怎么理解MySQL5.6中的PERFORMANCE_SCHEM

本篇内容介绍了“怎么理解MySQL5.6中的PERFORMANCE_SCHEM”的有关知识，在实际案例的操作过程中，不少人都会遇到这样的困境，接下来就让小编带领大家学习一下如何处理这些情况吧！希望大家仔细阅读，能够学有所成！通过sql语句找到在经历什么等待事件!Statement -> stage -> wait的三级结构，通过nesting_event_id进行关联，它表示某个事件的父event_id。比如分析包含count(*)的某条SQL语句，具体如下：(类似于oracle的v$sql, v$sqlstat, v$sqlarea)SELECTEVENT_ID,sql_textFROM
events_statements_historyWHERE
sql_text
LIKE
‘%count(*)%’;+———-+————————————–+|
EVENT_ID
|
sql_text
|+———-+————————————–+| 1690
|
select
count(*)
from
chuck.test_slow
|+———-+————————————–+a.查看每个阶段的时间消耗：(类似于oracle的时间模型V$SYS_TIME_MODEL V$SESS_TIME_MODEL)SELECTevent_id,EVENT_NAME,SOURCE,TIMER_END
–
TIMER_STARTFROM
events_stages_history_longWHERE
NESTING_EVENT_ID
= 1690;+———-+——————————–+———————-+———————–+|
event_id
|
EVENT_NAME
|
SOURCE
|
TIMER_END-TIMER_START
|+———-+——————————–+———————-+———————–+……| 2647
|
stage/sql/Sending data
|
sql_executor.cc:192
| 7369072089000
|b.查看某个阶段的锁等待情况
(类似于oracle的v$session_wait)针对每个stage可能出现的锁等待，一个stage会对应一个或多个wait，events_waits_history_long这个表容易爆满[默认阀值10000]。由于select
count(*)需要IO(逻辑IO或者物理IO)，所以在stage/sql/Sending data阶段会有io等待的统计。通过stage_xxx表的event_id字段与waits_xxx表的nesting_event_id进行关联。SELECTevent_id,event_name,source,timer_wait,object_name,index_name,operation,nesting_event_idFROM
events_waits_history_longWHERE
nesting_event_id
= 2647;+———-+—————————+—————–+————+————-+————+———–+——————+|
event_id
|
event_name
|
source
|
timer_wait
|
object_name
|
index_name
|
operation
|
nesting_event_id
|+———-+—————————+—————–+————+————-+————+———–+——————+| 190607
|
wait/io/table/sql/handler
|
handler.cc:2842
| 1845888
|
test_slow
|
idx_c1
|
fetch
| 2647
|https://www.cnblogs.com/zhoujinyi/p/5236705.htmlMySQL5.6 PERFORMANCE_SCHEMA
说明 背景：
MySQL 5.5开始新增一个数据库：PERFORMANCE_SCHEMA，主要用于收集数据库服务器性能参数。并且库里表的存储引擎均为PERFORMANCE_SCHEMA，而用户是不能创建存储引擎为PERFORMANCE_SCHEMA的表。MySQL5.5默认是关闭的，需要手动开启，在配置文件里添加：[mysqld]performance_schema=ON查看是否开启：mysql>show variables
like
‘performance_schema’;+——————–+——-+|
Variable_name
|
Value
|+——————–+——-+|
performance_schema
| ON
|+——————–+——-+从MySQL5.6开始，默认打开，本文就从MySQL5.6来说明，在数据库使用当中PERFORMANCE_SCHEMA的一些比较常用的功能。具体的信息可以查看官方文档。相关表信息：一：配置（setup）表：zjy@performance_schema 10:16:56>show tables
like
‘%setup%’;+—————————————-+|
Tables_in_performance_schema (%setup%)
|+—————————————-+|
setup_actors
||
setup_consumers
||
setup_instruments
||
setup_objects
||
setup_timers
|+—————————————-+1，setup_actors：配置用户纬度的监控，默认监控所有用户。zjy@performance_schema 10:19:11>select
*
from
setup_actors;+——+——+——+|
HOST
|
USER
|
ROLE
|+——+——+——+|
%
|
%
|
%
|+——+——+——+2，setup_consumers：配置events的消费者类型，即收集的events写入到哪些统计表中。zjy@: performance_schema
10:23:35>select
*
from
setup_consumers;+——————————–+———+|
NAME
|
ENABLED
|+——————————–+———+|
events_stages_current
|
NO
||
events_stages_history
|
NO
||
events_stages_history_long
|
NO
||
events_statements_current
|
YES
||
events_statements_history
|
NO
||
events_statements_history_long
|
NO
||
events_waits_current
|
NO
||
events_waits_history
|
NO
||
events_waits_history_long
|
NO
||
global_instrumentation
|
YES
||
thread_instrumentation
|
YES
||
statements_digest
|
YES
|+——————————–+———+这里需要说明的是需要查看哪个就更新其ENABLED列为YES。如：zjy@performance_schema 10:25:02>update
setup_consumers
set
ENABLED=’YES’
where
NAME
in
(‘events_stages_current’,’events_waits_current’);Query OK,
2
rows affected (0.00
sec)更新完后立即生效，但是服务器重启之后又会变回默认值，要永久生效需要在配置文件里添加：[mysqld]#performance_schemaperformance_schema_consumer_events_waits_current=onperformance_schema_consumer_events_stages_current=onperformance_schema_consumer_events_statements_current=onperformance_schema_consumer_events_waits_history=onperformance_schema_consumer_events_stages_history=onperformance_schema_consumer_events_statements_history=on即在这些表的前面加上：performance_schema_consumer_xxx。表setup_consumers里面的值有个层级关系：global_instrumentation
> thread_instrumentation
= statements_digest
>
events_stages_current
=
events_statements_current
=
events_waits_current
>
events_stages_history
=
events_statements_history
=
events_waits_history
>
events_stages_history_long
=
events_statements_history_long
=
events_waits_history_long只有上一层次的为YES，才会继续检查该本层为YES or NO。global_instrumentation是最高级别consumer，如果它设置为NO，则所有的consumer都会忽略。其中history和history_long存的是current表的历史记录条数，history表记录了每个线程最近等待的10个事件，而history_long表则记录了最近所有线程产生的10000个事件，这里的10和10000都是可以配置的。这三个表表结构相同，history和history_long表数据都来源于current表。长度通过控制参数：zjy@performance_schema 11:10:03>show variables
like
‘performance_schema%history%size’;+——————————————————–+——-+|
Variable_name
|
Value
|+——————————————————–+——-+|
performance_schema_events_stages_history_long_size
| 10000
||
performance_schema_events_stages_history_size
| 10
||
performance_schema_events_statements_history_long_size
| 10000
||
performance_schema_events_statements_history_size
| 10
||
performance_schema_events_waits_history_long_size
| 10000
||
performance_schema_events_waits_history_size
| 10
|+——————————————————–+——-+3，setup_instruments：配置具体的instrument，主要包含4大类：idle、stage/xxx、statement/xxx、wait/xxx：zjy@performance_schema 10:56:35>select
name,count(*)
from
setup_instruments
group
by
LEFT(name,5);+———————————+———-+|
name |
count(*)
|+———————————+———-+|
idle
|
1
||
stage/sql/After
create
|
111
||
statement/sql/select
|
179
||
wait/synch/mutex/sql/PAGE::lock
|
296
|+———————————+———-+idle表示socket空闲的时间，stage类表示语句的每个执行阶段的统计，statement类统计语句维度的信息，wait类统计各种等待事件，比如IO，mutux，spin_lock,condition等。4，setup_objects：配置监控对象，默认对mysql，performance_schema和information_schema中的表都不监控，而其它DB的所有表都监控。zjy@performance_schema 11:00:18>select
*
from
setup_o开发云主机域名bjects;+————-+——————–+————-+———+——-+|
OBJECT_TYPE
|
OBJECT_SCHEMA
|
OBJECT_NAME
|
ENABLED
|
TIMED
|+————-+——————–+————-+———+——-+|
TABLE
|
mysql
|
%
|
NO
|
NO
||
TABLE
|
performance_schema
|
%
|
NO
|
NO
||
TABLE
|
information_schema
|
%
|
NO
|
NO
||
TABLE
|
%
|
%
| YES
| YES
|+————-+——————–+————-+———+——-+5，setup_timers：配置每种类型指令的统计时间单位。MICROSECOND表示统计单位是微妙，CYCLE表示统计单位是时钟周期，时间度量与CPU的主频有关，NANOSECOND表示统计单位是纳秒。但无论采用哪种度量单位，最终统计表中统计的时间都会装换到皮秒。（1秒＝1000000000000皮秒）zjy@performance_schema 11:05:12>select
*
from
setup_timers;+———–+————-+|
NAME
|
TIMER_NAME
|+———–+————-+|
idle
|
MICROSECOND
||
wait
|
CYCLE
||
stage
|
NANOSECOND
||
statement
|
NANOSECOND
|+———–+————-+二：instance表1，cond_instances：条件等待对象实例表中记录了系统中使用的条件变量的对象，OBJECT_INSTANCE_BEGIN为对象的内存地址。2，file_instances：文件实例表中记录了系统中打开了文件的对象，包括ibdata文件，redo文件，binlog文件，用户的表文件等，open_count显示当前文件打开的数目，如果重来没有打开过，不会出现在表中。zjy@performance_schema 11:20:04>select
*
from
file_instances limit
2,5;+———————————+————————————–+————+|
FILE_NAME
|
EVENT_NAME
| OPEN_COUNT
|+———————————+————————————–+————+|
/var/lib/mysql/mysql/plugin.frm
|
wait/io/file/sql/FRM
|

||
/var/lib/mysql/mysql/plugin.MYI
|
wait/io/file/myisam/kfile
|
1
||
/var/lib/mysql/mysql/plugin.MYD
|
wait/io/file/myisam/dfile
| 1
||
/var/lib/mysql/ibdata1
|
wait/io/file/innodb/innodb_data_file
|
2
||
/var/lib/mysql/ib_logfile0
|
wait/io/file/innodb/innodb_log_file
|
2
|+———————————+————————————–+————+3，mutex_instances：互斥同步对象实例表中记录了系统中使用互斥量对象的所有记录，其中name为：wait/synch/mutex/*。LOCKED_BY_THREAD_ID显示哪个线程正持有mutex，若没有线程持有，则为NULL。4，rwlock_instances：读写锁同步对象实例表中记录了系统中使用读写锁对象的所有记录，其中name为
wait/synch/rwlock/*。WRITE_LOCKED_BY_THREAD_ID为正在持有该对象的thread_id，若没有线程持有，则为NULL。READ_LOCKED_BY_COUNT为记录了同时有多少个读者持有读锁。（通过
events_waits_current
表可以知道，哪个线程在等待锁；通过rwlock_instances知道哪个线程持有锁。rwlock_instances的缺陷是，只能记录持有写锁的线程，对于读锁则无能为力）。5，socket_instances：活跃会话对象实例
表中记录了thread_id,socket_id,ip和port，其它表可以通过thread_id与socket_instance进行关联，获取IP-PORT信息，能够与应用对接起来。
event_name主要包含3类：
wait/io/socket/sql/server_unix_socket，服务端unix监听socket
wait/io/socket/sql/server_tcpip_socket，服务端tcp监听socket
wait/io/socket/sql/client_connection，客户端socket三：Wait表1，events_waits_current：记录了当前线程等待的事件2，events_waits_history：记录了每个线程最近等待的10个事件3，events_waits_history_long：记录了最近所有线程产生的10000个事件表结构定义如下：CREATE
TABLE
`events_waits_current` ( `THREAD_ID`
bigint(20) unsigned
NOT
NULL
COMMENT
‘线程ID’, `EVENT_ID`
bigint(20) unsigned
NOT
NULL
COMMENT
‘当前线程的事件ID，和THREAD_ID确定唯一’, `END_EVENT_ID`
bigint(20) unsigned
DEFAULT
NULL
COMMENT
‘当事件开始时，这一列被设置为NULL。当事件结束时，再更新为当前的事件ID’, `EVENT_NAME`
varchar(128)
NOT
NULL
COMMENT
‘事件名称’, `SOURCE`
varchar(64)
DEFAULT
NULL
COMMENT
‘该事件产生时的源码文件’, `TIMER_START`
bigint(20) unsigned
DEFAULT
NULL
COMMENT
‘事件开始时间（皮秒）’, `TIMER_END`
bigint(20) unsigned
DEFAULT
NULL
COMMENT
‘事件结束结束时间（皮秒）’, `TIMER_WAIT`
bigint(20) unsigned
DEFAULT
NULL
COMMENT
‘事件等待时间（皮秒）’, `SPINS`
int(10) unsigned
DEFAULT
NULL
COMMENT
”, `OBJECT_SCHEMA`
varchar(64)
DEFAULT
NULL
COMMENT
‘库名’, `OBJECT_NAME`
varchar(512)
DEFAULT
NULL
COMMENT
‘文件名、表名、IP:SOCK值’, `OBJECT_TYPE`
varchar(64)
DEFAULT
NULL
COMMENT
‘FILE、TABLE、TEMPORARY TABLE’, `INDEX_NAME`
varchar(64)
DEFAULT
NULL
COMMENT
‘索引名’, `OBJECT_INSTANCE_BEGIN`
bigint(20) unsigned
NOT
NULL
COMMENT
‘内存地址’, `NESTING_EVENT_ID`
bigint(20) unsigned
DEFAULT
NULL
COMMENT
‘该事件对应的父事件ID’, `NESTING_EVENT_TYPE` enum(‘STATEMENT’,’STAGE’,’WAIT’)
DEFAULT
NULL
COMMENT
‘父事件类型(STATEMENT, STAGE, WAIT)’, `OPERATION`
varchar(32)
NOT
NULL
COMMENT
‘操作类型（lock, read, write）’, `NUMBER_OF_BYTES`
bigint(20)
DEFAULT
NULL
COMMENT
”, `FLAGS`
int(10) unsigned
DEFAULT
NULL
COMMENT
‘标记’) ENGINE=PERFORMANCE_SCHEMA
DEFAULT
CHARSET=utf8四：Stage
表1，events_stages_current：记录了当前线程所处的执行阶段2，events_stages_history：记录了当前线程所处的执行阶段10条历史记录3，events_stages_history_long：记录了当前线程所处的执行阶段10000条历史记录表结构定义如下：CREATE
TABLE
`events_stages_current` ( `THREAD_ID`
bigint(20) unsigned
NOT
NULL
COMMENT
‘线程ID’, `EVENT_ID`
bigint(20) unsigned
NOT
NULL
COMMENT
‘事件ID’, `END_EVENT_ID`
bigint(20) unsigned
DEFAULT
NULL
COMMENT
‘结束事件ID’, `EVENT_NAME`
varchar(128)
NOT
NULL
COMMENT
‘事件名称’, `SOURCE`
varchar(64)
DEFAULT
NULL
COMMENT
‘源码位置’, `TIMER_START`
bigint(20) unsigned
DEFAULT
NULL
COMMENT
‘事件开始时间（皮秒）’, `TIMER_END`
bigint(20) unsigned
DEFAULT
NULL
COMMENT
‘事件结束结束时间（皮秒）’, `TIMER_WAIT`
bigint(20) unsigned
DEFAULT
NULL
COMMENT
‘事件等待时间（皮秒）’, `NESTING_EVENT_ID`
bigint(20) unsigned
DEFAULT
NULL
COMMENT
‘该事件对应的父事件ID’, `NESTING_EVENT_TYPE` enum(‘STATEMENT’,’STAGE’,’WAIT’)
DEFAULT
NULL
COMMENT
‘父事件类型(STATEMENT, STAGE, WAIT)’) ENGINE=PERFORMANCE_SCHEMA
DEFAULT
CHARSET=utf8五：Statement
表1，events_statements_current：通过
thread_id+event_id可以唯一确定一条记录。Statments表只记录最顶层的请求，SQL语句或是COMMAND，每条语句一行。event_name形式为statement/sql/*，或statement/com/*2，events_statements_history3，events_statements_history_long表结构定义如下：CREATE
TABLE
`events_statements_current` ( `THREAD_ID`
bigint(20) unsigned
NOT
NULL
COMMENT
‘线程ID’, `EVENT_ID`
bigint(20) unsigned
NOT
NULL
COMMENT
‘事件ID’, `END_EVENT_ID`
bigint(20) unsigned
DEFAULT
NULL
COMMENT
‘结束事件ID’, `EVENT_NAME`
varchar(128)
NOT
NULL
COMMENT
‘事件名称’, `SOURCE`
varchar(64)
DEFAULT
NULL
COMMENT
‘源码位置’, `TIMER_START`
bigint(20) unsigned
DEFAULT
NULL
COMMENT
‘事件开始时间（皮秒）’, `TIMER_END`
bigint(20) unsigned
DEFAULT
NULL
COMMENT
‘事件结束结束时间（皮秒）’, `TIMER_WAIT`
bigint(20) unsigned
DEFAULT
NULL
COMMENT
‘事件等待时间（皮秒）’, `LOCK_TIME`
bigint(20) unsigned
NOT
NULL
COMMENT
‘锁时间’, `SQL_TEXT` longtext COMMENT
‘记录SQL语句’, `DIGEST`
varchar(32)
DEFAULT
NULL
COMMENT
‘对SQL_TEXT做MD5产生的32位字符串’, `DIGEST_TEXT` longtext COMMENT
‘将语句中值部分用问号代替，用于SQL语句归类’, `CURRENT_SCHEMA`
varchar(64)
DEFAULT
NULL
COMMENT
‘默认的数据库名’, `OBJECT_TYPE`
varchar(64)
DEFAULT
NULL
COMMENT
‘保留字段’, `OBJECT_SCHEMA`
varchar(64)
DEFAULT
NULL
COMMENT
‘保留字段’, `OBJECT_NAME`
varchar(64)
DEFAULT
NULL
COMMENT
‘保留字段’, `OBJECT_INSTANCE_BEGIN`
bigint(20) unsigned
DEFAULT
NULL
COMMENT
‘内存地址’, `MYSQL_ERRNO`
int(11)
DEFAULT
NULL
COMMENT
”, `RETURNED_SQLSTATE`
varchar(5)
DEFAULT
NULL
COMMENT
”, `MESSAGE_TEXT`
varchar(128)
DEFAULT
NULL
COMMENT
‘信息’, `ERRORS`
bigint(20) unsigned
NOT
NULL
COMMENT
‘错误数目’, `WARNINGS`
bigint(20) unsigned
NOT
NULL
COMMENT
‘警告数目’, `ROWS_AFFECTED`
bigint(20) unsigned
NOT
NULL
COMMENT
‘影响的数目’, `ROWS_SENT`
bigint(20) unsigned
NOT
NULL
COMMENT
‘返回的记录数’, `ROWS_EXAMINED`
bigint(20) unsigned
NOT
NULL
COMMENT
‘读取扫描的记录数目’, `CREATED_TMP_DISK_TABLES`
bigint(20) unsigned
NOT
NULL
COMMENT
‘创建磁盘临时表数目’, `CREATED_TMP_TABLES`
bigint(20) unsigned
NOT
NULL
COMMENT
‘创建临时表数目’, `SELECT_FULL_JOIN`
bigint(20) unsigned
NOT
NULL
COMMENT
‘join时，第一个表为全表扫描的数目’, `SELECT_FULL_RANGE_JOIN`
bigint(20) unsigned
NOT
NULL
COMMENT
‘引用表采用range方式扫描的数目’, `SELECT_RANGE`
bigint(20) unsigned
NOT
NULL
COMMENT
‘join时，第一个表采用range方式扫描的数目’, `SELECT_RANGE_CHECK`
bigint(20) unsigned
NOT
NULL
COMMENT
”, `SELECT_SCAN`
bigint(20) unsigned
NOT
NULL
COMMENT
‘join时，第一个表位全表扫描的数目’, `SORT_MERGE_PASSES`
bigint(20) unsigned
NOT
NULL
COMMENT
”, `SORT_RANGE`
bigint(20) unsigned
NOT
NULL
COMMENT
‘范围排序数目’, `SORT_ROWS`
bigint(20) unsigned
NOT
NULL
COMMENT
‘排序的记录数目’, `SORT_SCAN`
bigint(20) unsigned
NOT
NULL
COMMENT
‘全表排序数目’, `NO_INDEX_USED`
bigint(20) unsigned
NOT
NULL
COMMENT
‘没有使用索引数目’, `NO_GOOD_INDEX_USED`
bigint(20) unsigned
NOT
NULL
COMMENT
”, `NESTING_EVENT_ID`
bigint(20) unsigned
DEFAULT
NULL
COMMENT
‘该事件对应的父事件ID’, `NESTING_EVENT_TYPE` enum(‘STATEMENT’,’STAGE’,’WAIT’)
DEFAULT
NULL
COMMENT
‘父事件类型(STATEMENT, STAGE, WAIT)’) ENGINE=PERFORMANCE_SCHEMA
DEFAULT
CHARSET=utf8六：Connection
表1，users：记录用户连接数信息2，hosts：记录了主机连接数信息3，accounts：记录了用户主机连接数信息zjy@performance_schema 12:03:27>select
*
from
users;+——————+———————+——————-+|
USER
|
CURRENT_CONNECTIONS
|
TOTAL_CONNECTIONS
|+——————+———————+——————-+|
debian-sys-maint
|

|
36
||
zjy
|
1
|
22285
||
dchat_php
|

|
37864
||
dxyslave |
2
|
9
||
nagios
|

|
10770
||
dchat_data
|
140
|
2233023
||
NULL
|

|
15866
||
dchat_api
| 160
|
2754212
||
mha_data
|
1
|
36
||
backup
|

|
15
||
cacti
|

|
4312
||
kol
| 10
|
172414
|+——————+———————+——————-+12
rows
in
set
(0.00
sec)zjy@performance_schema 12:03:34>select
*
from
hosts;+—————–+———————+——————-+|
HOST |
CURRENT_CONNECTIONS
|
TOTAL_CONNECTIONS
|+—————–+———————+——————-+| 192.168.100.218
|
150
|
2499422
|| 192.168.100.240
|
10
|
172429
|| 192.168.100.139
|
|
698
|| 192.168.100.21
|

|
2
|| 192.168.100.220
|
150
|
2526136
|| 192.168.100.25
|
1
|
7
||
NULL
|
|
15867
|| 192.168.100.241
|

|
21558
|| 192.168.100.191
|
1
|
34
||
localhost
|

|
10807
|| 192.168.100.118
|
1
|
2
|| 192.168.100.251
|

|
4312
|| 192.168.100.23
|
1
|
31
|| 192.168.100.193
|

|
4313
||
debian-sys-maint
|
localhost
|

|
36
||
backup
| 192.168.100.193
|

|
15
||
dchat_api
| 192.168.100.220
|
80
|
1382585
||
dchat_php
| 192.168.100.220
|

|
20292
||
zjy
| 192.168.100.139
|

|
698
||
zjy
| 192.168.100.241
|

|
21558
||
mha_data
| 192.168.100.191
|
1
|
34
||
dxyslave
| 192.168.100.118
|
1
|
2
||
kol
| 192.168.100.240
|
10
|
172431
||
dxyslave
| 192.168.100.25
|
1
|
7
||
dchat_data
| 192.168.100.218
| 70
|
1109974
||
zjy
| 192.168.100.23
|
1
|
31
||
dchat_php
| 192.168.100.218
|

|
17572
||
dchat_data
| 192.168.100.220
|
70
|
1123306
||
NULL
|
NULL
|

|
15868
||
mha_data
| 192.168.100.21
|

|
2
||
dchat_api
| 192.168.100.218
|
80
|
1371918
||
nagios
|
localhost
|

|
10771
|+——————+—————–+———————+——————-+View Code七：Summary
表：Summary表聚集了各个维度的统计信息包括表维度，索引维度，会话维度，语句维度和锁维度的统计信息1，events_waits_summary_global_by_event_name：按等待事件类型聚合，每个事件一条记录CREATE
TABLE
`events_waits_summary_global_by_event_name` ( `EVENT_NAME`
varchar(128)
NOT
NULL
COMMENT
‘事件名称’, `COUNT_STAR`
bigint(20) unsigned
NOT
NULL
COMMENT
‘事件计数’, `SUM_TIMER_WAIT`
bigint(20) unsigned
NOT
NULL
COMMENT
‘总的等待时间’, `MIN_TIMER_WAIT`
bigint(20) unsigned
NOT
NULL
COMMENT
‘最小等待时间’, `AVG_TIMER_WAIT`
bigint(20) unsigned
NOT
NULL
COMMENT
‘平均等待时间’, `MAX_TIMER_WAIT`
bigint(20) unsigned
NOT
NULL
COMMENT
‘最大等待时间’) ENGINE=PERFORMANCE_SCHEMA
DEFAULT
CHARSET=utf82，events_waits_summary_by_instance：按等待事件对象聚合，同一种等待事件，可能有多个实例，每个实例有不同的内存地址，因此
event_name+object_instance_begin唯一确定一条记录。CREATE
TABLE
`events_waits_summary_by_instance` ( `EVENT_NAME`
varchar(128)
NOT
NULL
COMMENT
‘事件名称’, `OBJECT_INSTANCE_BEGIN`
bigint(20) unsigned
NOT
NULL
COMMENT
‘内存地址’, `COUNT_STAR`
bigint(20) unsigned
NOT
NULL
COMMENT
‘事件计数’, `SUM_TIMER_WAIT`
bigint(20) unsigned
NOT
NULL
COMMENT
‘总的等待时间’, `MIN_TIMER_WAIT`
bigint(20) unsigned
NOT
NULL
COMMENT
‘最小等待时间’, `AVG_TIMER_WAIT`
bigint(20) unsigned
NOT
NULL
COMMENT
‘平均等待时间’, `MAX_TIMER_WAIT`
bigint(20) unsigned
NOT
NULL
COMMENT
‘最大等待时间’) ENGINE=PERFORMANCE_SCHEMA
DEFAULT
CHARSET=utf83，events_waits_summary_by_thread_by_event_name：按每个线程和事件来统计，thread_id+event_name唯一确定一条记录。CREATE
TABLE
`events_waits_summary_by_thread_by_event_name` ( `THREAD_ID`
bigint(20) unsigned
NOT
NULL
COMMENT
‘线程ID’, `EVENT_NAME`
varchar(128)
NOT
NULL
COMMENT
‘事件名称’, `COUNT_STAR`
bigint(20) unsigned
NOT
NULL
COMMENT
‘事件计数’, `SUM_TIMER_WAIT`
bigint(20) unsigned
NOT
NULL
COMMENT
‘总的等待时间’, `MIN_TIMER_WAIT`
bigint(20) unsigned
NOT
NULL
COMMENT
‘最小等待时间’, `AVG_TIMER_WAIT`
bigint(20) unsigned
NOT
NULL
COMMENT
‘平均等待时间’, `MAX_TIMER_WAIT`
bigint(20) unsigned
NOT
NULL
COMMENT
‘最大等待时间’) ENGINE=PERFORMANCE_SCHEMA
DEFAULT
CHARSET=utf84，events_stages_summary_global_by_event_name：按事件阶段类型聚合，每个事件一条记录，表结构同上。5，events_stages_summary_by_thread_by_event_name：按每个线程和事件来阶段统计，表结构同上。6，events_statements_summary_by_digest：按照事件的语句进行聚合。CREATE
TABLE
`events_statements_summary_by_digest` ( `SCHEMA_NAME`
varchar(64)
DEFAULT
NULL
COMMENT
‘库名’, `DIGEST`
varchar(32)
DEFAULT
NULL
COMMENT
‘对SQL_TEXT做MD5产生的32位字符串。如果为consumer表中没有打开statement_digest选项，则为NULL’, `DIGEST_TEXT` longtext COMMENT
‘将语句中值部分用问号代替，用于SQL语句归类。如果为consumer表中没有打开statement_digest选项，则为NULL。’, `COUNT_STAR`
bigint(20) unsigned
NOT
NULL
COMMENT
‘事件计数’, `SUM_TIMER_WAIT`
bigint(20) unsigned
NOT
NULL
COMMENT
‘总的等待时间’, `MIN_TIMER_WAIT`
bigint(20) unsigned
NOT
NULL
COMMENT
‘最小等待时间’, `AVG_TIMER_WAIT`
bigint(20) unsigned
NOT
NULL
COMMENT
‘平均等待时间’, `MAX_TIMER_WAIT`
bigint(20) unsigned
NOT
NULL
COMMENT
‘最大等待时间’, `SUM_LOCK_TIME`
bigint(20) unsigned
NOT
NULL
COMMENT
‘锁时间总时长’, `SUM_ERRORS`
bigint(20) unsigned
NOT
NULL
COMMENT
‘错误数的总’, `SUM_WARNINGS`
bigint(20) unsigned
NOT
NULL
COMMENT
‘警告的总数’, `SUM_ROWS_AFFECTED`
bigint(20) unsigned
NOT
NULL
COMMENT
‘影响的总数目’, `SUM_ROWS_SENT`
bigint(20) unsigned
NOT
NULL
COMMENT
‘返回总数目’, `SUM_ROWS_EXAMINED`
bigint(20) unsigned
NOT
NULL
COMMENT
‘总的扫描的数目’, `SUM_CREATED_TMP_DISK_TABLES`
bigint(20) unsigned
NOT
NULL
COMMENT
‘创建磁盘临时表的总数目’, `SUM_CREATED_TMP_TABLES`
bigint(20) unsigned
NOT
NULL
COMMENT
‘创建临时表的总数目’, `SUM_SELECT_FULL_JOIN`
bigint(20) unsigned
NOT
NULL
COMMENT
‘第一个表全表扫描的总数目’, `SUM_SELECT_FULL_RANGE_JOIN`
bigint(20) unsigned
NOT
NULL
COMMENT
‘总的采用range方式扫描的数目’, `SUM_SELECT_RANGE`
bigint(20) unsigned
NOT
NULL
COMMENT
‘第一个表采用range方式扫描的总数目’, `SUM_SELECT_RANGE_CHECK`
bigint(20) unsigned
NOT
NULL
COMMENT
”, `SUM_SELECT_SCAN`
bigint(20) unsigned
NOT
NULL
COMMENT
‘第一个表位全表扫描的总数目’, `SUM_SORT_MERGE_PASSES`
bigint(20) unsigned
NOT
NULL
COMMENT
”, `SUM_SORT_RANGE`
bigint(20) unsigned
NOT
NULL
COMMENT
‘范围排序总数’, `SUM_SORT_ROWS`
bigint(20) unsigned
NOT
NULL
COMMENT
‘排序的记录总数目’, `SUM_SORT_SCAN`
bigint(20) unsigned
NOT
NULL
COMMENT
‘第一个表排序扫描总数目’, `SUM_NO_INDEX_USED`
bigint(20) unsigned
NOT
NULL
COMMENT
‘没有使用索引总数’, `SUM_NO_GOOD_INDEX_USED`
bigint(20) unsigned
NOT
NULL
COMMENT
”, `FIRST_SEEN`
timestamp
NOT
NULL
DEFAULT
‘0000-00-00 00:00:00’
COMMENT
‘第一次执行时间’, `LAST_SEEN`
timestamp
NOT
NULL
DEFAULT
‘0000-00-00 00:00:00’
COMMENT
‘最后一次执行时间’) ENGINE=PERFORMANCE_SCHEMA
DEFAULT
CHARSET=utf87，events_statements_summary_global_by_event_name：按照事件的语句进行聚合。表结构同上。8，events_statements_summary_by_thread_by_event_name：按照线程和事件的语句进行聚合，表结构同上。9，file_summary_by_instance：按事件类型统计（物理IO维度）10，file_summary_by_event_name：具体文件统计（物理IO维度）9和10一起说明：统计IO操作：COUNT_STAR，SUM_TIMER_WAIT,MIN_TIMER_WAIT,AVG_TIMER_WAIT,MAX_TIMER_WAIT统计读

：COUNT_READ,SUM_TIMER_READ,MIN_TIMER_READ,AVG_TIMER_READ,MAX_TIMER_READ, SUM_NUMBER_OF_BYTES_READ统计写

：COUNT_WRITE,SUM_TIMER_WRITE,MIN_TIMER_WRITE,AVG_TIMER_WRITE,MAX_TIMER_WRITE, SUM_NUMBER_OF_BYTES_WRITE统计其他IO事件，比如create，delete，open，close等：COUNT_MISC,SUM_TIMER_MISC,MIN_TIMER_MISC,AVG_TIMER_MISC,MAX_TIMER_MISC11，table_io_waits_summary_by_table：根据wait/io/table/sql/handler，聚合每个表的I/O操作（逻辑IO纬度）统计IO操作：COUNT_STAR,SUM_TIMER_WAIT,MIN_TIMER_WAIT,AVG_TIMER_WAIT,MAX_TIMER_WAIT统计读

：COUNT_READ,SUM_TIMER_READ,MIN_TIMER_READ,AVG_TIMER_READ,MAX_TIMER_READ
：COUNT_FETCH,SUM_TIMER_FETCH,MIN_TIMER_FETCH,AVG_TIMER_FETCH, MAX_TIMER_FETCH统计写

：COUNT_WRITE,SUM_TIMER_WRITE,MIN_TIMER_WRITE,AVG_TIMER_WRITE,MAX_TIMER_WRITEINSERT统计，相应的还有DELETE和UPDATE统计：COUNT_INSERT,SUM_TIMER_INSERT,MIN_TIMER_INSERT,AVG_TIMER_INSERT,MAX_TIMER_INSERT12，table_io_waits_summary_by_index_usage：与table_io_waits_summary_by_table类似，按索引维度统计13，table_lock_waits_summary_by_table：聚合了表锁等待事件，包括internal lock
和
external lockinternal lock通过SQL层函数thr_lock调用，OPERATION值为：
read normal、read with shared locks、read high priority、read no insert、write allow write、write concurrent insert、write delayed、write low priority、write normal
external lock则通过接口函数handler::external_lock调用存储引擎层，OPERATION列的值为：read external、write external14，Connection Summaries表：account、user、hostevents_waits_summary_by_account_by_event_name
events_waits_summary_by_user_by_event_name
events_waits_summary_by_host_by_event_name
events_stages_summary_by_account_by_event_name
events_stages_summary_by_user_by_event_name
events_stages_summary_by_host_by_event_name
events_statements_summary_by_account_by_event_name
events_statements_summary_by_user_by_event_name
events_statements_summary_by_host_by_event_name15，socket_summary_by_instance、socket_summary_by_event_name：socket聚合统计表。八：其他相关表1，performance_timers：系统支持的统计时间单位2，threads：监视服务端的当前运行的线程统计应用：
关于SQL维度的统计信息主要集中在events_statements_summary_by_digest表中，通过将SQL语句抽象出digest，可以统计某类SQL语句在各个维度的统计信息1，哪个SQL执行最多：zjy@performance_schema 11:36:22>SELECT
SCHEMA_NAME,DIGEST_TEXT,COUNT_STAR,SUM_ROWS_SENT,SUM_ROWS_EXAMINED,FIRST_SEEN,LAST_SEEN
FROM
events_statements_summary_by_digest
ORDER
BY
COUNT_STAR
desc
LIMIT
1G*************************** 1. row
*************************** SCHEMA_NAME: dchat
DIGEST_TEXT:
SELECT
…
COUNT_STAR:
1161210102 SUM_ROWS_SENT:
1161207842SUM_ROWS_EXAMINED: FIRST_SEEN:
2016–02–17
00:36:46 LAST_SEEN:
2016–03–07
11:36:29各个字段的注释可以看上面的表结构说明：从2月17号到3月7号该SQL执行了1161210102次。2，哪个SQL平均响应时间最多：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
1G*************************** 1. row
*************************** SCHEMA_NAME: dchat
DIGEST_TEXT:
SELECT
… COUNT_STAR:
1 AVG_TIMER_WAIT:
273238183964000 SUM_ROWS_SENT:
50208SUM_ROWS_EXAMINED:
5565651 FIRST_SEEN:
2016–02–22
13:27:33 LAST_SEEN:
2016–02–22
13:27:33各个字段的注释可以看上面的表结构说明：从2月17号到3月7号该SQL平均响应时间273238183964000皮秒（1000000000000皮秒=1秒）3，哪个SQL扫描的行数最多：SUM_ROWS_EXAMINED4，哪个SQL使用的临时表最多：SUM_CREATED_TMP_DISK_TABLES、SUM_CREATED_TMP_TABLES5，哪个SQL返回的结果集最多：SUM_ROWS_SENT6，哪个SQL排序数最多：SUM_SORT_ROWS通过上述指标我们可以间接获得某类SQL的逻辑IO(SUM_ROWS_EXAMINED)，CPU消耗(SUM_SORT_ROWS)，网络带宽(SUM_ROWS_SENT)的对比。通过file_summary_by_instance表，可以获得系统运行到现在，哪个文件(表)物理IO最多，这可能意味着这个表经常需要访问磁盘IO。7，哪个表、文件逻辑IO最多（热数据）：zjy@performance_schema 12:16:18>SELECT
FILE_NAME,EVENT_NAME,COUNT_READ,SUM_NUMBER_OF_BYTES_READ,COUNT_WRITE,SUM_NUMBER_OF_BYTES_WRITE
FROM
file_summary_by_instance
ORDER
BY
SUM_NUMBER_OF_BYTES_READ+SUM_NUMBER_OF_BYTES_WRITE
DESC
LIMIT
2G*************************** 1. row
***************************
FILE_NAME:
/var/lib/mysql/ibdata1 #文件 EVENT_NAME: wait/io/file/innodb/innodb_data_file COUNT_READ:
544SUM_NUMBER_OF_BYTES_READ:
10977280 COUNT_WRITE:
3700729SUM_NUMBER_OF_BYTES_WRITE:
1433734217728*************************** 2. row
***************************
FILE_NAME:
/var/lib/mysql/dchat/fans.ibd #表 EVENT_NAME: wait/io/file/innodb/innodb_data_file COUNT_READ:
9370680SUM_NUMBER_OF_BYTES_READ:
153529188352 COUNT_WRITE:
67576376SUM_NUMBER_OF_BYTES_WRITE:
11078154321928，哪个索引使用最多：zjy@performance_schema 12:18:42>SELECT
OBJECT_NAME, INDEX_NAME, COUNT_FETCH, COUNT_INSERT, COUNT_UPDATE, COUNT_DELETE
FROM
table_io_waits_summary_by_index_usage
ORDER
BY
SUM_TIMER_WAIT
DESC
limit
1;+————-+————+————-+————–+————–+————–+|
OBJECT_NAME
|
INDEX_NAME
|
COUNT_FETCH
|
COUNT_INSERT
|
COUNT_UPDATE
|
COUNT_DELETE
|+————-+————+————-+————–+————–+————–+| fans
| PRIMARY
| 29002695158
|

|
296373434
|

|+————-+————+————-+————–+————–+————–+1
row
in
set
(0.29
sec)通过table_io_waits_summary_by_index_usage表，可以获得系统运行到现在，哪个表的具体哪个索引(包括主键索引，二级索引)使用最多。9，哪个索引没有使用过：zjy@performance_schema 12:23:22>SELECT
OBJECT_SCHEMA,
OBJECT_NAME, INDEX_NAME
FROM
table_io_waits_summary_by_index_usage
WHERE
INDEX_NAME
IS
NOT
NULL
AND
COUNT_STAR
=

AND
OBJECT_SCHEMA

‘mysql’
ORDER
BY
OBJECT_SCHEMA,OBJECT_NAME;10，哪个等待事件消耗的时间最多：zjy@performance_schema 12:25:22>SELECT
EVENT_NAME, COUNT_STAR, SUM_TIMER_WAIT, AVG_TIMER_WAIT
FROM
events_waits_summary_global_by_event_name
WHERE
event_name
!=
‘idle’
ORDER
BY
SUM_TIMER_WAIT
DESC
LIMIT
1;11，类似profiling功能：分析具体某条SQL，该SQL在执行各个阶段的时间消耗，通过events_statements_xxx表和events_stages_xxx表，就可以达到目的。两个表通过event_id与nesting_event_id关联，stages表的nesting_event_id为对应statements表的event_id；针对每个stage可能出现的锁等待，一个stage会对应一个或多个wait，通过stage_xxx表的event_id字段与waits_xxx表的nesting_event_id进行关联。如：比如分析包含count(*)的某条SQL语句，具体如下：SELECTEVENT_ID,sql_textFROM
events_statements_historyWHERE
sql_text
LIKE
‘%count(*)%’;+———-+————————————–+|
EVENT_ID
|
sql_text
|+———-+————————————–+| 1690
|
select
count(*)
from
chuck.test_slow
|+———-+————————————–+首先得到了语句的event_id为1690，通过查找events_stages_xxx中nesting_event_id为1690的记录，可以达到目的。a.查看每个阶段的时间消耗：SELECTevent_id,EVENT_NAME,SOURCE,TIMER_END
–
TIMER_STARTFROM
events_stages_history_longWHERE
NESTING_EVENT_ID
= 1690;+———-+——————————–+———————-+———————–+|
event_id
|
EVENT_NAME
|
SOURCE
|
TIMER_END-TIMER_START
|+———-+——————————–+———————-+———————–+| 1691
|
stage/sql/init
|
mysqld.cc:990
| 316945000
|| 1693
|
stage/sql/checking
permissions
|
sql_parse.cc:5776
| 26774000
|| 1695
|
stage/sql/Opening tables
|
sql_base.cc:4970
| 41436934000
|| 2638
|
stage/sql/init
|
sql_select.cc:1050
| 85757000
|| 2639
|
stage/sql/System lock
|
lock.cc:303
| 40017000
|| 2643
|
stage/sql/optimizing
|
sql_optimizer.cc:138
| 38562000
|| 2644
|
stage/sql/statistics
|
sql_optimizer.cc:362
| 52845000
|| 2645
|
stage/sql/preparing
|
sql_optimizer.cc:485
| 53196000
|| 2646
|
stage/sql/executing
|
sql_executor.cc:112
| 3153000
|| 2647
|
stage/sql/Sending data
|
sql_executor.cc:192
| 7369072089000
|| 4304138
|
stage/sql/end
|
sql_select.cc:1105
| 19920000
|| 4304139
|
stage/sql/query
end
|
sql_parse.cc:5463
| 44721000
|| 4304145
|
stage/sql/closing tables
|
sql_parse.cc:5524
| 61723000
|| 4304152
|
stage/sql/freeing items
|
sql_parse.cc:6838
| 455678000
|| 4304155
|
stage/sql/logging slow query
|
sql_parse.cc:2258
| 83348000
|| 4304159
|
stage/sql/cleaning up
|
sql_parse.cc:2163
| 4433000
|+———-+——————————–+———————-+———————–+通过间接关联，我们能分析得到SQL语句在每个阶段的时间消耗，时间单位以皮秒表示。这里展示的结果很类似profiling功能，有了performance
schema，就不再需要profiling这个功能了。另外需要注意的是，由于默认情况下events_stages_history表中只为每个连接记录了最近10条记录，为了确保获取所有记录，需要访问events_stages_history_long表b.查看某个阶段的锁等待情况针对每个stage可能出现的锁等待，一个stage会对应一个或多个wait，events_waits_history_long这个表容易爆满[默认阀值10000]。由于select
count(*)需要IO(逻辑IO或者物理IO)，所以在stage/sql/Sending data阶段会有io等待的统计。通过stage_xxx表的event_id字段与waits_xxx表的nesting_event_id进行关联。SELECTevent_id,event_name,source,timer_wait,object_name,index_name,operation,nesting_event_idFROM
events_waits_history_longWHERE
nesting_event_id
= 2647;+———-+—————————+—————–+————+————-+————+———–+——————+|
event_id
|
event_name
|
source
|
timer_wait
|
object_name
|
index_name
|
operation
|
nesting_event_id
|+———-+—————————+—————–+————+————-+————+———–+——————+| 190607
|
wait/io/table/sql/handler
|
handler.cc:2842
| 1845888
|
test_slow
|
idx_c1
|
fetch
| 2647
|| 190608
|
wait/io/table/sql/handler
|
handler.cc:2842
| 1955328
|
test_slow
|
idx_c1
|
fetch
| 2647
|| 190609
|
wait/io/table/sql/handler
|
handler.cc:2842
| 1929792
|
test_slow
|
idx_c1
|
fetch
| 2647
|| 190610
|
wait/io/table/sql/handler
|
handler.cc:2842
| 1869600
|
test_slow
|
idx_c1
|
fetch
| 2647
|| 190611
|
wait/io/table/sql/handler
|
handler.cc:2842
| 1922496
|
test_slow
|
idx_c1
|
fetch
| 2647
|+———-+—————————+—————–+————+————-+————+———–+——————+通过上面的实验，我们知道了statement,stage,wait的三级结构，通过nesting_event_id进行关联，它表示某个事件的父event_id。(2).模拟innodb行锁等待的例子会话A执行语句update test_icp
set
y=y+1
where
x=1(x为primary
key)，不commit；会话B执行同样的语句update test_icp
set
y=y+1
where
x=1，会话B堵塞，并最终报错。通过连接连接查询events_statements_history_long和events_stages_history_long，可以看到在updating阶段花了大约60s的时间。这主要因为实例上的innodb_lock_wait_timeout设置为60，等待60s后超时报错了。SELECTstatement.EVENT_ID,stages.event_id,statement.sql_text,stages.event_name,stages.timer_waitFROM
events_statements_history_long statementjoin
events_stages_history_long stageson
statement.event_id=stages.nesting_event_idWHERE
statement.sql_text
=
‘update test_icp set y=y+1 where x=1’;+———-+———-+————————————-+——————————–+—————-+|
EVENT_ID
|
event_id
|
sql_text
|
event_name
|
timer_wait
|+———-+———-+————————————-+——————————–+—————-+| 5816
| 5817
|
update
test_icp
set
y=y+1
where
x=1
|
stage/sql/init
| 195543000
|| 5816
| 5819
|
update
test_icp
set
y=y+1
where
x=1
|
stage/sql/checking
permissions
| 22730000
|| 5816
| 5821
|
update
test_icp
set
y=y+1
where
x=1
|
stage/sql/Opening tables
| 66079000
|| 5816
| 5827
|
update
test_icp
set
y=y+1
where
x=1
|
stage/sql/init
| 89116000
|| 5816
| 5828
|
update
test_icp
set
y=y+1
where
x=1
|
stage/sql/System lock
| 218744000
|| 5816
| 5832
|
update
test_icp
set
y=y+1
where
x=1
|
stage/sql/updating
| 6001362045000
|| 5816
| 5968
|
update
test_icp
set
y=y+1
where
x=1
|
stage/sql/end
| 10435000
|| 5816
| 5969
|
update
test_icp
set
y=y+1
where
x=1
|
stage/sql/query
end
| 85979000
|| 5816
| 5983
|
update
test_icp
set
y=y+1
where
x=1
|
stage/sql/closing tables
| 56562000
|| 5816
| 5990
|
update
test_icp
set
y=y+1
where
x=1
|
stage/sql/freeing items
| 83563000
|| 5816
| 5992
|
update
test_icp
set
y=y+1
where
x=1
|
stage/sql/cleaning up
| 4589000
|+———-+———-+————————————-+——————————–+—————-+查看wait事件：SELECTevent_id,event_name,source,timer_wait,object_name,index_name,operation,nesting_event_idFROM
events_waits_history_longWHERE
nesting_event_id
= 5832;*************************** 1. row
***************************event_id:
5832event_name: wait/io/table/sql/handlersource: handler.cc:2782timer_wait:
6005946156624object_name: test_icpindex_name:
PRIMARYoperation:
fetch从结果来看，waits表中记录了一个fetch等待事件，但并没有更细的innodb行锁等待事件统计。(3).模拟MDL锁等待的例子会话A执行一个大查询select
count(*)
from
test_slow，会话B执行表结构变更alter
table
test_slow modify c2
varchar(152);通过如下语句可以得到alter语句的执行过程，重点关注“stage/sql/Waiting
for
table
metadata lock”阶段。SELECTstatement.EVENT_ID,stages.event_id,statement.sql_text,stages.event_name
as
stage_name,stages.timer_wait
as
stage_timeFROM
events_statements_history_long statementleft
join
events_stages_history_long stageson
statement.event_id=stages.nesting_event_idWHERE
statement.sql_text
=
‘alter table test_slow modify c2 varchar(152)’;+———–+———–+———————————————-+—————————————————-+—————+|
EVENT_ID
|
event_id
|
sql_text
|
stage_name
|
stage_time
|+———–+———–+———————————————-+—————————————————-+—————+| 326526744
| 326526745
|
alter
table
test_slow modify c2
varchar(152)
|
stage/sql/init
| 216662000
|| 326526744
| 326526747
|
alter
table
test_slow modify c2
varchar(152)
|
stage/sql/checking
permissions
| 18183000
|| 326526744
| 326526748
|
alter
table
test_slow modify c2
varchar(152)
|
stage/sql/checking
permissions
| 10294000
|| 326526744
| 326526750
|
alter
table
test_slow modify c2
varchar(152)
|
stage/sql/init
| 4783000
|| 326526744
| 326526751
|
alter
table
test_slow modify c2
varchar(152)
|
stage/sql/Opening tables
| 140172000
|| 326526744
| 326526760
|
alter
table
test_slow modify c2
varchar(152)
|
stage/sql/setup
| 157643000
|| 326526744
| 326526769
|
alter
table
test_slow modify c2
varchar(152)
|
stage/sql/creating
table
| 8723217000
|| 326526744
| 326526803
|
alter
table
test_slow modify c2
varchar(152)
|
stage/sql/After
create
| 257332000
|| 326526744
| 326526832
|
alter
table
test_slow modify c2
varchar(152)
|
stage/sql/Waiting
for
table
metadata lock
| 1000181831000
|| 326526744
| 326526835
|
alter
table
test_slow modify c2
varchar(152)
|
stage/sql/After
create
| 33483000
|| 326526744
| 326526838
|
alter
table
test_slow modify c2
varchar(152)
|
stage/sql/Waiting
for
table
metadata lock
| 1000091810000
|| 326526744
| 326526841
|
alter
table
test_slow modify c2
varchar(152)
|
stage/sql/After
create
| 17187000
|| 326526744
| 326526844
|
alter
table
test_slow modify c2
varchar(152)
|
stage/sql/Waiting
for
table
metadata lock
| 1000126464000
|| 326526744
| 326526847
|
alter
table
test_slow modify c2
varchar(152)
|
stage/sql/After
create
| 27472000
|| 326526744
| 326526850
|
alter
table
test_slow modify c2
varchar(152)
|
stage/sql/Waiting
for
table
metadata lock
| 561996133000
|| 326526744
| 326526853
|
alter
table
test_slow modify c2
varchar(152)
|
stage/sql/After
create
| 124876000
|| 326526744
| 326526877
|
alter
table
test_slow modify c2
varchar(152)
|
stage/sql/System lock
| 30659000
|| 326526744
| 326526881
|
alter
table
test_slow modify c2
varchar(152)
|
stage/sql/preparing
for
alter
table
| 40246000
|| 326526744
| 326526889
|
alter
table
test_slow modify c2
varchar(152)
|
stage/sql/altering
table
| 36628000
|| 326526744
| 326528280
|
alter
table
test_slow modify c2
varchar(152)
|
stage/sql/end
| 43824000
|| 326526744
| 326528281
|
alter
table
test_slow modify c2
varchar(152)
|
stage/sql/query
end
| 112557000
|| 326526744
| 326528299
|
alter
table
test_slow modify c2
varchar(152)
|
stage/sql/closing tables
| 27707000
|| 326526744
| 326528305
|
alter
table
test_slow modify c2
varchar(152)
|
stage/sql/freeing items
| 201614000
|| 326526744
| 326528308
|
alter
table
test_slow modify c2
varchar(152)
|
stage/sql/cleaning up
| 3584000
|+———–+———–+———————————————-+—————————————————-+—————+从结果可以看到，出现了多次stage/sql/Waiting
for
table
metadata lock阶段，并且间隔1s，说明每隔1s钟会重试判断。找一个该阶段的event_id,通过nesting_event_id关联，确定到底在等待哪个wait事件。SELECTevent_id,event_name,source,timer_wait,object_name,index_name,operation,nesting_event_idFROM
events_waits_history_longWHERE
nesting_event_id
= 326526850;+———–+—————————————————+——————+————–+————-+————+————+——————+|
event_id
|
event_name
|
source
|
timer_wait
|
object_name
|
index_name
|
operation
|
nesting_event_id
|+———–+—————————————————+——————+————–+————-+————+————+——————+| 326526851
|
wait/synch/cond/sql/MDL_context::COND_wait_status
|
mdl.cc:1327
| 562417991328
|
NULL
|
NULL
|
timed_wait
| 326526850
|| 326526852
|
wait/synch/mutex/mysys/my_thread_var::mutex
|
sql_class.h:3481
| 733248
|
NULL
|
NULL
|
lock
| 326526850
|+———–+—————————————————+——————+————–+————-+————+————+——————+通过结果可以知道，产生阻塞的是条件变量MDL_context::COND_wait_status，并且显示了代码的位置。View Code“怎么理解MySQL5.6中的PERFORMANCE_SCHEM”的内容就介绍到这里了，感谢大家的阅读。如果想了解更多行业相关的知识可以关注开发云网站，小编将为大家输出更多高质量的实用文章！

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