##感谢
前言
shell 中执行 mysql 命令
各项巡检命令
shell 脚本实现
在系统运行的过程中,DBA需要经常的对数据库进行一些检查,如数据库磁盘的占用量,缓存的命中率,内存的分配等;由于有个客户需要对系统的数据库进行检查,所以进行了一些学习,在此记录下;由于不可能让用户手动的输入这些繁琐的命令,所以写了个 shell 脚本。
在 shell 脚本中,去链接数据库,并执行相关的命令的步骤如下:
首先使用 touch 命令创建个文件, 使用 chmod 赋给这个文件执行权限
在文件中输入如下shell:
#!/bin/bash
host="127.0.0.1" #数据库IP
port="3306" #数据库端口
userName="root" #用户名
password="root" #密码
dbname="dbname" #数据库 名称
dbset="--default-character-set=utf8 -A" # 字符集
cmd="show variables like ‘%datadir%‘;"
/home/mysql/bin/mysql -h${host} -u${userName} -p${password} ${dbname} -P${port} -e "${cmd}")
如果要一次执行多个命令,则直接写多条命令就可以了,但是记得要换行,如下所示:
cmd2="show variables like ‘%datadir%‘;
show tables;
show databases;"
/home/mysql/bin/mysql -h${host} -u${userName} -p${password} ${dbname} -P${port} -e "${cmd}")
有时候需要知道mysql数据文件的存放位置,此时,可以使用 datadir 变量查看,命令如下:
进入到MySQL的bin目录下,执行如下命令来登陆mysql
./mysql -h127.0.0.1 -uroot -proot
然后执行 show variables like ‘%datadir%‘; 或者 elect @@datadir; 命令查看数据文件的存放路径:
#!/bin/bash
host="127.0.0.1" #数据库IP
port="3306" #数据库端口
userName="root" #用户名
password="root" #密码
dbname="dbname" #数据库 名称
dbset="--default-character-set=utf8 -A" # 字符集
datadir="show variables like ‘%datadir%‘;"
datadir_val=$(/home/mysql/bin/mysql -h${host} -u${userName} -p${password} ${dbname} -P${port} -e "${datadir}")
echo "mysql 数据文件存放位置:" `echo ${datadir_val} | cut -d‘ ‘ -f4`
其中,“cut -d‘ ‘ -f4” 意思是获取到字符串按照空格(‘ ’)进行分割,然后取第 4 个;
在MySQL中,要统计执行次数最大的SQL ,需要开启慢查询,通过慢查询日志进行统计,
查看是否开启慢查询日志命令:
show variables like ‘%slow_query%‘;
其中,slow_query_log
表示是否开启慢查询,OFF
表示未开启,ON
表示开启。slow_query_log_file
表示慢查询日志的路径。
开启慢查询日志
set global slow_query_log=ON;
慢查询是指SQL的执行时间超过一定的秒数之后才算是慢查询,这个时间默认是10秒,可以通过 long_query_time
变量查看,如下:
show variables like ‘%long_query_time%‘;
在测试的时候,可以把这个时间设置短一些,可以设置为1秒,0.1秒或者0.01秒都可以,通过如下命令设置:
set global long_query_time=秒数
当设置成功后,再次执行show variables like ‘%long_query_time%‘
;命令来查看发现还是10
秒,这时需要重新退出的,在进行登录,再查看就好了。
当开启慢查询日志后,就可以通过慢查询日志来分析执行次数最多的SQL了。
使用MySQL提供的 mysqldumpslow
工具来进行分析慢查询日志。mysqldumpslow
工具的主要功能是统计不同慢SQL的:
执行次数(count)
执行最长时间(time)
等待锁的时间(lock)
发送给客户端的总行数(rows)
进入到mysql的bin
目录下,执行 mysqldumpslow -help
来查看参数,如下:
-s:表示按照哪种方式进行排序,c, t, l, r, 分别表示按照执行次数,执行时间,等待锁时间和返回的记录数来排序,at, al, ar 分别按照平均执行时间,平均等待锁时间和平均发送行数进行排序。
-r:是前面排序的逆序
-t:top n 的意思,即返回排序后前面 n 条的数据
-g:正则匹配
现在可以通过该工具来统计执行次数最多的前 10 条SQL了,命令如下:
# -s c -t 10 表示按照执行次数排序,之后,取前10条
./mysqldumpslow -s c -t 10 /home/datas/mysql/data/R6-slow.log;
首先看下是否开启了查询缓存:
show variables like ‘%query_cache%‘;
其中 query_cache_type
为 ON
表示开启查询缓存,OFF
表示关闭缓存
query_cache_size
允许设置的值最小为40K,对于最大值则可以几乎认为无限制,但是,该值并不是越大, 查询缓存的命中率就越高,需要根据情况来定。
开启了查询缓存之后,接下来来看下缓存的相关选项说明:
执行查看命令:
show global status like ‘QCache%‘;
Qcache_free_blocks:目前还处于空闲状态的 Query Cache 中内存 Block 数目
Qcache_free_memory:目前还处于空闲状态的 Query Cache 内存总量
Qcache_hits:Query Cache 命中次数
Qcache_inserts:向 Query Cache 中插入新的 Query Cache 的次数,也就是没有命中的次数
Qcache_lowmem_prunes:当 Query Cache 内存容量不够,需要从中删除老的 Query Cache 以给新的 Cache 对象使用的次数
Qcache_not_cached:没有被 Cache 的 SQL 数,包括无法被 Cache 的 SQL 以及由于 query_cache_type 设置的不会被 7. Cache 的 SQL
Qcache_queries_in_cache:目前在 Query Cache 中的 SQL 数量
Qcache_total_blocks:Query Cache 中总的 Block 数量
此时可以根据这些值进行计算缓存的命中率和缓存的内存使用率
公式:
查询缓存命中率 ≈ (Qcache_hits – Qcache_inserts) / Qcache_hits * 100%
查询缓存内存使用率 ≈ (query_cache_size – Qcache_free_memory) / query_cache_size * 100%
#!/bin/bash
host="127.0.0.1" #数据库IP
port="3306" #数据库端口
userName="root" #用户名
password="root" #密码
dbname="dbname" #数据库 名称
dbset="--default-character-set=utf8 -A" # 字符集
cache_hits="show global status like ‘QCache_hits‘;"
hits=$(/home/mysql/bin/mysql -h${host} -u${userName} -p${password} ${dbname} -P${port} -e "${cache_hits}")
hits_val=`echo ${hits} | cut -d‘ ‘ -f4`
echo "缓存命中次数:" ${hits_val}
cache_not_hits="show global status like ‘Qcache_inserts‘;"
not_hits=$(/home/mysql/bin/mysql -h${host} -u${userName} -p${password} ${dbname} -P${port} -e "${cache_not_hits}")
not_hits_val=`echo ${not_hits} | cut -d‘ ‘ -f4`
echo "缓存未命中次数:" ${not_hits_val}
cache_hits_rate_1=$(($hits_val - $not_hits_val))
cache_hits_rate_2=`echo | awk "{print $cache_hits_rate_1/$hits_val * 100}"`
echo "缓存命中率:" ${cache_hits_rate_2} "%"
执行该脚本,如下所示:
查询等待事件相关的需要通过 performance_schema
来进行统计,MySQL的 performance schema
主要用于监控MySQL server在一个较低级别的运行过程中的资源消耗、资源等待等.
关于
performance_schema
的介绍,可以参考 https://mp.weixin.qq.com/s?__biz=MzU0MTczNzA1OA==&mid=2247483711&idx=1&sn=aef31942ae6294053cddc0ba83630597&chksm=fb242832cc53a12477febfb309aa5ed9c4c5652a7dafee28ac32ce81a214a0fd72758ff045e9&scene=21#wechat_redirect,介绍得比较详细。
统计 top 10 的等待事件 SQL 如下:
select event_name, count_star, sum_timer_wait from performance_schema.events_waits_summary_by_user_by_event_name where count_star > 0 order by sum_timer_wait desc limit 10;
#!/bin/bash
host="127.0.0.1" #数据库IP
port="3306" #数据库端口
userName="root" #用户名
password="root" #密码
dbname="dbname" #数据库 名称
dbset="--default-character-set=utf8 -A" # 字符集
top_event_10="select event_name, count_star, sum_timer_wait from performance_schema.events_waits_summary_global_by_event_name where count_star > 0 order by sum_timer_wait desc limit 10;"
echo "等待事件 TOP 10:"
/home/mysql/bin/mysql -h${host} -u${userName} -p${password} ${dbname} -P${port} -e "${top_event_10}"
可以通过查看相关的变量来查看mysql内存 分配:
show variables like ‘innodb_buffer_pool_size‘; //InnoDB 数据和索引缓存
show variables like ‘innodb_log_buffer_size‘; // InnoDB 日志缓冲区
show variables like ‘binlog_cache_size‘; // 二进制日志缓冲区
show variables like ‘thread_cache_size‘; // 连接线程缓存
show variables like ‘query_cache_size‘; // 查询缓存
show variables like ‘table_open_cache‘; // 表缓存
show variables like ‘table_definition_cache‘; // 表定义信息缓存
show variables like ‘max_connections‘; // 最大线程数
show variables like ‘thread_stack‘; // 线程栈信息使用内存
show variables like ‘sort_buffer_size‘; // 排序使用内存
show variables like ‘join_buffer_size‘; // Join操作使用内存
show variables like ‘read_buffer_size‘; // 顺序读取数据缓冲区使用内存
show variables like ‘read_rnd_buffer_size‘; // 随机读取数据缓冲区使用内存
show variables like ‘tmp_table_size‘; // 临时表使用内存
除了使用 show variables
的方式。还可以使用 select @@xxx
的方式:
#!/bin/bash
host="127.0.0.1" #数据库IP
port="3306" #数据库端口
userName="root" #用户名
password="root" #密码
dbname="dbname" #数据库 名称
dbset="--default-character-set=utf8 -A" # 字符集
echo "================= 内存配置情况 ==============================="
mem_dis_1="show variables like ‘innodb_buffer_pool_size‘;"
mem_dis_1_val=$(/home/mysql/bin/mysql -h${host} -u${userName} -p${password} ${dbname} -P${port} -e "${mem_dis_1}")
mem_dis_1_val_1=`echo ${mem_dis_1_val} | cut -d‘ ‘ -f4`
mem_dis_1_val_2=`echo | awk "{print $mem_dis_1_val_1/1024/1024}"`
echo "InnoDB 数据和索引缓存:" $mem_dis_1_val_1
mem_dis_2="show variables like ‘innodb_log_buffer_size‘;"
mem_dis_2_val=$(/home/mysql/bin/mysql -h${host} -u${userName} -p${password} ${dbname} -P${port} -e "${mem_dis_2}")
mem_dis_2_val_1=`echo ${mem_dis_2_val} | cut -d‘ ‘ -f4`
mem_dis_2_val_2=`echo | awk "{print $mem_dis_2_val_1/1024/1024}"`
echo "InnoDB 日志缓冲区:" $mem_dis_2_val_1
mem_dis_3="show variables like ‘binlog_cache_size‘;"
mem_dis_3_val=$(/home/mysql/bin/mysql -h${host} -u${userName} -p${password} ${dbname} -P${port} -e "${mem_dis_3}")
mem_dis_3_val_1=`echo ${mem_dis_3_val} | cut -d‘ ‘ -f4`
mem_dis_3_val_2=`echo | awk "{print $mem_dis_3_val_1/1024/1024}"`
echo "二进制日志缓冲区:" $mem_dis_3_val_1
mem_dis_4="show variables like ‘thread_cache_size‘;"
mem_dis_4_val=$(/home/mysql/bin/mysql -h${host} -u${userName} -p${password} ${dbname} -P${port} -e "${mem_dis_4}")
echo "连接线程缓存:" `echo $mem_dis_4_val | cut -d‘ ‘ -f4`
mem_dis_5="show variables like ‘query_cache_size‘;"
mem_dis_5_val=$(/home/mysql/bin/mysql -h${host} -u${userName} -p${password} ${dbname} -P${port} -e "${mem_dis_5}")
echo "查询缓存:" `echo ${mem_dis_5_val} | cut -d‘ ‘ -f4`
mem_dis_6="show variables like ‘table_open_cache‘;"
mem_dis_6_val=$(/home/mysql/bin/mysql -h${host} -u${userName} -p${password} ${dbname} -P${port} -e "${mem_dis_6}")
echo "表缓存:" `echo ${mem_dis_6_val} | cut -d‘ ‘ -f4`
mem_dis_7="show variables like ‘table_definition_cache‘;"
mem_dis_7_val=$(/home/mysql/bin/mysql -h${host} -u${userName} -p${password} ${dbname} -P${port} -e "${mem_dis_7}")
echo "表定义缓存:" `echo ${mem_dis_7_val} | cut -d‘ ‘ -f4`
mem_dis_8="show variables like ‘max_connections‘;"
mem_dis_8_val=$(/home/mysql/bin/mysql -h${host} -u${userName} -p${password} ${dbname} -P${port} -e "${mem_dis_8}")
echo "最大线程数:" `echo ${mem_dis_8_val} | cut -d‘ ‘ -f4`
mem_dis_9="show variables like ‘thread_stack‘;"
mem_dis_9_val=$(/home/mysql/bin/mysql -h${host} -u${userName} -p${password} ${dbname} -P${port} -e "${mem_dis_9}")
echo "线程栈信息使用内存:" `echo ${mem_dis_9_val} | cut -d‘ ‘ -f4`
mem_dis_10="show variables like ‘sort_buffer_size‘;"
mem_dis_10_val=$(/home/mysql/bin/mysql -h${host} -u${userName} -p${password} ${dbname} -P${port} -e "${mem_dis_10}")
echo "排序使用内存:" `echo ${mem_dis_10_val} | cut -d‘ ‘ -f4`
mem_dis_11="show variables like ‘join_buffer_size‘;"
mem_dis_11_val=$(/home/mysql/bin/mysql -h${host} -u${userName} -p${password} ${dbname} -P${port} -e "${mem_dis_11}")
echo "Join操作使用内存:" `echo ${mem_dis_11_val} | cut -d‘ ‘ -f4`
mem_dis_12="show variables like ‘read_buffer_size‘;"
mem_dis_12_val=$(/home/mysql/bin/mysql -h${host} -u${userName} -p${password} ${dbname} -P${port} -e "${mem_dis_12}")
echo "顺序读取数据缓冲区使用内存:" `echo ${mem_dis_12_val} | cut -d‘ ‘ -f4`
mem_dis_13="show variables like ‘read_rnd_buffer_size‘;"
mem_dis_13_val=$(/home/mysql/bin/mysql -h${host} -u${userName} -p${password} ${dbname} -P${port} -e "${mem_dis_13}")
echo "随机读取数据缓冲区使用内存:" `echo ${mem_dis_13_val} | cut -d‘ ‘ -f4`
mem_dis_14="show variables like ‘tmp_table_size‘;"
mem_dis_14_val=$(/home/mysql/bin/mysql -h${host} -u${userName} -p${password} ${dbname} -P${port} -e "${mem_dis_14}")
echo "临时表使用内存:" `echo ${mem_dis_14_val} | cut -d‘ ‘ -f4`
执行??结果:
1.查询整个数据库的占用量
select sum((data_length+index_length)/1024/1024) m from information_schema.tables where table_schema="dbname";
2.某个表的占用量:
select (data_length+index_length)/1024/1024 M from information_schema.tables where table_schema="dbname" and table_name="table_name";
3.整个mysql server 所有数据库的磁盘用量
select table_schema, sum((data_length+index_length)/1024/1024) M from information_schema.tables where table_schema is not null group by table_schema;
host="127.0.0.1"
port="3306"
userName="root"
password="root"
dbname="dbname"
dbset="--default-character-set=utf8 -A"
echo "================= 数据库磁盘占用量 ==========================="
_disk_used="select sum((data_length+index_length)/1024/1024) M from information_schema.tables where table_schema=\"m_dp_eup\""
_disk_used_val=$(/home/mysql/bin/mysql -h${host} -u${userName} -p${password} ${dbname} -P${port} -e "${_disk_used}")
echo "磁盘占用量(单位:M):" `echo ${_disk_used_val} | cut -d‘ ‘ -f2`
当系统在运行中,mysql 可以会有一些异常,可以通过查看错误日志来分析。
查看mysql的错误日志文件:
show global variables like ‘log_error‘;
#或
select @@log_error;
使用 grep 命令查找错误信息输出到文件:
grep ‘error‘ ./mysql.err* > error.log 或 egrep -i ‘error|Failed‘ ./mysqld.err* > error.log
如下想根据时间来过滤,则可以在后面加上日期就可以了
grep -i -E ‘error‘ ./mysqld.err* | grep -E ‘2019-03-28|2019-06-14‘ > error.log
查看最近一周的错误日志文件中是否有错误
_time=$(date -d ‘6 days ago‘ +%Y-%m-%d)\|$(date -d ‘5 days ago‘ +%Y-%m-%d)\|$(date -d ‘4 days ago‘ +%Y-%m-%d)\|$(date -d ‘3 days ago‘ +%Y-%m-%d)\|$(date -d ‘2 days ago‘ +%Y-%m-%d)\|$(date -d ‘1 days ago‘ +%Y-%m-%d)\|$(date -d ‘0 days ago‘ +%Y-%m-%d)
echo "==================最近一周的错误日志 =========================="
#grep -i -E ‘error‘ /home/logs/mysql/mysqld.err* | grep -E ‘2019-03-28|2019-06-14‘
grep -i -E ‘error‘ /home/logs/mysql/mysql.err*| grep -E \‘$_time\‘
_time 是获取最近一周的日期,形如:‘2019-06-13|2019-06-14|………………………‘
当然还有很多的检查项,这里就不一一列出来了。
以上就是一些检查项及其 shell 脚本的实现
###如果是5.6 以及56.以下版本的mysql , 最好能建立sys database;
https://github.com/mysql/mysql-sys
安装方法如下:
A collection of views, functions and procedures to help MySQL administrators get insight in to MySQL Database usage.
There are install files available for 5.6 and 5.7 respectively. To load these, you must position yourself within the directory that you downloaded to, as these top level files SOURCE individual files that are shared across versions in most cases (though not all).
The objects should all be created as the root user (but run with the privileges of the invoker).
For instance if you download to /tmp/mysql-sys/, and want to install the 5.6 version you should:
cd /tmp/mysql-sys/
mysql -u root -p < ./sys_56.sql
Or if you would like to log in to the client, and install the 5.7 version:
cd /tmp/mysql-sys/
mysql -u root -p
SOURCE ./sys_57.sql
Alternatively, you could just choose to load individual files based on your needs, but beware, certain objects have dependencies on other objects. You will need to ensure that these are also loaded.
###########sample
4.1巡检报告里有一个项目
26.4.3.11 The io_global_by_file_by_bytes and x$io_global_by_file_by_bytes Views
These views summarize global I/O consumers to display amount of I/O, grouped by file. By default, rows are sorted by descending total I/O (bytes read and written).
The io_global_by_file_by_bytes and x$io_global_by_file_by_bytes views have these columns:
file
The file path name.
count_read
The total number of read events for the file.
total_read
The total number of bytes read from the file.
avg_read
The average number of bytes per read from the file.
count_write
The total number of write events for the file.
total_written
The total number of bytes written to the file.
avg_write
The average number of bytes per write to the file.
total
The total number of bytes read and written for the file.
write_pct
The percentage of total bytes of I/O that were writes.
4.3 实例输出如下:
file | count_read | total_read | avg_read | count_write | total_written | avg_write | total | write_pct |
---|---|---|---|---|---|---|---|---|
/db/mysql/data/mydata/ibdata1 | 7872 | 131039232 | 16646.2439 | 2120577 | 62741856256 | 29587.1625 | 62872895488 | 99.79 |
/db/mysql/data/mydata/scheduled/triggers.ibd | 185 | 3031040 | 16384.0000 | 193640 | 4465164288 | 23059.1008 | 4468195328 | 99.93 |
解释如下: /db/mysql/data/mydata/ibdata1 文件 total_written is 62741856256 bytes. 并且 avg_write is 29587.1625 bytes
.ibd 文件解释参考https://www.cnblogs.com/feiyun8616/p/12893443.html
##### sample 3.4 TOP SQL 采集自 x$statement_analysis
db | exec_count | query | full_scan | avg_latency |
---|---|---|---|---|
NULL | 639206 | SET `autocommit` = ? | 89.64 us | |
NULL | 637710 | SET NAMES `utf8` | 103.61 us | |
lepus | 469714 | SELECT `first_seen` , `last_se ... ry_review` WHERE CHECKSUM = ? | * | 286.88 us |
lepus | 469714 | INSERT INTO `lepus` . `mysql_s ... COALESCE ( ? , NOW ( ) ) ) ) | 5.62 ms |
解释如下:
该段是根据 exec_count 进行排序的,full_scan 这一列是 是否使用全表扫描,avg_latency 是平均每次的执行的等待时间。
具体时间解释如下:
us是微西门子,ms是毫西门子,都是电导的单e68a84e799bee5baa6e997aee7ad9431333366303838位。
S是电导率的单位“西门子”,m(毫)、u(实际是μ,希腊字母“缪”,表示“微”,10的-6次方)是数量级词头。
1s=1000ms
1ms=1000us
1us=1000ns
26.4.3.35 The statement_analysis and x$statement_analysis Views
These views list normalized statements with aggregated statistics. The content mimics the MySQL Enterprise Monitor Query Analysis view. By default, rows are sorted by descending total latency.
The statement_analysis and x$statement_analysis views have these columns:
query
The normalized statement string.
db
The default database for the statement, or NULL if there is none.
full_scan
The total number of full table scans performed by occurrences of the statement.
exec_count
The total number of times the statement has executed.
err_count
The total number of errors produced by occurrences of the statement.
warn_count
The total number of warnings produced by occurrences of the statement.
total_latency
The total wait time of timed occurrences of the statement.
max_latency
The maximum single wait time of timed occurrences of the statement.
avg_latency
The average wait time per timed occurrence of the statement.
lock_latency
The total time waiting for locks by timed occurrences of the statement.
rows_sent
The total number of rows returned by occurrences of the statement.
rows_sent_avg
The average number of rows returned per occurrence of the statement.
rows_examined
The total number of rows read from storage engines by occurrences of the statement.
rows_examined_avg
The average number of rows read from storage engines per occurrence of the statement.
rows_affected
The total number of rows affected by occurrences of the statement.
rows_affected_avg
The average number of rows affected per occurrence of the statement.
tmp_tables
The total number of internal in-memory temporary tables created by occurrences of the statement.
tmp_disk_tables
The total number of internal on-disk temporary tables created by occurrences of the statement.
rows_sorted
The total number of rows sorted by occurrences of the statement.
sort_merge_passes
The total number of sort merge passes by occurrences of the statement.
digest
The statement digest.
first_seen
The time at which the statement was first seen.
last_seen
The time at which the statement was most recently seen.
####sample
还有一段来自performance_schema.events_waits_summary_global_by_event_name
event_name | count_star | sum_timer_wait |
---|---|---|
idle | 23106328 | 2135447869942725760 |
wait/io/table/sql/handler | 94658377684 | 987399391349498508 |
sql/handle 这个等待事件,总等待次数为 94658377684次,总等待事件为987399391349498508 皮秒(约为987399 秒)
273238183964000皮秒(1000000000000皮秒=1秒) 12个0
select event_name, count_star, sum_timer_wait from performance_schema.events_waits_summary_global_by_event_name
events_waits_summary_global_by_event_name has an EVENT_NAME column. Each row summarizes events for a given event name. An instrument might be used to create multiple instances of the instrumented object. For example, if there is an instrument for a mutex that is created for each connection, there are as many instances as there are connections. The summary row for the instrument summarizes over all these instances.
Each wait event summary table has these summary columns containing aggregated values:
COUNT_STAR
The number of summarized events. This value includes all events, whether timed or nontimed.
SUM_TIMER_WAIT
The total wait time of the summarized timed events. This value is calculated only for timed events because nontimed events have a wait time of NULL. The same is true for the other xxx_TIMER_WAIT values.
MIN_TIMER_WAIT
The minimum wait time of the summarized timed events.
AVG_TIMER_WAIT 皮秒为单位(1000000000000皮秒=1秒)
The average wait time of the summarized timed events.
MAX_TIMER_WAIT
The maximum wait time of the summarized timed events.
感谢 zhoujinyi/
zjy@performance_schema 11:36:28>SELECT SCHEMA_NAME,DIGEST_TEXT,COUNT_STAR,AVG_TIMER_WAIT,SUM_ROWS_SENT,SUM_ROWS_EXAMINED,FIRST_SEEN,LAST_SEEN FROM events_statements_summary_by_digest ORDER BY AVG_TIMER_WAIT desc LIMIT 1\G
*************************** 1. row ***************************
SCHEMA_NAME: dchat
DIGEST_TEXT: SELECT ...
COUNT_STAR: 1
AVG_TIMER_WAIT: 273238183964000
SUM_ROWS_SENT: 50208
SUM_ROWS_EXAMINED: 5565651
FIRST_SEEN: 2016-02-22 13:27:33
LAST_SEEN: 2016-02-22 13:27:33
复制代码
https://www.cnblogs.com/zhoujinyi/p/5236705.html
原文:https://www.cnblogs.com/chaochang/p/13958168.html