请求 #1
SEQ 75{
"isolation_policy_hash": "788e04b0065f23bee6e63310b335a471eb4036212c4f226f27de456bde8ea2fe",
"status": "running"
}案例记录 case-run-00016
相关子查询分群均值
找出金额高于同客户分群已完成订单平均金额的已完成订单，输出 order_id、customer_id、segment、total_amount、segment_avg_amount，并按 total_amount 降序、order_id 升序；必须使用外层引用的相关子查询。
运行信息
以下字段来自本次运行的冻结记录。
run
#11case run
#16attempt
1status
completedtoken total
19,434estimated cost
不可估算model generation
未记录SQL execution
237msadapter
codex_cliresponse mode
textrequested model
gpt-5.6-solresolved model
gpt-5.6-solprovider request id
未提供started
2026年8月29日 16:26finished
2026年8月29日 16:26suite hash
0a4a18b4374f510f5eff18b06272c30c3375e1f082ae405adc8ead7dd9c81556模型输入
显示本次实际保存的完整 Prompt。
你是 Text-to-SQL 生成器。只生成完成问题所需的 SQL 和简短可见摘要，不输出隐藏推理。
方言与安全规则：
Use DuckDB SQL. Return exactly one read-only query. Do not access files, URLs, extensions, or schemas outside the supplied tables.
数据库结构：
{"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"]}]}
语义层与业务口径：
{"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。"],"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"}]}
问题：
找出金额高于同客户分群已完成订单平均金额的已完成订单，输出 order_id、customer_id、segment、total_amount、segment_avg_amount，并按 total_amount 降序、order_id 升序；必须使用外层引用的相关子查询。
输出必须严格匹配此 JSON Schema：
{"additionalProperties":false,"properties":{"assumptions":{"items":{"type":"string"},"title":"Assumptions","type":"array"},"sql":{"title":"Sql","type":"string"},"summary":{"title":"Summary","type":"string"}},"required":["sql","summary","assumptions"],"title":"GenerationOutput","type":"object"}调用请求（1）
按事件序号排列；密钥和 Authorization 已移除。
历史证据边界：完整 Prompt 已保存，但这次 codex_cli 记录没有保存底层 HTTP 报文或 CLI 参数。本站不会把推测内容伪装成原始请求；未来运行会在 provider.requested 中记录脱敏后的完整调用信封。
模型输出
分别显示原始响应、解析结果和 SQL。
原始响应 raw_output
{"sql":"SELECT\n o.order_id,\n o.customer_id,\n c.segment,\n o.total_amount,\n (\n SELECT AVG(o2.total_amount)\n FROM fact_orders AS o2\n JOIN dim_customers AS c2\n ON c2.customer_id = o2.customer_id\n WHERE o2.status = 'completed'\n AND c2.segment = c.segment\n ) AS segment_avg_amount\nFROM fact_orders AS o\nJOIN dim_customers AS c\n ON c.customer_id = o.customer_id\nWHERE o.status = 'completed'\n AND o.total_amount > (\n SELECT AVG(o3.total_amount)\n FROM fact_orders AS o3\n JOIN dim_customers AS c3\n ON c3.customer_id = o3.customer_id\n WHERE o3.status = 'completed'\n AND c3.segment = c.segment\n )\nORDER BY o.total_amount DESC, o.order_id ASC;","summary":"返回金额高于其客户分群已完成订单平均金额的已完成订单，并按订单金额降序、订单 ID 升序排列。","assumptions":["订单金额采用 fact_orders.total_amount。","分群平均金额仅基于同 segment 且状态为 completed 的订单计算。"]}结构化查询方案 plan
没有可解析方案。
模型生成 SQL
SELECT
o.order_id,
o.customer_id,
c.segment,
o.total_amount,
(
SELECT AVG(o2.total_amount)
FROM fact_orders AS o2
JOIN dim_customers AS c2
ON c2.customer_id = o2.customer_id
WHERE o2.status = 'completed'
AND c2.segment = c.segment
) AS segment_avg_amount
FROM fact_orders AS o
JOIN dim_customers AS c
ON c.customer_id = o.customer_id
WHERE o.status = 'completed'
AND o.total_amount > (
SELECT AVG(o3.total_amount)
FROM fact_orders AS o3
JOIN dim_customers AS c3
ON c3.customer_id = o3.customer_id
WHERE o3.status = 'completed'
AND c3.segment = c.segment
)
ORDER BY o.total_amount DESC, o.order_id ASC;规范化 SQL
SELECT
o.order_id,
o.customer_id,
c.segment,
o.total_amount,
(
SELECT
AVG(o2.total_amount)
FROM fact_orders AS o2
JOIN dim_customers AS c2
ON c2.customer_id = o2.customer_id
WHERE
o2.status = 'completed' AND c2.segment = c.segment
) AS segment_avg_amount
FROM fact_orders AS o
JOIN dim_customers AS c
ON c.customer_id = o.customer_id
WHERE
o.status = 'completed'
AND o.total_amount > (
SELECT
AVG(o3.total_amount)
FROM fact_orders AS o3
JOIN dim_customers AS c3
ON c3.customer_id = o3.customer_id
WHERE
o3.status = 'completed' AND c3.segment = c.segment
)
ORDER BY
o.total_amount DESC,
o.order_id ASCToken 与耗时
{
"token_usage": {
"cache_write_input_tokens": 0,
"cached_input_tokens": 0,
"input_tokens": 19149,
"output_tokens": 285,
"reasoning_output_tokens": 0
},
"generation_ms": null,
"execution_ms": 236.56695800309535
}评分结果
包含评分明细、参考 SQL、结构要求、比较规则和结果差异。
评分明细 score
{
"ast_rules": [
{
"details": {
"actual": 2,
"required": 1
},
"id": "correlated",
"kind": "correlated_subquery",
"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
}参考 SQL
SELECT o.order_id, o.customer_id, c.segment, o.total_amount, a.segment_avg_amount FROM fact_orders o JOIN dim_customers c ON c.customer_id = o.customer_id JOIN LATERAL (SELECT ROUND(AVG(o2.total_amount), 2) AS segment_avg_amount FROM fact_orders o2 JOIN dim_customers c2 ON c2.customer_id = o2.customer_id WHERE o2.status = 'completed' AND c2.segment = c.segment) a ON TRUE WHERE o.status = 'completed' AND o.total_amount > a.segment_avg_amount ORDER BY o.total_amount DESC, o.order_id ASCAST 结构要求
[
{
"id": "correlated",
"kind": "correlated_subquery",
"min": 1
}
]结果比较规则
{
"abs_tolerance": "0.005",
"decimal_scale": 2,
"duplicate_policy": "multiset",
"max_rows": 10000,
"rel_tolerance": "0",
"row_order_significant": true
}期望结果预览
{
"columns": [
{
"name": "order_id",
"type": "BIGINT"
},
{
"name": "customer_id",
"type": "BIGINT"
},
{
"name": "segment",
"type": "VARCHAR"
},
{
"name": "total_amount",
"type": "DECIMAL(14,2)"
},
{
"name": "segment_avg_amount",
"type": "DOUBLE"
}
],
"digest": "9ff6d9203b1fe6cbdc9b4682f3a261e1ec9b367d85dd1e6c1256fc6d56144ed0",
"row_count": 232,
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}实际结果预览
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}摘要、错误与结果哈希
{
"visible_summary": "返回金额高于其客户分群已完成订单平均金额的已完成订单，并按订单金额降序、订单 ID 升序排列。",
"error_code": null,
"error_message": null,
"expected_digest": "9ff6d9203b1fe6cbdc9b4682f3a261e1ec9b367d85dd1e6c1256fc6d56144ed0",
"actual_digest": "7c32b1ee8a3f5ebde7ffe5380537bb7f0e336db813586a2194f0006dcc416ff3",
"assumptions": null
}事件记录（7）
按全局事件序号排列，保留时间、级别、类型、消息和 payload。
SEQ 73case.startedinfo{
"status": "generating"
}SEQ 74prompt.builtinfo{
"status": "completed"
}SEQ 75provider.requestedinfo{
"isolation_policy_hash": "788e04b0065f23bee6e63310b335a471eb4036212c4f226f27de456bde8ea2fe",
"status": "running"
}SEQ 76provider.deltainfo{
"text": "{\"sql\":\"SELECT\\n o.order_id,\\n o.customer_id,\\n c.segment,\\n o.total_amount,\\n (\\n SELECT AVG(o2.total_amount)\\n FROM fact_orders AS o2\\n JOIN dim_customers AS c2\\n ON c2.customer_id = o2.customer_id\\n WHERE o2.status = 'completed'\\n AND c2.segment = c.segment\\n ) AS segment_avg_amount\\nFROM fact_orders AS o\\nJOIN dim_customers AS c\\n ON c.customer_id = o.customer_id\\nWHERE o.status = 'completed'\\n AND o.total_amount > (\\n SELECT AVG(o3.total_amount)\\n FROM fact_orders AS o3\\n JOIN dim_customers AS c3\\n ON c3.customer_id = o3.customer_id\\n WHERE o3.status = 'completed'\\n AND c3.segment = c.segment\\n )\\nORDER BY o.total_amount DESC, o.order_id ASC;\",\"summary\":\"返回金额高于其客户分群已完成订单平均金额的已完成订单，并按订单金额降序、订单 ID 升序排列。\",\"assumptions\":[\"订单金额采用 fact_orders.total_amount。\",\"分群平均金额仅基于同 segment 且状态为 completed 的订单计算。\"]}"
}SEQ 77provider.completedinfo{
"elapsed_ms": 19159.36325000075,
"status": "completed",
"token_usage": {
"cache_write_input_tokens": 0,
"cached_input_tokens": 0,
"input_tokens": 19149,
"output_tokens": 285,
"reasoning_output_tokens": 0
}
}SEQ 78sql.parsedinfo{
"status": "completed"
}SEQ 79score.completedinfo{
"score": 100,
"status": "completed"
}原始案例数据
完整 JSON 字段，不经过页面裁剪。
展开全部原始字段
{
"actual_digest": "7c32b1ee8a3f5ebde7ffe5380537bb7f0e336db813586a2194f0006dcc416ff3",
"assumptions": null,
"attempt": 1,
"category": "subquery",
"comparison": {
"abs_tolerance": "0.005",
"decimal_scale": 2,
"duplicate_policy": "multiset",
"max_rows": 10000,
"rel_tolerance": "0",
"row_order_significant": true
},
"difficulty": "hard",
"error_code": null,
"error_message": null,
"execution_ms": 236.56695800309535,
"expected_digest": "9ff6d9203b1fe6cbdc9b4682f3a261e1ec9b367d85dd1e6c1256fc6d56144ed0",
"expected_result_preview": {
"columns": [
{
"name": "order_id",
"type": "BIGINT"
},
{
"name": "customer_id",
"type": "BIGINT"
},
{
"name": "segment",
"type": "VARCHAR"
},
{
"name": "total_amount",
"type": "DECIMAL(14,2)"
},
{
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"type": "DOUBLE"
}
],
"digest": "9ff6d9203b1fe6cbdc9b4682f3a261e1ec9b367d85dd1e6c1256fc6d56144ed0",
"row_count": 232,
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},
"finished_at": "2026-08-29T16:26:59.803871",
"formatted_sql": "SELECT\n o.order_id,\n o.customer_id,\n c.segment,\n o.total_amount,\n (\n SELECT\n AVG(o2.total_amount)\n FROM fact_orders AS o2\n JOIN dim_customers AS c2\n ON c2.customer_id = o2.customer_id\n WHERE\n o2.status = 'completed' AND c2.segment = c.segment\n ) AS segment_avg_amount\nFROM fact_orders AS o\nJOIN dim_customers AS c\n ON c.customer_id = o.customer_id\nWHERE\n o.status = 'completed'\n AND o.total_amount > (\n SELECT\n AVG(o3.total_amount)\n FROM fact_orders AS o3\n JOIN dim_customers AS c3\n ON c3.customer_id = o3.customer_id\n WHERE\n o3.status = 'completed' AND c3.segment = c.segment\n )\nORDER BY\n o.total_amount DESC,\n o.order_id ASC",
"generated_sql": "SELECT\n o.order_id,\n o.customer_id,\n c.segment,\n o.total_amount,\n (\n SELECT AVG(o2.total_amount)\n FROM fact_orders AS o2\n JOIN dim_customers AS c2\n ON c2.customer_id = o2.customer_id\n WHERE o2.status = 'completed'\n AND c2.segment = c.segment\n ) AS segment_avg_amount\nFROM fact_orders AS o\nJOIN dim_customers AS c\n ON c.customer_id = o.customer_id\nWHERE o.status = 'completed'\n AND o.total_amount > (\n SELECT AVG(o3.total_amount)\n FROM fact_orders AS o3\n JOIN dim_customers AS c3\n ON c3.customer_id = o3.customer_id\n WHERE o3.status = 'completed'\n AND c3.segment = c.segment\n )\nORDER BY o.total_amount DESC, o.order_id ASC;",
"generation_ms": null,
"id": 16,
"model_name": "Sol 本机实测",
"model_run_id": 11,
"plan": null,
"prompt": "你是 Text-to-SQL 生成器。只生成完成问题所需的 SQL 和简短可见摘要，不输出隐藏推理。\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。\"],\"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找出金额高于同客户分群已完成订单平均金额的已完成订单，输出 order_id、customer_id、segment、total_amount、segment_avg_amount，并按 total_amount 降序、order_id 升序；必须使用外层引用的相关子查询。\n\n输出必须严格匹配此 JSON Schema：\n{\"additionalProperties\":false,\"properties\":{\"assumptions\":{\"items\":{\"type\":\"string\"},\"title\":\"Assumptions\",\"type\":\"array\"},\"sql\":{\"title\":\"Sql\",\"type\":\"string\"},\"summary\":{\"title\":\"Summary\",\"type\":\"string\"}},\"required\":[\"sql\",\"summary\",\"assumptions\"],\"title\":\"GenerationOutput\",\"type\":\"object\"}",
"provider_request_id": null,
"question": "找出金额高于同客户分群已完成订单平均金额的已完成订单，输出 order_id、customer_id、segment、total_amount、segment_avg_amount，并按 total_amount 降序、order_id 升序；必须使用外层引用的相关子查询。",
"radar_dimension": "子查询",
"raw_output": "{\"sql\":\"SELECT\\n o.order_id,\\n o.customer_id,\\n c.segment,\\n o.total_amount,\\n (\\n SELECT AVG(o2.total_amount)\\n FROM fact_orders AS o2\\n JOIN dim_customers AS c2\\n ON c2.customer_id = o2.customer_id\\n WHERE o2.status = 'completed'\\n AND c2.segment = c.segment\\n ) AS segment_avg_amount\\nFROM fact_orders AS o\\nJOIN dim_customers AS c\\n ON c.customer_id = o.customer_id\\nWHERE o.status = 'completed'\\n AND o.total_amount > (\\n SELECT AVG(o3.total_amount)\\n FROM fact_orders AS o3\\n JOIN dim_customers AS c3\\n ON c3.customer_id = o3.customer_id\\n WHERE o3.status = 'completed'\\n AND c3.segment = c.segment\\n )\\nORDER BY o.total_amount DESC, o.order_id ASC;\",\"summary\":\"返回金额高于其客户分群已完成订单平均金额的已完成订单，并按订单金额降序、订单 ID 升序排列。\",\"assumptions\":[\"订单金额采用 fact_orders.total_amount。\",\"分群平均金额仅基于同 segment 且状态为 completed 的订单计算。\"]}",
"reference_sql": "SELECT o.order_id, o.customer_id, c.segment, o.total_amount, a.segment_avg_amount FROM fact_orders o JOIN dim_customers c ON c.customer_id = o.customer_id JOIN LATERAL (SELECT ROUND(AVG(o2.total_amount), 2) AS segment_avg_amount FROM fact_orders o2 JOIN dim_customers c2 ON c2.customer_id = o2.customer_id WHERE o2.status = 'completed' AND c2.segment = c.segment) a ON TRUE WHERE o.status = 'completed' AND o.total_amount > a.segment_avg_amount ORDER BY o.total_amount DESC, o.order_id ASC",
"requested_model_id": "gpt-5.6-sol",
"required_ast": [
{
"id": "correlated",
"kind": "correlated_subquery",
"min": 1
}
],
"resolved_model_id": "gpt-5.6-sol",
"result_preview": {
"columns": [
{
"name": "order_id",
"type": "BIGINT"
},
{
"name": "customer_id",
"type": "BIGINT"
},
{
"name": "segment",
"type": "VARCHAR"
},
{
"name": "total_amount",
"type": "DECIMAL(14,2)"
},
{
"name": "segment_avg_amount",
"type": "DOUBLE"
}
],
"extra": [],
"missing": [],
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"score": {
"ast_rules": [
{
"details": {
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"required": 1
},
"id": "correlated",
"kind": "correlated_subquery",
"passed": true
}
],
"column_count": 5,
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"execution": 10,
"ordering": 10,
"protocol": 5,
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"row_f1": 45,
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"total": 100
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"stable_key": "correlated_segment_average",
"started_at": "2026-08-29T16:26:40.370307",
"status": "completed",
"suite_content_hash": "0a4a18b4374f510f5eff18b06272c30c3375e1f082ae405adc8ead7dd9c81556",
"title": "相关子查询分群均值",
"token_usage": {
"cache_write_input_tokens": 0,
"cached_input_tokens": 0,
"input_tokens": 19149,
"output_tokens": 285,
"reasoning_output_tokens": 0
},
"visible_summary": "返回金额高于其客户分群已完成订单平均金额的已完成订单，并按订单金额降序、订单 ID 升序排列。"
}