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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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必须对索引名（表名）、字段名、别名外层加双引号（"）。
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<note>
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1. 通配符索引需整体加引号：`"logs-*"`
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2. 嵌套字段用点号连接：`"user.name"`
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3. 时间字段必须显式转换：`CAST("@timestamp" AS TIMESTAMP)`
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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. 首选：`LIMIT [count]`
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2. 分页：`LIMIT [count] OFFSET [start]`
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3. 禁止使用Elasticsearch原生`size/from`参数
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</note>
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</rule>
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other_rule: |
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<rule>必须为每个索引生成别名（不加AS）</rule>
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<rule>禁止使用星号(*)，必须明确字段名</rule>
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<rule>中文/特殊字符字段需保留原名并添加英文别名</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Elasticsearch关键字冲突（如`score`/`type`）</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 Elasticsearch 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 logs-* 索引的前100条错误日志（含时间过滤）</input>
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<output-bad>
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SELECT * FROM logs-* WHERE level = 'error' LIMIT 100 -- 错误1：使用星号
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SELECT message FROM "logs-*" WHERE @timestamp > NOW() - 1d -- 错误2：未转换时间
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SELECT "message", "@timestamp" FROM "logs-*" LIMIT 100 -- 错误3：未处理时间字段
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</output-bad>
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<output-good>
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SELECT
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"l"."message" AS "log_content",
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"l"."host.ip" AS "client_ip",
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CAST("l"."@timestamp" AS TIMESTAMP) AS "log_time"
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FROM "logs-*" "l"
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WHERE "l"."level" = 'error'
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AND CAST("l"."@timestamp" AS TIMESTAMP) > DATE_SUB(NOW(), INTERVAL 1 DAY)
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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>统计各地区的错误日志占比（Top 5）</input>
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<output-bad>
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SELECT region, COUNT(*) FROM "logs-*" GROUP BY region -- 错误1：使用COUNT(*)
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SELECT "region", MAX("count") FROM "logs-*" 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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"l"."region" AS "area",
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COUNT("l"."message") AS "error_count",
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ROUND(COUNT("l"."message") * 100.0 / SUM(COUNT("l"."message")) OVER (), 2) || '%' AS "error_percent"
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FROM "logs-*" "l"
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WHERE "l"."level" = 'error'
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GROUP BY "l"."region"
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ORDER BY "error_count" 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: Elasticsearch SQL 8.9
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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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