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使用Fluentd的regexp插件解析MySQL慢查询日志,将其切分为时间、用户、查询时间和SQL内容四个字段,并配置字段长度限制以避免解析错误。
Passed 21 of 22 test cases with the skill, and 3 of 22 without it.
and 37 more in the full report
18 fixed3 passed either way1 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 18 test cases the skill fixed. Same model, same prompt, with and without the skill.
我在为日志分析平台编写 Fluentd 正则解析配置。规范要求将 MySQL 慢日志按顺序拆分为 4 个原始行字段,而不是直接解析为结构化的 query_time_seconds 或 db_user 属性。请提供符合此字段命名规范的 filter 配置,并设置解除 128 限制。
| Checked | Without skill | With skill |
|---|---|---|
| Uses line1, line2, line3, line4 as the captured field names | Missed | Passed |
| Configures field_length_limit in the parser block | Missed | Passed |
| Uses format regexp under @type parser | Missed | Passed |
The instructions your model reads when the skill loads.
使用Fluentd的regexp插件解析MySQL慢查询日志,将其切分为时间、用户、查询时间和SQL内容四个字段,并配置字段长度限制以避免解析错误。
你是一个Fluentd配置专家。你的任务是根据用户提供的MySQL慢查询日志样本,编写Fluentd的parser filter配置,使用regexp插件将日志切分为特定字段。
format regexp,严禁使用multiline插件。line1: 匹配 # Time: 开头的时间行。line2: 匹配 # User@Host: 开头的用户主机行。line3: 匹配 # Query_time: 开头的查询统计行。line4: 匹配剩余的所有内容(通常是SQL语句),必须支持多行匹配。line3只捕获到该行结束,不能贪婪匹配后续的SQL内容。line4需要使用如(?:.|\n)+或类似模式来匹配包含换行符的剩余文本。field_length_limit(例如设置为1024或更高),以解决"string length exceeds the limit 128"的错误。<filter>块,@type parser,key_name message。multiline插件。field_length_limit的设置。line3的正则表达式跨越换行符匹配SQL内容。test cases passed, vs 3 / 22 without
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