分类： Mysql/postgreSQL
2012-02-22 11:47:24
mk-query-digest 一个功能很强大的工具，能分析慢查询日志，也可以对当前的语句进行分析等。安装方法查看这里。
一、分析慢查询日志,生成报表
mysql通过log-slow-queries和long_query_time参数来记录慢查询，默认的格式如下：
| # Time: 090909 4:34:28 # User@Host: sparty[sparty] @ [localhost] # Query_time: 18 Lock_time: 0 Rows_sent: 5 Rows_examined: 52830 select * from test; # Time: 090909 14:04:24 # User@Host: sparty[sparty] @ [localhost] # Query_time: 20 Lock_time: 0 Rows_sent: 10 Rows_examined: 2500284 select * from test2; |
每产生一条慢查询记录一行，分析起来不直观，也无法进行统计。mk-query-digest能对slow log进行了统计和分析产生报告，可以更具自己的需要，分析出想要的结果。例如
| mk-query-digest --limit 2 --select Query_time,Lock_time,Rows_sent,Rows_examined,ts slow.log \ |grep -v '1us' |grep -v '10us'|grep -v '1ms'|grep -v '10ms'|grep -v '100ms' \ |grep -v '1s'|grep -v '10s'|grep -v 'SHOW'|grep -v '100us'|grep -v 'EXPLAIN' # Overall: 3 total, 2 unique, 0.00 QPS, 0.00x concurrency ________________ # total min max avg 95% stddev median # Exec time 78s 8s 44s 26s 42s 14s 25s # Lock time 2ms 0 2ms 588us 2ms 822us 0 # Rows sent 23.87M 1 11.93M 7.96M 11.87M 5.59M 11.87M # Rows exam 35.80M 11.93M 11.93M 11.93M 11.87M 0 11.87M # Time range 2009-05-20 20:33:59 to 2009-05-27 14:50:13 # Query 1: 0.08 QPS, 2.68x concurrency, ID 0x67A347A2812914DF at byte 1240 # This item is included in the report because it matches --limit. # pct total min max avg 95% stddev median # Count 66 2 # Exec time 89 70s 26s 44s 35s 44s 13s 35s # Lock time 0 0 0 0 0 0 0 0 # Rows sent 99 23.87M 11.93M 11.93M 11.93M 11.93M 0.71 11.93M # Rows exam 66 23.87M 11.93M 11.93M 11.93M 11.93M 0.71 11.93M # Time range 2009-05-27 14:49:47 to 2009-05-27 14:50:13 # Query_time distribution # Tables SELECT /*!40001 SQL_NO_CACHE */ * FROM `test`\G # Query 2: 0 QPS, 0x concurrency, ID 0x92203A59492D2ECF at byte 0 ________ # This item is included in the report because it matches --limit. # pct total min max avg 95% stddev median # Count 33 1 # Exec time 10 8s 8s 8s 8s 8s 0 8s # Lock time 100 2ms 2ms 2ms 2ms 2ms 0 2ms # Rows sent 0 1 1 1 1 1 0 1 # Rows exam 33 11.93M 11.93M 11.93M 11.93M 11.93M 0 11.93M # Time range 2009-05-20 20:33:59 to 2009-05-20 20:33:59 # Query_time distribution # Tables select count(*) from test where t1=20 and t2=100\G # Rank Query ID Response time Calls R/Call Item # ==== ================== ================ ======= ========== ==== # 1 0x67A347A2812914DF 69.7409 89.4% 2 34.870474 SELECT test # 2 0x92203A59492D2ECF 8.2742 10.6% 1 8.274248 SELECT test |
报表的输出分三部分，开头部分是整个报表的综合统计。中间部分把单独的Query进行统计，按照total Exec time从高到低排序。结尾部分是输出的每条Query的一些统计。
解释一下主要参数：
-limit 指输出耗时最多的Query的条数限制。
-select 选择需要统计的指标。
二、对当前的查询进行统计分析
mk-query-digest也能使用–processlist参数，对指定mysql的当前Query进行统计分析，例如
| mk-query-digest –processlist h=localhost -u sg -p |
然后在CTRL+C结束，将对这段时间h=localhost里所进行的所有Query进行统计分析并生成报表，报表的输出和上面介绍的一样。
三、分析慢查询日志，将结果导入到指定表。
mk-query-digest也能使用–review参数，将慢查询日志的分析结果插入到指定表中。
首先需要创建表，存放分析结果：
| CREATE TABLE query_review ( checksum BIGINT UNSIGNED NOT NULL PRIMARY KEY, fingerprint TEXT NOT NULL, sample TEXT NOT NULL, first_seen DATETIME, last_seen DATETIME, reviewed_by VARCHAR(20), reviewed_on DATETIME, comments TEXT ) COLUMN MEANING =========== =============== checksum A 64-bit checksum of the query fingerprint fingerprint The abstracted version of the query; its primary key sample The query text of a sample of the class of queries first_seen The smallest timestamp of this class of queries last_seen The largest timestamp of this class of queries reviewed_by Initially NULL; if set, query is skipped thereafter reviewed_on Initially NULL; not assigned any special meaning comments Initially NULL; not assigned any special meaning例如： mk-query-digest --review h=host1,D=test,t=query_review /path/to/slow.log mysql> use test; Database changed mysql> select * from query_review\G; *************************** 1. row *************************** checksum: 7467891370387641567 fingerprint: mysqldump sample: SELECT /*!40001 SQL_NO_CACHE */ * FROM `test` first_seen: 2009-05-27 14:49:47 last_seen: 2009-05-27 14:50:13 reviewed_by: NULL reviewed_on: NULL comments: NULL *************************** 2. row *************************** checksum: 10529480083946417871 fingerprint: select count(*) from test where test1=? and test2=? sample: select count(*) from test where test1=20 and test2=100 first_seen: 2009-05-20 20:33:59 last_seen: 2009-05-20 20:33:59 reviewed_by: NULL reviewed_on: NULL comments: NULL 2 rows in set (0.00 sec) |
四、查找未走索引的语句
mk-query-digest还可以用来找出当前数据库未走索引的语句，例如我使用下面命令：
| tcpdump -i bond0 port 3306 -s 65535 -x -n -q -tttt | mk-query-digest –type tcpdump –filter '($event->{No_index_used} || $event->{No_good_index_used})' |
然后在CTRL+C结束，将生成下面的报告。
| tcpdump: verbose output suppressed, use -v or -vv for full protocol decode listening on bond0, link-type EN10MB (Ethernet), capture size 65535 bytes 3 packets captured 3 packets received by filter 0 packets dropped by kernel # Caught SIGINT. # 170ms user time, 20ms system time, 12.00M rss, 73.26M vsz # Overall: 1 total, 1 unique, 0 QPS, 0x concurrency ______________________ # total min max avg 95% stddev median # Exec time 223us 223us 223us 223us 223us 0 223us # Time range 2009-09-16 09:22:50.637146 to 2009-09-16 09:22:50.637146 # bytes 26 26 26 26 26 0 26 # Rows affe 0 0 0 0 0 0 0 # Warning c 0 0 0 0 0 0 0 # 100% (1) No_index_used # Query 1: 0 QPS, 0x concurrency, ID 0x3D8C074C26D05CD7 at byte 0 ________ # This item is included in the report because it matches --limit. # pct total min max avg 95% stddev median # Count 100 1 # Exec time 100 223us 223us 223us 223us 223us 0 223us # Hosts 1 10.0.0.203 # Time range 2009-09-16 09:22:50.637146 to 2009-09-16 09:22:50.637146 # bytes 100 26 26 26 26 26 0 26 # Errors 1 none # Rows affe 0 0 0 0 0 0 0 0 # Warning c 0 0 0 0 0 0 0 0 # 100% (1) No_index_used select * from test\G # Rank Query ID Response time Calls R/Call Item # ==== ================== ================ ======= ========== ==== # 1 0x3D8C074C26D05CD7 0.0002 100.0% 1 0.000223 SELECT test |
很明显，使用tcpdump只能对本地的mysql进行监听，一目了然的找到了哪条sql是没走索引的。
最后，我们在看下这个工具的帮助选项：
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