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92 lines
4.8 KiB
YAML
92 lines
4.8 KiB
YAML
template:
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quot_rule: |
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<rule>
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必须对数据库名、表名、字段名、别名外层加双引号（"）。
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<note>
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1. 点号（.）不能包含在引号内，必须写成 "database"."table"
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2. ClickHouse 严格区分大小写，必须通过引号保留原始大小写
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3. 嵌套字段使用点号连接：`"json_column.field"`
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</note>
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</rule>
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limit_rule: |
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<rule>
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当需要限制行数时，必须使用标准的LIMIT语法
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<note>
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1. 标准写法：LIMIT [count]
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2. 分页写法：LIMIT [count] OFFSET [start]
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3. 禁止使用原生 `topk()` 等函数替代
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</note>
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</rule>
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other_rule: |
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<rule>必须为每个表生成简短别名（如t1/t2）</rule>
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{multi_table_condition}
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<rule>禁止使用星号(*)，必须明确字段名</rule>
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<rule>JSON字段需用点号语法访问：`"column.field"`</rule>
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<rule>函数字段必须加别名</rule>
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<rule>百分比显示为：`ROUND(x*100,2) || '%'`</rule>
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<rule>避免与ClickHouse关键字冲突（如`timestamp`/`default`）</rule>
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basic_example: |
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<basic-examples>
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<intro>
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📌 以下示例严格遵循<Rules>中的 ClickHouse 规范，展示符合要求的 SQL 写法与典型错误案例。
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⚠️ 注意：示例中的表名、字段名均为演示虚构，实际使用时需替换为用户提供的真实标识符。
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🔍 重点观察：
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1. 双引号包裹所有数据库对象的规范用法
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2. 中英别名/百分比/函数等特殊字段的处理
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3. 关键字冲突的规避方式
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</intro>
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<example>
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<input>查询 events 表的前100条错误日志（含JSON字段）</input>
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<output-bad>
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SELECT * FROM default.events LIMIT 100 -- 错误1：使用星号
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SELECT message FROM "default"."events" WHERE level = 'error' -- 错误2：未处理JSON字段
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SELECT "message", "extra.error_code" FROM events LIMIT 100 -- 错误3：表名未加引号
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</output-bad>
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<output-good>
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SELECT
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"e"."message" AS "log_content",
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"e"."extra"."error_code" AS "error_id",
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toDateTime("e"."timestamp") AS "log_time"
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FROM "default"."events" "e"
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WHERE "e"."level" = 'error'
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LIMIT 100
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</output-good>
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</example>
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<example>
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<input>统计各地区的错误率Top 5（含百分比）</input>
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<output-bad>
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SELECT region, COUNT(*) FROM events GROUP BY region -- 错误1：使用COUNT(*)
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SELECT "region", MAX("count") FROM "events" GROUP BY 1 -- 错误2：使用序号分组
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</output-bad>
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<output-good>
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SELECT
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"e"."region" AS "area",
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COUNT(*) AS "total",
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COUNTIf("e"."level" = 'error') AS "error_count",
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ROUND(error_count * 100.0 / total, 2) || '%' AS "error_rate"
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FROM "default"."events" "e"
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GROUP BY "e"."region"
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ORDER BY "error_rate" DESC
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LIMIT 5
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</output-good>
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</example>
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</basic-examples>
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example_engine: ClickHouse 23.3
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example_answer_1: |
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{"success":true,"sql":"SELECT \"country\" AS \"country_name\", \"continent\" AS \"continent_name\", \"year\" AS \"year\", \"gdp\" AS \"gdp_usd\" FROM \"Sample_Database\".\"sample_country_gdp\" ORDER BY \"country\", \"year\"","tables":["sample_country_gdp"],"chart-type":"line"}
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example_answer_1_with_limit: |
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{"success":true,"sql":"SELECT \"country\" AS \"country_name\", \"continent\" AS \"continent_name\", \"year\" AS \"year\", \"gdp\" AS \"gdp_usd\" FROM \"Sample_Database\".\"sample_country_gdp\" ORDER BY \"country\", \"year\" LIMIT 1000","tables":["sample_country_gdp"],"chart-type":"line"}
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example_answer_2: |
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{"success":true,"sql":"SELECT \"country\" AS \"country_name\", \"gdp\" AS \"gdp_usd\" FROM \"Sample_Database\".\"sample_country_gdp\" WHERE \"year\" = '2024' ORDER BY \"gdp\" DESC","tables":["sample_country_gdp"],"chart-type":"pie"}
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example_answer_2_with_limit: |
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{"success":true,"sql":"SELECT \"country\" AS \"country_name\", \"gdp\" AS \"gdp_usd\" FROM \"Sample_Database\".\"sample_country_gdp\" WHERE \"year\" = '2024' ORDER BY \"gdp\" DESC LIMIT 1000","tables":["sample_country_gdp"],"chart-type":"pie"}
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example_answer_3: |
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{"success":true,"sql":"SELECT \"country\" AS \"country_name\", \"gdp\" AS \"gdp_usd\" FROM \"Sample_Database\".\"sample_country_gdp\" WHERE \"year\" = '2025' AND \"country\" = '中国'","tables":["sample_country_gdp"],"chart-type":"table"}
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example_answer_3_with_limit: |
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{"success":true,"sql":"SELECT \"country\" AS \"country_name\", \"gdp\" AS \"gdp_usd\" FROM \"Sample_Database\".\"sample_country_gdp\" WHERE \"year\" = '2025' AND \"country\" = '中国' LIMIT 1000","tables":["sample_country_gdp"],"chart-type":"table"}
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