慢查询与pt-query-digest使用
如果你发现系统中mysql的cpu占用很高，有可能是系统上有慢查询，通过mysql的慢查询确认嫌疑sql非常有必要
怎么查慢查询?
– 查看慢查询配置
show VARIABLES LIKE ‘slow%’;
slow_launch_time 2
slow_query_log ON
slow_query_log_file /alidata/server/mysql/data/1.log– 多长时间的会被记录为慢查询
SHOW VARIABLES LIKE ‘long_query_time’;
– 设置慢查询的参数
set global slow_query_log = ON;
set global long_query_time = 5;
set global slow_query_log_file = ‘/alidata/server/mysql/data/1.log’;
找到慢查询的 服务器路径，
比如：
tail -11f /alidata/server/mysql/data/1.log
# Time: 170217 22:25:46
# User@Host: root[root] @ [223.73.113.210]
# Query_time: 9.048088 Lock_time: 0.000093 Rows_sent: 8964 Rows_examined: 2809648
SET timestamp=1487341546;
SELECT * FROM mtest where major_name='商务英语';
# Time: 170217 22:28:25
# User@Host: root[root] @ [223.73.113.210]
# Query_time: 8.462414 Lock_time: 0.000102 Rows_sent: 8964 Rows_examined: 2809648
SET timestamp=1487341705;
SELECT * FROM mtest where major_name='商务英语';
# Time: 170217 22:31:44
# User@Host: root[root] @ [223.73.113.210]
# Query_time: 9.137539 Lock_time: 0.000080 Rows_sent: 8964 Rows_examined: 2809648
SET timestamp=1487341904;
SELECT * FROM mtest where major_name='商务英语';针对 查出来的慢查询进行优化配置，比如 缺少索引了
tp-query-digest 怎么安装?
tp-query-digest 是 Percona Toolkit 的其中一个工具,官网在https://www.percona.com/downloads/percona-toolkit/
这边服务器是ubuntu ，下载deb包安装
sudo dpkg -i percona-toolkit.deb，有不少依赖，一个个搞定
perl 要5.20,但服务器是 5.14……..
更新perl,试了2个多钟还是搞不定，最后，下载了低版本Percona Toolkit, percona-toolkit_2.0.3_all.deb
用tp-query-digest 怎么使用?
pt-query-digest /alidata/server/mysql/data/1.log
# 250ms user time, 20ms system time, 21.62M rss, 66.34M vsz
# Current date: Sat Feb 18 17:30:59 2017
# Hostname: iZ28gy61tjeZ
# Files: /alidata/server/mysql/data/1.log
# Overall: 102 total, 1 unique, 0.09 QPS, 0.84x concurrency ______________
# Time range: 2017-02-18 14:28:23 to 14:46:50
# Attribute total min max avg 95% stddev median
# ============ ======= ======= ======= ======= ======= ======= =======
# Exec time 925s 9s 14s 9s 9s 784ms 8s
# Lock time 9ms 70us 130us 84us 103us 11us 80us
# Rows sent 892.53k 8.38k 8.75k 8.75k 8.46k 40.66 8.46k
# Rows examine 273.25M 2.62M 2.68M 2.68M 2.62M 0.04 2.62M
# Query size 5.08k 51 51 51 51 0 51
# Profile
# Rank Query ID Response time Calls R/Call Apdx V/M Item
# ==== ================== =============== ===== ====== ==== ===== ========
# 1 0x07B4534FA3E77537 925.4291 100.0% 102 9.0728 0.00 0.07 SELECT mtest
# Query 1: 0.09 QPS, 0.84x concurrency, ID 0x07B4534FA3E77537 at byte 21684
# This item is included in the report because it matches --limit.
# Scores: Apdex = 0.00 [1.0], V/M = 0.07
# Query_time sparkline: | ^_|
# Time range: 2017-02-18 14:28:23 to 14:46:50
# Attribute pct total min max avg 95% stddev median
# ============ === ======= ======= ======= ======= ======= ======= =======
# Count 100 102
# Exec time 100 925s 9s 14s 9s 9s 784ms 8s
# Lock time 100 9ms 70us 130us 84us 103us 11us 80us
# Rows sent 100 892.53k 8.38k 8.75k 8.75k 8.46k 40.66 8.46k
# Rows examine 100 273.25M 2.62M 2.68M 2.68M 2.62M 0.04 2.62M
# Query size 100 5.08k 51 51 51 51 0 51
# String:
# Databases channel
# Hosts
# Users root
# Query_time distribution
# 1us
# 10us
# 100us
# 1ms
# 10ms
# 100ms
# 1s ################################################################
# 10s+ ##
# Tables
# SHOW TABLE STATUS FROM `channel` LIKE 'mtest'\G
# SHOW CREATE TABLE `channel`.`mtest`\G
# EXPLAIN /*!50100 PARTITIONS*/
SELECT * FROM mtest where major_name='商务英è¯'\G后记
上面是工具分析的结果，可以做个参考,个人觉得 慢查询本身的日志已经能提供很多信息了，