请求 #1
SEQ 85{
"isolation_policy_hash": "18d1a831cd9de94a945d5ed61d26e7d81105a9ad44215981632f087d3e4c0ea5",
"status": "running"
}案例记录 case-run-00156
先分别聚合已完成订单的售出数量和退货数量,再计算品类退货率;输出 category、sold_qty、returned_qty、return_rate,比率四舍五入 4 位,按 return_rate 降序、category 升序;必须至少两个 CTE 且不得明细直接 JOIN 造成 fan-out。
以下字段来自本次运行的冻结记录。
#18#1561completed20,210不可估算未记录201mscodex_clitextgpt-5.6-solgpt-5.6-sol未提供2026年8月29日 22:512026年8月29日 22:515b5d98876ea35114f18ce6dfa48cc9800d88b6baba80d311b2f52552a38b31af显示本次实际保存的完整 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。
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。","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"}]}
问题:
先分别聚合已完成订单的售出数量和退货数量,再计算品类退货率;输出 category、sold_qty、returned_qty、return_rate,比率四舍五入 4 位,按 return_rate 降序、category 升序;必须至少两个 CTE 且不得明细直接 JOIN 造成 fan-out。
规划要求:
plan 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。
SQL 必须严格实现该 plan,并遵循语义层业务口径。
summary 只概括最终做法,assumptions 只列无法由上下文确定的必要假设。
输出必须严格匹配此 JSON Schema:
{"$defs":{"QueryPlan":{"additionalProperties":false,"properties":{"filters":{"items":{"type":"string"},"title":"Filters","type":"array"},"grain":{"title":"Grain","type":"string"},"joins":{"items":{"type":"string"},"title":"Joins","type":"array"},"metrics":{"items":{"type":"string"},"title":"Metrics","type":"array"},"risks":{"items":{"type":"string"},"title":"Risks","type":"array"},"sources":{"items":{"type":"string"},"title":"Sources","type":"array"},"steps":{"items":{"type":"string"},"title":"Steps","type":"array"}},"required":["grain","sources","joins","filters","metrics","steps","risks"],"title":"QueryPlan","type":"object"}},"additionalProperties":false,"properties":{"assumptions":{"items":{"type":"string"},"title":"Assumptions","type":"array"},"plan":{"$ref":"#/$defs/QueryPlan"},"sql":{"title":"Sql","type":"string"},"summary":{"title":"Summary","type":"string"}},"required":["plan","sql","summary","assumptions"],"title":"GenerationOutput","type":"object"}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。
SEQ 85{
"isolation_policy_hash": "18d1a831cd9de94a945d5ed61d26e7d81105a9ad44215981632f087d3e4c0ea5",
"status": "running"
}分别显示原始响应、解析结果和 SQL。
{"plan":{"grain":"每个商品品类一行","sources":["fact_orders","fact_order_items","dim_products","fact_returns"],"joins":["订单行按 order_id 连接订单","订单行按 product_id 连接商品","退货按 order_id、line_no 连接订单行","品类汇总结果按 category 连接"],"filters":["fact_orders.status = 'completed'"],"metrics":["sold_qty:完成订单行 quantity 之和","returned_qty:完成订单退货 return_qty 之和","return_rate:returned_qty / sold_qty,四舍五入 4 位"],"steps":["按品类聚合完成订单售出数量","独立按品类聚合完成订单退货数量","连接两个品类级汇总并计算退货率","按 return_rate 降序、category 升序排序"],"risks":["退货明细不得与售出明细在同一聚合中直接连接","无退货品类需补零","使用 NULLIF 防止除零"]},"sql":"WITH sold_by_category AS (\n SELECT\n p.category,\n SUM(oi.quantity) AS sold_qty\n FROM fact_order_items AS oi\n JOIN fact_orders AS o\n ON oi.order_id = o.order_id\n JOIN dim_products AS p\n ON oi.product_id = p.product_id\n WHERE o.status = 'completed'\n GROUP BY p.category\n),\nreturned_by_category AS (\n SELECT\n p.category,\n SUM(r.return_qty) AS returned_qty\n FROM fact_returns AS r\n JOIN fact_order_items AS oi\n ON r.order_id = oi.order_id\n AND r.line_no = oi.line_no\n JOIN fact_orders AS o\n ON oi.order_id = o.order_id\n JOIN dim_products AS p\n ON oi.product_id = p.product_id\n WHERE o.status = 'completed'\n GROUP BY p.category\n)\nSELECT\n s.category,\n s.sold_qty,\n COALESCE(r.returned_qty, 0) AS returned_qty,\n ROUND(\n COALESCE(r.returned_qty, 0)::DECIMAL / NULLIF(s.sold_qty, 0),\n 4\n ) AS return_rate\nFROM sold_by_category AS s\nLEFT JOIN returned_by_category AS r\n ON s.category = r.category\nORDER BY return_rate DESC, s.category ASC","summary":"分别在品类粒度汇总完成订单的售出量和退货量,再连接汇总结果计算退货率,从而避免明细连接引起的 fan-out。","assumptions":[]}{
"filters": [
"fact_orders.status = 'completed'"
],
"grain": "每个商品品类一行",
"joins": [
"订单行按 order_id 连接订单",
"订单行按 product_id 连接商品",
"退货按 order_id、line_no 连接订单行",
"品类汇总结果按 category 连接"
],
"metrics": [
"sold_qty:完成订单行 quantity 之和",
"returned_qty:完成订单退货 return_qty 之和",
"return_rate:returned_qty / sold_qty,四舍五入 4 位"
],
"risks": [
"退货明细不得与售出明细在同一聚合中直接连接",
"无退货品类需补零",
"使用 NULLIF 防止除零"
],
"sources": [
"fact_orders",
"fact_order_items",
"dim_products",
"fact_returns"
],
"steps": [
"按品类聚合完成订单售出数量",
"独立按品类聚合完成订单退货数量",
"连接两个品类级汇总并计算退货率",
"按 return_rate 降序、category 升序排序"
]
}WITH sold_by_category AS (
SELECT
p.category,
SUM(oi.quantity) AS sold_qty
FROM fact_order_items AS oi
JOIN fact_orders AS o
ON oi.order_id = o.order_id
JOIN dim_products AS p
ON oi.product_id = p.product_id
WHERE o.status = 'completed'
GROUP BY p.category
),
returned_by_category AS (
SELECT
p.category,
SUM(r.return_qty) AS returned_qty
FROM fact_returns AS r
JOIN fact_order_items AS oi
ON r.order_id = oi.order_id
AND r.line_no = oi.line_no
JOIN fact_orders AS o
ON oi.order_id = o.order_id
JOIN dim_products AS p
ON oi.product_id = p.product_id
WHERE o.status = 'completed'
GROUP BY p.category
)
SELECT
s.category,
s.sold_qty,
COALESCE(r.returned_qty, 0) AS returned_qty,
ROUND(
COALESCE(r.returned_qty, 0)::DECIMAL / NULLIF(s.sold_qty, 0),
4
) AS return_rate
FROM sold_by_category AS s
LEFT JOIN returned_by_category AS r
ON s.category = r.category
ORDER BY return_rate DESC, s.category ASCWITH sold_by_category AS (
SELECT
p.category,
SUM(oi.quantity) AS sold_qty
FROM fact_order_items AS oi
JOIN fact_orders AS o
ON oi.order_id = o.order_id
JOIN dim_products AS p
ON oi.product_id = p.product_id
WHERE
o.status = 'completed'
GROUP BY
p.category
), returned_by_category AS (
SELECT
p.category,
SUM(r.return_qty) AS returned_qty
FROM fact_returns AS r
JOIN fact_order_items AS oi
ON r.order_id = oi.order_id AND r.line_no = oi.line_no
JOIN fact_orders AS o
ON oi.order_id = o.order_id
JOIN dim_products AS p
ON oi.product_id = p.product_id
WHERE
o.status = 'completed'
GROUP BY
p.category
)
SELECT
s.category,
s.sold_qty,
COALESCE(r.returned_qty, 0) AS returned_qty,
ROUND(CAST(COALESCE(r.returned_qty, 0) AS DECIMAL(18, 3)) / NULLIF(s.sold_qty, 0), 4) AS return_rate
FROM sold_by_category AS s
LEFT JOIN returned_by_category AS r
ON s.category = r.category
ORDER BY
return_rate DESC,
s.category ASC{
"token_usage": {
"cache_write_input_tokens": 0,
"cached_input_tokens": 0,
"input_tokens": 19540,
"output_tokens": 670,
"reasoning_output_tokens": 88
},
"generation_ms": null,
"execution_ms": 200.6555829939316
}包含评分明细、参考 SQL、结构要求、比较规则和结果差异。
{
"ast_rules": [
{
"details": {
"actual": 2,
"required": 2
},
"id": "cte-2",
"kind": "cte_count",
"passed": true
},
{
"details": {},
"id": "preaggregate",
"kind": "separate_measure_preaggregation",
"passed": false
}
],
"column_count": 5,
"column_names": 5,
"execution": 10,
"ordering": 10,
"protocol": 5,
"read_only_ast": 5,
"row_f1": 45,
"sql_capability": 7.5,
"total": 92.5
}WITH sold AS (SELECT p.category, SUM(i.quantity) AS sold_qty FROM fact_order_items i JOIN fact_orders o ON o.order_id = i.order_id JOIN dim_products p ON p.product_id = i.product_id WHERE o.status = 'completed' GROUP BY p.category), returned AS (SELECT p.category, SUM(r.return_qty) AS returned_qty FROM fact_returns r JOIN fact_order_items i ON i.order_id = r.order_id AND i.line_no = r.line_no JOIN fact_orders o ON o.order_id = i.order_id JOIN dim_products p ON p.product_id = i.product_id WHERE o.status = 'completed' GROUP BY p.category) SELECT s.category, s.sold_qty, COALESCE(r.returned_qty, 0) AS returned_qty, ROUND(COALESCE(r.returned_qty, 0)::DECIMAL / NULLIF(s.sold_qty, 0), 4) AS return_rate FROM sold s LEFT JOIN returned r ON r.category = s.category ORDER BY return_rate DESC, s.category ASC[
{
"id": "cte-2",
"kind": "cte_count",
"min": 2
},
{
"group_keys": [
"category"
],
"id": "preaggregate",
"kind": "separate_measure_preaggregation",
"left_cte": "sold",
"left_measure_column": "quantity",
"left_measure_table": "fact_order_items",
"right_cte": "returned",
"right_measure_column": "return_qty",
"right_measure_table": "fact_returns"
}
]{
"abs_tolerance": "0.00005",
"decimal_scale": 4,
"duplicate_policy": "multiset",
"max_rows": 10000,
"rel_tolerance": "0",
"row_order_significant": true
}{
"columns": [
{
"name": "category",
"type": "VARCHAR"
},
{
"name": "sold_qty",
"type": "HUGEINT"
},
{
"name": "returned_qty",
"type": "HUGEINT"
},
{
"name": "return_rate",
"type": "DOUBLE"
}
],
"digest": "1cd2adf76508064abb1c4545713625bdc2f4ecc4e9ddaba90d4cde74b93e3aed",
"row_count": 6,
"rows": [
[
"品类-5",
531,
58,
"0.1092"
],
[
"品类-3",
624,
52,
"0.0833"
],
[
"品类-4",
592,
49,
"0.0828"
],
[
"品类-6",
667,
50,
"0.075"
],
[
"品类-2",
649,
25,
"0.0385"
],
[
"品类-1",
593,
17,
"0.0287"
]
]
}{
"columns": [
{
"name": "category",
"type": "VARCHAR"
},
{
"name": "sold_qty",
"type": "HUGEINT"
},
{
"name": "returned_qty",
"type": "HUGEINT"
},
{
"name": "return_rate",
"type": "DOUBLE"
}
],
"extra": [],
"missing": [],
"row_count": 6,
"rows": [
[
"品类-5",
531,
58,
0.1092
],
[
"品类-3",
624,
52,
0.0833
],
[
"品类-4",
592,
49,
0.0828
],
[
"品类-6",
667,
50,
0.075
],
[
"品类-2",
649,
25,
0.0385
],
[
"品类-1",
593,
17,
0.0287
]
]
}{
"visible_summary": "分别在品类粒度汇总完成订单的售出量和退货量,再连接汇总结果计算退货率,从而避免明细连接引起的 fan-out。",
"error_code": null,
"error_message": null,
"expected_digest": "1cd2adf76508064abb1c4545713625bdc2f4ecc4e9ddaba90d4cde74b93e3aed",
"actual_digest": "733702af92a3c65ebb8f41c0ca46a721682381e97b14443eb8f2430a16c9a65e",
"assumptions": []
}按全局事件序号排列,保留时间、级别、类型、消息和 payload。
SEQ 83case.startedinfo{
"status": "generating"
}SEQ 84prompt.builtinfo{
"status": "completed"
}SEQ 85provider.requestedinfo{
"isolation_policy_hash": "18d1a831cd9de94a945d5ed61d26e7d81105a9ad44215981632f087d3e4c0ea5",
"status": "running"
}SEQ 86provider.deltainfo{
"text": "{\"plan\":{\"grain\":\"每个商品品类一行\",\"sources\":[\"fact_orders\",\"fact_order_items\",\"dim_products\",\"fact_returns\"],\"joins\":[\"订单行按 order_id 连接订单\",\"订单行按 product_id 连接商品\",\"退货按 order_id、line_no 连接订单行\",\"品类汇总结果按 category 连接\"],\"filters\":[\"fact_orders.status = 'completed'\"],\"metrics\":[\"sold_qty:完成订单行 quantity 之和\",\"returned_qty:完成订单退货 return_qty 之和\",\"return_rate:returned_qty / sold_qty,四舍五入 4 位\"],\"steps\":[\"按品类聚合完成订单售出数量\",\"独立按品类聚合完成订单退货数量\",\"连接两个品类级汇总并计算退货率\",\"按 return_rate 降序、category 升序排序\"],\"risks\":[\"退货明细不得与售出明细在同一聚合中直接连接\",\"无退货品类需补零\",\"使用 NULLIF 防止除零\"]},\"sql\":\"WITH sold_by_category AS (\\n SELECT\\n p.category,\\n SUM(oi.quantity) AS sold_qty\\n FROM fact_order_items AS oi\\n JOIN fact_orders AS o\\n ON oi.order_id = o.order_id\\n JOIN dim_products AS p\\n ON oi.product_id = p.product_id\\n WHERE o.status = 'completed'\\n GROUP BY p.category\\n),\\nreturned_by_category AS (\\n SELECT\\n p.category,\\n SUM(r.return_qty) AS returned_qty\\n FROM fact_returns AS r\\n JOIN fact_order_items AS oi\\n ON r.order_id = oi.order_id\\n AND r.line_no = oi.line_no\\n JOIN fact_orders AS o\\n ON oi.order_id = o.order_id\\n JOIN dim_products AS p\\n ON oi.product_id = p.product_id\\n WHERE o.status = 'completed'\\n GROUP BY p.category\\n)\\nSELECT\\n s.category,\\n s.sold_qty,\\n COALESCE(r.returned_qty, 0) AS returned_qty,\\n ROUND(\\n COALESCE(r.returned_qty, 0)::DECIMAL / NULLIF(s.sold_qty, 0),\\n 4\\n ) AS return_rate\\nFROM sold_by_category AS s\\nLEFT JOIN returned_by_category AS r\\n ON s.category = r.category\\nORDER BY return_rate DESC, s.category ASC\",\"summary\":\"分别在品类粒度汇总完成订单的售出量和退货量,再连接汇总结果计算退货率,从而避免明细连接引起的 fan-out。\",\"assumptions\":[]}"
}SEQ 87provider.completedinfo{
"elapsed_ms": 26653.061375000107,
"status": "completed",
"token_usage": {
"cache_write_input_tokens": 0,
"cached_input_tokens": 0,
"input_tokens": 19540,
"output_tokens": 670,
"reasoning_output_tokens": 88
}
}SEQ 88plan.completedinfo{
"grain": "每个商品品类一行",
"status": "completed",
"steps": 4
}SEQ 89sql.parsedinfo{
"status": "completed"
}SEQ 90score.completedinfo{
"score": 92.5,
"status": "completed"
}完整 JSON 字段,不经过页面裁剪。
{
"actual_digest": "733702af92a3c65ebb8f41c0ca46a721682381e97b14443eb8f2430a16c9a65e",
"assumptions": [],
"attempt": 1,
"category": "multi_stage_cte",
"comparison": {
"abs_tolerance": "0.00005",
"decimal_scale": 4,
"duplicate_policy": "multiset",
"max_rows": 10000,
"rel_tolerance": "0",
"row_order_significant": true
},
"difficulty": "hard",
"error_code": null,
"error_message": null,
"execution_ms": 200.6555829939316,
"expected_digest": "1cd2adf76508064abb1c4545713625bdc2f4ecc4e9ddaba90d4cde74b93e3aed",
"expected_result_preview": {
"columns": [
{
"name": "category",
"type": "VARCHAR"
},
{
"name": "sold_qty",
"type": "HUGEINT"
},
{
"name": "returned_qty",
"type": "HUGEINT"
},
{
"name": "return_rate",
"type": "DOUBLE"
}
],
"digest": "1cd2adf76508064abb1c4545713625bdc2f4ecc4e9ddaba90d4cde74b93e3aed",
"row_count": 6,
"rows": [
[
"品类-5",
531,
58,
"0.1092"
],
[
"品类-3",
624,
52,
"0.0833"
],
[
"品类-4",
592,
49,
"0.0828"
],
[
"品类-6",
667,
50,
"0.075"
],
[
"品类-2",
649,
25,
"0.0385"
],
[
"品类-1",
593,
17,
"0.0287"
]
]
},
"finished_at": "2026-08-29T22:51:47.117468",
"formatted_sql": "WITH sold_by_category AS (\n SELECT\n p.category,\n SUM(oi.quantity) AS sold_qty\n FROM fact_order_items AS oi\n JOIN fact_orders AS o\n ON oi.order_id = o.order_id\n JOIN dim_products AS p\n ON oi.product_id = p.product_id\n WHERE\n o.status = 'completed'\n GROUP BY\n p.category\n), returned_by_category AS (\n SELECT\n p.category,\n SUM(r.return_qty) AS returned_qty\n FROM fact_returns AS r\n JOIN fact_order_items AS oi\n ON r.order_id = oi.order_id AND r.line_no = oi.line_no\n JOIN fact_orders AS o\n ON oi.order_id = o.order_id\n JOIN dim_products AS p\n ON oi.product_id = p.product_id\n WHERE\n o.status = 'completed'\n GROUP BY\n p.category\n)\nSELECT\n s.category,\n s.sold_qty,\n COALESCE(r.returned_qty, 0) AS returned_qty,\n ROUND(CAST(COALESCE(r.returned_qty, 0) AS DECIMAL(18, 3)) / NULLIF(s.sold_qty, 0), 4) AS return_rate\nFROM sold_by_category AS s\nLEFT JOIN returned_by_category AS r\n ON s.category = r.category\nORDER BY\n return_rate DESC,\n s.category ASC",
"generated_sql": "WITH sold_by_category AS (\n SELECT\n p.category,\n SUM(oi.quantity) AS sold_qty\n FROM fact_order_items AS oi\n JOIN fact_orders AS o\n ON oi.order_id = o.order_id\n JOIN dim_products AS p\n ON oi.product_id = p.product_id\n WHERE o.status = 'completed'\n GROUP BY p.category\n),\nreturned_by_category AS (\n SELECT\n p.category,\n SUM(r.return_qty) AS returned_qty\n FROM fact_returns AS r\n JOIN fact_order_items AS oi\n ON r.order_id = oi.order_id\n AND r.line_no = oi.line_no\n JOIN fact_orders AS o\n ON oi.order_id = o.order_id\n JOIN dim_products AS p\n ON oi.product_id = p.product_id\n WHERE o.status = 'completed'\n GROUP BY p.category\n)\nSELECT\n s.category,\n s.sold_qty,\n COALESCE(r.returned_qty, 0) AS returned_qty,\n ROUND(\n COALESCE(r.returned_qty, 0)::DECIMAL / NULLIF(s.sold_qty, 0),\n 4\n ) AS return_rate\nFROM sold_by_category AS s\nLEFT JOIN returned_by_category AS r\n ON s.category = r.category\nORDER BY return_rate DESC, s.category ASC",
"generation_ms": null,
"id": 156,
"model_name": "Sol 本机实测",
"model_run_id": 22,
"plan": {
"filters": [
"fact_orders.status = 'completed'"
],
"grain": "每个商品品类一行",
"joins": [
"订单行按 order_id 连接订单",
"订单行按 product_id 连接商品",
"退货按 order_id、line_no 连接订单行",
"品类汇总结果按 category 连接"
],
"metrics": [
"sold_qty:完成订单行 quantity 之和",
"returned_qty:完成订单退货 return_qty 之和",
"return_rate:returned_qty / sold_qty,四舍五入 4 位"
],
"risks": [
"退货明细不得与售出明细在同一聚合中直接连接",
"无退货品类需补零",
"使用 NULLIF 防止除零"
],
"sources": [
"fact_orders",
"fact_order_items",
"dim_products",
"fact_returns"
],
"steps": [
"按品类聚合完成订单售出数量",
"独立按品类聚合完成订单退货数量",
"连接两个品类级汇总并计算退货率",
"按 return_rate 降序、category 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先分别聚合已完成订单的售出数量和退货数量,再计算品类退货率;输出 category、sold_qty、returned_qty、return_rate,比率四舍五入 4 位,按 return_rate 降序、category 升序;必须至少两个 CTE 且不得明细直接 JOIN 造成 fan-out。\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": "先分别聚合已完成订单的售出数量和退货数量,再计算品类退货率;输出 category、sold_qty、returned_qty、return_rate,比率四舍五入 4 位,按 return_rate 降序、category 升序;必须至少两个 CTE 且不得明细直接 JOIN 造成 fan-out。",
"radar_dimension": "数据开发",
"raw_output": "{\"plan\":{\"grain\":\"每个商品品类一行\",\"sources\":[\"fact_orders\",\"fact_order_items\",\"dim_products\",\"fact_returns\"],\"joins\":[\"订单行按 order_id 连接订单\",\"订单行按 product_id 连接商品\",\"退货按 order_id、line_no 连接订单行\",\"品类汇总结果按 category 连接\"],\"filters\":[\"fact_orders.status = 'completed'\"],\"metrics\":[\"sold_qty:完成订单行 quantity 之和\",\"returned_qty:完成订单退货 return_qty 之和\",\"return_rate:returned_qty / sold_qty,四舍五入 4 位\"],\"steps\":[\"按品类聚合完成订单售出数量\",\"独立按品类聚合完成订单退货数量\",\"连接两个品类级汇总并计算退货率\",\"按 return_rate 降序、category 升序排序\"],\"risks\":[\"退货明细不得与售出明细在同一聚合中直接连接\",\"无退货品类需补零\",\"使用 NULLIF 防止除零\"]},\"sql\":\"WITH sold_by_category AS (\\n SELECT\\n p.category,\\n SUM(oi.quantity) AS sold_qty\\n FROM fact_order_items AS oi\\n JOIN fact_orders AS o\\n ON oi.order_id = o.order_id\\n JOIN dim_products AS p\\n ON oi.product_id = p.product_id\\n WHERE o.status = 'completed'\\n GROUP BY p.category\\n),\\nreturned_by_category AS (\\n SELECT\\n p.category,\\n SUM(r.return_qty) AS returned_qty\\n FROM fact_returns AS r\\n JOIN fact_order_items AS oi\\n ON r.order_id = oi.order_id\\n AND r.line_no = oi.line_no\\n JOIN fact_orders AS o\\n ON oi.order_id = o.order_id\\n JOIN dim_products AS p\\n ON oi.product_id = p.product_id\\n WHERE o.status = 'completed'\\n GROUP BY p.category\\n)\\nSELECT\\n s.category,\\n s.sold_qty,\\n COALESCE(r.returned_qty, 0) AS returned_qty,\\n ROUND(\\n COALESCE(r.returned_qty, 0)::DECIMAL / NULLIF(s.sold_qty, 0),\\n 4\\n ) AS return_rate\\nFROM sold_by_category AS s\\nLEFT JOIN returned_by_category AS r\\n ON s.category = r.category\\nORDER BY return_rate DESC, s.category ASC\",\"summary\":\"分别在品类粒度汇总完成订单的售出量和退货量,再连接汇总结果计算退货率,从而避免明细连接引起的 fan-out。\",\"assumptions\":[]}",
"reference_sql": "WITH sold AS (SELECT p.category, SUM(i.quantity) AS sold_qty FROM fact_order_items i JOIN fact_orders o ON o.order_id = i.order_id JOIN dim_products p ON p.product_id = i.product_id WHERE o.status = 'completed' GROUP BY p.category), returned AS (SELECT p.category, SUM(r.return_qty) AS returned_qty FROM fact_returns r JOIN fact_order_items i ON i.order_id = r.order_id AND i.line_no = r.line_no JOIN fact_orders o ON o.order_id = i.order_id JOIN dim_products p ON p.product_id = i.product_id WHERE o.status = 'completed' GROUP BY p.category) SELECT s.category, s.sold_qty, COALESCE(r.returned_qty, 0) AS returned_qty, ROUND(COALESCE(r.returned_qty, 0)::DECIMAL / NULLIF(s.sold_qty, 0), 4) AS return_rate FROM sold s LEFT JOIN returned r ON r.category = s.category ORDER BY return_rate DESC, s.category ASC",
"requested_model_id": "gpt-5.6-sol",
"required_ast": [
{
"id": "cte-2",
"kind": "cte_count",
"min": 2
},
{
"group_keys": [
"category"
],
"id": "preaggregate",
"kind": "separate_measure_preaggregation",
"left_cte": "sold",
"left_measure_column": "quantity",
"left_measure_table": "fact_order_items",
"right_cte": "returned",
"right_measure_column": "return_qty",
"right_measure_table": "fact_returns"
}
],
"resolved_model_id": "gpt-5.6-sol",
"result_preview": {
"columns": [
{
"name": "category",
"type": "VARCHAR"
},
{
"name": "sold_qty",
"type": "HUGEINT"
},
{
"name": "returned_qty",
"type": "HUGEINT"
},
{
"name": "return_rate",
"type": "DOUBLE"
}
],
"extra": [],
"missing": [],
"row_count": 6,
"rows": [
[
"品类-5",
531,
58,
0.1092
],
[
"品类-3",
624,
52,
0.0833
],
[
"品类-4",
592,
49,
0.0828
],
[
"品类-6",
667,
50,
0.075
],
[
"品类-2",
649,
25,
0.0385
],
[
"品类-1",
593,
17,
0.0287
]
]
},
"run_id": 18,
"score": {
"ast_rules": [
{
"details": {
"actual": 2,
"required": 2
},
"id": "cte-2",
"kind": "cte_count",
"passed": true
},
{
"details": {},
"id": "preaggregate",
"kind": "separate_measure_preaggregation",
"passed": false
}
],
"column_count": 5,
"column_names": 5,
"execution": 10,
"ordering": 10,
"protocol": 5,
"read_only_ast": 5,
"row_f1": 45,
"sql_capability": 7.5,
"total": 92.5
},
"stable_key": "category_return_rate",
"started_at": "2026-08-29T22:51:20.242762",
"status": "completed",
"suite_content_hash": "5b5d98876ea35114f18ce6dfa48cc9800d88b6baba80d311b2f52552a38b31af",
"title": "品类退货率",
"token_usage": {
"cache_write_input_tokens": 0,
"cached_input_tokens": 0,
"input_tokens": 19540,
"output_tokens": 670,
"reasoning_output_tokens": 88
},
"visible_summary": "分别在品类粒度汇总完成订单的售出量和退货量,再连接汇总结果计算退货率,从而避免明细连接引起的 fan-out。"
}