前两天折腾了mysqlsla,今天才发现hackmysql.com中的工具已沦为历史产物,建议使用Percona Toolkit代替。
一、下载安装
[root@VMUest tools]# wget https://www.percona.com/downloads/percona-toolkit/3.0.2/binary/tarball/percona-toolkit-3.0.2_i386.tar.gz [root@VMUest tools]# tar xf percona-toolkit-3.0.2_i386.tar.gz -C /usr/local/ [root@VMUest tools]# cd /usr/local/ [root@VMUest local]# mv /usr/local/percona-toolkit-3.0.2/ /usr/local/toolkit [root@VMUest local]# cd toolkit [root@VMUest toolkit]# cat README #配置编译安装 [root@VMUest toolkit]# perl Makefile.PL Checking if your kit is complete... Looks good Warning: prerequisite DBD::mysql 3 not found. Writing Makefile for percona-toolkit #根据需求安装,之前mysqlsla已安装部分依赖包 [root@VMUest toolkit]# yum install perl-DBD-MySQL [root@VMUest toolkit]# perl Makefile.PL [root@VMUest toolkit]# make && make test && make install
完成后相关工具自动添加到环境变量,我的机器上在/usr/local/bin/目录下有对应的文件
#查看安装了哪些工具 [root@VMUest toolkit]# man percona-toolkit #查看具体工具如何使用 [root@VMUest toolkit]# man pt-query-digest [root@VMUest toolkit]# pt-query-digest --help
二、用法示例
#1、直接分析慢查询文件并将结果写入118slow_report.log文件 [root@VMUest ~]# pt-query-digest /myshare/118mysqldumpslow-20161227.log > /myshare/118slow_report.log [root@VMUest ~]# pt-query-digest --group-by fingerprint --order-by Query_time:sum --limit 10 /myshare/118mysqldumpslow-20161227.log #2、查看指定fingerprint(参数化Query ID)的语句 [root@VMUest ~]# pt-query-digest /myshare/118mysqldumpslow-20161227.log --filter '$event->{fingerprint} && make_checksum($event->{fingerprint}) eq "6C0C2937AEF1D27C"' [root@VMUest ~]# pt-query-digest /myshare/118mysqldumpslow-20161227.log --no-report --output slowlog --filter '$event->{fingerprint} && make_checksum($event->{fingerprint}) eq "6C0C2937AEF1D27C"' #3、指定时间范围内的查询 [root@VMUest ~]# pt-query-digest /myshare/118mysqldumpslow-20161227.log --since '2016-12-27 07:51:20' --until '2016-12-27 10:10:34' #4、分析含有delete语句的慢查询 [root@VMUest ~]# pt-query-digest --filter '$event->{fingerprint} =~ m/^delete/i' /myshare/118mysqldumpslow-20161227.log #5、把查询保存到query_review表 [root@VMUest ~]# pt-query-digest --user=mydba --password=mysql5635 --review h=192.168.85.129,P=3306,D=test,t=query_review /myshare/118mysqldumpslow-20161227.log mysql> select * from test.query_review; #6、把查询保存到query_history表 [root@VMUest ~]# pt-query-digest --user=mydba --password=mysql5635 --history h=192.168.85.129,P=3306,D=test,t=query_history /myshare/118mysqldumpslow-20161227.log mysql> select * from test.query_history; #7、分析binlog [root@VMUest ~]# mysqlbinlog /usr/local/mysql/log/mysql-bin.000001 > /myshare/mysql-bin000001.sql [root@VMUest ~]# pt-query-digest --type=binlog /myshare/mysql-bin000001.sql #8、分析general log mysql> set global general_log_file='/usr/local/mysql/log/mysql-general.log'; mysql> set global general_log =1; [root@VMUest ~]# pt-query-digest --type=genlog /usr/local/mysql/log/mysql-general.log
三、报告解释
![](https://images.cnblogs.com/OutliningIndicators/ContractedBlock.gif)
[root@VMUest ~]# pt-query-digest --filter '$event->{fingerprint} =~ m/^delete/i' /myshare/118mysqldumpslow-20161227.log --limit 100% # 5.4s user time, 80ms system time, 13.06M rss, 17.15M vsz # Current date: Fri Mar 31 17:37:00 2017 # Hostname: VMUest # Files: /myshare/118mysqldumpslow-20161227.log # Overall: 8 total, 2 unique, 0.00 QPS, 0.03x concurrency ________________ # Time range: 2016-12-27 00:00:28 to 00:30:35 # Attribute total min max avg 95% stddev median # ============ ======= ======= ======= ======= ======= ======= ======= # Exec time 56s 256us 16s 7s 15s 5s 9s # Lock time 9s 20us 9s 1s 9s 3s 128us # Rows sent 0 0 0 0 0 0 0 # Rows examine 2.52M 0 657.18k 322.91k 650.62k 220.00k 410.39k # Query size 504 56 84 63 80.10 11.21 54.21 # Profile # Rank Query ID Response time Calls R/Call V/M Item # ==== ================== ============== ===== ====== ===== ============== # 1 0x6C0C2937AEF1D27C 56.1986 100.0% 6 9.3664 1.08 DELETE Ranking # 2 0xE0735FE2ADE92491 0.0008 0.0% 2 0.0004 0.00 DELETE Rank # Query 1: 0.00 QPS, 0.03x concurrency, ID 0x6C0C2937AEF1D27C at byte 5162025 # This item is included in the report because it matches --limit. # Scores: V/M = 1.08 # Time range: 2016-12-27 00:00:28 to 00:30:35 # Attribute pct total min max avg 95% stddev median # ============ === ======= ======= ======= ======= ======= ======= ======= # Count 75 6 # Exec time 99 56s 5s 16s 9s 15s 3s 10s # Lock time 99 9s 20us 9s 2s 9s 3s 37us # Rows sent 0 0 0 0 0 0 0 0 # Rows examine 100 2.52M 241.92k 657.18k 430.55k 650.62k 142.45k 487.82k # Query size 66 336 56 56 56 56 0 56 # String: # Databases Zipai # Hosts 192.168.85.129 # Users root # Query_time distribution # 1us # 10us # 100us # 1ms # 10ms # 100ms # 1s ################################################################ # 10s+ ################################ # Tables # SHOW TABLE STATUS FROM `Zipai` LIKE 'Ranking'G # SHOW CREATE TABLE `Zipai`.`Ranking`G delete from Ranking where eventTypeID=2 and rankTypeID=7G # Converted for EXPLAIN # EXPLAIN /*!50100 PARTITIONS*/ select * from Ranking where eventTypeID=2 and rankTypeID=7G # Query 2: 0 QPS, 0x concurrency, ID 0xE0735FE2ADE92491 at byte 5183064 __ # This item is included in the report because it matches --limit. # Scores: V/M = 0.00 # Time range: all events occurred at 2016-12-27 00:02:00 # Attribute pct total min max avg 95% stddev median # ============ === ======= ======= ======= ======= ======= ======= ======= # Count 25 2 # Exec time 0 827us 256us 571us 413us 571us 222us 413us # Lock time 0 730us 205us 525us 365us 525us 226us 365us # Rows sent 0 0 0 0 0 0 0 0 # Rows examine 0 0 0 0 0 0 0 0 # Query size 33 168 84 84 84 84 0 84 # String: # Databases Zipai (1/50%), test_db (1/50%) # Hosts % # Users root # Query_time distribution # 1us # 10us # 100us ################################################################ # 1ms # 10ms # 100ms # 1s # 10s+ # Tables # SHOW TABLE STATUS FROM `Zipai` LIKE 'Rank'G # SHOW CREATE TABLE `Zipai`.`Rank`G delete from Rank where typeID=16 or typeID=17 or typeID=13 or typeID=14 or typeID=15G # Converted for EXPLAIN # EXPLAIN /*!50100 PARTITIONS*/ select * from Rank where typeID=16 or typeID=17 or typeID=13 or typeID=14 or typeID=15G
3.1、总体统计结果
第一行:此工具执行日志分析时的所用时间、内存资源(rss物理内存占用大小,vsz虚拟内存占用大小)
第二行:分析时的系统时间
第三行:进行分析的主机名,非记录日志的数据库服务器
第四行:分析的日志文件名称
第五行:文件中总共的语句数量(Overall 8),唯一的语句数量(对语句进行了格式化,unique 2),QPS,并发数
Time range:查询执行的时间范围
total:总计; min:最小; max:最大; avg:平均;95%:把所有值从小到大排列,位置位于95%的那个数,这个数一般最具有参考价值;median:中位数,把所有值从小到大排列,位置位于中间那个数
Exec time:语句执行时间;Lock time:锁占有时间;Rows sent:发送到客户端的行数;Row examine:扫描的行数;Query size:查询语句的字符数
3.2、查询分组统计结果
Response time:总的响应时间以及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
Item:查询对象
3.3、每一种查询的详细统计结果
最上面的表格列出了百分比、总计、最大、最小、平均、95%等各项目的统计
Databases:库名
Users:用户
Query_time distribution:查询时间分布, 长短体现区间占比,本例中1s-10s之间查询数量是10s以上的两倍
Tables:查询中涉及到的表
Explain:示例,非select语句会转换为select语句
14:43 2017/6/20 补充
# 参数说明 --limit 95%:20 --outliers Query_time:1:10
limit默认返回前20条或者总响应时间占比(从大到小)累计达到95%(取最先满足的)最差的查询;outliers默认返回95%栏位的Query_time>=1秒,且执行次数>=10次。最终结果是取limit和outliers的并集。这也就是为什么显示指定limit参数,返回的结果并不全满足limit参数,还会返回匹配outliers的结果。
如果使用了--limit或(和)--outliers参数,在返回结果的第二部分"查询分组统计结果",rank的最末行是MISC,代表那些没有计算入内的查询统计结果。详细内容参考官方文档pt-query-digest.