Example analysis of usage records of pt-query-digest tool in MySQL

This article brings you relevant knowledge about mysql. It mainly introduces a tool pt-query-digest for analyzing mysql slow query logs. Let’s take a look at it together. I hope it will be helpful to everyone.

1. Introduction

pt-query-digest is a tool used to analyze mysql slow query logs. It can also analyze queries from "SHOW PROCESSLIST" and MySQL Protocol data in tcpdump. We can output the analysis log to a specified file and perform corresponding optimization and other operations by analyzing the log file.

2. Download and install

• Install according to different systems. My system is centos, so I directly choose centos installation,Click to download
• Use yum to install directly

> wget https://downloads.percona.com/downloads/percona-toolkit/3.4.0/binary/redhat/7/x86_64/percona-toolkit-3.4.0-3.el7.x86_64.rpm > yum install percona-toolkit-3.4.0-3.el7.x86_64.rpm

• Or use the source code package to compile and install

> wget https://downloads.percona.com/downloads/percona-toolkit/3.4.0/source/debian/percona-toolkit-3.4.0.tar.gz > tar -zxvf percona-toolkit-3.4.0.tar.gz > cd percona-toolkit-3.4.0 > perl Makefile.PL PREFIX=/usr/local/percona-toolkit > make && make install

3. Installation completed

##4. Analysis of msql’s slow query log

pt-query-digest The parameters can be viewed using the perldoc command

perldoc /usr/bin/pt-query-digest

pt-query-digest mysql-slow.log > slow_report.log

pt-query-digest mysql-slow.log --since '2022-10-01 00:00:00' --until '2022-11-05 00:00:00' > slow_report_date_20221021-202221105.log

pt-query-digest --user=root --password=123456 --history h=192.168.33.10,D=local_test_db,t=query_review --create-history-table mysql-slow.log --since '2022-11-01 00:00:00' --until '2022-11-05 00:00:00'

5. Result Analysis

• Overall: How many queries are there in total

• Time range: The time range of query execution

• unique: The number of unique queries, that is, how many different queries there are after parameterizing the query conditions

• total: Total duration of all queries

• min: Minimum duration of all queries

• max: All Maximum query duration

• avg: Average query duration

• 95%: Arrange all duration values from small to large, and the position is at 95% That duration number, this number generally has the most reference value

• median: Median, arranges all duration values from small to large, and the duration number located in the middle

# A software update is available: # 23.7s user time, 15.8s system time, 35.67M rss, 249.01M vsz 说明： 执行过程中，在用户中所花费的所有时间 执行过程中，在内核空间中所花费的所有时间 pt-query-digest 进程所分配的内存大小 pt-query-digest 进程所分配的虚拟内存大小 # Current date: Mon Nov 7 09:01:23 2022 说明：当前时间 # Hostname: localhost.localdomain 说明：执行pt-query-digest的主机名 # Files: mysql-slow.log 说明：被分析的文件名称 # Overall: 44.78k total, 54 unique, 0.01 QPS, 0.07x concurrency __________ 说明： total: 语句总数量 unique: 唯一语句数量 QPS: 每秒查询量 concurrency: 查询的并发 # Time range: 2022-10-01 00:00:03 to 2022-11-04 16:05:24 说明：执行过程中日志记录的时间范围 # Attribute total min max avg 95% stddev median 说明：属性 总计 最小值 最大值 平均值 95% 标准差 中位数 95%： 把所有时长值从小到大排列，位置位于 95% 的那个时长数，这个数一般最具有参考价值 median： 中位数，把所有时长值从小到大排列，位置位于中间那个时长数 # ============ ======= ======= ======= ======= ======= ======= ======= # Exec time 204553s 3s 1540s 5s 10s 8s 3s 说明：执行时间 # Lock time 8s 0 107ms 186us 80us 2ms 36us 说明：锁占用时间 # Rows sent 238.87M 0 2.88M 5.46k 11.95 68.22k 0.99 说明：发送到客户端的行数 # Rows examine 73.56G 0 5.01M 1.68M 3.86M 724.49k 1.32M 说明：扫描的语句行数 # Query size 8.18M 30 4.36k 191.46 511.45 224.63 72.65 说明：查询的字符数

• Rank: Ranking of all statements, by default arranged in descending order of query time, specified by –order-by
  –order-by Query_time:sum: Sort by total query time in reverse order
  • Sort parameter introduction:
    sum Sum/total attribute value (default value)
    min Minimum attribute value (minimum value)
    max Maximum attribute value (minimum value)
    cnt Frequency/count of the query (by the number of times sql appears)
    
• Query ID: statement ID (remove extra spaces and text characters, calculate hash value)

• Response: Total response time

• time: The query is in this The total time proportion in this analysis

• Calls: the number of executions, that is, the total number of query statements of this type in this analysis

• R/Call: Average response time per execution

• V/M: Ratio of response time Variance-to-mean

• Item : Query object

# Profile 说明：分析 # Rank Query ID Response time Calls R/Call # ==== =================================== ================ ===== ======= # 1 0xC000AA97F210B2AEAE4933AF9B00296A 104236.2061 5... 30988 3.3638 0.03 SELECT xxx # 2 0x974C6E6D54DB8B0DF505CA7BDC508686 32167.9607 15.7% 3418 9.4113 1.34 SELECT xxx # 3 0x6BE180C5804B585F25BB16550447DC6C 18453.0185 9.0% 2499 7.3842 0.92 SELECT xxx # 4 0xADF16E3E9EB5D6B08245E39FF1428C9F 17873.4338 8.7% 3114 5.7397 0.84 SELECT xxx # 5 0x2964CD629A24595719659BDAEBCF0E6F 10648.5404 5.2% 1437 7.4103 0.93 SELECT xxx # 6 0x50566E6DCF8FA562B88AE41AB1E32DC6 7424.3855 3.6% 303 24.5029 15.41 SELECT xxx # 7 0xDB0A3D60F85C2212C476B144E1678AB8 5327.8370 2.6% 1627 3.2746 0.05 SELECT xxx # 8 0x04BB0B332CEED517298AB06DE2A30AD6 3190.6822 1.6% 657 4.8564 1.36 SELECT xxx # 10 0xDAB0AF524151C621DC0E9B92AC002C38 526.6288 0.3% 140 3.7616 0.01 SELECT xxx # MISC 0xMISC 1807.1067 0.9% 57 31.7036 0.0 <27 ITEMS>

• pct: A certain execution attribute of this SQL statement accounts for all slow queries Percentage of an execution attribute of the statement

• total: All attribute times of an execution attribute of the SQL statement.

• Count: The number of times the sql statement is executed. The corresponding pct indicates that the number of execution times of this SQL statement accounts for the % of the number of execution times of all slow query statements (69% in the figure below), and the corresponding total indicates that a total of 30988 times were executed.

• Exec time: sql execution time

• Lock time: The time when sql is locked during execution

• Rows sent: The valid data transmitted has a value only in the select query statement

• Rows examine: The total queried data, non-target data.

• Query_time distribution: Query time distribution

• SQL statement: The picture below is select sleep(7)\G

# Query 1: 0.01 QPS, 0.03x concurrency, ID 0xC000AA97F210B2AEAE4933AF9B00296A at byte 221452362 说明：查询队列1：每秒查询量，查询的并发，队列1的ID值，对应第二部分的Query ID, 221452362表示偏移量(查看方法看下面的“查看偏移”) # This item is included in the report because it matches --limit. # Scores: V/M = 0.03 # Time range: 2022-10-01 00:00:05 to 2022-11-04 16:05:24 说明：sql语句在慢日志文件mysql_slow.log出现的时间范围 # Attribute pct total min max avg 95% stddev median 说明：属性 占整个 总数 最小值 最大值 平均值 95% 标准差 中间值 分析中 的百分 比 # ============ === ======= ======= ======= ======= ======= ======= ======= # Count 69 30988 说明：执行语句总数量 # Exec time 50 104236s 3s 7s 3s 4s 303ms 3s 说明：执行时间 # Lock time 24 2s 22us 93ms 65us 66us 775us 38us 说明：锁占用时间 # Rows sent 0 70.53k 0 799 2.33 3.89 16.60 0.99 说明：发送到客户端的行数 # Rows examine 54 40.28G 1.32M 1.35M 1.33M 1.32M 15.65k 1.32M 说明：扫描语句的行数 # Query size 26 2.16M 73 73 73 73 0 73 说明：查询的字符数 # String: # Hosts localhost 说明：使用的数据主机IP # Users xxx 说明：使用的用户 # Query_time distribution # 1us # 10us # 100us # 1ms # 10ms # 100ms # 1s ################################################################ # 10s+ 说明：查询时间分布 # Tables # SHOW TABLE STATUS LIKE 'xxx'\G # SHOW CREATE TABLE `xxx`\G # EXPLAIN /*!50100 PARTITIONS*/ select * from `table_name` where `updated_at` >= '2022-10-15 00:00:40'\G 说明：查询的mysql语句 第三部分是每一种查询比较慢的 sql 的详细统计结果 pct：该 sql 语句某执行属性占所有慢查询语句某执行属性的百分比 total：该 sql 语句某执行属性的所有属性时间。 Count：sql 语句执行的次数。 Exec time：sql 执行时间 Lock time：sql 执行期间被

Six View Offset

You can use the offset to find the specific SQL statement in the slow query log file. The search method is as follows:

• [localhost]# tail -c +221452362 ./mysql-slow.log | head t: root[root] @ localhost [] Id: 13704150 # Query_time: 7.058835 Lock_time: 0.000040 Rows_sent: 2 Rows_examined: 1392521 SET timestamp=1665763267; select * from `xxxxxx` where `updated_at` >= '2022-10-15 00:00:40'; # User@Host: root[localhost] @ localhost [] Id: 13704174 # Query_time: 7.445741 Lock_time: 0.000015 Rows_sent: 3 Rows_examined: 2214002 SET timestamp=1665763267; select xxx from table where xxx # Time: 221015 008 # User@Host: root[localhost] @ localhost [] Id: 13704414

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