantity * i.unit_price - i.discount_amount) AS monthly_revenue\n    FROM fact_orders AS o\n    JOIN fact_order_items AS i\n        ON i.order_id = o.order_id\n    WHERE o.status = 'completed'\n      AND o.order_date >= DATE '2025-01-01'\n      AND o.order_date < DATE '2026-01-01'\n    GROUP BY 1\n)\nSELECT\n    month,\n    monthly_revenue,\n    SUM(monthly_revenue) OVER (\n        ORDER BY month\n        ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW\n    ) AS cumulative_revenue\nFROM monthly\nORDER BY month;",
  "generation_ms": null,
  "id": 134,
  "model_name": "Luna 本机实测",
  "model_run_id": 21,
  "plan": {
    "filters": [
      "fact_orders.status = 'completed'",
      "fact_orders.order_date >= DATE '2025-01-01'",
      "fact_orders.order_date < DATE '2026-01-01'"
    ],
    "grain": "每月",
    "joins": [
      "fact_order_items.order_id = fact_orders.order_id"
    ],
    "metrics": [
      "monthly_revenue：完成订单行净额汇总",
      "cumulative_revenue：按月份升序的 SUM 窗口累计"
    ],
    "risks": [
      "仅使用完成订单",
      "订单行净额口径为 quantity * unit_price - discount_amount"
    ],
    "sources": [
      "fact_orders",
      "fact_order_items"
    ],
    "steps": [
      "按 UTC 月份聚合完成订单行净销售额",
      "使用 SUM 窗口按 month 升序计算累计收入"
    ]
  },
  "prompt": "你是 Text-to-SQL 数据分析与数据开发生成器。先形成简洁、可审计的结构化查询方案，再生成完成问题所需的 SQL；不要输出隐藏推理。\n\n方言与安全规则：\nUse DuckDB SQL. Return exactly one read-only query. Do not access files, URLs, extensions, or schemas outside the supplied tables.\n\n数据库结构：\n{\"semantic_relationships\":[{\"cardinality\":\"many_to_one\",\"from_entity\":\"order\",\"sql_on\":\"fact_orders.customer_id = dim_customers.customer_id\",\"to_entity\":\"customer\"},{\"cardinality\":\"many_to_one\",\"from_entity\":\"order\",\"sql_on\":\"fact_orders.channel_id = dim_channels.channel_id\",\"to_entity\":\"channel\"},{\"cardinality\":\"many_to_one\",\"from_entity\":\"order_item\",\"sql_on\":\"fact_order_items.order_id = fact_orders.order_id\",\"to_entity\":\"order\"},{\"cardinality\":\"many_to_one\",\"from_entity\":\"order_item\",\"sql_on\":\"fact_order_items.product_id = dim_products.product_id\",\"to_entity\":\"product\"},{\"cardinality\":\"many_to_one\",\"from_entity\":\"payment\",\"sql_on\":\"fact_payments.order_id = fact_orders.order_id\",\"to_entity\":\"order\"},{\"cardinality\":\"many_to_one\",\"from_entity\":\"return\",\"sql_on\":\"fact_returns.order_id = fact_order_items.order_id AND fact_returns.line_no = fact_order_items.line_no\",\"to_entity\":\"order_item\"}],\"tables\":[{\"columns\":[{\"data_type\":\"BIGINT\",\"name\":\"channel_id\",\"nullable\":false},{\"data_type\":\"VARCHAR\",\"name\":\"channel_name\",\"nullable\":false},{\"data_type\":\"VARCHAR\",\"name\":\"channel_type\",\"nullable\":false}],\"foreign_keys\":[],\"name\":\"dim_channels\",\"primary_key\":[\"channel_id\"]},{\"columns\":[{\"data_type\":\"BIGINT\",\"name\":\"customer_id\",\"nullable\":false},{\"data_type\":\"VARCHAR\",\"name\":\"customer_name\",\"nullable\":false},{\"data_type\":\"VARCHAR\",\"name\":\"city\",\"nullable\":true},{\"data_type\":\"DATE\",\"name\":\"signup_date\",\"nullable\":false},{\"data_type\":\"VARCHAR\",\"name\":\"segment\",\"nullable\":false}],\"foreign_keys\":[],\"name\":\"dim_customers\",\"primary_key\":[\"customer_id\"]},{\"columns\":[{\"data_type\":\"BIGINT\",\"name\":\"product_id\",\"nullable\":false},{\"data_type\":\"VARCHAR\",\"name\":\"product_name\",\"nullable\":false},{\"data_type\":\"VARCHAR\",\"name\":\"category\",\"nullable\":false},{\"data_type\":\"VARCHAR\",\"name\":\"brand\",\"nullable\":false},{\"data_type\":\"DECIMAL(14,2)\",\"name\":\"list_price\",\"nullable\":false}],\"foreign_keys\":[],\"name\":\"dim_products\",\"primary_key\":[\"product_id\"]},{\"columns\":[{\"data_type\":\"BIGINT\",\"name\":\"order_id\",\"nullable\":false},{\"data_type\":\"BIGINT\",\"name\":\"line_no\",\"nullable\":false},{\"data_type\":\"BIGINT\",\"name\":\"product_id\",\"nullable\":false},{\"data_type\":\"BIGINT\",\"name\":\"quantity\",\"nullable\":false},{\"data_type\":\"DECIMAL(14,2)\",\"name\":\"unit_price\",\"nullable\":false},{\"data_type\":\"DECIMAL(14,2)\",\"name\":\"discount_amount\",\"nullable\":false}],\"foreign_keys\":[{\"columns\":[\"order_id\"],\"referenced_columns\":[\"order_id\"],\"referenced_table\":\"fact_orders\"},{\"columns\":[\"product_id\"],\"referenced_columns\":[\"product_id\"],\"referenced_table\":\"dim_products\"}],\"name\":\"fact_order_items\",\"primary_key\":[\"order_id\",\"line_no\"]},{\"columns\":[{\"data_type\":\"BIGINT\",\"name\":\"order_id\",\"nullable\":false},{\"data_type\":\"BIGINT\",\"name\":\"customer_id\",\"nullable\":false},{\"data_type\":\"BIGINT\",\"name\":\"channel_id\",\"nullable\":false},{\"data_type\":\"DATE\",\"name\":\"order_date\",\"nullable\":false},{\"data_type\":\"VARCHAR\",\"name\":\"status\",\"nullable\":false},{\"data_type\":\"DECIMAL(14,2)\",\"name\":\"total_amount\",\"nullable\":false}],\"foreign_keys\":[{\"columns\":[\"customer_id\"],\"referenced_columns\":[\"customer_id\"],\"referenced_table\":\"dim_customers\"},{\"columns\":[\"channel_id\"],\"referenced_columns\":[\"channel_id\"],\"referenced_table\":\"dim_channels\"}],\"name\":\"fact_orders\",\"primary_key\":[\"order_id\"]},{\"columns\":[{\"data_type\":\"BIGINT\",\"name\":\"payment_id\",\"nullable\":false},{\"data_type\":\"BIGINT\",\"name\":\"order_id\",\"nullable\":false},{\"data_type\":\"TIMESTAMP\",\"name\":\"paid_at\",\"nullable\":false},{\"data_type\":\"VARCHAR\",\"name\":\"payment_method\",\"nullable\":false},{\"data_type\":\"DECIMAL(14,2)\",\"name\":\"amount\",\"nullable\":false},{\"data_type\":\"VARCHAR\",\"name\":\"status\",\"nullable\":false}],\"foreign_keys\":[{\"columns\":[\"order_id\"],\"referenced_columns\":[\"order_id\"],\"referenced_table\":\"fact_orders\"}],\"name\":\"fact_payments\",\"primary_key\":[\"payment_id\"]},{\"columns\":[{\"data_type\":\"BIGINT\",\"name\":\"return_id\",\"nullable\":false},{\"data_type\":\"BIGINT\",\"name\":\"order_id\",\"nullable\":false},{\"data_type\":\"BIGINT\",\"name\":\"line_no\",\"nullable\":false},{\"data_type\":\"TIMESTAMP\",\"name\":\"returned_at\",\"nullable\":false},{\"data_type\":\"BIGINT\",\"name\":\"return_qty\",\"nullable\":false},{\"data_type\":\"DECIMAL(14,2)\",\"name\":\"refund_amount\",\"nullable\":false},{\"data_type\":\"VARCHAR\",\"name\":\"reason\",\"nullable\":true}],\"foreign_keys\":[{\"columns\":[\"order_id\",\"line_no\"],\"referenced_columns\":[\"order_id\",\"line_no\"],\"referenced_table\":\"fact_order_items\"}],\"name\":\"fact_returns\",\"primary_key\":[\"return_id\"]}]}\n\n语义层与业务口径：\n{\"business_rules\":[\"完成订单仅指 fact_orders.status = 'completed'。\",\"净销售额为 quantity * unit_price - discount_amount。\",\"paid、refunded、failed 金额只按 fact_payments.status 分类。\",\"退货率为完成订单的 returned_qty / sold_qty，售出数量仅含完成订单。\",\"月份按 UTC Gregorian calendar 计算。\",\"订单头 total_amount 应等于订单行净额汇总，差异视为数据质量异常。\"],\"dimensions\":[{\"data_type\":\"VARCHAR\",\"description\":\"客户分群\",\"expression\":\"dim_customers.segment\",\"name\":\"customer_segment\"},{\"data_type\":\"VARCHAR\",\"description\":\"商品品类\",\"expression\":\"dim_products.category\",\"name\":\"product_category\"},{\"data_type\":\"VARCHAR\",\"description\":\"渠道类型\",\"expression\":\"dim_channels.channel_type\",\"name\":\"channel_type\"},{\"data_type\":\"VARCHAR\",\"description\":\"UTC Gregorian 月份\",\"expression\":\"strftime(fact_orders.order_date, '%Y-%m')\",\"name\":\"order_month\"}],\"entities\":[{\"description\":\"客户主数据\",\"grain\":\"每行一个客户\",\"name\":\"customer\",\"primary_key\":[\"customer_id\"],\"table\":\"dim_customers\"},{\"description\":\"商品主数据\",\"grain\":\"每行一个商品\",\"name\":\"product\",\"primary_key\":[\"product_id\"],\"table\":\"dim_products\"},{\"description\":\"渠道主数据\",\"grain\":\"每行一个渠道\",\"name\":\"channel\",\"primary_key\":[\"channel_id\"],\"table\":\"dim_channels\"},{\"description\":\"订单头\",\"grain\":\"每行一个订单\",\"name\":\"order\",\"primary_key\":[\"order_id\"],\"table\":\"fact_orders\"},{\"description\":\"订单行\",\"grain\":\"每行一个订单商品行\",\"name\":\"order_item\",\"primary_key\":[\"order_id\",\"line_no\"],\"table\":\"fact_order_items\"},{\"description\":\"支付尝试\",\"grain\":\"每行一笔支付\",\"name\":\"payment\",\"primary_key\":[\"payment_id\"],\"table\":\"fact_payments\"},{\"description\":\"退货记录\",\"grain\":\"每行一条订单行退货\",\"name\":\"return\",\"primary_key\":[\"return_id\"],\"table\":\"fact_returns\"}],\"metrics\":[{\"description\":\"已完成订单数\",\"expression\":\"COUNT(DISTINCT CASE WHEN fact_orders.status = 'completed' THEN fact_orders.order_id END)\",\"filters\":[\"fact_orders.status = 'completed'\"],\"grain\":\"聚合\",\"name\":\"completed_order_count\"},{\"description\":\"完成订单商品行净销售额\",\"expression\":\"SUM(fact_order_items.quantity * fact_order_items.unit_price - fact_order_items.discount_amount)\",\"filters\":[\"fact_orders.status = 'completed'\"],\"grain\":\"聚合\",\"name\":\"net_revenue\"},{\"description\":\"成功支付金额\",\"expression\":\"SUM(CASE WHEN fact_payments.status = 'paid' THEN fact_payments.amount ELSE 0 END)\",\"filters\":[],\"grain\":\"聚合\",\"name\":\"paid_amount\"},{\"description\":\"退款状态支付金额\",\"expression\":\"SUM(CASE WHEN fact_payments.status = 'refunded' THEN fact_payments.amount ELSE 0 END)\",\"filters\":[],\"grain\":\"聚合\",\"name\":\"refunded_amount\"},{\"description\":\"失败支付金额\",\"expression\":\"SUM(CASE WHEN fact_payments.status = 'failed' THEN fact_payments.amount ELSE 0 END)\",\"filters\":[],\"grain\":\"聚合\",\"name\":\"failed_amount\"},{\"description\":\"完成订单退货数量除以售出数量\",\"expression\":\"SUM(fact_returns.return_qty) / SUM(fact_order_items.quantity)\",\"filters\":[\"fact_orders.status = 'completed'\"],\"grain\":\"聚合\",\"name\":\"return_rate\"}],\"relationships\":[{\"cardinality\":\"many_to_one\",\"from_entity\":\"order\",\"sql_on\":\"fact_orders.customer_id = dim_customers.customer_id\",\"to_entity\":\"customer\"},{\"cardinality\":\"many_to_one\",\"from_entity\":\"order\",\"sql_on\":\"fact_orders.channel_id = dim_channels.channel_id\",\"to_entity\":\"channel\"},{\"cardinality\":\"many_to_one\",\"from_entity\":\"order_item\",\"sql_on\":\"fact_order_items.order_id = fact_orders.order_id\",\"to_entity\":\"order\"},{\"cardinality\":\"many_to_one\",\"from_entity\":\"order_item\",\"sql_on\":\"fact_order_items.product_id = dim_products.product_id\",\"to_entity\":\"product\"},{\"cardinality\":\"many_to_one\",\"from_entity\":\"payment\",\"sql_on\":\"fact_payments.order_id = fact_orders.order_id\",\"to_entity\":\"order\"},{\"cardinality\":\"many_to_one\",\"from_entity\":\"return\",\"sql_on\":\"fact_returns.order_id = fact_order_items.order_id AND fact_returns.line_no = fact_order_items.line_no\",\"to_entity\":\"order_item\"}]}\n\n问题：\n输出 2025 年每月已完成订单收入及累计收入 month、monthly_revenue、cumulative_revenue，按 month 升序；必须使用 SUM 窗口并按 month 排序。\n\n规划要求：\nplan 只记录输出粒度、数据源、连接、过滤、指标、执行步骤和风险检查；每项保持简短。\nSQL 必须严格实现该 plan，并遵循语义层业务口径。\nsummary 只概括最终做法，assumptions 只列无法由上下文确定的必要假设。\n输出必须严格匹配此 JSON Schema：\n{\"$defs\":{\"QueryPlan\":{\"additionalProperties\":false,\"properties\":{\"filters\":{\"items\":{\"type\":\"string\"},\"title\":\"Filters\",\"type\":\"array\"},\"grain\":{\"title\":\"Grain\",\"type\":\"string\"},\"joins\":{\"items\":{\"type\":\"string\"},\"title\":\"Joins\",\"type\":\"array\"},\"metrics\":{\"items\":{\"type\":\"string\"},\"title\":\"Metrics\",\"type\":\"array\"},\"risks\":{\"items\":{\"type\":\"string\"},\"title\":\"Risks\",\"type\":\"array\"},\"sources\":{\"items\":{\"type\":\"string\"},\"title\":\"Sources\",\"type\":\"array\"},\"steps\":{\"items\":{\"type\":\"string\"},\"title\":\"Steps\",\"type\":\"array\"}},\"required\":[\"grain\",\"sources\",\"joins\",\"filters\",\"metrics\",\"steps\",\"risks\"],\"title\":\"QueryPlan\",\"type\":\"object\"}},\"additionalProperties\":false,\"properties\":{\"assumptions\":{\"items\":{\"type\":\"string\"},\"title\":\"Assumptions\",\"type\":\"array\"},\"plan\":{\"$ref\":\"#/$defs/QueryPlan\"},\"sql\":{\"title\":\"Sql\",\"type\":\"string\"},\"summary\":{\"title\":\"Summary\",\"type\":\"string\"}},\"required\":[\"plan\",\"sql\",\"summary\",\"assumptions\"],\"title\":\"GenerationOutput\",\"type\":\"object\"}",
  "provider_request_id": null,
  "question": "输出 2025 年每月已完成订单收入及累计收入 month、monthly_revenue、cumulative_revenue，按 month 升序；必须使用 SUM 窗口并按 month 排序。",
  "radar_dimension": "时间与窗口",
  "raw_output": "{\"plan\":{\"grain\":\"每月\",\"sources\":[\"fact_orders\",\"fact_order_items\"],\"joins\":[\"fact_order_items.order_id = fact_orders.order_id\"],\"filters\":[\"fact_orders.status = 'completed'\",\"fact_orders.order_date >= DATE '2025-01-01'\",\"fact_orders.order_date < DATE '2026-01-01'\"],\"metrics\":[\"monthly_revenue：完成订单行净额汇总\",\"cumulative_revenue：按月份升序的 SUM 窗口累计\"],\"steps\":[\"按 UTC 月份聚合完成订单行净销售额\",\"使用 SUM 窗口按 month 升序计算累计收入\"],\"risks\":[\"仅使用完成订单\",\"订单行净额口径为 quantity * unit_price - discount_amount\"]},\"sql\":\"WITH monthly AS (\\n    SELECT\\n        strftime(o.order_date, '%Y-%m') AS month,\\n        SUM(i.quantity * i.unit_price - i.discount_amount) AS monthly_revenue\\n    FROM fact_orders AS o\\n    JOIN fact_order_items AS i\\n        ON i.order_id = o.order_id\\n    WHERE o.status = 'completed'\\n      AND o.order_date >= DATE '2025-01-01'\\n      AND o.order_date < DATE '2026-01-01'\\n    GROUP BY 1\\n)\\nSELECT\\n    month,\\n    monthly_revenue,\\n    SUM(monthly_revenue) OVER (\\n        ORDER BY month\\n        ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW\\n    ) AS cumulative_revenue\\nFROM monthly\\nORDER BY month;\",\"summary\":\"按 UTC 月份汇总 2025 年完成订单的订单行净销售额，并使用按 month 升序的 SUM 窗口计算累计收入。\",\"assumptions\":[]}",
  "reference_sql": "WITH monthly AS (SELECT strftime(order_date, '%Y-%m') AS month, SUM(total_amount) AS monthly_revenue FROM fact_orders WHERE status = 'completed' AND order_date >= DATE '2025-01-01' AND order_date < DATE '2026-01-01' GROUP BY month) SELECT month, monthly_revenue, SUM(monthly_revenue) OVER (ORDER BY month ASC ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS cumulative_revenue FROM monthly ORDER BY month ASC",
  "requested_model_id": "gpt-5.6-luna",
  "required_ast": [
    {
      "id": "running-sum",
      "kind": "window_function",
      "min": 1,
      "name": "SUM",
      "order_by": [
        {
          "direction": "ASC",
          "expression": "month"
        }
      ],
      "partition_columns": []
    }
  ],
  "resolved_model_id": "gpt-5.6-luna",
  "result_preview": {
    "columns": [
      {
        "name": "month",
        "type": "VARCHAR"
      },
      {
        "name": "monthly_revenue",
        "type": "DECIMAL(38,2)"
      },
      {
        "name": "cumulative_revenue",
        "type": "DECIMAL(38,2)"
      }
    ],
    "extra": [],
    "missing": [],
    "row_count": 12,
    "rows": [
      [
        "2025-01",
        "41876.75",
        "41876.75"
      ],
      [
        "2025-02",
        "31673.25",
        "73550.00"
      ],
      [
        "2025-03",
        "34373.25",
        "107923.25"
      ],
      [
        "2025-04",
        "25069.00",
        "132992.25"
      ],
      [
        "2025-05",
        "30064.50",
        "163056.75"
      ],
      [
        "2025-06",
        "31993.75",
        "195050.50"
      ],
      [
        "2025-07",
        "36093.75",
        "231144.25"
      ],
      [
        "2025-08",
        "29252.75",
        "260397.00"
      ],
      [
        "2025-09",
        "26246.25",
        "286643.25"
      ],
      [
        "2025-10",
        "21555.25",
        "308198.50"
      ],
      [
        "2025-11",
        "34944.25",
        "343142.75"
      ],
      [
        "2025-12",
        "20373.00",
        "363515.75"
      ]
    ]
  },
  "run_id": 18,
  "score": {
    "ast_rules": [
      {
        "details": {
          "actual": 1,
          "required": 1
        },
        "id": "running-sum",
        "kind": "window_function",
        "passed": true
      }
    ],
    "column_count": 5,
    "column_names": 5,
    "execution": 10,
    "ordering": 10,
    "protocol": 5,
    "read_only_ast": 5,
    "row_f1": 45,
    "sql_capability": 15,
    "total": 100
  },
  "stable_key": "monthly_running_revenue",
  "started_at": "2026-08-29T22:56:37.124868",
  "status": "completed",
  "suite_content_hash": "5b5d98876ea35114f18ce6dfa48cc9800d88b6baba80d311b2f52552a38b31af",
  "title": "月收入与累计收入",
  "token_usage": {
    "cache_write_input_tokens": 0,
    "cached_input_tokens": 0,
    "input_tokens": 18013,
    "output_tokens": 555,
    "reasoning_output_tokens": 165
  },
  "visible_summary": "按 UTC 月份汇总 2025 年完成订单的订单行净销售额，并使用按 month 升序的 SUM 窗口计算累计收入。"
}