请求 #1
SEQ 125{
"isolation_policy_hash": "922fe6e1a33b0726bb5797d57755d8c5afd03a15fb6fffe56964e8f75389c3bc",
"status": "running"
}案例记录 case-run-00161
按 channel_type 输出 completed_order_count、net_revenue、paid_amount、refunded_amount、failed_amount。所有指标必须遵循语义层口径,避免订单行与支付记录直接连接造成重复计算,并按 channel_type 升序。
以下字段来自本次运行的冻结记录。
#18#1611completed20,618不可估算未记录216mscodex_clitextgpt-5.6-solgpt-5.6-sol未提供2026年8月29日 22:532026年8月29日 22:535b5d98876ea35114f18ce6dfa48cc9800d88b6baba80d311b2f52552a38b31af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:
按 channel_type 输出 completed_order_count、net_revenue、paid_amount、refunded_amount、failed_amount。所有指标必须遵循语义层口径,避免订单行与支付记录直接连接造成重复计算,并按 channel_type 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"}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 125{
"isolation_policy_hash": "922fe6e1a33b0726bb5797d57755d8c5afd03a15fb6fffe56964e8f75389c3bc",
"status": "running"
}分别显示原始响应、解析结果和 SQL。
{"plan":{"grain":"每行一个 channel_type","sources":["dim_channels","fact_orders","fact_order_items","fact_payments"],"joins":["fact_orders.channel_id = dim_channels.channel_id","fact_order_items.order_id = fact_orders.order_id","fact_payments.order_id = fact_orders.order_id"],"filters":["订单数和净销售额仅含 fact_orders.status = 'completed'","支付金额仅按 fact_payments.status 分类"],"metrics":["completed_order_count:完成订单去重计数","net_revenue:完成订单行 quantity * unit_price - discount_amount 汇总","paid_amount:status = 'paid' 的支付金额","refunded_amount:status = 'refunded' 的支付金额","failed_amount:status = 'failed' 的支付金额"],"steps":["分别聚合完成订单数、订单行净销售额和支付状态金额","以 channel_type 汇总渠道维表","连接各指标聚合并将缺失值补零","按 channel_type 升序输出"],"risks":["订单行与支付记录不得直接连接","同一 channel_type 可对应多个 channel_id","支付指标不得套用完成订单过滤"]},"sql":"WITH channel_types AS (\n SELECT channel_type\n FROM dim_channels\n GROUP BY channel_type\n),\ncompleted_orders AS (\n SELECT\n c.channel_type,\n COUNT(DISTINCT o.order_id) AS completed_order_count\n FROM fact_orders AS o\n JOIN dim_channels AS c\n ON o.channel_id = c.channel_id\n WHERE o.status = 'completed'\n GROUP BY c.channel_type\n),\nnet_revenue AS (\n SELECT\n c.channel_type,\n SUM(oi.quantity * oi.unit_price - oi.discount_amount) AS net_revenue\n FROM fact_order_items AS oi\n JOIN fact_orders AS o\n ON oi.order_id = o.order_id\n JOIN dim_channels AS c\n ON o.channel_id = c.channel_id\n WHERE o.status = 'completed'\n GROUP BY c.channel_type\n),\npayment_amounts AS (\n SELECT\n c.channel_type,\n SUM(CASE WHEN p.status = 'paid' THEN p.amount ELSE 0 END) AS paid_amount,\n SUM(CASE WHEN p.status = 'refunded' THEN p.amount ELSE 0 END) AS refunded_amount,\n SUM(CASE WHEN p.status = 'failed' THEN p.amount ELSE 0 END) AS failed_amount\n FROM fact_payments AS p\n JOIN fact_orders AS o\n ON p.order_id = o.order_id\n JOIN dim_channels AS c\n ON o.channel_id = c.channel_id\n GROUP BY c.channel_type\n)\nSELECT\n ct.channel_type,\n COALESCE(co.completed_order_count, 0) AS completed_order_count,\n COALESCE(nr.net_revenue, 0) AS net_revenue,\n COALESCE(pa.paid_amount, 0) AS paid_amount,\n COALESCE(pa.refunded_amount, 0) AS refunded_amount,\n COALESCE(pa.failed_amount, 0) AS failed_amount\nFROM channel_types AS ct\nLEFT JOIN completed_orders AS co\n ON ct.channel_type = co.channel_type\nLEFT JOIN net_revenue AS nr\n ON ct.channel_type = nr.channel_type\nLEFT JOIN payment_amounts AS pa\n ON ct.channel_type = pa.channel_type\nORDER BY ct.channel_type ASC","summary":"分别在订单、订单行和支付粒度聚合指标,再按 channel_type 合并,避免订单行与支付记录相乘导致重复计算。","assumptions":["输出 dim_channels 中定义的所有 channel_type;没有对应事实记录的指标显示为 0。"]}{
"filters": [
"订单数和净销售额仅含 fact_orders.status = 'completed'",
"支付金额仅按 fact_payments.status 分类"
],
"grain": "每行一个 channel_type",
"joins": [
"fact_orders.channel_id = dim_channels.channel_id",
"fact_order_items.order_id = fact_orders.order_id",
"fact_payments.order_id = fact_orders.order_id"
],
"metrics": [
"completed_order_count:完成订单去重计数",
"net_revenue:完成订单行 quantity * unit_price - discount_amount 汇总",
"paid_amount:status = 'paid' 的支付金额",
"refunded_amount:status = 'refunded' 的支付金额",
"failed_amount:status = 'failed' 的支付金额"
],
"risks": [
"订单行与支付记录不得直接连接",
"同一 channel_type 可对应多个 channel_id",
"支付指标不得套用完成订单过滤"
],
"sources": [
"dim_channels",
"fact_orders",
"fact_order_items",
"fact_payments"
],
"steps": [
"分别聚合完成订单数、订单行净销售额和支付状态金额",
"以 channel_type 汇总渠道维表",
"连接各指标聚合并将缺失值补零",
"按 channel_type 升序输出"
]
}WITH channel_types AS (
SELECT channel_type
FROM dim_channels
GROUP BY channel_type
),
completed_orders AS (
SELECT
c.channel_type,
COUNT(DISTINCT o.order_id) AS completed_order_count
FROM fact_orders AS o
JOIN dim_channels AS c
ON o.channel_id = c.channel_id
WHERE o.status = 'completed'
GROUP BY c.channel_type
),
net_revenue AS (
SELECT
c.channel_type,
SUM(oi.quantity * oi.unit_price - oi.discount_amount) AS net_revenue
FROM fact_order_items AS oi
JOIN fact_orders AS o
ON oi.order_id = o.order_id
JOIN dim_channels AS c
ON o.channel_id = c.channel_id
WHERE o.status = 'completed'
GROUP BY c.channel_type
),
payment_amounts AS (
SELECT
c.channel_type,
SUM(CASE WHEN p.status = 'paid' THEN p.amount ELSE 0 END) AS paid_amount,
SUM(CASE WHEN p.status = 'refunded' THEN p.amount ELSE 0 END) AS refunded_amount,
SUM(CASE WHEN p.status = 'failed' THEN p.amount ELSE 0 END) AS failed_amount
FROM fact_payments AS p
JOIN fact_orders AS o
ON p.order_id = o.order_id
JOIN dim_channels AS c
ON o.channel_id = c.channel_id
GROUP BY c.channel_type
)
SELECT
ct.channel_type,
COALESCE(co.completed_order_count, 0) AS completed_order_count,
COALESCE(nr.net_revenue, 0) AS net_revenue,
COALESCE(pa.paid_amount, 0) AS paid_amount,
COALESCE(pa.refunded_amount, 0) AS refunded_amount,
COALESCE(pa.failed_amount, 0) AS failed_amount
FROM channel_types AS ct
LEFT JOIN completed_orders AS co
ON ct.channel_type = co.channel_type
LEFT JOIN net_revenue AS nr
ON ct.channel_type = nr.channel_type
LEFT JOIN payment_amounts AS pa
ON ct.channel_type = pa.channel_type
ORDER BY ct.channel_type ASCWITH channel_types AS (
SELECT
channel_type
FROM dim_channels
GROUP BY
channel_type
), completed_orders AS (
SELECT
c.channel_type,
COUNT(DISTINCT o.order_id) AS completed_order_count
FROM fact_orders AS o
JOIN dim_channels AS c
ON o.channel_id = c.channel_id
WHERE
o.status = 'completed'
GROUP BY
c.channel_type
), net_revenue AS (
SELECT
c.channel_type,
SUM(oi.quantity * oi.unit_price - oi.discount_amount) AS net_revenue
FROM fact_order_items AS oi
JOIN fact_orders AS o
ON oi.order_id = o.order_id
JOIN dim_channels AS c
ON o.channel_id = c.channel_id
WHERE
o.status = 'completed'
GROUP BY
c.channel_type
), payment_amounts AS (
SELECT
c.channel_type,
SUM(CASE WHEN p.status = 'paid' THEN p.amount ELSE 0 END) AS paid_amount,
SUM(CASE WHEN p.status = 'refunded' THEN p.amount ELSE 0 END) AS refunded_amount,
SUM(CASE WHEN p.status = 'failed' THEN p.amount ELSE 0 END) AS failed_amount
FROM fact_payments AS p
JOIN fact_orders AS o
ON p.order_id = o.order_id
JOIN dim_channels AS c
ON o.channel_id = c.channel_id
GROUP BY
c.channel_type
)
SELECT
ct.channel_type,
COALESCE(co.completed_order_count, 0) AS completed_order_count,
COALESCE(nr.net_revenue, 0) AS net_revenue,
COALESCE(pa.paid_amount, 0) AS paid_amount,
COALESCE(pa.refunded_amount, 0) AS refunded_amount,
COALESCE(pa.failed_amount, 0) AS failed_amount
FROM channel_types AS ct
LEFT JOIN completed_orders AS co
ON ct.channel_type = co.channel_type
LEFT JOIN net_revenue AS nr
ON ct.channel_type = nr.channel_type
LEFT JOIN payment_amounts AS pa
ON ct.channel_type = pa.channel_type
ORDER BY
ct.channel_type ASC{
"token_usage": {
"cache_write_input_tokens": 0,
"cached_input_tokens": 0,
"input_tokens": 19519,
"output_tokens": 1099,
"reasoning_output_tokens": 291
},
"generation_ms": null,
"execution_ms": 215.86691700213123
}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": 4,
"required": 2
},
"id": "kpi-preaggregation",
"kind": "cte_count",
"passed": true
}
],
"column_count": 5,
"column_names": 5,
"execution": 10,
"ordering": 10,
"protocol": 5,
"read_only_ast": 5,
"row_f1": 45,
"sql_capability": 15,
"total": 100
}WITH sales AS (SELECT ch.channel_type, COUNT(DISTINCT o.order_id) AS completed_order_count, SUM(i.quantity * i.unit_price - i.discount_amount) AS net_revenue FROM dim_channels ch JOIN fact_orders o ON o.channel_id = ch.channel_id AND o.status = 'completed' JOIN fact_order_items i ON i.order_id = o.order_id GROUP BY ch.channel_type), payments AS (SELECT ch.channel_type, SUM(CASE WHEN p.status = 'paid' THEN p.amount ELSE 0 END) AS paid_amount, SUM(CASE WHEN p.status = 'refunded' THEN p.amount ELSE 0 END) AS refunded_amount, SUM(CASE WHEN p.status = 'failed' THEN p.amount ELSE 0 END) AS failed_amount FROM dim_channels ch JOIN fact_orders o ON o.channel_id = ch.channel_id JOIN fact_payments p ON p.order_id = o.order_id GROUP BY ch.channel_type) SELECT ch.channel_type, COALESCE(s.completed_order_count, 0) AS completed_order_count, COALESCE(s.net_revenue, 0) AS net_revenue, COALESCE(p.paid_amount, 0) AS paid_amount, COALESCE(p.refunded_amount, 0) AS refunded_amount, COALESCE(p.failed_amount, 0) AS failed_amount FROM (SELECT DISTINCT channel_type FROM dim_channels) ch LEFT JOIN sales s ON s.channel_type = ch.channel_type LEFT JOIN payments p ON p.channel_type = ch.channel_type ORDER BY ch.channel_type ASC[
{
"id": "kpi-preaggregation",
"kind": "cte_count",
"min": 2
}
]{
"abs_tolerance": "0.005",
"decimal_scale": 2,
"duplicate_policy": "multiset",
"max_rows": 10000,
"rel_tolerance": "0",
"row_order_significant": true
}{
"columns": [
{
"name": "channel_type",
"type": "VARCHAR"
},
{
"name": "completed_order_count",
"type": "BIGINT"
},
{
"name": "net_revenue",
"type": "DECIMAL(38,2)"
},
{
"name": "paid_amount",
"type": "DECIMAL(38,2)"
},
{
"name": "refunded_amount",
"type": "DECIMAL(38,2)"
},
{
"name": "failed_amount",
"type": "DECIMAL(38,2)"
}
],
"digest": "c2e7ea06590c967caa9ecc5dd8be012a5ae8d46f9b6d6dbdea1d4b8e72a692e2",
"row_count": 5,
"rows": [
[
"affiliate",
114,
"129676.50",
"130639.25",
"5602.25",
"13165.50"
],
[
"offline",
112,
"140491.50",
"140754.00",
"5162.75",
"22860.50"
],
[
"organic",
141,
"145543.00",
"134754.50",
"8260.00",
"24282.50"
],
[
"paid_search",
117,
"143237.25",
"121154.50",
"8709.75",
"19564.25"
],
[
"partner",
0,
"0.00",
"0.00",
"0.00",
"0.00"
]
]
}{
"columns": [
{
"name": "channel_type",
"type": "VARCHAR"
},
{
"name": "completed_order_count",
"type": "BIGINT"
},
{
"name": "net_revenue",
"type": "DECIMAL(38,2)"
},
{
"name": "paid_amount",
"type": "DECIMAL(38,2)"
},
{
"name": "refunded_amount",
"type": "DECIMAL(38,2)"
},
{
"name": "failed_amount",
"type": "DECIMAL(38,2)"
}
],
"extra": [],
"missing": [],
"row_count": 5,
"rows": [
[
"affiliate",
114,
"129676.50",
"130639.25",
"5602.25",
"13165.50"
],
[
"offline",
112,
"140491.50",
"140754.00",
"5162.75",
"22860.50"
],
[
"organic",
141,
"145543.00",
"134754.50",
"8260.00",
"24282.50"
],
[
"paid_search",
117,
"143237.25",
"121154.50",
"8709.75",
"19564.25"
],
[
"partner",
0,
"0.00",
"0.00",
"0.00",
"0.00"
]
]
}{
"visible_summary": "分别在订单、订单行和支付粒度聚合指标,再按 channel_type 合并,避免订单行与支付记录相乘导致重复计算。",
"error_code": null,
"error_message": null,
"expected_digest": "c2e7ea06590c967caa9ecc5dd8be012a5ae8d46f9b6d6dbdea1d4b8e72a692e2",
"actual_digest": "e011205b29b762f8fcac07678b0ff932ec989049e2d79621e5e081ae7a1b067c",
"assumptions": [
"输出 dim_channels 中定义的所有 channel_type;没有对应事实记录的指标显示为 0。"
]
}按全局事件序号排列,保留时间、级别、类型、消息和 payload。
SEQ 123case.startedinfo{
"status": "generating"
}SEQ 124prompt.builtinfo{
"status": "completed"
}SEQ 125provider.requestedinfo{
"isolation_policy_hash": "922fe6e1a33b0726bb5797d57755d8c5afd03a15fb6fffe56964e8f75389c3bc",
"status": "running"
}SEQ 126provider.deltainfo{
"text": "{\"plan\":{\"grain\":\"每行一个 channel_type\",\"sources\":[\"dim_channels\",\"fact_orders\",\"fact_order_items\",\"fact_payments\"],\"joins\":[\"fact_orders.channel_id = dim_channels.channel_id\",\"fact_order_items.order_id = fact_orders.order_id\",\"fact_payments.order_id = fact_orders.order_id\"],\"filters\":[\"订单数和净销售额仅含 fact_orders.status = 'completed'\",\"支付金额仅按 fact_payments.status 分类\"],\"metrics\":[\"completed_order_count:完成订单去重计数\",\"net_revenue:完成订单行 quantity * unit_price - discount_amount 汇总\",\"paid_amount:status = 'paid' 的支付金额\",\"refunded_amount:status = 'refunded' 的支付金额\",\"failed_amount:status = 'failed' 的支付金额\"],\"steps\":[\"分别聚合完成订单数、订单行净销售额和支付状态金额\",\"以 channel_type 汇总渠道维表\",\"连接各指标聚合并将缺失值补零\",\"按 channel_type 升序输出\"],\"risks\":[\"订单行与支付记录不得直接连接\",\"同一 channel_type 可对应多个 channel_id\",\"支付指标不得套用完成订单过滤\"]},\"sql\":\"WITH channel_types AS (\\n SELECT channel_type\\n FROM dim_channels\\n GROUP BY channel_type\\n),\\ncompleted_orders AS (\\n SELECT\\n c.channel_type,\\n COUNT(DISTINCT o.order_id) AS completed_order_count\\n FROM fact_orders AS o\\n JOIN dim_channels AS c\\n ON o.channel_id = c.channel_id\\n WHERE o.status = 'completed'\\n GROUP BY c.channel_type\\n),\\nnet_revenue AS (\\n SELECT\\n c.channel_type,\\n SUM(oi.quantity * oi.unit_price - oi.discount_amount) AS net_revenue\\n FROM fact_order_items AS oi\\n JOIN fact_orders AS o\\n ON oi.order_id = o.order_id\\n JOIN dim_channels AS c\\n ON o.channel_id = c.channel_id\\n WHERE o.status = 'completed'\\n GROUP BY c.channel_type\\n),\\npayment_amounts AS (\\n SELECT\\n c.channel_type,\\n SUM(CASE WHEN p.status = 'paid' THEN p.amount ELSE 0 END) AS paid_amount,\\n SUM(CASE WHEN p.status = 'refunded' THEN p.amount ELSE 0 END) AS refunded_amount,\\n SUM(CASE WHEN p.status = 'failed' THEN p.amount ELSE 0 END) AS failed_amount\\n FROM fact_payments AS p\\n JOIN fact_orders AS o\\n ON p.order_id = o.order_id\\n JOIN dim_channels AS c\\n ON o.channel_id = c.channel_id\\n GROUP BY c.channel_type\\n)\\nSELECT\\n ct.channel_type,\\n COALESCE(co.completed_order_count, 0) AS completed_order_count,\\n COALESCE(nr.net_revenue, 0) AS net_revenue,\\n COALESCE(pa.paid_amount, 0) AS paid_amount,\\n COALESCE(pa.refunded_amount, 0) AS refunded_amount,\\n COALESCE(pa.failed_amount, 0) AS failed_amount\\nFROM channel_types AS ct\\nLEFT JOIN completed_orders AS co\\n ON ct.channel_type = co.channel_type\\nLEFT JOIN net_revenue AS nr\\n ON ct.channel_type = nr.channel_type\\nLEFT JOIN payment_amounts AS pa\\n ON ct.channel_type = pa.channel_type\\nORDER BY ct.channel_type ASC\",\"summary\":\"分别在订单、订单行和支付粒度聚合指标,再按 channel_type 合并,避免订单行与支付记录相乘导致重复计算。\",\"assumptions\":[\"输出 dim_channels 中定义的所有 channel_type;没有对应事实记录的指标显示为 0。\"]}"
}SEQ 127provider.completedinfo{
"elapsed_ms": 33212.904250001884,
"status": "completed",
"token_usage": {
"cache_write_input_tokens": 0,
"cached_input_tokens": 0,
"input_tokens": 19519,
"output_tokens": 1099,
"reasoning_output_tokens": 291
}
}SEQ 128plan.completedinfo{
"grain": "每行一个 channel_type",
"status": "completed",
"steps": 4
}SEQ 129sql.parsedinfo{
"status": "completed"
}SEQ 130score.completedinfo{
"score": 100,
"status": "completed"
}完整 JSON 字段,不经过页面裁剪。
{
"actual_digest": "e011205b29b762f8fcac07678b0ff932ec989049e2d79621e5e081ae7a1b067c",
"assumptions": [
"输出 dim_channels 中定义的所有 channel_type;没有对应事实记录的指标显示为 0。"
],
"attempt": 1,
"category": "semantic_metrics",
"comparison": {
"abs_tolerance": "0.005",
"decimal_scale": 2,
"duplicate_policy": "multiset",
"max_rows": 10000,
"rel_tolerance": "0",
"row_order_significant": true
},
"difficulty": "hard",
"error_code": null,
"error_message": null,
"execution_ms": 215.86691700213123,
"expected_digest": "c2e7ea06590c967caa9ecc5dd8be012a5ae8d46f9b6d6dbdea1d4b8e72a692e2",
"expected_result_preview": {
"columns": [
{
"name": "channel_type",
"type": "VARCHAR"
},
{
"name": "completed_order_count",
"type": "BIGINT"
},
{
"name": "net_revenue",
"type": "DECIMAL(38,2)"
},
{
"name": "paid_amount",
"type": "DECIMAL(38,2)"
},
{
"name": "refunded_amount",
"type": "DECIMAL(38,2)"
},
{
"name": "failed_amount",
"type": "DECIMAL(38,2)"
}
],
"digest": "c2e7ea06590c967caa9ecc5dd8be012a5ae8d46f9b6d6dbdea1d4b8e72a692e2",
"row_count": 5,
"rows": [
[
"affiliate",
114,
"129676.50",
"130639.25",
"5602.25",
"13165.50"
],
[
"offline",
112,
"140491.50",
"140754.00",
"5162.75",
"22860.50"
],
[
"organic",
141,
"145543.00",
"134754.50",
"8260.00",
"24282.50"
],
[
"paid_search",
117,
"143237.25",
"121154.50",
"8709.75",
"19564.25"
],
[
"partner",
0,
"0.00",
"0.00",
"0.00",
"0.00"
]
]
},
"finished_at": "2026-08-29T22:53:42.348600",
"formatted_sql": "WITH channel_types AS (\n SELECT\n channel_type\n FROM dim_channels\n GROUP BY\n channel_type\n), completed_orders AS (\n SELECT\n c.channel_type,\n COUNT(DISTINCT o.order_id) AS completed_order_count\n FROM fact_orders AS o\n JOIN dim_channels AS c\n ON o.channel_id = c.channel_id\n WHERE\n o.status = 'completed'\n GROUP BY\n c.channel_type\n), net_revenue AS (\n SELECT\n c.channel_type,\n SUM(oi.quantity * oi.unit_price - oi.discount_amount) AS net_revenue\n FROM fact_order_items AS oi\n JOIN fact_orders AS o\n ON oi.order_id = o.order_id\n JOIN dim_channels AS c\n ON o.channel_id = c.channel_id\n WHERE\n o.status = 'completed'\n GROUP BY\n c.channel_type\n), payment_amounts AS (\n SELECT\n c.channel_type,\n SUM(CASE WHEN p.status = 'paid' THEN p.amount ELSE 0 END) AS paid_amount,\n SUM(CASE WHEN p.status = 'refunded' THEN p.amount ELSE 0 END) AS refunded_amount,\n SUM(CASE WHEN p.status = 'failed' THEN p.amount ELSE 0 END) AS failed_amount\n FROM fact_payments AS p\n JOIN fact_orders AS o\n ON p.order_id = o.order_id\n JOIN dim_channels AS c\n ON o.channel_id = c.channel_id\n GROUP BY\n c.channel_type\n)\nSELECT\n ct.channel_type,\n COALESCE(co.completed_order_count, 0) AS completed_order_count,\n COALESCE(nr.net_revenue, 0) AS net_revenue,\n COALESCE(pa.paid_amount, 0) AS paid_amount,\n COALESCE(pa.refunded_amount, 0) AS refunded_amount,\n COALESCE(pa.failed_amount, 0) AS failed_amount\nFROM channel_types AS ct\nLEFT JOIN completed_orders AS co\n ON ct.channel_type = co.channel_type\nLEFT JOIN net_revenue AS nr\n ON ct.channel_type = nr.channel_type\nLEFT JOIN payment_amounts AS pa\n ON ct.channel_type = pa.channel_type\nORDER BY\n ct.channel_type ASC",
"generated_sql": "WITH channel_types AS (\n SELECT channel_type\n FROM dim_channels\n GROUP BY channel_type\n),\ncompleted_orders AS (\n SELECT\n c.channel_type,\n COUNT(DISTINCT o.order_id) AS completed_order_count\n FROM fact_orders AS o\n JOIN dim_channels AS c\n ON o.channel_id = c.channel_id\n WHERE o.status = 'completed'\n GROUP BY c.channel_type\n),\nnet_revenue AS (\n SELECT\n c.channel_type,\n SUM(oi.quantity * oi.unit_price - oi.discount_amount) AS net_revenue\n FROM fact_order_items AS oi\n JOIN fact_orders AS o\n ON oi.order_id = o.order_id\n JOIN dim_channels AS c\n ON o.channel_id = c.channel_id\n WHERE o.status = 'completed'\n GROUP BY c.channel_type\n),\npayment_amounts AS (\n SELECT\n c.channel_type,\n SUM(CASE WHEN p.status = 'paid' THEN p.amount ELSE 0 END) AS paid_amount,\n SUM(CASE WHEN p.status = 'refunded' THEN p.amount ELSE 0 END) AS refunded_amount,\n SUM(CASE WHEN p.status = 'failed' THEN p.amount ELSE 0 END) AS failed_amount\n FROM fact_payments AS p\n JOIN fact_orders AS o\n ON p.order_id = o.order_id\n JOIN dim_channels AS c\n ON o.channel_id = c.channel_id\n GROUP BY c.channel_type\n)\nSELECT\n ct.channel_type,\n COALESCE(co.completed_order_count, 0) AS completed_order_count,\n COALESCE(nr.net_revenue, 0) AS net_revenue,\n COALESCE(pa.paid_amount, 0) AS paid_amount,\n COALESCE(pa.refunded_amount, 0) AS refunded_amount,\n COALESCE(pa.failed_amount, 0) AS failed_amount\nFROM channel_types AS ct\nLEFT JOIN completed_orders AS co\n ON ct.channel_type = co.channel_type\nLEFT JOIN net_revenue AS nr\n ON ct.channel_type = nr.channel_type\nLEFT JOIN payment_amounts AS pa\n ON ct.channel_type = pa.channel_type\nORDER BY ct.channel_type ASC",
"generation_ms": null,
"id": 161,
"model_name": "Sol 本机实测",
"model_run_id": 22,
"plan": {
"filters": [
"订单数和净销售额仅含 fact_orders.status = 'completed'",
"支付金额仅按 fact_payments.status 分类"
],
"grain": "每行一个 channel_type",
"joins": [
"fact_orders.channel_id = dim_channels.channel_id",
"fact_order_items.order_id = fact_orders.order_id",
"fact_payments.order_id = fact_orders.order_id"
],
"metrics": [
"completed_order_count:完成订单去重计数",
"net_revenue:完成订单行 quantity * unit_price - discount_amount 汇总",
"paid_amount:status = 'paid' 的支付金额",
"refunded_amount:status = 'refunded' 的支付金额",
"failed_amount:status = 'failed' 的支付金额"
],
"risks": [
"订单行与支付记录不得直接连接",
"同一 channel_type 可对应多个 channel_id",
"支付指标不得套用完成订单过滤"
],
"sources": [
"dim_channels",
"fact_orders",
"fact_order_items",
"fact_payments"
],
"steps": [
"分别聚合完成订单数、订单行净销售额和支付状态金额",
"以 channel_type 汇总渠道维表",
"连接各指标聚合并将缺失值补零",
"按 channel_type 升序输出"
]
},
"prompt": "你是 Text-to-SQL 数据分析与数据开发生成器。先形成简洁、可审计的结构化查询方案,再生成完成问题所需的 SQL;不要输出隐藏推理。\n\n方言与安全规则:\nUse DuckDB SQL. Return exactly one read-only query. Do not access files, URLs, extensions, or schemas outside the supplied tables.\n\n数据库结构:\n{\"semantic_relationships\":[{\"cardinality\":\"many_to_one\",\"from_entity\":\"order\",\"sql_on\":\"fact_orders.customer_id = dim_customers.customer_id\",\"to_entity\":\"customer\"},{\"cardinality\":\"many_to_one\",\"from_entity\":\"order\",\"sql_on\":\"fact_orders.channel_id = dim_channels.channel_id\",\"to_entity\":\"channel\"},{\"cardinality\":\"many_to_one\",\"from_entity\":\"order_item\",\"sql_on\":\"fact_order_items.order_id = fact_orders.order_id\",\"to_entity\":\"order\"},{\"cardinality\":\"many_to_one\",\"from_entity\":\"order_item\",\"sql_on\":\"fact_order_items.product_id = dim_products.product_id\",\"to_entity\":\"product\"},{\"cardinality\":\"many_to_one\",\"from_entity\":\"payment\",\"sql_on\":\"fact_payments.order_id = fact_orders.order_id\",\"to_entity\":\"order\"},{\"cardinality\":\"many_to_one\",\"from_entity\":\"return\",\"sql_on\":\"fact_returns.order_id = fact_order_items.order_id AND fact_returns.line_no = fact_order_items.line_no\",\"to_entity\":\"order_item\"}],\"tables\":[{\"columns\":[{\"data_type\":\"BIGINT\",\"name\":\"channel_id\",\"nullable\":false},{\"data_type\":\"VARCHAR\",\"name\":\"channel_name\",\"nullable\":false},{\"data_type\":\"VARCHAR\",\"name\":\"channel_type\",\"nullable\":false}],\"foreign_keys\":[],\"name\":\"dim_channels\",\"primary_key\":[\"channel_id\"]},{\"columns\":[{\"data_type\":\"BIGINT\",\"name\":\"customer_id\",\"nullable\":false},{\"data_type\":\"VARCHAR\",\"name\":\"customer_name\",\"nullable\":false},{\"data_type\":\"VARCHAR\",\"name\":\"city\",\"nullable\":true},{\"data_type\":\"DATE\",\"name\":\"signup_date\",\"nullable\":false},{\"data_type\":\"VARCHAR\",\"name\":\"segment\",\"nullable\":false}],\"foreign_keys\":[],\"name\":\"dim_customers\",\"primary_key\":[\"customer_id\"]},{\"columns\":[{\"data_type\":\"BIGINT\",\"name\":\"product_id\",\"nullable\":false},{\"data_type\":\"VARCHAR\",\"name\":\"product_name\",\"nullable\":false},{\"data_type\":\"VARCHAR\",\"name\":\"category\",\"nullable\":false},{\"data_type\":\"VARCHAR\",\"name\":\"brand\",\"nullable\":false},{\"data_type\":\"DECIMAL(14,2)\",\"name\":\"list_price\",\"nullable\":false}],\"foreign_keys\":[],\"name\":\"dim_products\",\"primary_key\":[\"product_id\"]},{\"columns\":[{\"data_type\":\"BIGINT\",\"name\":\"order_id\",\"nullable\":false},{\"data_type\":\"BIGINT\",\"name\":\"line_no\",\"nullable\":false},{\"data_type\":\"BIGINT\",\"name\":\"product_id\",\"nullable\":false},{\"data_type\":\"BIGINT\",\"name\":\"quantity\",\"nullable\":false},{\"data_type\":\"DECIMAL(14,2)\",\"name\":\"unit_price\",\"nullable\":false},{\"data_type\":\"DECIMAL(14,2)\",\"name\":\"discount_amount\",\"nullable\":false}],\"foreign_keys\":[{\"columns\":[\"order_id\"],\"referenced_columns\":[\"order_id\"],\"referenced_table\":\"fact_orders\"},{\"columns\":[\"product_id\"],\"referenced_columns\":[\"product_id\"],\"referenced_table\":\"dim_products\"}],\"name\":\"fact_order_items\",\"primary_key\":[\"order_id\",\"line_no\"]},{\"columns\":[{\"data_type\":\"BIGINT\",\"name\":\"order_id\",\"nullable\":false},{\"data_type\":\"BIGINT\",\"name\":\"customer_id\",\"nullable\":false},{\"data_type\":\"BIGINT\",\"name\":\"channel_id\",\"nullable\":false},{\"data_type\":\"DATE\",\"name\":\"order_date\",\"nullable\":false},{\"data_type\":\"VARCHAR\",\"name\":\"status\",\"nullable\":false},{\"data_type\":\"DECIMAL(14,2)\",\"name\":\"total_amount\",\"nullable\":false}],\"foreign_keys\":[{\"columns\":[\"customer_id\"],\"referenced_columns\":[\"customer_id\"],\"referenced_table\":\"dim_customers\"},{\"columns\":[\"channel_id\"],\"referenced_columns\":[\"channel_id\"],\"referenced_table\":\"dim_channels\"}],\"name\":\"fact_orders\",\"primary_key\":[\"order_id\"]},{\"columns\":[{\"data_type\":\"BIGINT\",\"name\":\"payment_id\",\"nullable\":false},{\"data_type\":\"BIGINT\",\"name\":\"order_id\",\"nullable\":false},{\"data_type\":\"TIMESTAMP\",\"name\":\"paid_at\",\"nullable\":false},{\"data_type\":\"VARCHAR\",\"name\":\"payment_method\",\"nullable\":false},{\"data_type\":\"DECIMAL(14,2)\",\"name\":\"amount\",\"nullable\":false},{\"data_type\":\"VARCHAR\",\"name\":\"status\",\"nullable\":false}],\"foreign_keys\":[{\"columns\":[\"order_id\"],\"referenced_columns\":[\"order_id\"],\"referenced_table\":\"fact_orders\"}],\"name\":\"fact_payments\",\"primary_key\":[\"payment_id\"]},{\"columns\":[{\"data_type\":\"BIGINT\",\"name\":\"return_id\",\"nullable\":false},{\"data_type\":\"BIGINT\",\"name\":\"order_id\",\"nullable\":false},{\"data_type\":\"BIGINT\",\"name\":\"line_no\",\"nullable\":false},{\"data_type\":\"TIMESTAMP\",\"name\":\"returned_at\",\"nullable\":false},{\"data_type\":\"BIGINT\",\"name\":\"return_qty\",\"nullable\":false},{\"data_type\":\"DECIMAL(14,2)\",\"name\":\"refund_amount\",\"nullable\":false},{\"data_type\":\"VARCHAR\",\"name\":\"reason\",\"nullable\":true}],\"foreign_keys\":[{\"columns\":[\"order_id\",\"line_no\"],\"referenced_columns\":[\"order_id\",\"line_no\"],\"referenced_table\":\"fact_order_items\"}],\"name\":\"fact_returns\",\"primary_key\":[\"return_id\"]}]}\n\n语义层与业务口径:\n{\"business_rules\":[\"完成订单仅指 fact_orders.status = 'completed'。\",\"净销售额为 quantity * unit_price - discount_amount。\",\"paid、refunded、failed 金额只按 fact_payments.status 分类。\",\"退货率为完成订单的 returned_qty / sold_qty,售出数量仅含完成订单。\",\"月份按 UTC Gregorian calendar 计算。\",\"订单头 total_amount 应等于订单行净额汇总,差异视为数据质量异常。\"],\"dimensions\":[{\"data_type\":\"VARCHAR\",\"description\":\"客户分群\",\"expression\":\"dim_customers.segment\",\"name\":\"customer_segment\"},{\"data_type\":\"VARCHAR\",\"description\":\"商品品类\",\"expression\":\"dim_products.category\",\"name\":\"product_category\"},{\"data_type\":\"VARCHAR\",\"description\":\"渠道类型\",\"expression\":\"dim_channels.channel_type\",\"name\":\"channel_type\"},{\"data_type\":\"VARCHAR\",\"description\":\"UTC Gregorian 月份\",\"expression\":\"strftime(fact_orders.order_date, '%Y-%m')\",\"name\":\"order_month\"}],\"entities\":[{\"description\":\"客户主数据\",\"grain\":\"每行一个客户\",\"name\":\"customer\",\"primary_key\":[\"customer_id\"],\"table\":\"dim_customers\"},{\"description\":\"商品主数据\",\"grain\":\"每行一个商品\",\"name\":\"product\",\"primary_key\":[\"product_id\"],\"table\":\"dim_products\"},{\"description\":\"渠道主数据\",\"grain\":\"每行一个渠道\",\"name\":\"channel\",\"primary_key\":[\"channel_id\"],\"table\":\"dim_channels\"},{\"description\":\"订单头\",\"grain\":\"每行一个订单\",\"name\":\"order\",\"primary_key\":[\"order_id\"],\"table\":\"fact_orders\"},{\"description\":\"订单行\",\"grain\":\"每行一个订单商品行\",\"name\":\"order_item\",\"primary_key\":[\"order_id\",\"line_no\"],\"table\":\"fact_order_items\"},{\"description\":\"支付尝试\",\"grain\":\"每行一笔支付\",\"name\":\"payment\",\"primary_key\":[\"payment_id\"],\"table\":\"fact_payments\"},{\"description\":\"退货记录\",\"grain\":\"每行一条订单行退货\",\"name\":\"return\",\"primary_key\":[\"return_id\"],\"table\":\"fact_returns\"}],\"metrics\":[{\"description\":\"已完成订单数\",\"expression\":\"COUNT(DISTINCT CASE WHEN fact_orders.status = 'completed' THEN fact_orders.order_id END)\",\"filters\":[\"fact_orders.status = 'completed'\"],\"grain\":\"聚合\",\"name\":\"completed_order_count\"},{\"description\":\"完成订单商品行净销售额\",\"expression\":\"SUM(fact_order_items.quantity * fact_order_items.unit_price - fact_order_items.discount_amount)\",\"filters\":[\"fact_orders.status = 'completed'\"],\"grain\":\"聚合\",\"name\":\"net_revenue\"},{\"description\":\"成功支付金额\",\"expression\":\"SUM(CASE WHEN fact_payments.status = 'paid' THEN fact_payments.amount ELSE 0 END)\",\"filters\":[],\"grain\":\"聚合\",\"name\":\"paid_amount\"},{\"description\":\"退款状态支付金额\",\"expression\":\"SUM(CASE WHEN fact_payments.status = 'refunded' THEN fact_payments.amount ELSE 0 END)\",\"filters\":[],\"grain\":\"聚合\",\"name\":\"refunded_amount\"},{\"description\":\"失败支付金额\",\"expression\":\"SUM(CASE WHEN fact_payments.status = 'failed' THEN fact_payments.amount ELSE 0 END)\",\"filters\":[],\"grain\":\"聚合\",\"name\":\"failed_amount\"},{\"description\":\"完成订单退货数量除以售出数量\",\"expression\":\"SUM(fact_returns.return_qty) / SUM(fact_order_items.quantity)\",\"filters\":[\"fact_orders.status = 'completed'\"],\"grain\":\"聚合\",\"name\":\"return_rate\"}],\"relationships\":[{\"cardinality\":\"many_to_one\",\"from_entity\":\"order\",\"sql_on\":\"fact_orders.customer_id = dim_customers.customer_id\",\"to_entity\":\"customer\"},{\"cardinality\":\"many_to_one\",\"from_entity\":\"order\",\"sql_on\":\"fact_orders.channel_id = dim_channels.channel_id\",\"to_entity\":\"channel\"},{\"cardinality\":\"many_to_one\",\"from_entity\":\"order_item\",\"sql_on\":\"fact_order_items.order_id = fact_orders.order_id\",\"to_entity\":\"order\"},{\"cardinality\":\"many_to_one\",\"from_entity\":\"order_item\",\"sql_on\":\"fact_order_items.product_id = dim_products.product_id\",\"to_entity\":\"product\"},{\"cardinality\":\"many_to_one\",\"from_entity\":\"payment\",\"sql_on\":\"fact_payments.order_id = fact_orders.order_id\",\"to_entity\":\"order\"},{\"cardinality\":\"many_to_one\",\"from_entity\":\"return\",\"sql_on\":\"fact_returns.order_id = fact_order_items.order_id AND fact_returns.line_no = fact_order_items.line_no\",\"to_entity\":\"order_item\"}]}\n\n问题:\n按 channel_type 输出 completed_order_count、net_revenue、paid_amount、refunded_amount、failed_amount。所有指标必须遵循语义层口径,避免订单行与支付记录直接连接造成重复计算,并按 channel_type 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": "按 channel_type 输出 completed_order_count、net_revenue、paid_amount、refunded_amount、failed_amount。所有指标必须遵循语义层口径,避免订单行与支付记录直接连接造成重复计算,并按 channel_type 升序。",
"radar_dimension": "聚合与指标",
"raw_output": "{\"plan\":{\"grain\":\"每行一个 channel_type\",\"sources\":[\"dim_channels\",\"fact_orders\",\"fact_order_items\",\"fact_payments\"],\"joins\":[\"fact_orders.channel_id = dim_channels.channel_id\",\"fact_order_items.order_id = fact_orders.order_id\",\"fact_payments.order_id = fact_orders.order_id\"],\"filters\":[\"订单数和净销售额仅含 fact_orders.status = 'completed'\",\"支付金额仅按 fact_payments.status 分类\"],\"metrics\":[\"completed_order_count:完成订单去重计数\",\"net_revenue:完成订单行 quantity * unit_price - discount_amount 汇总\",\"paid_amount:status = 'paid' 的支付金额\",\"refunded_amount:status = 'refunded' 的支付金额\",\"failed_amount:status = 'failed' 的支付金额\"],\"steps\":[\"分别聚合完成订单数、订单行净销售额和支付状态金额\",\"以 channel_type 汇总渠道维表\",\"连接各指标聚合并将缺失值补零\",\"按 channel_type 升序输出\"],\"risks\":[\"订单行与支付记录不得直接连接\",\"同一 channel_type 可对应多个 channel_id\",\"支付指标不得套用完成订单过滤\"]},\"sql\":\"WITH channel_types AS (\\n SELECT channel_type\\n FROM dim_channels\\n GROUP BY channel_type\\n),\\ncompleted_orders AS (\\n SELECT\\n c.channel_type,\\n COUNT(DISTINCT o.order_id) AS completed_order_count\\n FROM fact_orders AS o\\n JOIN dim_channels AS c\\n ON o.channel_id = c.channel_id\\n WHERE o.status = 'completed'\\n GROUP BY c.channel_type\\n),\\nnet_revenue AS (\\n SELECT\\n c.channel_type,\\n SUM(oi.quantity * oi.unit_price - oi.discount_amount) AS net_revenue\\n FROM fact_order_items AS oi\\n JOIN fact_orders AS o\\n ON oi.order_id = o.order_id\\n JOIN dim_channels AS c\\n ON o.channel_id = c.channel_id\\n WHERE o.status = 'completed'\\n GROUP BY c.channel_type\\n),\\npayment_amounts AS (\\n SELECT\\n c.channel_type,\\n SUM(CASE WHEN p.status = 'paid' THEN p.amount ELSE 0 END) AS paid_amount,\\n SUM(CASE WHEN p.status = 'refunded' THEN p.amount ELSE 0 END) AS refunded_amount,\\n SUM(CASE WHEN p.status = 'failed' THEN p.amount ELSE 0 END) AS failed_amount\\n FROM fact_payments AS p\\n JOIN fact_orders AS o\\n ON p.order_id = o.order_id\\n JOIN dim_channels AS c\\n ON o.channel_id = c.channel_id\\n GROUP BY c.channel_type\\n)\\nSELECT\\n ct.channel_type,\\n COALESCE(co.completed_order_count, 0) AS completed_order_count,\\n COALESCE(nr.net_revenue, 0) AS net_revenue,\\n COALESCE(pa.paid_amount, 0) AS paid_amount,\\n COALESCE(pa.refunded_amount, 0) AS refunded_amount,\\n COALESCE(pa.failed_amount, 0) AS failed_amount\\nFROM channel_types AS ct\\nLEFT JOIN completed_orders AS co\\n ON ct.channel_type = co.channel_type\\nLEFT JOIN net_revenue AS nr\\n ON ct.channel_type = nr.channel_type\\nLEFT JOIN payment_amounts AS pa\\n ON ct.channel_type = pa.channel_type\\nORDER BY ct.channel_type ASC\",\"summary\":\"分别在订单、订单行和支付粒度聚合指标,再按 channel_type 合并,避免订单行与支付记录相乘导致重复计算。\",\"assumptions\":[\"输出 dim_channels 中定义的所有 channel_type;没有对应事实记录的指标显示为 0。\"]}",
"reference_sql": "WITH sales AS (SELECT ch.channel_type, COUNT(DISTINCT o.order_id) AS completed_order_count, SUM(i.quantity * i.unit_price - i.discount_amount) AS net_revenue FROM dim_channels ch JOIN fact_orders o ON o.channel_id = ch.channel_id AND o.status = 'completed' JOIN fact_order_items i ON i.order_id = o.order_id GROUP BY ch.channel_type), payments AS (SELECT ch.channel_type, SUM(CASE WHEN p.status = 'paid' THEN p.amount ELSE 0 END) AS paid_amount, SUM(CASE WHEN p.status = 'refunded' THEN p.amount ELSE 0 END) AS refunded_amount, SUM(CASE WHEN p.status = 'failed' THEN p.amount ELSE 0 END) AS failed_amount FROM dim_channels ch JOIN fact_orders o ON o.channel_id = ch.channel_id JOIN fact_payments p ON p.order_id = o.order_id GROUP BY ch.channel_type) SELECT ch.channel_type, COALESCE(s.completed_order_count, 0) AS completed_order_count, COALESCE(s.net_revenue, 0) AS net_revenue, COALESCE(p.paid_amount, 0) AS paid_amount, COALESCE(p.refunded_amount, 0) AS refunded_amount, COALESCE(p.failed_amount, 0) AS failed_amount FROM (SELECT DISTINCT channel_type FROM dim_channels) ch LEFT JOIN sales s ON s.channel_type = ch.channel_type LEFT JOIN payments p ON p.channel_type = ch.channel_type ORDER BY ch.channel_type ASC",
"requested_model_id": "gpt-5.6-sol",
"required_ast": [
{
"id": "kpi-preaggregation",
"kind": "cte_count",
"min": 2
}
],
"resolved_model_id": "gpt-5.6-sol",
"result_preview": {
"columns": [
{
"name": "channel_type",
"type": "VARCHAR"
},
{
"name": "completed_order_count",
"type": "BIGINT"
},
{
"name": "net_revenue",
"type": "DECIMAL(38,2)"
},
{
"name": "paid_amount",
"type": "DECIMAL(38,2)"
},
{
"name": "refunded_amount",
"type": "DECIMAL(38,2)"
},
{
"name": "failed_amount",
"type": "DECIMAL(38,2)"
}
],
"extra": [],
"missing": [],
"row_count": 5,
"rows": [
[
"affiliate",
114,
"129676.50",
"130639.25",
"5602.25",
"13165.50"
],
[
"offline",
112,
"140491.50",
"140754.00",
"5162.75",
"22860.50"
],
[
"organic",
141,
"145543.00",
"134754.50",
"8260.00",
"24282.50"
],
[
"paid_search",
117,
"143237.25",
"121154.50",
"8709.75",
"19564.25"
],
[
"partner",
0,
"0.00",
"0.00",
"0.00",
"0.00"
]
]
},
"run_id": 18,
"score": {
"ast_rules": [
{
"details": {
"actual": 4,
"required": 2
},
"id": "kpi-preaggregation",
"kind": "cte_count",
"passed": true
}
],
"column_count": 5,
"column_names": 5,
"execution": 10,
"ordering": 10,
"protocol": 5,
"read_only_ast": 5,
"row_f1": 45,
"sql_capability": 15,
"total": 100
},
"stable_key": "semantic_channel_kpis",
"started_at": "2026-08-29T22:53:08.881645",
"status": "completed",
"suite_content_hash": "5b5d98876ea35114f18ce6dfa48cc9800d88b6baba80d311b2f52552a38b31af",
"title": "渠道核心指标",
"token_usage": {
"cache_write_input_tokens": 0,
"cached_input_tokens": 0,
"input_tokens": 19519,
"output_tokens": 1099,
"reasoning_output_tokens": 291
},
"visible_summary": "分别在订单、订单行和支付粒度聚合指标,再按 channel_type 合并,避免订单行与支付记录相乘导致重复计算。"
}