渠道支付状态金额

{
  "actual_digest": "6c40f8a90c80021b60f512f484d9886d0ecd7a9206a0380787a0383ae986e2f7",
  "assumptions": [],
  "attempt": 1,
  "category": "conditional_aggregation",
  "comparison": {
    "abs_tolerance": "0.005",
    "decimal_scale": 2,
    "duplicate_policy": "multiset",
    "max_rows": 10000,
    "rel_tolerance": "0",
    "row_order_significant": true
  },
  "difficulty": "medium",
  "error_code": null,
  "error_message": null,
  "execution_ms": 201.53850000497187,
  "expected_digest": "6c40f8a90c80021b60f512f484d9886d0ecd7a9206a0380787a0383ae986e2f7",
  "expected_result_preview": {
    "columns": [
      {
        "name": "channel_type",
        "type": "VARCHAR"
      },
      {
        "name": "paid_amount",
        "type": "DECIMAL(38,2)"
      },
      {
        "name": "refunded_amount",
        "type": "DECIMAL(38,2)"
      },
      {
        "name": "failed_amount",
        "type": "DECIMAL(38,2)"
      }
    ],
    "digest": "6c40f8a90c80021b60f512f484d9886d0ecd7a9206a0380787a0383ae986e2f7",
    "row_count": 4,
    "rows": [
      [
        "affiliate",
        "130639.25",
        "5602.25",
        "13165.50"
      ],
      [
        "offline",
        "140754.00",
        "5162.75",
        "22860.50"
      ],
      [
        "organic",
        "134754.50",
        "8260.00",
        "24282.50"
      ],
      [
        "paid_search",
        "121154.50",
        "8709.75",
        "19564.25"
      ]
    ]
  },
  "finished_at": "2026-08-29T22:08:03.668137",
  "formatted_sql": "SELECT\n  c.channel_type,\n  SUM(CASE WHEN p.status = 'paid' THEN p.amount ELSE 0 END) AS paid_amount,\n  SUM(CASE WHEN p.status = 'refunded' THEN p.amount ELSE 0 END) AS refunded_amount,\n  SUM(CASE WHEN p.status = 'failed' THEN p.amount ELSE 0 END) AS failed_amount\nFROM fact_payments AS p\nJOIN fact_orders AS o\n  ON p.order_id = o.order_id\nJOIN dim_channels AS c\n  ON o.channel_id = c.channel_id\nGROUP BY\n  c.channel_type\nORDER BY\n  c.channel_type ASC",
  "generated_sql": "SELECT\n    c.channel_type,\n    SUM(CASE WHEN p.status = 'paid' THEN p.amount ELSE 0 END) AS paid_amount,\n    SUM(CASE WHEN p.status = 'refunded' THEN p.amount ELSE 0 END) AS refunded_amount,\n    SUM(CASE WHEN p.status = 'failed' THEN p.amount ELSE 0 END) AS failed_amount\nFROM fact_payments AS p\nJOIN fact_orders AS o\n    ON p.order_id = o.order_id\nJOIN dim_channels AS c\n    ON o.channel_id = c.channel_id\nGROUP BY c.channel_type\nORDER BY c.channel_type ASC",
  "generation_ms": null,
  "id": 118,
  "model_name": "GPT 当前会话桥接（流程验收）",
  "model_run_id": 19,
  "plan": {
    "filters": [],
    "grain": "每行一个渠道类型（channel_type）",
    "joins": [
      "fact_payments.order_id = fact_orders.order_id",
      "fact_orders.channel_id = dim_channels.channel_id"
    ],
    "metrics": [
      "paid_amount = SUM(CASE WHEN fact_payments.status = 'paid' THEN fact_payments.amount ELSE 0 END)",
      "refunded_amount = SUM(CASE WHEN fact_payments.status = 'refunded' THEN fact_payments.amount ELSE 0 END)",
      "failed_amount = SUM(CASE WHEN fact_payments.status = 'failed' THEN fact_payments.amount ELSE 0 END)"
    ],
    "risks": [
      "一个订单可有多笔支付；按支付尝试粒度汇总金额，符合指标口径",
      "仅有支付记录关联到的渠道类型会出现在结果中"
    ],
    "sources": [
      "dim_channels",
      "fact_orders",
      "fact_payments"
    ],
    "steps": [
      "连接支付、订单和渠道表",
      "按 channel_type 分组并执行三组条件聚合",
      "按 channel_type 升序排序"
    ]
  },
  "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按渠道类型输出 channel_type、paid_amount、refunded_amount、failed_amount，并按 channel_type 升序；必须使用三组 SUM(CASE WHEN ...) 条件聚合。\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": "按渠道类型输出 channel_type、paid_amount、refunded_amount、failed_amount，并按 channel_type 升序；必须使用三组 SUM(CASE WHEN ...) 条件聚合。",
  "radar_dimension": "聚合与指标",
  "raw_output": "{\"plan\":{\"grain\":\"每行一个渠道类型（channel_type）\",\"sources\":[\"dim_channels\",\"fact_orders\",\"fact_payments\"],\"joins\":[\"fact_payments.order_id = fact_orders.order_id\",\"fact_orders.channel_id = dim_channels.channel_id\"],\"filters\":[],\"metrics\":[\"paid_amount = SUM(CASE WHEN fact_payments.status = 'paid' THEN fact_payments.amount ELSE 0 END)\",\"refunded_amount = SUM(CASE WHEN fact_payments.status = 'refunded' THEN fact_payments.amount ELSE 0 END)\",\"failed_amount = SUM(CASE WHEN fact_payments.status = 'failed' THEN fact_payments.amount ELSE 0 END)\"],\"steps\":[\"连接支付、订单和渠道表\",\"按 channel_type 分组并执行三组条件聚合\",\"按 channel_type 升序排序\"],\"risks\":[\"一个订单可有多笔支付；按支付尝试粒度汇总金额，符合指标口径\",\"仅有支付记录关联到的渠道类型会出现在结果中\"]},\"sql\":\"SELECT\\n    c.channel_type,\\n    SUM(CASE WHEN p.status = 'paid' THEN p.amount ELSE 0 END) AS paid_amount,\\n    SUM(CASE WHEN p.status = 'refunded' THEN p.amount ELSE 0 END) AS refunded_amount,\\n    SUM(CASE WHEN p.status = 'failed' THEN p.amount ELSE 0 END) AS failed_amount\\nFROM fact_payments AS p\\nJOIN fact_orders AS o\\n    ON p.order_id = o.order_id\\nJOIN dim_channels AS c\\n    ON o.channel_id = c.channel_id\\nGROUP BY c.channel_type\\nORDER BY c.channel_type ASC\",\"summary\":\"将支付记录经订单关联到渠道，按渠道类型分组，并使用三组 SUM(CASE WHEN ...) 分别汇总 paid、refunded 和 failed 状态金额。\",\"assumptions\":[]}",
  "reference_sql": "SELECT ch.channel_type, SUM(CASE WHEN p.status = 'paid' THEN p.amount ELSE 0 END) AS paid_amount, SUM(CASE WHEN p.status = 'refunded' THEN p.amount ELSE 0 END) AS refunded_amount, SUM(CASE WHEN p.status = 'failed' THEN p.amount ELSE 0 END) AS failed_amount FROM fact_payments p JOIN fact_orders o ON o.order_id = p.order_id JOIN dim_channels ch ON ch.channel_id = o.channel_id WHERE o.status = 'completed' GROUP BY ch.channel_type ORDER BY ch.channel_type ASC",
  "requested_model_id": "gpt-session-bridge",
  "required_ast": [
    {
      "aggregate": "SUM",
      "id": "sum-case-3",
      "kind": "aggregate_case_count",
      "when_count": 3
    }
  ],
  "resolved_model_id": "gpt-session-bridge",
  "result_preview": {
    "columns": [
      {
        "name": "channel_type",
        "type": "VARCHAR"
      },
      {
        "name": "paid_amount",
        "type": "DECIMAL(38,2)"
      },
      {
        "name": "refunded_amount",
        "type": "DECIMAL(38,2)"
      },
      {
        "name": "failed_amount",
        "type": "DECIMAL(38,2)"
      }
    ],
    "extra": [],
    "missing": [],
    "row_count": 4,
    "rows": [
      [
        "affiliate",
        "130639.25",
        "5602.25",
        "13165.50"
      ],
      [
        "offline",
        "140754.00",
        "5162.75",
        "22860.50"
      ],
      [
        "organic",
        "134754.50",
        "8260.00",
        "24282.50"
      ],
      [
        "paid_search",
        "121154.50",
        "8709.75",
        "19564.25"
      ]
    ]
  },
  "run_id": 16,
  "score": {
    "ast_rules": [
      {
        "details": {
          "actual": 3,
          "required": 3
        },
        "id": "sum-case-3",
        "kind": "aggregate_case_count",
        "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": "payment_status_by_channel",
  "started_at": "2026-08-29T22:07:54.596238",
  "status": "completed",
  "suite_content_hash": "5b5d98876ea35114f18ce6dfa48cc9800d88b6baba80d311b2f52552a38b31af",
  "title": "渠道支付状态金额",
  "token_usage": {
    "completion_tokens": 318,
    "prompt_tokens": 2374,
    "total_tokens": 2692
  },
  "visible_summary": "将支付记录经订单关联到渠道，按渠道类型分组，并使用三组 SUM(CASE WHEN ...) 分别汇总 paid、refunded 和 failed 状态金额。"
}