demo数据
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zhaoawd
330
demo/水务/水务-gpt5-snippet.json
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330
demo/水务/水务-gpt5-snippet.json
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[
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{
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"id": "snpt_topn_station",
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"desc": "按站点统计水表数量并取前N",
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"type": "topn",
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"title": "站点TopN水表数",
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"examples": [
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"各站点水表数量排名前10",
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"站点水表覆盖情况排行"
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],
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"variables": [
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{
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"name": "top_n",
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"type": "int",
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"default": 10
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}
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],
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"dialect_sql": {
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"mysql": "SELECT station,\n COUNT(DISTINCT service_point_id) AS meter_cnt\nFROM `data-ge`.`water_meter_info`\nGROUP BY station\nORDER BY meter_cnt DESC\nLIMIT {{top_n}};"
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},
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"applicability": {
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"constraints": {
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"notes": [
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"TopN建议N<=36",
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"以service_point_id去重计数",
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"无时间列，无法做趋势"
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],
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"fk_join_available": false,
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"dim_cardinality_hint": 36
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},
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"time_column": null,
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"required_columns": [
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"station",
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"service_point_id"
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]
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},
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"business_caliber": "水表数=按service_point_id去重计数；粒度=站点。仅统计当前表中的有效记录（不含时间口径）。安全限制：用于分析排名，避免扩大LIMIT造成全量导出。"
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},
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{
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"id": "snpt_share_district",
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"desc": "统计各辖区水表数及其占比",
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"type": "ratio",
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"title": "辖区水表占比",
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"examples": [
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"各辖区水表占比",
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"哪个辖区水表最多"
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],
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"variables": [],
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"dialect_sql": {
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"mysql": "WITH by_district AS (\n SELECT district, COUNT(DISTINCT service_point_id) AS meter_cnt\n FROM `data-ge`.`water_meter_info`\n GROUP BY district\n), tot AS (\n SELECT COUNT(DISTINCT service_point_id) AS total_cnt\n FROM `data-ge`.`water_meter_info`\n)\nSELECT b.district,\n b.meter_cnt,\n ROUND(b.meter_cnt / NULLIF(t.total_cnt, 0) * 100, 2) AS pct\nFROM by_district b\nCROSS JOIN tot t\nORDER BY pct DESC, b.district;"
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},
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"applicability": {
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"constraints": {
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"notes": [
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"占比分母为全表service_point_id去重总数",
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"service_point_id为空将被忽略"
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],
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"fk_join_available": false,
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"dim_cardinality_hint": 13
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},
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"time_column": null,
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"required_columns": [
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"district",
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"service_point_id"
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]
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},
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"business_caliber": "水表数=按service_point_id去重计数；粒度=辖区。占比=辖区水表数/全表水表总数。安全限制：仅基于本表，不代表全市/全网口径；无时间维度。"
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},
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{
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"id": "snpt_dist_diameter",
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"desc": "按表径统计水表数量分布",
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"type": "aggregate",
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"title": "表径分布统计",
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"examples": [
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"不同口径水表有多少",
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"查看表径分布情况"
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],
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"variables": [],
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"dialect_sql": {
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"mysql": "SELECT meter_diameter,\n COUNT(DISTINCT service_point_id) AS meter_cnt\nFROM `data-ge`.`water_meter_info`\nGROUP BY meter_diameter\nORDER BY meter_cnt DESC, meter_diameter;"
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},
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"applicability": {
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"constraints": {
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"notes": [
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"以service_point_id去重计数",
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"适合绘制条形图/饼图"
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],
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"fk_join_available": false,
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"dim_cardinality_hint": 8
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},
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"time_column": null,
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"required_columns": [
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"meter_diameter",
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"service_point_id"
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]
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},
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"business_caliber": "水表数=按service_point_id去重计数；粒度=表径。安全限制：仅用于分布分析，不含时间过滤；避免用于明细导出。"
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},
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{
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"id": "snpt_type_subtype_matrix",
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"desc": "统计水表类型与子类组合的数量",
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"type": "aggregate",
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"title": "类型子类分布",
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"examples": [
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"不同类型与子类的水表数量",
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"查看类型与子类的组合分布"
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],
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"variables": [],
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"dialect_sql": {
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"mysql": "SELECT meter_type,\n meter_subtype,\n COUNT(DISTINCT service_point_id) AS meter_cnt\nFROM `data-ge`.`water_meter_info`\nGROUP BY meter_type, meter_subtype\nORDER BY meter_cnt DESC, meter_type, meter_subtype;"
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},
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"applicability": {
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"constraints": {
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"notes": [
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"组合基数<=5×9=45",
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"以service_point_id去重计数"
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],
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"fk_join_available": false,
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"dim_cardinality_hint": 45
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},
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"time_column": null,
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"required_columns": [
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"meter_type",
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"meter_subtype",
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"service_point_id"
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]
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},
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"business_caliber": "水表数=按service_point_id去重计数；粒度=类型×子类组合。安全限制：仅用于汇总分析，不包含时间或业务状态变化。"
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},
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{
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"id": "snpt_quality_spid_uniq",
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"desc": "评估service_point_id的空值与重复情况",
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"type": "quality",
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"title": "服务点唯一性检",
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"examples": [
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"检查服务点ID是否唯一",
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"统计service_point_id空值与重复情况"
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],
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"variables": [],
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"dialect_sql": {
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"mysql": "SELECT\n COUNT(*) AS total_rows,\n SUM(service_point_id IS NULL) AS null_cnt,\n COUNT(DISTINCT service_point_id) AS distinct_cnt,\n (COUNT(*) - COUNT(DISTINCT service_point_id)) AS duplicate_rows_est,\n (\n SELECT COUNT(*) FROM (\n SELECT service_point_id\n FROM `data-ge`.`water_meter_info`\n GROUP BY service_point_id\n HAVING COUNT(*) > 1\n ) AS dup\n ) AS dup_key_groups\nFROM `data-ge`.`water_meter_info`;"
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},
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"applicability": {
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"constraints": {
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"notes": [
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"用于键完整性检查",
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"重复行估算=总行数-去重数"
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],
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"fk_join_available": false,
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"dim_cardinality_hint": null
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},
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"time_column": null,
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"required_columns": [
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"service_point_id"
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]
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},
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"business_caliber": "质量检查口径：在本表内评估service_point_id的非空与唯一性，不代表跨表全局唯一。安全限制：仅输出汇总指标，不暴露明细重复值。"
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},
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{
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"id": "snpt_quality_account_nulls",
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"desc": "抽取account_id为空的记录用于排查",
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"type": "quality",
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"title": "账户ID缺失明细",
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"examples": [
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"列出account_id为空的水表",
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"抽样查看账户缺失的数据行"
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],
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"variables": [
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{
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"name": "limit_n",
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"type": "int",
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"default": 50
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}
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],
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"dialect_sql": {
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"mysql": "SELECT *\nFROM `data-ge`.`water_meter_info`\nWHERE account_id IS NULL\nLIMIT {{limit_n}};"
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},
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"applicability": {
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"constraints": {
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"notes": [
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"明细仅限小样本抽取",
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"建议LIMIT<=100，避免全量导出"
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],
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"fk_join_available": false,
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"dim_cardinality_hint": null
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},
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"time_column": null,
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"required_columns": [
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"account_id"
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]
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},
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"business_caliber": "质量抽样：筛出账户ID缺失的水表记录，便于核对。安全限制：仅用于样本排查，不建议在生产中全量导出；如需口径统计请改为COUNT聚合。"
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},
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{
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"id": "snpt_sample_random_rows",
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"desc": "随机抽取水表信息用于人工核验",
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"type": "sample",
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"title": "随机抽样明细",
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"examples": [
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"抽样查看水表信息",
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"随机抽取20条做质检"
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],
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"variables": [
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{
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"name": "sample_size",
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"type": "int",
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"default": 20
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}
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],
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"dialect_sql": {
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"mysql": "SELECT *\nFROM `data-ge`.`water_meter_info`\nORDER BY RAND()\nLIMIT {{sample_size}};"
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},
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"applicability": {
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"constraints": {
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"notes": [
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"使用RAND()随机，样本不可复现",
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"建议限制样本量"
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],
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"fk_join_available": false,
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"dim_cardinality_hint": 300
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},
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"time_column": null,
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"required_columns": [
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"service_point_id"
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]
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},
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"business_caliber": "样本抽取：从本表随机返回若干行明细。安全限制：避免扩大LIMIT进行全量下载；如需可复现样本，请改用带种子的随机方法（MySQL不原生支持）。"
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},
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{
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"id": "snpt_filter_office_type_where",
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"desc": "常用WHERE筛选条件片段：按营业所与类型且为有效",
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"type": "sample",
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"title": "机构类型筛选片",
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"examples": [
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"筛选A营业所的机械表",
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"仅查看某营业所的指定类型水表"
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],
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"variables": [
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{
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"name": "supply_office",
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"type": "string"
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},
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{
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"name": "meter_type",
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"type": "string"
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}
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],
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"dialect_sql": {
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"mysql": "WHERE supply_office = '{{supply_office}}'\n AND meter_type = '{{meter_type}}'\n AND meter_status = '有效'"
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},
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"applicability": {
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"constraints": {
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"notes": [
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"这是条件片段，可拼接到其他查询",
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"meter_status当前为单一值“有效”"
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],
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"fk_join_available": false,
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"dim_cardinality_hint": 11
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},
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"time_column": null,
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"required_columns": [
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"supply_office",
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"meter_type",
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"meter_status"
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]
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},
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"business_caliber": "过滤口径：仅保留指定营业所与指定水表类型、且状态为“有效”的记录。安全限制：为片段用途，需拼接在SELECT…FROM之后使用。"
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},
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{
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"id": "snpt_office_station_dist",
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"desc": "按营业所与站点组合统计水表数",
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"type": "aggregate",
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"title": "所站层级分布",
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"examples": [
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"按营业所查看各站点水表数",
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"所站两级的水表分布情况"
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],
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"variables": [],
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"dialect_sql": {
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"mysql": "SELECT supply_office,\n station,\n COUNT(DISTINCT service_point_id) AS meter_cnt\nFROM `data-ge`.`water_meter_info`\nGROUP BY supply_office, station\nORDER BY supply_office, meter_cnt DESC, station;"
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},
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"applicability": {
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"constraints": {
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"notes": [
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"组合基数<=11×36=396",
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"以service_point_id去重计数",
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"如结果过长可再按TopN筛选"
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],
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"fk_join_available": false,
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"dim_cardinality_hint": 396
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},
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"time_column": null,
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"required_columns": [
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"supply_office",
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"station",
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"service_point_id"
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]
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},
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"business_caliber": "水表数=按service_point_id去重计数；粒度=营业所×站点。安全限制：结果行数可能较多，建议在可视化端增加筛选或分页。"
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},
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{
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"id": "snpt_total_meter_baseline",
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"desc": "获取全表水表去重总量基线",
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"type": "aggregate",
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"title": "水表总量基线",
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"examples": [
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"当前有多少只水表",
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"作为占比分析的分母基线"
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],
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"variables": [],
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"dialect_sql": {
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"mysql": "SELECT COUNT(DISTINCT service_point_id) AS meter_total\nFROM `data-ge`.`water_meter_info`;"
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},
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"applicability": {
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"constraints": {
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"notes": [
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"作为其他占比/分摊分母基线",
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"忽略service_point_id为空的记录"
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],
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"fk_join_available": false,
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"dim_cardinality_hint": 300
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},
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"time_column": null,
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"required_columns": [
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"service_point_id"
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]
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},
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"business_caliber": "水表总量=按service_point_id去重计数；基于当前表的全量记录。安全限制：无时间维度，无法反映存量随时间变化。"
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}
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]
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