请求 #1
SEQ 166{
"isolation_policy_hash": "697c62794ad9c660f81ca062fbbbd514ed5bb8b6fa0a100fb936b561c4740d31",
"status": "running"
}案例记录 case-run-00130
保留零订单客户
列出所有客户及已完成订单数，必须保留零订单客户；输出 customer_id、customer_name、completed_order_count，并按 completed_order_count 降序、customer_id 升序；必须使用 LEFT JOIN。
运行信息
以下字段来自本次运行的冻结记录。
run
#18case run
#130attempt
1status
completedtoken total
18,354estimated cost
不可估算model generation
未记录SQL execution
198msadapter
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 22:55finished
2026年8月29日 22:55suite 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：
列出所有客户及已完成订单数，必须保留零订单客户；输出 customer_id、customer_name、completed_order_count，并按 completed_order_count 降序、customer_id 升序；必须使用 LEFT JOIN。
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":"每个客户一行","sources":["dim_customers","fact_orders"],"joins":["dim_customers.customer_id = fact_orders.customer_id，使用 LEFT JOIN"],"filters":["仅将 fact_orders.status = 'completed' 计入订单数"],"metrics":["completed_order_count：完成订单去重计数"],"steps":["客户表 LEFT JOIN 订单表","按客户标识和名称分组","计算完成订单数并排序"],"risks":["完成状态条件置于聚合表达式中以保留零订单客户"]},"sql":"SELECT\n c.customer_id,\n c.customer_name,\n COUNT(DISTINCT CASE WHEN o.status = 'completed' THEN o.order_id END) AS completed_order_count\nFROM dim_customers AS c\nLEFT JOIN fact_orders AS o\n ON c.customer_id = o.customer_id\nGROUP BY\n c.customer_id,\n c.customer_name\nORDER BY\n completed_order_count DESC,\n c.customer_id ASC;","summary":"以客户为粒度，从客户表 LEFT JOIN 订单表，将完成状态条件放入去重计数中，保留零完成订单客户并按要求排序。","assumptions":[]}结构化查询方案 plan
{
"filters": [
"仅将 fact_orders.status = 'completed' 计入订单数"
],
"grain": "每个客户一行",
"joins": [
"dim_customers.customer_id = fact_orders.customer_id，使用 LEFT JOIN"
],
"metrics": [
"completed_order_count：完成订单去重计数"
],
"risks": [
"完成状态条件置于聚合表达式中以保留零订单客户"
],
"sources": [
"dim_customers",
"fact_orders"
],
"steps": [
"客户表 LEFT JOIN 订单表",
"按客户标识和名称分组",
"计算完成订单数并排序"
]
}模型生成 SQL
SELECT
c.customer_id,
c.customer_name,
COUNT(DISTINCT CASE WHEN o.status = 'completed' THEN o.order_id END) AS completed_order_count
FROM dim_customers AS c
LEFT JOIN fact_orders AS o
ON c.customer_id = o.customer_id
GROUP BY
c.customer_id,
c.customer_name
ORDER BY
completed_order_count DESC,
c.customer_id ASC;规范化 SQL
SELECT
c.customer_id,
c.customer_name,
COUNT(DISTINCT CASE WHEN o.status = 'completed' THEN o.order_id END) AS completed_order_count
FROM dim_customers AS c
LEFT JOIN fact_orders AS o
ON c.customer_id = o.customer_id
GROUP BY
c.customer_id,
c.customer_name
ORDER BY
completed_order_count DESC,
c.customer_id ASCToken 与耗时
{
"token_usage": {
"cache_write_input_tokens": 0,
"cached_input_tokens": 0,
"input_tokens": 18004,
"output_tokens": 350,
"reasoning_output_tokens": 80
},
"generation_ms": null,
"execution_ms": 197.59858299948974
}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": 1,
"required": 1
},
"id": "left-join",
"kind": "join_type",
"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 c.customer_id, c.customer_name, COUNT(o.order_id) AS completed_order_count FROM dim_customers c LEFT JOIN fact_orders o ON o.customer_id = c.customer_id AND o.status = 'completed' GROUP BY c.customer_id, c.customer_name ORDER BY completed_order_count DESC, c.customer_id ASCAST 结构要求
[
{
"id": "left-join",
"join_type": "LEFT",
"kind": "join_type",
"min": 1
}
]结果比较规则
{
"abs_tolerance": "0",
"decimal_scale": 0,
"duplicate_policy": "multiset",
"max_rows": 10000,
"rel_tolerance": "0",
"row_order_significant": true
}期望结果预览
{
"columns": [
{
"name": "customer_id",
"type": "BIGINT"
},
{
"name": "customer_name",
"type": "VARCHAR"
},
{
"name": "completed_order_count",
"type": "BIGINT"
}
],
"digest": "d0930aa0c0840f902dc9acbe1aaf084d6341194824b553f5a51ed3ed7743edf5",
"row_count": 120,
"rows": [
[
1,
"客户-001",
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],
[
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"客户-013",
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[
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"客户-017",
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],
[
12,
"客户-012",
9
],
[
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"客户-053",
9
],
[
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"客户-107",
9
],
[
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"客户-005",
8
],
[
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"客户-021",
8
],
[
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"客户-104",
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7
],
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7
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"客户-090",
7
],
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"客户-109",
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"客户-009",
6
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"客户-010",
6
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"客户-015",
6
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6
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"客户-024",
6
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6
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"客户-041",
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4
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4
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[
92,
"客户-092",
4
],
[
93,
"客户-093",
4
],
[
95,
"客户-095",
4
],
[
100,
"客户-100",
4
],
[
11,
"客户-011",
3
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[
18,
"客户-018",
3
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25,
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[
27,
"客户-027",
3
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34,
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3
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[
37,
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3
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3
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[
62,
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3
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[
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3
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77,
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3
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[
86,
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3
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[
87,
"客户-087",
3
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[
108,
"客户-108",
3
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[
3,
"客户-003",
2
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[
6,
"客户-006",
2
],
[
23,
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2
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[
28,
"客户-028",
2
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[
39,
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2
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[
51,
"客户-051",
2
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[
55,
"客户-055",
2
],
[
63,
"客户-063",
2
],
[
73,
"客户-073",
2
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[
75,
"客户-075",
2
],
[
96,
"客户-096",
2
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[
103,
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2
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[
110,
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2
],
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7,
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1
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8,
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33,
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1
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40,
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1
],
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42,
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1
],
[
54,
"客户-054",
1
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68,
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1
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[
91,
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1
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[
99,
"客户-099",
0
],
[
101,
"客户-101",
0
],
[
111,
"客户-111",
0
],
[
112,
"客户-112",
0
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[
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"客户-113",
0
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[
114,
"客户-114",
0
],
[
115,
"客户-115",
0
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[
116,
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0
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[
117,
"客户-117",
0
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[
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"客户-118",
0
],
[
119,
"客户-119",
0
],
[
120,
"客户-120",
0
]
]
}实际结果预览
{
"columns": [
{
"name": "customer_id",
"type": "BIGINT"
},
{
"name": "customer_name",
"type": "VARCHAR"
},
{
"name": "completed_order_count",
"type": "BIGINT"
}
],
"extra": [],
"missing": [],
"row_count": 120,
"rows": [
[
1,
"客户-001",
12
],
[
13,
"客户-013",
10
],
[
17,
"客户-017",
10
],
[
12,
"客户-012",
9
],
[
53,
"客户-053",
9
],
[
107,
"客户-107",
9
],
[
5,
"客户-005",
8
],
[
21,
"客户-021",
8
],
[
104,
"客户-104",
8
],
[
2,
"客户-002",
7
],
[
4,
"客户-004",
7
],
[
20,
"客户-020",
7
],
[
36,
"客户-036",
7
],
[
48,
"客户-048",
7
],
[
67,
"客户-067",
7
],
[
90,
"客户-090",
7
],
[
109,
"客户-109",
7
],
[
9,
"客户-009",
6
],
[
10,
"客户-010",
6
],
[
15,
"客户-015",
6
],
[
19,
"客户-019",
6
],
[
24,
"客户-024",
6
],
[
29,
"客户-029",
6
],
[
41,
"客户-041",
6
],
[
43,
"客户-043",
6
],
[
64,
"客户-064",
6
],
[
69,
"客户-069",
6
],
[
71,
"客户-071",
6
],
[
80,
"客户-080",
6
],
[
94,
"客户-094",
6
],
[
105,
"客户-105",
6
],
[
26,
"客户-026",
5
],
[
30,
"客户-030",
5
],
[
31,
"客户-031",
5
],
[
44,
"客户-044",
5
],
[
46,
"客户-046",
5
],
[
52,
"客户-052",
5
],
[
57,
"客户-057",
5
],
[
60,
"客户-060",
5
],
[
65,
"客户-065",
5
],
[
74,
"客户-074",
5
],
[
82,
"客户-082",
5
],
[
84,
"客户-084",
5
],
[
97,
"客户-097",
5
],
[
98,
"客户-098",
5
],
[
102,
"客户-102",
5
],
[
106,
"客户-106",
5
],
[
14,
"客户-014",
4
],
[
16,
"客户-016",
4
],
[
22,
"客户-022",
4
],
[
32,
"客户-032",
4
],
[
35,
"客户-035",
4
],
[
38,
"客户-038",
4
],
[
45,
"客户-045",
4
],
[
49,
"客户-049",
4
],
[
50,
"客户-050",
4
],
[
56,
"客户-056",
4
],
[
58,
"客户-058",
4
],
[
59,
"客户-059",
4
],
[
61,
"客户-061",
4
],
[
70,
"客户-070",
4
],
[
72,
"客户-072",
4
],
[
76,
"客户-076",
4
],
[
78,
"客户-078",
4
],
[
79,
"客户-079",
4
],
[
81,
"客户-081",
4
],
[
83,
"客户-083",
4
],
[
85,
"客户-085",
4
],
[
88,
"客户-088",
4
],
[
89,
"客户-089",
4
],
[
92,
"客户-092",
4
],
[
93,
"客户-093",
4
],
[
95,
"客户-095",
4
],
[
100,
"客户-100",
4
],
[
11,
"客户-011",
3
],
[
18,
"客户-018",
3
],
[
25,
"客户-025",
3
],
[
27,
"客户-027",
3
],
[
34,
"客户-034",
3
],
[
37,
"客户-037",
3
],
[
47,
"客户-047",
3
],
[
62,
"客户-062",
3
],
[
66,
"客户-066",
3
],
[
77,
"客户-077",
3
],
[
86,
"客户-086",
3
],
[
87,
"客户-087",
3
],
[
108,
"客户-108",
3
],
[
3,
"客户-003",
2
],
[
6,
"客户-006",
2
],
[
23,
"客户-023",
2
],
[
28,
"客户-028",
2
],
[
39,
"客户-039",
2
],
[
51,
"客户-051",
2
],
[
55,
"客户-055",
2
],
[
63,
"客户-063",
2
],
[
73,
"客户-073",
2
],
[
75,
"客户-075",
2
],
[
96,
"客户-096",
2
],
[
103,
"客户-103",
2
],
[
110,
"客户-110",
2
],
[
7,
"客户-007",
1
],
[
8,
"客户-008",
1
],
[
33,
"客户-033",
1
],
[
40,
"客户-040",
1
],
[
42,
"客户-042",
1
],
[
54,
"客户-054",
1
],
[
68,
"客户-068",
1
],
[
91,
"客户-091",
1
],
[
99,
"客户-099",
0
],
[
101,
"客户-101",
0
],
[
111,
"客户-111",
0
],
[
112,
"客户-112",
0
],
[
113,
"客户-113",
0
],
[
114,
"客户-114",
0
],
[
115,
"客户-115",
0
],
[
116,
"客户-116",
0
],
[
117,
"客户-117",
0
],
[
118,
"客户-118",
0
],
[
119,
"客户-119",
0
],
[
120,
"客户-120",
0
]
]
}摘要、错误与结果哈希
{
"visible_summary": "以客户为粒度，从客户表 LEFT JOIN 订单表，将完成状态条件放入去重计数中，保留零完成订单客户并按要求排序。",
"error_code": null,
"error_message": null,
"expected_digest": "d0930aa0c0840f902dc9acbe1aaf084d6341194824b553f5a51ed3ed7743edf5",
"actual_digest": "cd40a6e44569e7a66556bfeecb9d72bca881dab5f1ec79061a728a991eacb475",
"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 164case.startedinfo{
"status": "generating"
}SEQ 165prompt.builtinfo{
"status": "completed"
}SEQ 166provider.requestedinfo{
"isolation_policy_hash": "697c62794ad9c660f81ca062fbbbd514ed5bb8b6fa0a100fb936b561c4740d31",
"status": "running"
}SEQ 167provider.deltainfo{
"text": "{\"plan\":{\"grain\":\"每个客户一行\",\"sources\":[\"dim_customers\",\"fact_orders\"],\"joins\":[\"dim_customers.customer_id = fact_orders.customer_id，使用 LEFT JOIN\"],\"filters\":[\"仅将 fact_orders.status = 'completed' 计入订单数\"],\"metrics\":[\"completed_order_count：完成订单去重计数\"],\"steps\":[\"客户表 LEFT JOIN 订单表\",\"按客户标识和名称分组\",\"计算完成订单数并排序\"],\"risks\":[\"完成状态条件置于聚合表达式中以保留零订单客户\"]},\"sql\":\"SELECT\\n c.customer_id,\\n c.customer_name,\\n COUNT(DISTINCT CASE WHEN o.status = 'completed' THEN o.order_id END) AS completed_order_count\\nFROM dim_customers AS c\\nLEFT JOIN fact_orders AS o\\n ON c.customer_id = o.customer_id\\nGROUP BY\\n c.customer_id,\\n c.customer_name\\nORDER BY\\n completed_order_count DESC,\\n c.customer_id ASC;\",\"summary\":\"以客户为粒度，从客户表 LEFT JOIN 订单表，将完成状态条件放入去重计数中，保留零完成订单客户并按要求排序。\",\"assumptions\":[]}"
}SEQ 168provider.completedinfo{
"elapsed_ms": 19101.997750003648,
"status": "completed",
"token_usage": {
"cache_write_input_tokens": 0,
"cached_input_tokens": 0,
"input_tokens": 18004,
"output_tokens": 350,
"reasoning_output_tokens": 80
}
}SEQ 169plan.completedinfo{
"grain": "每个客户一行",
"status": "completed",
"steps": 3
}SEQ 170sql.parsedinfo{
"status": "completed"
}SEQ 171score.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": "cd40a6e44569e7a66556bfeecb9d72bca881dab5f1ec79061a728a991eacb475",
"assumptions": [],
"attempt": 1,
"category": "join_semantics",
"comparison": {
"abs_tolerance": "0",
"decimal_scale": 0,
"duplicate_policy": "multiset",
"max_rows": 10000,
"rel_tolerance": "0",
"row_order_significant": true
},
"difficulty": "medium",
"error_code": null,
"error_message": null,
"execution_ms": 197.59858299948974,
"expected_digest": "d0930aa0c0840f902dc9acbe1aaf084d6341194824b553f5a51ed3ed7743edf5",
"expected_result_preview": {
"columns": [
{
"name": "customer_id",
"type": "BIGINT"
},
{
"name": "customer_name",
"type": "VARCHAR"
},
{
"name": "completed_order_count",
"type": "BIGINT"
}
],
"digest": "d0930aa0c0840f902dc9acbe1aaf084d6341194824b553f5a51ed3ed7743edf5",
"row_count": 120,
"rows": [
[
1,
"客户-001",
12
],
[
13,
"客户-013",
10
],
[
17,
"客户-017",
10
],
[
12,
"客户-012",
9
],
[
53,
"客户-053",
9
],
[
107,
"客户-107",
9
],
[
5,
"客户-005",
8
],
[
21,
"客户-021",
8
],
[
104,
"客户-104",
8
],
[
2,
"客户-002",
7
],
[
4,
"客户-004",
7
],
[
20,
"客户-020",
7
],
[
36,
"客户-036",
7
],
[
48,
"客户-048",
7
],
[
67,
"客户-067",
7
],
[
90,
"客户-090",
7
],
[
109,
"客户-109",
7
],
[
9,
"客户-009",
6
],
[
10,
"客户-010",
6
],
[
15,
"客户-015",
6
],
[
19,
"客户-019",
6
],
[
24,
"客户-024",
6
],
[
29,
"客户-029",
6
],
[
41,
"客户-041",
6
],
[
43,
"客户-043",
6
],
[
64,
"客户-064",
6
],
[
69,
"客户-069",
6
],
[
71,
"客户-071",
6
],
[
80,
"客户-080",
6
],
[
94,
"客户-094",
6
],
[
105,
"客户-105",
6
],
[
26,
"客户-026",
5
],
[
30,
"客户-030",
5
],
[
31,
"客户-031",
5
],
[
44,
"客户-044",
5
],
[
46,
"客户-046",
5
],
[
52,
"客户-052",
5
],
[
57,
"客户-057",
5
],
[
60,
"客户-060",
5
],
[
65,
"客户-065",
5
],
[
74,
"客户-074",
5
],
[
82,
"客户-082",
5
],
[
84,
"客户-084",
5
],
[
97,
"客户-097",
5
],
[
98,
"客户-098",
5
],
[
102,
"客户-102",
5
],
[
106,
"客户-106",
5
],
[
14,
"客户-014",
4
],
[
16,
"客户-016",
4
],
[
22,
"客户-022",
4
],
[
32,
"客户-032",
4
],
[
35,
"客户-035",
4
],
[
38,
"客户-038",
4
],
[
45,
"客户-045",
4
],
[
49,
"客户-049",
4
],
[
50,
"客户-050",
4
],
[
56,
"客户-056",
4
],
[
58,
"客户-058",
4
],
[
59,
"客户-059",
4
],
[
61,
"客户-061",
4
],
[
70,
"客户-070",
4
],
[
72,
"客户-072",
4
],
[
76,
"客户-076",
4
],
[
78,
"客户-078",
4
],
[
79,
"客户-079",
4
],
[
81,
"客户-081",
4
],
[
83,
"客户-083",
4
],
[
85,
"客户-085",
4
],
[
88,
"客户-088",
4
],
[
89,
"客户-089",
4
],
[
92,
"客户-092",
4
],
[
93,
"客户-093",
4
],
[
95,
"客户-095",
4
],
[
100,
"客户-100",
4
],
[
11,
"客户-011",
3
],
[
18,
"客户-018",
3
],
[
25,
"客户-025",
3
],
[
27,
"客户-027",
3
],
[
34,
"客户-034",
3
],
[
37,
"客户-037",
3
],
[
47,
"客户-047",
3
],
[
62,
"客户-062",
3
],
[
66,
"客户-066",
3
],
[
77,
"客户-077",
3
],
[
86,
"客户-086",
3
],
[
87,
"客户-087",
3
],
[
108,
"客户-108",
3
],
[
3,
"客户-003",
2
],
[
6,
"客户-006",
2
],
[
23,
"客户-023",
2
],
[
28,
"客户-028",
2
],
[
39,
"客户-039",
2
],
[
51,
"客户-051",
2
],
[
55,
"客户-055",
2
],
[
63,
"客户-063",
2
],
[
73,
"客户-073",
2
],
[
75,
"客户-075",
2
],
[
96,
"客户-096",
2
],
[
103,
"客户-103",
2
],
[
110,
"客户-110",
2
],
[
7,
"客户-007",
1
],
[
8,
"客户-008",
1
],
[
33,
"客户-033",
1
],
[
40,
"客户-040",
1
],
[
42,
"客户-042",
1
],
[
54,
"客户-054",
1
],
[
68,
"客户-068",
1
],
[
91,
"客户-091",
1
],
[
99,
"客户-099",
0
],
[
101,
"客户-101",
0
],
[
111,
"客户-111",
0
],
[
112,
"客户-112",
0
],
[
113,
"客户-113",
0
],
[
114,
"客户-114",
0
],
[
115,
"客户-115",
0
],
[
116,
"客户-116",
0
],
[
117,
"客户-117",
0
],
[
118,
"客户-118",
0
],
[
119,
"客户-119",
0
],
[
120,
"客户-120",
0
]
]
},
"finished_at": "2026-08-29T22:55:31.536667",
"formatted_sql": "SELECT\n c.customer_id,\n c.customer_name,\n COUNT(DISTINCT CASE WHEN o.status = 'completed' THEN o.order_id END) AS completed_order_count\nFROM dim_customers AS c\nLEFT JOIN fact_orders AS o\n ON c.customer_id = o.customer_id\nGROUP BY\n c.customer_id,\n c.customer_name\nORDER BY\n completed_order_count DESC,\n c.customer_id ASC",
"generated_sql": "SELECT\n c.customer_id,\n c.customer_name,\n COUNT(DISTINCT CASE WHEN o.status = 'completed' THEN o.order_id END) AS completed_order_count\nFROM dim_customers AS c\nLEFT JOIN fact_orders AS o\n ON c.customer_id = o.customer_id\nGROUP BY\n c.customer_id,\n c.customer_name\nORDER BY\n completed_order_count DESC,\n c.customer_id ASC;",
"generation_ms": null,
"id": 130,
"model_name": "Luna 本机实测",
"model_run_id": 21,
"plan": {
"filters": [
"仅将 fact_orders.status = 'completed' 计入订单数"
],
"grain": "每个客户一行",
"joins": [
"dim_customers.customer_id = fact_orders.customer_id，使用 LEFT JOIN"
],
"metrics": [
"completed_order_count：完成订单去重计数"
],
"risks": [
"完成状态条件置于聚合表达式中以保留零订单客户"
],
"sources": [
"dim_customers",
"fact_orders"
],
"steps": [
"客户表 LEFT JOIN 订单表",
"按客户标识和名称分组",
"计算完成订单数并排序"
]
},
"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列出所有客户及已完成订单数，必须保留零订单客户；输出 customer_id、customer_name、completed_order_count，并按 completed_order_count 降序、customer_id 升序；必须使用 LEFT JOIN。\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": "列出所有客户及已完成订单数，必须保留零订单客户；输出 customer_id、customer_name、completed_order_count，并按 completed_order_count 降序、customer_id 升序；必须使用 LEFT JOIN。",
"radar_dimension": "连接与粒度",
"raw_output": "{\"plan\":{\"grain\":\"每个客户一行\",\"sources\":[\"dim_customers\",\"fact_orders\"],\"joins\":[\"dim_customers.customer_id = fact_orders.customer_id，使用 LEFT JOIN\"],\"filters\":[\"仅将 fact_orders.status = 'completed' 计入订单数\"],\"metrics\":[\"completed_order_count：完成订单去重计数\"],\"steps\":[\"客户表 LEFT JOIN 订单表\",\"按客户标识和名称分组\",\"计算完成订单数并排序\"],\"risks\":[\"完成状态条件置于聚合表达式中以保留零订单客户\"]},\"sql\":\"SELECT\\n c.customer_id,\\n c.customer_name,\\n COUNT(DISTINCT CASE WHEN o.status = 'completed' THEN o.order_id END) AS completed_order_count\\nFROM dim_customers AS c\\nLEFT JOIN fact_orders AS o\\n ON c.customer_id = o.customer_id\\nGROUP BY\\n c.customer_id,\\n c.customer_name\\nORDER BY\\n completed_order_count DESC,\\n c.customer_id ASC;\",\"summary\":\"以客户为粒度，从客户表 LEFT JOIN 订单表，将完成状态条件放入去重计数中，保留零完成订单客户并按要求排序。\",\"assumptions\":[]}",
"reference_sql": "SELECT c.customer_id, c.customer_name, COUNT(o.order_id) AS completed_order_count FROM dim_customers c LEFT JOIN fact_orders o ON o.customer_id = c.customer_id AND o.status = 'completed' GROUP BY c.customer_id, c.customer_name ORDER BY completed_order_count DESC, c.customer_id ASC",
"requested_model_id": "gpt-5.6-luna",
"required_ast": [
{
"id": "left-join",
"join_type": "LEFT",
"kind": "join_type",
"min": 1
}
],
"resolved_model_id": "gpt-5.6-luna",
"result_preview": {
"columns": [
{
"name": "customer_id",
"type": "BIGINT"
},
{
"name": "customer_name",
"type": "VARCHAR"
},
{
"name": "completed_order_count",
"type": "BIGINT"
}
],
"extra": [],
"missing": [],
"row_count": 120,
"rows": [
[
1,
"客户-001",
12
],
[
13,
"客户-013",
10
],
[
17,
"客户-017",
10
],
[
12,
"客户-012",
9
],
[
53,
"客户-053",
9
],
[
107,
"客户-107",
9
],
[
5,
"客户-005",
8
],
[
21,
"客户-021",
8
],
[
104,
"客户-104",
8
],
[
2,
"客户-002",
7
],
[
4,
"客户-004",
7
],
[
20,
"客户-020",
7
],
[
36,
"客户-036",
7
],
[
48,
"客户-048",
7
],
[
67,
"客户-067",
7
],
[
90,
"客户-090",
7
],
[
109,
"客户-109",
7
],
[
9,
"客户-009",
6
],
[
10,
"客户-010",
6
],
[
15,
"客户-015",
6
],
[
19,
"客户-019",
6
],
[
24,
"客户-024",
6
],
[
29,
"客户-029",
6
],
[
41,
"客户-041",
6
],
[
43,
"客户-043",
6
],
[
64,
"客户-064",
6
],
[
69,
"客户-069",
6
],
[
71,
"客户-071",
6
],
[
80,
"客户-080",
6
],
[
94,
"客户-094",
6
],
[
105,
"客户-105",
6
],
[
26,
"客户-026",
5
],
[
30,
"客户-030",
5
],
[
31,
"客户-031",
5
],
[
44,
"客户-044",
5
],
[
46,
"客户-046",
5
],
[
52,
"客户-052",
5
],
[
57,
"客户-057",
5
],
[
60,
"客户-060",
5
],
[
65,
"客户-065",
5
],
[
74,
"客户-074",
5
],
[
82,
"客户-082",
5
],
[
84,
"客户-084",
5
],
[
97,
"客户-097",
5
],
[
98,
"客户-098",
5
],
[
102,
"客户-102",
5
],
[
106,
"客户-106",
5
],
[
14,
"客户-014",
4
],
[
16,
"客户-016",
4
],
[
22,
"客户-022",
4
],
[
32,
"客户-032",
4
],
[
35,
"客户-035",
4
],
[
38,
"客户-038",
4
],
[
45,
"客户-045",
4
],
[
49,
"客户-049",
4
],
[
50,
"客户-050",
4
],
[
56,
"客户-056",
4
],
[
58,
"客户-058",
4
],
[
59,
"客户-059",
4
],
[
61,
"客户-061",
4
],
[
70,
"客户-070",
4
],
[
72,
"客户-072",
4
],
[
76,
"客户-076",
4
],
[
78,
"客户-078",
4
],
[
79,
"客户-079",
4
],
[
81,
"客户-081",
4
],
[
83,
"客户-083",
4
],
[
85,
"客户-085",
4
],
[
88,
"客户-088",
4
],
[
89,
"客户-089",
4
],
[
92,
"客户-092",
4
],
[
93,
"客户-093",
4
],
[
95,
"客户-095",
4
],
[
100,
"客户-100",
4
],
[
11,
"客户-011",
3
],
[
18,
"客户-018",
3
],
[
25,
"客户-025",
3
],
[
27,
"客户-027",
3
],
[
34,
"客户-034",
3
],
[
37,
"客户-037",
3
],
[
47,
"客户-047",
3
],
[
62,
"客户-062",
3
],
[
66,
"客户-066",
3
],
[
77,
"客户-077",
3
],
[
86,
"客户-086",
3
],
[
87,
"客户-087",
3
],
[
108,
"客户-108",
3
],
[
3,
"客户-003",
2
],
[
6,
"客户-006",
2
],
[
23,
"客户-023",
2
],
[
28,
"客户-028",
2
],
[
39,
"客户-039",
2
],
[
51,
"客户-051",
2
],
[
55,
"客户-055",
2
],
[
63,
"客户-063",
2
],
[
73,
"客户-073",
2
],
[
75,
"客户-075",
2
],
[
96,
"客户-096",
2
],
[
103,
"客户-103",
2
],
[
110,
"客户-110",
2
],
[
7,
"客户-007",
1
],
[
8,
"客户-008",
1
],
[
33,
"客户-033",
1
],
[
40,
"客户-040",
1
],
[
42,
"客户-042",
1
],
[
54,
"客户-054",
1
],
[
68,
"客户-068",
1
],
[
91,
"客户-091",
1
],
[
99,
"客户-099",
0
],
[
101,
"客户-101",
0
],
[
111,
"客户-111",
0
],
[
112,
"客户-112",
0
],
[
113,
"客户-113",
0
],
[
114,
"客户-114",
0
],
[
115,
"客户-115",
0
],
[
116,
"客户-116",
0
],
[
117,
"客户-117",
0
],
[
118,
"客户-118",
0
],
[
119,
"客户-119",
0
],
[
120,
"客户-120",
0
]
]
},
"run_id": 18,
"score": {
"ast_rules": [
{
"details": {
"actual": 1,
"required": 1
},
"id": "left-join",
"kind": "join_type",
"passed": true
}
],
"column_count": 5,
"column_names": 5,
"execution": 10,
"ordering": 10,
"protocol": 5,
"read_only_ast": 5,
"row_f1": 45,
"sql_capability": 15,
"total": 100
},
"stable_key": "left_join_zero_orders",
"started_at": "2026-08-29T22:55:12.191046",
"status": "completed",
"suite_content_hash": "5b5d98876ea35114f18ce6dfa48cc9800d88b6baba80d311b2f52552a38b31af",
"title": "保留零订单客户",
"token_usage": {
"cache_write_input_tokens": 0,
"cached_input_tokens": 0,
"input_tokens": 18004,
"output_tokens": 350,
"reasoning_output_tokens": 80
},
"visible_summary": "以客户为粒度，从客户表 LEFT JOIN 订单表，将完成状态条件放入去重计数中，保留零完成订单客户并按要求排序。"
}