Elasticsearch慢查询日志分析
Posted
tags:
篇首语：本文由小常识网(cha138.com)小编为大家整理，主要介绍了Elasticsearch慢查询日志分析相关的知识，希望对你有一定的参考价值。
目前架构：
n台filebeat客户端来将每台应用上的日志传到kafka，3台kafka做集群用于日志队列，四台ES做集群，前两台存放近两天热数据日志，后两台存放两天前的历史日志，数据保存一个月，目前总数据量6T。logstash与kibana与ES在一台机器上，kibana访问域名三个kibana做轮询，
目前ELK中发现有些索引查询有点慢，于是打开ES索引查询日志来记录慢查询，进而对慢查询日志进行分析，定位问题。慢日志内容如下：
[2017-08-28T11:21:02,377][WARN ][index.search.slowlog.query] [node-3] [logstash-nginx-2017.08.01][4] took[15s], took_millis[15029], types[], stats[], search _type[QUERY_THEN_FETCH], total_shards[140], source[{"size":0,"query":{"bool":{"filter":[{"match_none":{"boost":1.0}},{"query_string":{"query":"NOT status:200 OR NOT status:304","fields":[],"use_dis_max":true,"tie_breaker":0.0,"default_operator":"or","auto_generate_phrase_queries":false,"max_determined_states":10000,"enable_position _increment":true,"fuzziness":"AUTO","fuzzy_prefix_length":0,"fuzzy_max_expansions":50,"phrase_slop":0,"analyze_wildcard":true,"escape":false,"split_on_whitespace":true, "boost":1.0}}],"disable_coord":false,"adjust_pure_negative":true,"boost":1.0}},"aggregations":{"3":{"terms":{"field":"status","size":5,"min_doc_count":0,"shard_min_doc_ count":0,"show_term_doc_count_error":false,"order":[{"_count":"desc"},{"_term":"asc"}]},"aggregations":{"2":{"date_histogram":{"field":"@timestamp","format":"epoch_mill is","interval":"20m","offset":0,"order":{"_key":"asc"},"keyed":false,"min_doc_count":0,"extended_bounds":{"min":"1503886846372","max":"1503890446372"}}}}}}}], [2017-08-28T11:21:02,377][WARN ][index.search.slowlog.query] [node-3] [logstash-nginx-2017.08.01][2] took[15.7s], took_millis[15787], types[], stats[], sear ch_type[QUERY_THEN_FETCH], total_shards[140], source[{"size":0,"query":{"bool":{"filter":[{"match_none":{"boost":1.0}},{"query_string":{"query":"NOT status:200 OR NOT status:304","fields":[],"use_dis_max":true,"tie_breaker":0.0,"default_operator":"or","auto_generate_phrase_queries":false,"max_determined_states":10000,"enable_positi on_increment":true,"fuzziness":"AUTO","fuzzy_prefix_length":0,"fuzzy_max_expansions":50,"phrase_slop":0,"analyze_wildcard":true,"escape":false,"split_on_whitespace":tru e,"boost":1.0}}],"disable_coord":false,"adjust_pure_negative":true,"boost":1.0}},"aggregations":{"3":{"terms":{"field":"status","size":5,"min_doc_count":0,"shard_min_do c_count":0,"show_term_doc_count_error":false,"order":[{"_count":"desc"},{"_term":"asc"}]},"aggregations":{"2":{"date_histogram":{"field":"@timestamp","format":"epoch_mi llis","interval":"20m","offset":0,"order":{"_key":"asc"},"keyed":false,"min_doc_count":0,"extended_bounds":{"min":"1503886846372","max":"1503890446372"}}}}}}}],
下面进行分析：
待续
本文出自 “努力奔向前方” 博客，请务必保留此出处http://liucb.blog.51cto.com/3230681/1959875
以上是关于Elasticsearch慢查询日志分析的主要内容，如果未能解决你的问题，请参考以下文章