请求 #1
SEQ 5{
"isolation_policy_hash": "747b1ca3decdc24da64208265966caf487d37482255536a35fa93e138bee8f77",
"status": "running"
}案例记录 case-run-00127
基础筛选与排序
查询 2026-01-01 起已完成订单，输出 order_id、customer_name、order_date、total_amount，并按 total_amount 降序、order_id 升序。
运行信息
以下字段来自本次运行的冻结记录。
run
#17case run
#127attempt
1status
completedtoken total
18,345estimated cost
不可估算model generation
未记录SQL execution
360msadapter
codex_cliresponse mode
textrequested model
gpt-5.6-lunaresolved model
gpt-5.6-lunaprovider request id
未提供started
2026年8月29日 22:46finished
2026年8月29日 22:47suite hash
5b5d98876ea35114f18ce6dfa48cc9800d88b6baba80d311b2f52552a38b31af模型输入
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：
查询 2026-01-01 起已完成订单，输出 order_id、customer_name、order_date、total_amount，并按 total_amount 降序、order_id 升序。
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"}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
{"plan":{"grain":"每行一个订单","sources":["fact_orders","dim_customers"],"joins":["fact_orders.customer_id = dim_customers.customer_id"],"filters":["fact_orders.status = 'completed'","fact_orders.order_date >= DATE '2026-01-01'"],"metrics":["输出订单头 total_amount"],"steps":["筛选完成订单及日期范围","连接客户维度获取 customer_name","按 total_amount 降序、order_id 升序排序"],"risks":["仅使用订单头 total_amount，不重复汇总订单行"]},"sql":"SELECT\n o.order_id,\n c.customer_name,\n o.order_date,\n o.total_amount\nFROM fact_orders AS o\nJOIN dim_customers AS c\n ON o.customer_id = c.customer_id\nWHERE o.status = 'completed'\n AND o.order_date >= DATE '2026-01-01'\nORDER BY o.total_amount DESC, o.order_id ASC;","summary":"筛选 2026-01-01 起的已完成订单，连接客户名称，输出订单信息并按订单金额降序、订单号升序排列。","assumptions":[]}结构化查询方案 plan
{
"filters": [
"fact_orders.status = 'completed'",
"fact_orders.order_date >= DATE '2026-01-01'"
],
"grain": "每行一个订单",
"joins": [
"fact_orders.customer_id = dim_customers.customer_id"
],
"metrics": [
"输出订单头 total_amount"
],
"risks": [
"仅使用订单头 total_amount，不重复汇总订单行"
],
"sources": [
"fact_orders",
"dim_customers"
],
"steps": [
"筛选完成订单及日期范围",
"连接客户维度获取 customer_name",
"按 total_amount 降序、order_id 升序排序"
]
}模型生成 SQL
SELECT
o.order_id,
c.customer_name,
o.order_date,
o.total_amount
FROM fact_orders AS o
JOIN dim_customers AS c
ON o.customer_id = c.customer_id
WHERE o.status = 'completed'
AND o.order_date >= DATE '2026-01-01'
ORDER BY o.total_amount DESC, o.order_id ASC;规范化 SQL
SELECT
o.order_id,
c.customer_name,
o.order_date,
o.total_amount
FROM fact_orders AS o
JOIN dim_customers AS c
ON o.customer_id = c.customer_id
WHERE
o.status = 'completed' AND o.order_date >= CAST('2026-01-01' AS DATE)
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": 17999,
"output_tokens": 346,
"reasoning_output_tokens": 85
},
"generation_ms": null,
"execution_ms": 359.98508300690446
}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": [],
"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, c.customer_name, o.order_date, o.total_amount FROM fact_orders o JOIN dim_customers c ON c.customer_id = o.customer_id WHERE o.status = 'completed' AND o.order_date >= DATE '2026-01-01' ORDER BY o.total_amount DESC, o.order_id ASCAST 结构要求
[]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_name",
"type": "VARCHAR"
},
{
"name": "order_date",
"type": "DATE"
},
{
"name": "total_amount",
"type": "DECIMAL(14,2)"
}
],
"digest": "d780841b19b0607647e55663cbe9eab3c35ff2b55eba3e78334a7fb27e22c268",
"row_count": 162,
"rows": [
[
562,
"客户-059",
"2026-01-13",
"3278.25"
],
[
157,
"客户-002",
"2026-03-26",
"3065.50"
],
[
497,
"客户-078",
"2026-05-26",
"3039.75"
],
[
529,
"客户-095",
"2026-04-21",
"3037.25"
],
[
315,
"客户-065",
"2026-03-11",
"3006.75"
],
[
287,
"客户-080",
"2026-03-08",
"2831.00"
],
[
93,
"客户-044",
"2026-03-17",
"2775.50"
],
[
36,
"客户-065",
"2026-02-15",
"2756.25"
],
[
44,
"客户-059",
"2026-01-06",
"2743.00"
],
[
238,
"客户-014",
"2026-06-03",
"2697.00"
],
[
255,
"客户-017",
"2026-04-24",
"2417.25"
],
[
206,
"客户-063",
"2026-06-30",
"2372.00"
],
[
503,
"客户-044",
"2026-02-26",
"2363.25"
],
[
38,
"客户-095",
"2026-05-07",
"2307.75"
],
[
144,
"客户-038",
"2026-04-18",
"2272.25"
],
[
526,
"客户-027",
"2026-06-28",
"2269.75"
],
[
368,
"客户-045",
"2026-02-13",
"2257.25"
],
[
105,
"客户-019",
"2026-01-19",
"2244.75"
],
[
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"客户-044",
"2026-04-03",
"2234.00"
],
[
202,
"客户-109",
"2026-06-15",
"2177.25"
],
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27,
"客户-085",
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],
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597,
"客户-094",
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],
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272,
"客户-032",
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],
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"客户-082",
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],
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"客户-050",
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],
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159,
"客户-034",
"2026-05-04",
"2060.50"
],
[
279,
"客户-040",
"2026-04-02",
"2018.50"
],
[
98,
"客户-021",
"2026-03-31",
"1982.25"
],
[
68,
"客户-013",
"2026-01-05",
"1975.75"
],
[
266,
"客户-058",
"2026-06-01",
"1969.00"
],
[
172,
"客户-062",
"2026-03-07",
"1968.00"
],
[
298,
"客户-094",
"2026-01-09",
"1951.25"
],
[
63,
"客户-094",
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],
[
523,
"客户-060",
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"1890.50"
],
[
57,
"客户-105",
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],
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"客户-046",
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],
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"客户-006",
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],
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"客户-093",
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"1798.00"
],
[
192,
"客户-076",
"2026-04-24",
"1793.75"
],
[
578,
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],
[
388,
"客户-015",
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"1789.75"
],
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"1789.00"
],
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405,
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"1774.50"
],
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95,
"客户-015",
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],
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"客户-079",
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],
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],
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177,
"客户-093",
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],
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55,
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"1714.25"
],
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229,
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],
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138,
"客户-064",
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],
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],
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],
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"客户-057",
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],
[
305,
"客户-053",
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"1621.75"
],
[
508,
"客户-012",
"2026-01-07",
"1584.25"
],
[
148,
"客户-095",
"2026-01-16",
"1496.75"
],
[
399,
"客户-109",
"2026-05-03",
"1493.00"
],
[
267,
"客户-017",
"2026-05-15",
"1489.00"
],
[
103,
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],
[
343,
"客户-084",
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567,
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52,
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243,
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[
339,
"客户-081",
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"1368.75"
],
[
537,
"客户-093",
"2026-04-25",
"1363.25"
],
[
594,
"客户-041",
"2026-05-30",
"1345.50"
],
[
463,
"客户-107",
"2026-02-02",
"1342.25"
],
[
58,
"客户-073",
"2026-04-17",
"1334.25"
],
[
357,
"客户-019",
"2026-01-06",
"1318.50"
],
[
195,
"客户-029",
"2026-01-09",
"1309.50"
],
[
64,
"客户-081",
"2026-01-09",
"1259.25"
],
[
367,
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524,
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],
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583,
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316,
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263,
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900001,
"客户-001",
"2026-06-30",
"1189.00"
],
[
384,
"客户-052",
"2026-02-10",
"1175.75"
],
[
116,
"客户-010",
"2026-03-13",
"1156.25"
],
[
244,
"客户-072",
"2026-01-20",
"1145.25"
],
[
416,
"客户-017",
"2026-05-03",
"1138.75"
],
[
88,
"客户-098",
"2026-02-17",
"1136.25"
],
[
359,
"客户-019",
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"1058.00"
],
[
256,
"客户-036",
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],
[
516,
"客户-005",
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],
[
75,
"客户-001",
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"988.75"
],
[
253,
"客户-074",
"2026-01-17",
"971.50"
],
[
376,
"客户-011",
"2026-06-03",
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],
[
559,
"客户-057",
"2026-04-06",
"946.75"
],
[
74,
"客户-068",
"2026-05-29",
"928.25"
],
[
382,
"客户-087",
"2026-01-27",
"920.75"
],
[
467,
"客户-102",
"2026-05-18",
"918.75"
],
[
539,
"客户-062",
"2026-04-28",
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],
[
309,
"客户-093",
"2026-02-03",
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],
[
464,
"客户-053",
"2026-02-12",
"822.75"
],
[
176,
"客户-018",
"2026-01-04",
"804.25"
],
[
363,
"客户-030",
"2026-04-06",
"801.00"
],
[
149,
"客户-013",
"2026-03-08",
"786.25"
],
[
498,
"客户-065",
"2026-01-23",
"759.50"
],
[
582,
"客户-100",
"2026-06-25",
"744.00"
],
[
84,
"客户-041",
"2026-04-22",
"741.25"
],
[
66,
"客户-090",
"2026-02-25",
"710.00"
],
[
412,
"客户-074",
"2026-03-23",
"701.75"
],
[
169,
"客户-013",
"2026-03-09",
"685.75"
],
[
32,
"客户-072",
"2026-06-21",
"680.00"
],
[
457,
"客户-029",
"2026-04-29",
"662.50"
],
[
69,
"客户-105",
"2026-01-19",
"604.75"
],
[
37,
"客户-105",
"2026-05-09",
"597.00"
],
[
314,
"客户-025",
"2026-05-24",
"548.00"
],
[
168,
"客户-024",
"2026-01-10",
"543.25"
],
[
484,
"客户-002",
"2026-05-02",
"531.75"
],
[
592,
"客户-080",
"2026-06-20",
"530.50"
],
[
517,
"客户-041",
"2026-03-18",
"512.50"
],
[
185,
"客户-073",
"2026-04-06",
"499.75"
],
[
209,
"客户-012",
"2026-03-18",
"496.50"
],
[
286,
"客户-072",
"2026-02-16",
"486.75"
],
[
108,
"客户-081",
"2026-03-21",
"482.00"
],
[
487,
"客户-002",
"2026-01-29",
"474.25"
],
[
85,
"客户-001",
"2026-02-03",
"462.75"
],
[
507,
"客户-086",
"2026-05-18",
"453.00"
],
[
505,
"客户-108",
"2026-04-10",
"444.00"
],
[
219,
"客户-103",
"2026-06-10",
"421.25"
],
[
164,
"客户-012",
"2026-03-07",
"416.75"
],
[
109,
"客户-076",
"2026-02-11",
"415.50"
],
[
318,
"客户-015",
"2026-02-13",
"412.75"
],
[
394,
"客户-016",
"2026-03-19",
"378.75"
],
[
118,
"客户-048",
"2026-06-13",
"357.00"
],
[
353,
"客户-062",
"2026-06-26",
"354.50"
],
[
302,
"客户-069",
"2026-05-03",
"341.50"
],
[
333,
"客户-077",
"2026-04-11",
"333.50"
],
[
439,
"客户-060",
"2026-05-26",
"333.50"
],
[
288,
"客户-060",
"2026-03-09",
"322.50"
],
[
596,
"客户-009",
"2026-03-30",
"313.50"
],
[
175,
"客户-010",
"2026-04-11",
"312.00"
],
[
158,
"客户-012",
"2026-03-24",
"310.50"
],
[
555,
"客户-064",
"2026-04-03",
"310.00"
],
[
322,
"客户-094",
"2026-01-06",
"256.50"
],
[
485,
"客户-021",
"2026-02-15",
"245.75"
],
[
205,
"客户-027",
"2026-04-22",
"230.00"
],
[
214,
"客户-052",
"2026-01-17",
"215.75"
],
[
56,
"客户-037",
"2026-04-30",
"198.75"
],
[
125,
"客户-064",
"2026-02-20",
"192.00"
],
[
226,
"客户-089",
"2026-03-31",
"180.50"
],
[
173,
"客户-013",
"2026-06-05",
"174.50"
],
[
76,
"客户-024",
"2026-03-12",
"165.00"
],
[
385,
"客户-019",
"2026-04-24",
"164.75"
],
[
579,
"客户-083",
"2026-05-28",
"135.75"
],
[
188,
"客户-053",
"2026-05-07",
"134.00"
],
[
139,
"客户-005",
"2026-02-05",
"133.00"
],
[
7,
"客户-020",
"2026-01-09",
"131.50"
],
[
354,
"客户-092",
"2026-02-28",
"111.75"
],
[
900002,
"客户-001",
"2026-06-30",
"100.00"
],
[
900004,
"客户-001",
"2026-06-30",
"100.00"
],
[
522,
"客户-102",
"2026-06-30",
"70.50"
],
[
297,
"客户-107",
"2026-02-08",
"65.75"
],
[
900003,
"客户-001",
"2026-06-30",
"50.00"
],
[
515,
"客户-079",
"2026-03-26",
"39.25"
],
[
348,
"客户-004",
"2026-05-21",
"27.00"
]
]
}实际结果预览
{
"columns": [
{
"name": "order_id",
"type": "BIGINT"
},
{
"name": "customer_name",
"type": "VARCHAR"
},
{
"name": "order_date",
"type": "DATE"
},
{
"name": "total_amount",
"type": "DECIMAL(14,2)"
}
],
"extra": [],
"missing": [],
"row_count": 162,
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],
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193,
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369,
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305,
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32,
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457,
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37,
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314,
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168,
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484,
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592,
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517,
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185,
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286,
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108,
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487,
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85,
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507,
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505,
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219,
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164,
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109,
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318,
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394,
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118,
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],
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353,
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}摘要、错误与结果哈希
{
"visible_summary": "筛选 2026-01-01 起的已完成订单，连接客户名称，输出订单信息并按订单金额降序、订单号升序排列。",
"error_code": null,
"error_message": null,
"expected_digest": "d780841b19b0607647e55663cbe9eab3c35ff2b55eba3e78334a7fb27e22c268",
"actual_digest": "13f156ad254e4b51653641773d34274de496c781c9bc68a9ca81c55e1f87d4b2",
"assumptions": []
}事件记录（8）
按全局事件序号排列，保留时间、级别、类型、消息和 payload。
SEQ 3case.startedinfo{
"status": "generating"
}SEQ 4prompt.builtinfo{
"status": "completed"
}SEQ 5provider.requestedinfo{
"isolation_policy_hash": "747b1ca3decdc24da64208265966caf487d37482255536a35fa93e138bee8f77",
"status": "running"
}SEQ 6provider.deltainfo{
"text": "{\"plan\":{\"grain\":\"每行一个订单\",\"sources\":[\"fact_orders\",\"dim_customers\"],\"joins\":[\"fact_orders.customer_id = dim_customers.customer_id\"],\"filters\":[\"fact_orders.status = 'completed'\",\"fact_orders.order_date >= DATE '2026-01-01'\"],\"metrics\":[\"输出订单头 total_amount\"],\"steps\":[\"筛选完成订单及日期范围\",\"连接客户维度获取 customer_name\",\"按 total_amount 降序、order_id 升序排序\"],\"risks\":[\"仅使用订单头 total_amount，不重复汇总订单行\"]},\"sql\":\"SELECT\\n o.order_id,\\n c.customer_name,\\n o.order_date,\\n o.total_amount\\nFROM fact_orders AS o\\nJOIN dim_customers AS c\\n ON o.customer_id = c.customer_id\\nWHERE o.status = 'completed'\\n AND o.order_date >= DATE '2026-01-01'\\nORDER BY o.total_amount DESC, o.order_id ASC;\",\"summary\":\"筛选 2026-01-01 起的已完成订单，连接客户名称，输出订单信息并按订单金额降序、订单号升序排列。\",\"assumptions\":[]}"
}SEQ 7provider.completedinfo{
"elapsed_ms": 20533.108416995674,
"status": "completed",
"token_usage": {
"cache_write_input_tokens": 0,
"cached_input_tokens": 0,
"input_tokens": 17999,
"output_tokens": 346,
"reasoning_output_tokens": 85
}
}SEQ 8plan.completedinfo{
"grain": "每行一个订单",
"status": "completed",
"steps": 3
}SEQ 9sql.parsedinfo{
"status": "completed"
}SEQ 10score.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": "13f156ad254e4b51653641773d34274de496c781c9bc68a9ca81c55e1f87d4b2",
"assumptions": [],
"attempt": 1,
"category": "filter",
"comparison": {
"abs_tolerance": "0.005",
"decimal_scale": 2,
"duplicate_policy": "multiset",
"max_rows": 10000,
"rel_tolerance": "0",
"row_order_significant": true
},
"difficulty": "easy",
"error_code": null,
"error_message": null,
"execution_ms": 359.98508300690446,
"expected_digest": "d780841b19b0607647e55663cbe9eab3c35ff2b55eba3e78334a7fb27e22c268",
"expected_result_preview": {
"columns": [
{
"name": "order_id",
"type": "BIGINT"
},
{
"name": "customer_name",
"type": "VARCHAR"
},
{
"name": "order_date",
"type": "DATE"
},
{
"name": "total_amount",
"type": "DECIMAL(14,2)"
}
],
"digest": "d780841b19b0607647e55663cbe9eab3c35ff2b55eba3e78334a7fb27e22c268",
"row_count": 162,
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"客户-001",
"2026-06-30",
"100.00"
],
[
900004,
"客户-001",
"2026-06-30",
"100.00"
],
[
522,
"客户-102",
"2026-06-30",
"70.50"
],
[
297,
"客户-107",
"2026-02-08",
"65.75"
],
[
900003,
"客户-001",
"2026-06-30",
"50.00"
],
[
515,
"客户-079",
"2026-03-26",
"39.25"
],
[
348,
"客户-004",
"2026-05-21",
"27.00"
]
]
},
"finished_at": "2026-08-29T22:47:09.320999",
"formatted_sql": "SELECT\n o.order_id,\n c.customer_name,\n o.order_date,\n o.total_amount\nFROM fact_orders AS o\nJOIN dim_customers AS c\n ON o.customer_id = c.customer_id\nWHERE\n o.status = 'completed' AND o.order_date >= CAST('2026-01-01' AS DATE)\nORDER BY\n o.total_amount DESC,\n o.order_id ASC",
"generated_sql": "SELECT\n o.order_id,\n c.customer_name,\n o.order_date,\n o.total_amount\nFROM fact_orders AS o\nJOIN dim_customers AS c\n ON o.customer_id = c.customer_id\nWHERE o.status = 'completed'\n AND o.order_date >= DATE '2026-01-01'\nORDER BY o.total_amount DESC, o.order_id ASC;",
"generation_ms": null,
"id": 127,
"model_name": "Luna 本机实测",
"model_run_id": 20,
"plan": {
"filters": [
"fact_orders.status = 'completed'",
"fact_orders.order_date >= DATE '2026-01-01'"
],
"grain": "每行一个订单",
"joins": [
"fact_orders.customer_id = dim_customers.customer_id"
],
"metrics": [
"输出订单头 total_amount"
],
"risks": [
"仅使用订单头 total_amount，不重复汇总订单行"
],
"sources": [
"fact_orders",
"dim_customers"
],
"steps": [
"筛选完成订单及日期范围",
"连接客户维度获取 customer_name",
"按 total_amount 降序、order_id 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查询 2026-01-01 起已完成订单，输出 order_id、customer_name、order_date、total_amount，并按 total_amount 降序、order_id 升序。\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": "查询 2026-01-01 起已完成订单，输出 order_id、customer_name、order_date、total_amount，并按 total_amount 降序、order_id 升序。",
"radar_dimension": "基础查询",
"raw_output": "{\"plan\":{\"grain\":\"每行一个订单\",\"sources\":[\"fact_orders\",\"dim_customers\"],\"joins\":[\"fact_orders.customer_id = dim_customers.customer_id\"],\"filters\":[\"fact_orders.status = 'completed'\",\"fact_orders.order_date >= DATE '2026-01-01'\"],\"metrics\":[\"输出订单头 total_amount\"],\"steps\":[\"筛选完成订单及日期范围\",\"连接客户维度获取 customer_name\",\"按 total_amount 降序、order_id 升序排序\"],\"risks\":[\"仅使用订单头 total_amount，不重复汇总订单行\"]},\"sql\":\"SELECT\\n o.order_id,\\n c.customer_name,\\n o.order_date,\\n o.total_amount\\nFROM fact_orders AS o\\nJOIN dim_customers AS c\\n ON o.customer_id = c.customer_id\\nWHERE o.status = 'completed'\\n AND o.order_date >= DATE '2026-01-01'\\nORDER BY o.total_amount DESC, o.order_id ASC;\",\"summary\":\"筛选 2026-01-01 起的已完成订单，连接客户名称，输出订单信息并按订单金额降序、订单号升序排列。\",\"assumptions\":[]}",
"reference_sql": "SELECT o.order_id, c.customer_name, o.order_date, o.total_amount FROM fact_orders o JOIN dim_customers c ON c.customer_id = o.customer_id WHERE o.status = 'completed' AND o.order_date >= DATE '2026-01-01' ORDER BY o.total_amount DESC, o.order_id ASC",
"requested_model_id": "gpt-5.6-luna",
"required_ast": [],
"resolved_model_id": "gpt-5.6-luna",
"result_preview": {
"columns": [
{
"name": "order_id",
"type": "BIGINT"
},
{
"name": "customer_name",
"type": "VARCHAR"
},
{
"name": "order_date",
"type": "DATE"
},
{
"name": "total_amount",
"type": "DECIMAL(14,2)"
}
],
"extra": [],
"missing": [],
"row_count": 162,
"rows": [
[
562,
"客户-059",
"2026-01-13",
"3278.25"
],
[
157,
"客户-002",
"2026-03-26",
"3065.50"
],
[
497,
"客户-078",
"2026-05-26",
"3039.75"
],
[
529,
"客户-095",
"2026-04-21",
"3037.25"
],
[
315,
"客户-065",
"2026-03-11",
"3006.75"
],
[
287,
"客户-080",
"2026-03-08",
"2831.00"
],
[
93,
"客户-044",
"2026-03-17",
"2775.50"
],
[
36,
"客户-065",
"2026-02-15",
"2756.25"
],
[
44,
"客户-059",
"2026-01-06",
"2743.00"
],
[
238,
"客户-014",
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"2697.00"
],
[
255,
"客户-017",
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],
[
206,
"客户-063",
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],
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503,
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],
[
38,
"客户-095",
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],
[
144,
"客户-038",
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"2272.25"
],
[
526,
"客户-027",
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],
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368,
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],
[
105,
"客户-019",
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],
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356,
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],
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202,
"客户-109",
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],
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27,
"客户-085",
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],
[
597,
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],
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272,
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258,
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],
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62,
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],
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159,
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],
[
279,
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],
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98,
"客户-021",
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],
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68,
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"1975.75"
],
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266,
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],
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172,
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],
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298,
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],
[
63,
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],
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523,
"客户-060",
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],
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57,
"客户-105",
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],
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73,
"客户-046",
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393,
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],
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129,
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192,
"客户-076",
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"1793.75"
],
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578,
"客户-104",
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],
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388,
"客户-015",
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],
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49,
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],
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405,
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],
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95,
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],
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422,
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],
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459,
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],
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177,
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],
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55,
"客户-069",
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],
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229,
"客户-012",
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],
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138,
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"1695.25"
],
[
296,
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],
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193,
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],
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369,
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],
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22,
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],
[
486,
"客户-020",
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],
[
216,
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],
[
305,
"客户-053",
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],
[
508,
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],
[
148,
"客户-095",
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"1496.75"
],
[
399,
"客户-109",
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"1493.00"
],
[
267,
"客户-017",
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"1489.00"
],
[
103,
"客户-095",
"2026-05-29",
"1464.25"
],
[
343,
"客户-084",
"2026-05-02",
"1462.50"
],
[
478,
"客户-096",
"2026-02-04",
"1415.00"
],
[
567,
"客户-048",
"2026-02-07",
"1409.50"
],
[
52,
"客户-090",
"2026-01-06",
"1376.75"
],
[
243,
"客户-092",
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}