00 前言
在进行mysql性能优化的时候,第一个想到的便是查看慢sql。
但是对于慢sql有没有什么好的工具进行分析呢?
推荐两个工具mysqldumpslow及pt-query-digest。
mysqlslowdump较为简单,常用命令:
#得到返回记录最多的20个sql
mysqldumpslow -s r -t 20 slowSQl.log
# 得到平均访问次数最多的20条sql
mysqldumpslow -s ar -t 20 slowSQl.log
如果linux上没有安装mysqldumpslow,yum install安装下就行了。
本文主要说下pt-query-digest。
pt-query-digest可以非常清晰地将slowSQL分析出来,类似oracle的AWR报告。
# Rank Query ID Response time Calls R/Call V/M
# ==== =============================== =============== ===== ====== =====
# 1 0xABD1DCCCCD5AA5128E10C27B34... 1246.6948 41.7% 283 4.4053 0.04 UPDATE ziweidashi_deviceinfo
# 2 0x6914B81AAD1785E50708ABD113... 877.6900 29.3% 339 2.5891 0.09 SELECT birthDay_notify
# 3 0x44D9474C6D5C58DD07B5FEEA0D... 299.4193 10.0% 71 4.2172 0.05 SELECT tmall_product_orders
# 4 0xA9BE84CBE3DAA9B1CDD9B5A9EC... 127.0137 4.2% 46 2.7612 0.04 SELECT daily_user_action_log
# 5 0xCF0E12117C971C3013142E3717... 118.3138 4.0% 49 2.4146 0.05 SELECT tmall_user_take_coupon_record
# 6 0x94263184D24186330B13193534... 97.0805 3.2% 35 2.7737 0.56 SELECT tgg_users
# 7 0xC51165F1287A2ECDA221AC1F54... 52.5870 1.8% 22 2.3903 0.04 SELECT util_user_task_log
# 8 0xB8004D6D8A7A7967E04CD81E26... 43.7895 1.5% 16 2.7368 0.08 SELECT daily_user_action_log
# 9 0x910E19224F33DAA6391927B8E8... 41.3720 1.4% 15 2.7581 1.17 SELECT qifugong_tianbi_record
# MISC 0xMISC 86.7871 2.9% 30 2.8929 0.0 <12 ITEMS>
并且不只可以分析慢SQL日志,还可以分析binlog、general log。
此外,pt-query-digest是percona-toolkit工具包的其中一个工具。
这个工具包下还有很多实用的性能分析辅助工具。
01 安装排坑
1、下载
# 进入安装目录
cd /usr/local/src
# 下载percona-toolkit 工具包
wget percona.com/get/percona-toolkit.tar.gz
# 解压
tar zxf percona-toolkit.tar.gz
# 进入解压文件夹
cd /usr/local/src/percona-toolkit-3.1.0
# 安装perl模块,制定依赖路径
perl Makefile.PL PREFIX=/usr/local/percona-toolkit
2、报错 prerequisite DBD::mysql 3 not found
报错如下,找不到DBD包
[root@iZ2zebthf35ejlps5v87ksZ percona-toolkit-3.1.0]# perl Makefile.PL PREFIX=/usr/local/percona-toolkit
Checking if your kit is complete...
Looks good
Warning: prerequisite DBD::mysql 3 not found.
Warning: prerequisite DBI 1.46 not found.
Writing Makefile for percona-toolkit
百度问题,找到链接,https://blog.csdn.net/heizistudio/article/details/45724707?locationNum=8&fps=1
安装依赖包
yum install perl-DBD-MySQL
然后重新执行命令
[root@iZ2zebthf35ejlps5v87ksZ percona-toolkit-3.1.0]# perl Makefile.PL PREFIX=/usr/local/percona-toolkit
Writing Makefile for percona-toolkit
3、安装
make && make install
安装后内容如下
……
Installing /usr/local/percona-toolkit/bin/pt-summary
Installing /usr/local/percona-toolkit/bin/pt-table-sync
Appending installation info to /usr/local/percona-toolkit/lib64/perl5/perllocal.pod
4、使用
[root@iZ2zebthf35ejlps5v87ksZ bin]# pt-query-digest /usr/local/mysql/data/slow.log
-bash: pt-query-digest: command not found
发现没找到pt-query-digest命令,是因为bash命令默认是从/usr/bin下找的;
如果rpm安装,会默认添加到/usr/bin下;
而我们现在是编译二进制安装到,并且默认是装到了/usr/local/percona-toolkit下,发现本文件夹下有个bin目录,pt工具都在其下。
-rwxrwxr-x 1 hc hc 41747 Sep 16 2019 pt-align
-rwxrwxr-x 1 hc hc 270675 Sep 16 2019 pt-archiver
-rwxrwxr-x 1 hc hc 170783 Sep 16 2019 pt-config-diff
-rwxrwxr-x 1 hc hc 167978 Sep 16 2019 pt-deadlock-logger
-rwxrwxr-x 1 hc hc 166450 Sep 16 2019 pt-diskstats
-rwxrwxr-x 1 hc hc 171099 Sep 16 2019 pt-duplicate-key-checker
-rwxrwxr-x 1 hc hc 50157 Sep 16 2019 pt-fifo-split
-rwxrwxr-x 1 hc hc 151809 Sep 16 2019 pt-find
-rwxrwxr-x 1 hc hc 67304 Sep 16 2019 pt-fingerprint
-rwxrwxr-x 1 hc hc 134955 Sep 16 2019 pt-fk-error-logger
-rwxrwxr-x 1 hc hc 223887 Sep 16 2019 pt-heartbeat
-rwxrwxr-x 1 hc hc 228213 Sep 16 2019 pt-index-usage
-rwxrwxr-x 1 hc hc 32405 Sep 16 2019 pt-ioprofile
-rwxrwxr-x 1 hc hc 256092 Sep 16 2019 pt-kill
-rwxrwxr-x 1 hc hc 21913 Sep 16 2019 pt-mext
-rwxrwxr-x 1 hc hc 8196032 Sep 16 2019 pt-mongodb-query-digest
-rwxrwxr-x 1 hc hc 8522944 Sep 16 2019 pt-mongodb-summary
-rwxrwxr-x 1 hc hc 108113 Sep 16 2019 pt-mysql-summary
-rwxrwxr-x 1 hc hc 426996 Sep 16 2019 pt-online-schema-change
-rwxrwxr-x 1 hc hc 4794784 Sep 16 2019 pt-pg-summary
-rwxrwxr-x 1 hc hc 24598 Sep 16 2019 pt-pmp
-rwxrwxr-x 1 hc hc 527607 Sep 16 2019 pt-query-digest
-rwxrwxr-x 1 hc hc 3624992 Sep 16 2019 pt-secure-collect
-rwxrwxr-x 1 hc hc 78242 Sep 16 2019 pt-show-grants
-rwxrwxr-x 1 hc hc 37784 Sep 16 2019 pt-sift
-rwxrwxr-x 1 hc hc 146952 Sep 16 2019 pt-slave-delay
-rwxrwxr-x 1 hc hc 131404 Sep 16 2019 pt-slave-find
-rwxrwxr-x 1 hc hc 184944 Sep 16 2019 pt-slave-restart
-rwxrwxr-x 1 hc hc 76226 Sep 16 2019 pt-stalk
-rwxrwxr-x 1 hc hc 90816 Sep 16 2019 pt-summary
-rwxrwxr-x 1 hc hc 459729 Sep 16 2019 pt-table-checksum
-rwxrwxr-x 1 hc hc 405119 Sep 16 2019 pt-table-sync
-rwxrwxr-x 1 hc hc 247743 Sep 16 2019 pt-table-usage
-rwxrwxr-x 1 hc hc 333011 Sep 16 2019 pt-upgrade
-rwxrwxr-x 1 hc hc 178415 Sep 16 2019 pt-variable-advisor
-rwxrwxr-x 1 hc hc 102545 Sep 16 2019 pt-visual-explain
本次使用到主力工具,pt-query-digest,执行命令,进行慢日志分析
./pt-query-digest /usr/local/mysql/data/slow.log
5、又报错 Can't locate Digest/MD5.pm in @INC
[root@iZ2zebthf35ejlps5v87ksZ bin]# ./pt-query-digest /usr/local/mysql/data/slow.log
Can't locate Digest/MD5.pm in @INC (@INC contains: /usr/local/lib64/perl5 /usr/local/share/perl5 /usr/lib64/perl5/vendor_perl /usr/share/perl5/vendor_perl /usr/lib64/perl5 /usr/share/perl5 .) at ./pt-query-digest line 2470.
BEGIN failed--compilation aborted at ./pt-query-digest line 2470.
安装perl-Digest-MD5工具
yum -y install perl-Digest-MD5
终于可以运行了
./pt-query-digest /usr/local/mysql/data/slow.log
6、无脑命令如下
yum -y install perl-DBD-MySQL
yum -y install perl-Digest-MD5
cd /usr/local/src
wget percona.com/get/percona-toolkit.tar.gz
tar zxf percona-toolkit.tar.gz
cd /usr/local/src/percona-toolkit-3.1.0
perl Makefile.PL PREFIX=/usr/local/percona-toolkit
make && make install
二、分析实战
1、执行工具pt-query-digest
./pt-query-digest /usr/local/src/slowsqlExample/slow0312.log
2、结果分析
找了一个慢sql,分析结果如下
[root@iZ2zebthf35ejlps5v87ksZ bin]# ./pt-query-digest /usr/local/src/slowsqlExample/slow0312.log
第一部分
该工具执行日志分析的用户时间,系统时间,物理内存占用大小,虚拟内存占用大小
# 360ms user time, 10ms system time, 22.56M rss, 187.09M vsz
工具执行时间
# Current date: Fri Mar 20 22:54:14 2020
运行分析工具的主机名
# Hostname: iZ2zebthf35ejlps5v87ksZ
被分析的文件名
# Files: /usr/local/src/slowsqlExample/slow0312.log
语句总数量,唯一的语句数量,QPS,并发数
# Overall: 906 total, 21 unique, 0.02 QPS, 0.07x concurrency _____________
日志记录的时间范围
# Time range: 2020-03-11 12:22:13 to 2020-03-12 00:16:57
# Attribute total min max avg 95% stddev median
# ============ ======= ======= ======= ======= ======= ======= =======
语句执行时间
# Exec time 2991s 2s 10s 3s 5s 1s 3s
锁占用时间
# Lock time 552ms 24us 371ms 609us 103us 12ms 57us
发送到客户端的行数
# Rows sent 167.53k 0 17.99k 189.35 487.09 1.22k 0
select语句扫描行数
# Rows examine 980.73M 238 1.96M 1.08M 1.95M 757.80k 753.18k
查询的字符数
# Query size 258.71k 17 1.77k 292.41 463.90 202.02 329.68
第二部分
# Profile
Rank:所有语句的排名,默认按查询时间降序排列,通过--order-by指定
Query ID:语句的ID,(去掉多余空格和文本字符,计算hash值)
Response:总的响应时间
time:该查询在本次分析中总的时间占比
calls:执行次数,即本次分析总共有多少条这种类型的查询语句
R/Call:平均每次执行的响应时间
V/M:响应时间Variance-to-mean的比率
Item:查询对象
# Rank Query ID Response time Calls R/Call V/M
# ==== =============================== =============== ===== ====== =====
# 1 0xABD1DCCCCD5AA5128E10C27B34... 1246.6948 41.7% 283 4.4053 0.04 UPDATE ziweidashi_deviceinfo
# 2 0x6914B81AAD1785E50708ABD113... 877.6900 29.3% 339 2.5891 0.09 SELECT birthDay_notify
# 3 0x44D9474C6D5C58DD07B5FEEA0D... 299.4193 10.0% 71 4.2172 0.05 SELECT tmall_product_orders
# 4 0xA9BE84CBE3DAA9B1CDD9B5A9EC... 127.0137 4.2% 46 2.7612 0.04 SELECT daily_user_action_log
# 5 0xCF0E12117C971C3013142E3717... 118.3138 4.0% 49 2.4146 0.05 SELECT tmall_user_take_coupon_record
# 6 0x94263184D24186330B13193534... 97.0805 3.2% 35 2.7737 0.56 SELECT tgg_users
# 7 0xC51165F1287A2ECDA221AC1F54... 52.5870 1.8% 22 2.3903 0.04 SELECT util_user_task_log
# 8 0xB8004D6D8A7A7967E04CD81E26... 43.7895 1.5% 16 2.7368 0.08 SELECT daily_user_action_log
# 9 0x910E19224F33DAA6391927B8E8... 41.3720 1.4% 15 2.7581 1.17 SELECT qifugong_tianbi_record
# MISC 0xMISC 86.7871 2.9% 30 2.8929 0.0 <12 ITEMS>
第三及后续部分,第一条查询语句 query id:0xABD1DCCCCD5AA5128E10C27B34BC04E7
# Query 1: 0.01 QPS, 0.03x concurrency, ID 0xABD1DCCCCD5AA5128E10C27B34BC04E7 at byte 355748
# Scores: V/M = 0.04
# Time range: 2020-03-11 12:24:03 to 2020-03-12 00:16:13
# Attribute pct total min max avg 95% stddev median
# ============ === ======= ======= ======= ======= ======= ======= =======
# Count 31 283
# Exec time 41 1247s 4s 8s 4s 5s 437ms 4s
# Lock time 69 386ms 24us 371ms 1ms 93us 21ms 44us
# Rows sent 0 0 0 0 0 0 0 0
# Rows examine 18 180.00M 651.14k 651.45k 651.29k 650.62k 0 650.62k
# Query size 10 27.64k 100 100 100 100 0 100
# String:
数据库名
# Databases taxen_ziweidashi
执行主机
# Hosts 118.190.93.166
执行用户
# Users devAccount
查询时间占比
# Query_time distribution
# 1us
# 10us
# 100us
# 1ms
# 10ms
# 100ms
# 1s ################################################################
# 10s+
# Tables
# SHOW TABLE STATUS FROM `taxen_ziweidashi` LIKE 'ziweidashi_deviceinfo'\G
# SHOW CREATE TABLE `taxen_ziweidashi`.`ziweidashi_deviceinfo`\G
UPDATE ziweidashi_deviceinfo
SET expired = 1
WHERE createTime <= 1583942580685\G
# Converted for EXPLAIN
# EXPLAIN /*!50100 PARTITIONS*/
select expired = 1 from ziweidashi_deviceinfo where createTime <= 1583942580685\G
# Query 2: 0.03 QPS, 0.07x concurrency, ID 0x6914B81AAD1785E50708ABD11319E02E at byte 13829
# Scores: V/M = 0.09
# Time range: 2020-03-11 12:22:13 to 16:05:47
# Attribute pct total min max avg 95% stddev median
# ============ === ======= ======= ======= ======= ======= ======= =======
# Count 37 339
# Exec time 29 878s 2s 4s 3s 4s 472ms 2s
# Lock time 5 29ms 31us 4ms 86us 98us 229us 66us
# Rows sent 0 24 0 2 0.07 0 0.32 0
# Rows examine 67 665.20M 1.96M 1.96M 1.96M 1.96M 0 1.96M
# Query size 59 154.47k 462 467 466.60 463.90 2.07 463.90
# String:
# Hosts 10.66.186.115
# Users root
# Query_time distribution
# 1us
# 10us
# 100us
# 1ms
# 10ms
# 100ms
# 1s ################################################################
# 10s+
# Tables
# SHOW TABLE STATUS LIKE 'birthDay_notify'\G
# SHOW CREATE TABLE `birthDay_notify`\G
# EXPLAIN /*!50100 PARTITIONS*/
select birthdayno0_.id as id1_1_, birthdayno0_.index_card_show_date as index_ca2_1_, birthdayno0_.userId as userId3_1_, birthdayno0_.push_content as push_con4_1_, birthdayno0_.card_content as card_con5_1_, birthdayno0_.birthday_userId as birthday6_1_, birthdayno0_.birthday_contactId as birthday7_1_, birthdayno0_.need_push as need_pus8_1_ from birthDay_notify birthdayno0_ where birthdayno0_.userId=1304747 and birthdayno0_.index_card_show_date='2020-03-11 00:00:00'\G
……省略
3、实例优化
找出这几条语句,对症下药,进行写法的修改、索引的设计,基本可以解决慢SQL问题。
例如query1的语句
UPDATE ziweidashi_deviceinfo
SET expired = 1
WHERE createTime <= 1583942580685
分析后发现,这张表大部分数据的expired字段都是1,每次update都相当于全表查询、锁定了一次。
从逻辑上分析,是expired不等于1才修改的。
可以修改为
UPDATE ziweidashi_deviceinfo
SET expired = 1
WHERE createTime <= 1583942580685
and expired != 1
直接从平均的5秒执行时间降低到了0.04秒。
其他语句类似。
三、常用命令
1.分析慢查询文件
pt-query-digest slow.log > slow_report.log
2.分析最近12小时内的查询
pt-query-digest --since=12h slow.log > slow_report2.log
3.分析指定时间范围内的查询
pt-query-digest slow.log --since '2017-01-07 09:30:00' --until '2017-01-07 10:00:00'> > slow_report3.log
4、通过tcpdump抓取mysql的tcp协议数据,然后再分析
tcpdump -s 65535 -x -nn -q -tttt -i any -c 1000 port 3306 > mysql.tcp.txt
pt-query-digest --type tcpdump mysql.tcp.txt> slow_report9.log
5、分析binlog
mysqlbinlog mysql-bin.000093 > mysql-bin000093.sql
pt-query-digest --type=binlog mysql-bin000093.sql > slow_report10.log
6、分析general log
pt-query-digest --type=genlog localhost.log > slow_report11.log
四、参考资料
1、高性能mysql(第三版)
2、MySQL慢查询分析工具pt-query-digest详解 作者:枫叶工作室。
3、Warning: prerequisite DBD::mysql 3 not found 作者:ora600
4、使用lcov时遇到错误can't locate Digest/MD5.pm in @INC (@INC contains: /usr/local/lib64/perl5 ...的错误 作者:迷茫的叶
来源:oschina
链接:https://my.oschina.net/u/4398470/blog/3228851