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:
1.
[mysqld]
2.
performance_schema=ON
查看是否开启:
1.
mysql>show variables like
'performance_schema'
;
2.
+--------------------+-------+
3.
| Variable_name | Value |
4.
+--------------------+-------+
5.
| performance_schema | <strong>ON</strong> |
6.
+--------------------+-------+
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:
01.
zjy
@performance_schema
10
:
16
:
56
>show tables like
'%setup%'
;
02.
+----------------------------------------+
03.
| Tables_in_performance_schema (%setup%) |
04.
+----------------------------------------+
05.
| setup_actors |
06.
| setup_consumers |
07.
| setup_instruments |
08.
| setup_objects |
09.
| setup_timers |
10.
+----------------------------------------+
1,setup_actors:配置用户纬度的监控,默认监控所有用户。
1.
zjy
@performance_schema
10
:
19
:
11
>select * from setup_actors;
2.
+------+------+------+
3.
| HOST | USER | ROLE |
4.
+------+------+------+
5.
| % | % | % |
6.
+------+------+------+
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。
01.
zjy@: performance_schema
10
:
23
:
35
>select * from setup_consumers;
02.
+--------------------------------+---------+
03.
| NAME | ENABLED |
04.
+--------------------------------+---------+
05.
| events_stages_current | NO |
06.
| events_stages_history | NO |
07.
| events_stages_history_long | NO |
08.
| events_statements_current | YES |
09.
| events_statements_history | NO |
10.
| events_statements_history_long | NO |
11.
| events_waits_current | NO |
12.
| events_waits_history | NO |
13.
| events_waits_history_long | NO |
14.
| global_instrumentation | YES |
15.
| thread_instrumentation | YES |
16.
| statements_digest | YES |
17.
+--------------------------------+---------+
这里需要说明的是需要查看哪个就更新其ENABLED列为YES。如:
1.
zjy
@performance_schema
10
:
25
:
02
>update setup_consumers set ENABLED=
'YES'
where NAME in (
'events_stages_current'
,
'events_waits_current'
);
2.
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:
1.
[mysqld]
2.
#performance_schema
3.
performance_schema_consumer_events_waits_current=on
4.
performance_schema_consumer_events_stages_current=on
5.
performance_schema_consumer_events_statements_current=on
6.
performance_schema_consumer_events_waits_history=on
7.
performance_schema_consumer_events_stages_history=on
8.
performance_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:
1.
<strong>global_instrumentation</strong> > <strong>thread_instrumentation</strong> = <strong>statements_digest</strong> > events_stages_<strong>current</strong> = events_statements_current = events_waits_current > events_stages_<strong>history</strong> = events_statements_history = events_waits_history > events_stages_<strong>history_long</strong> = 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:
01.
zjy
@performance_schema
11
:
10
:
03
>show variables like
'performance_schema%history%size'
;
02.
+--------------------------------------------------------+-------+
03.
| Variable_name | Value |
04.
+--------------------------------------------------------+-------+
05.
| performance_schema_events_stages_history_long_size |
10000
|
06.
| performance_schema_events_stages_history_size |
10
|
07.
| performance_schema_events_statements_history_long_size |
10000
|
08.
| performance_schema_events_statements_history_size |
10
|
09.
| performance_schema_events_waits_history_long_size |
10000
|
10.
| performance_schema_events_waits_history_size |
10
|
11.
+--------------------------------------------------------+-------+
3,setup_instruments:配置具体的instrument,主要包含4大类:idle、stage/xxx、statement/xxx、wait/xxx:
01.
zjy
@performance_schema
10
:
56
:
35
>select name,count(*) from setup_instruments group by LEFT(name,
5
);
02.
+---------------------------------+----------+
03.
| name | count(*) |
04.
+---------------------------------+----------+
05.
| idle |
1
|
06.
| stage/sql/After create |
111
|
07.
| statement/sql/select |
179
|
08.
| wait/synch/mutex/sql/PAGE::lock |
296
|
09.
+---------------------------------+----------+
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。
01.
zjy
@performance_schema
11
:
00
:
18
>select * from setup_objects;
02.
+-------------+--------------------+-------------+---------+-------+
03.
| OBJECT_TYPE | OBJECT_SCHEMA | OBJECT_NAME | ENABLED | TIMED |
04.
+-------------+--------------------+-------------+---------+-------+
05.
| TABLE | mysql | % | NO | NO |
06.
| TABLE | performance_schema | % | NO | NO |
07.
| TABLE | information_schema | % | NO | NO |
08.
| TABLE | % | % | <strong>YES</strong> | <strong>YES</strong> |
09.
+-------------+--------------------+-------------+---------+-------+
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)
01.
zjy
@performance_schema
11
:
05
:
12
>select * from setup_timers;
02.
+-----------+-------------+
03.
| NAME | TIMER_NAME |
04.
+-----------+-------------+
05.
| idle | MICROSECOND |
06.
| wait | CYCLE |
07.
| stage | NANOSECOND |
08.
| statement | NANOSECOND |
09.
+-----------+-------------+
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。
01.
zjy
@performance_schema
11
:
20
:
04
>select * from file_instances limit
2
,
5
;
02.
+---------------------------------+--------------------------------------+------------+
03.
| FILE_NAME | EVENT_NAME | <strong>OPEN_COUNT</strong> |
04.
+---------------------------------+--------------------------------------+------------+
05.
| /var/lib/mysql/mysql/plugin.frm | wait/io/file/sql/FRM |
0
|
06.
| /var/lib/mysql/mysql/plugin.MYI | wait/io/file/myisam/kfile |
1
|
07.
| /var/lib/mysql/mysql/plugin.MYD | wait/io/file/myisam/dfile |
1
|
08.
| /var/lib/mysql/ibdata1 | wait/io/file/innodb/innodb_data_file |
2
|
09.
| /var/lib/mysql/ib_logfile0 | wait/io/file/innodb/innodb_log_file |
2
|
10.
+---------------------------------+--------------------------------------+------------+
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:
01.
CREATE TABLE `events_waits_current` (
02.
`THREAD_ID` bigint(
20
) unsigned NOT NULL COMMENT
'线程ID'
,
03.
`EVENT_ID` bigint(
20
) unsigned NOT NULL COMMENT
'当前线程的事件ID,和THREAD_ID确定唯一'
,
04.
`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'
,
05.
`EVENT_NAME` varchar(
128
) NOT NULL COMMENT
'事件名称'
,
06.
`SOURCE` varchar(
64
) DEFAULT NULL COMMENT
'该事件产生时的源码文件'
,
07.
`TIMER_START` bigint(
20
) unsigned DEFAULT NULL COMMENT
'事件开始时间(皮秒)'
,
08.
`TIMER_END` bigint(
20
) unsigned DEFAULT NULL COMMENT
'事件结束结束时间(皮秒)'
,
09.
`TIMER_WAIT` bigint(
20
) unsigned DEFAULT NULL COMMENT
'事件等待时间(皮秒)'
,
10.
`SPINS`
int
(
10
) unsigned DEFAULT NULL COMMENT
''
,
11.
`OBJECT_SCHEMA` varchar(
64
) DEFAULT NULL COMMENT
'库名'
,
12.
`OBJECT_NAME` varchar(
512
) DEFAULT NULL COMMENT
'文件名、表名、IP:SOCK值'
,
13.
`OBJECT_TYPE` varchar(
64
) DEFAULT NULL COMMENT
'FILE、TABLE、TEMPORARY TABLE'
,
14.
`INDEX_NAME` varchar(
64
) DEFAULT NULL COMMENT
'索引名'
,
15.
`OBJECT_INSTANCE_BEGIN` bigint(
20
) unsigned NOT NULL COMMENT
'内存地址'
,
16.
`NESTING_EVENT_ID` bigint(
20
) unsigned DEFAULT NULL COMMENT
'该事件对应的父事件ID'
,
17.
`NESTING_EVENT_TYPE`
enum
(
'STATEMENT'
,
'STAGE'
,
'WAIT'
) DEFAULT NULL COMMENT
'父事件类型(STATEMENT, STAGE, WAIT)'
,
18.
`OPERATION` varchar(
32
) NOT NULL COMMENT
'操作类型(lock, read, write)'
,
19.
`NUMBER_OF_BYTES` bigint(
20
) DEFAULT NULL COMMENT
''
,
20.
`FLAGS`
int
(
10
) unsigned DEFAULT NULL COMMENT
'标记'
21.
) 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:
01.
CREATE TABLE `events_stages_current` (
02.
`THREAD_ID` bigint(
20
) unsigned NOT NULL COMMENT
'线程ID'
,
03.
`EVENT_ID` bigint(
20
) unsigned NOT NULL COMMENT
'事件ID'
,
04.
`END_EVENT_ID` bigint(
20
) unsigned DEFAULT NULL COMMENT
'结束事件ID'
,
05.
`EVENT_NAME` varchar(
128
) NOT NULL COMMENT
'事件名称'
,
06.
`SOURCE` varchar(
64
) DEFAULT NULL COMMENT
'源码位置'
,
07.
`TIMER_START` bigint(
20
) unsigned DEFAULT NULL COMMENT
'事件开始时间(皮秒)'
,
08.
`TIMER_END` bigint(
20
) unsigned DEFAULT NULL COMMENT
'事件结束结束时间(皮秒)'
,
09.
`TIMER_WAIT` bigint(
20
) unsigned DEFAULT NULL COMMENT
'事件等待时间(皮秒)'
,
10.
`NESTING_EVENT_ID` bigint(
20
) unsigned DEFAULT NULL COMMENT
'该事件对应的父事件ID'
,
11.
`NESTING_EVENT_TYPE`
enum
(
'STATEMENT'
,
'STAGE'
,
'WAIT'
) DEFAULT NULL COMMENT
'父事件类型(STATEMENT, STAGE, WAIT)'
12.
) 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_history
3,events_statements_history_long
表结构定义如下:
01.
CREATE TABLE `events_statements_current` (
02.
`THREAD_ID` bigint(
20
) unsigned NOT NULL COMMENT
'线程ID'
,
03.
`EVENT_ID` bigint(
20
) unsigned NOT NULL COMMENT
'事件ID'
,
04.
`END_EVENT_ID` bigint(
20
) unsigned DEFAULT NULL COMMENT
'结束事件ID'
,
05.
`EVENT_NAME` varchar(
128
) NOT NULL COMMENT
'事件名称'
,
06.
`SOURCE` varchar(
64
) DEFAULT NULL COMMENT
'源码位置'
,
07.
`TIMER_START` bigint(
20
) unsigned DEFAULT NULL COMMENT
'事件开始时间(皮秒)'
,
08.
`TIMER_END` bigint(
20
) unsigned DEFAULT NULL COMMENT
'事件结束结束时间(皮秒)'
,
09.
`TIMER_WAIT` bigint(
20
) unsigned DEFAULT NULL COMMENT
'事件等待时间(皮秒)'
,
10.
`LOCK_TIME` bigint(
20
) unsigned NOT NULL COMMENT
'锁时间'
,
11.
`SQL_TEXT` longtext COMMENT
'记录SQL语句'
,
12.
`DIGEST` varchar(
32
) DEFAULT NULL COMMENT
'对SQL_TEXT做MD5产生的32位字符串'
,
13.
`DIGEST_TEXT` longtext COMMENT
'将语句中值部分用问号代替,用于SQL语句归类'
,
14.
`CURRENT_SCHEMA` varchar(
64
) DEFAULT NULL COMMENT
'默认的数据库名'
,
15.
`OBJECT_TYPE` varchar(
64
) DEFAULT NULL COMMENT
'保留字段'
,
16.
`OBJECT_SCHEMA` varchar(
64
) DEFAULT NULL COMMENT
'保留字段'
,
17.
`OBJECT_NAME` varchar(
64
) DEFAULT NULL COMMENT
'保留字段'
,
18.
`OBJECT_INSTANCE_BEGIN` bigint(
20
) unsigned DEFAULT NULL COMMENT
'内存地址'
,
19.
`MYSQL_ERRNO`
int
(
11
) DEFAULT NULL COMMENT
''
,
20.
`RETURNED_SQLSTATE` varchar(
5
) DEFAULT NULL COMMENT
''
,
21.
`MESSAGE_TEXT` varchar(
128
) DEFAULT NULL COMMENT
'信息'
,
22.
`ERRORS` bigint(
20
) unsigned NOT NULL COMMENT
'错误数目'
,
23.
`WARNINGS` bigint(
20
) unsigned NOT NULL COMMENT
'警告数目'
,
24.
`ROWS_AFFECTED` bigint(
20
) unsigned NOT NULL COMMENT
'影响的数目'
,
25.
`ROWS_SENT` bigint(
20
) unsigned NOT NULL COMMENT
'返回的记录数'
,
26.
`ROWS_EXAMINED` bigint(
20
) unsigned NOT NULL COMMENT
'读取扫描的记录数目'
,
27.
`CREATED_TMP_DISK_TABLES` bigint(
20
) unsigned NOT NULL COMMENT
'创建磁盘临时表数目'
,
28.
`CREATED_TMP_TABLES` bigint(
20
) unsigned NOT NULL COMMENT
'创建临时表数目'
,
29.
`SELECT_FULL_JOIN` bigint(
20
) unsigned NOT NULL COMMENT
'join时,第一个表为全表扫描的数目'
,
30.
`SELECT_FULL_RANGE_JOIN` bigint(
20
) unsigned NOT NULL COMMENT
'引用表采用range方式扫描的数目'
,
31.
`SELECT_RANGE` bigint(
20
) unsigned NOT NULL COMMENT
'join时,第一个表采用range方式扫描的数目'
,
32.
`SELECT_RANGE_CHECK` bigint(
20
) unsigned NOT NULL COMMENT
''
,
33.
`SELECT_SCAN` bigint(
20
) unsigned NOT NULL COMMENT
'join时,第一个表位全表扫描的数目'
,
34.
`SORT_MERGE_PASSES` bigint(
20
) unsigned NOT NULL COMMENT
''
,
35.
`SORT_RANGE` bigint(
20
) unsigned NOT NULL COMMENT
'范围排序数目'
,
36.
`SORT_ROWS` bigint(
20
) unsigned NOT NULL COMMENT
'排序的记录数目'
,
37.
`SORT_SCAN` bigint(
20
) unsigned NOT NULL COMMENT
'全表排序数目'
,
38.
`NO_INDEX_USED` bigint(
20
) unsigned NOT NULL COMMENT
'没有使用索引数目'
,
39.
`NO_GOOD_INDEX_USED` bigint(
20
) unsigned NOT NULL COMMENT
''
,
40.
`NESTING_EVENT_ID` bigint(
20
) unsigned DEFAULT NULL COMMENT
'该事件对应的父事件ID'
,
41.
`NESTING_EVENT_TYPE`
enum
(
'STATEMENT'
,
'STAGE'
,
'WAIT'
) DEFAULT NULL COMMENT
'父事件类型(STATEMENT, STAGE, WAIT)'
42.
) 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
01.
zjy
@performance_schema
12
:
03
:
27
>select * from users;
02.
+------------------+---------------------+-------------------+
03.
| USER | CURRENT_CONNECTIONS | TOTAL_CONNECTIONS |
04.
+------------------+---------------------+-------------------+
05.
| debian-sys-maint |
0
|
36
|
06.
| zjy |
1
|
22285
|
07.
| dchat_php |
0
|
37864
|
08.
| dxyslave |
2
|
9
|
09.
| nagios |
0
|
10770
|
10.
| dchat_data |
140
|
2233023
|
11.
| NULL |
0
|
15866
|
12.
| dchat_api |
160
|
2754212
|
13.
| mha_data |
1
|
36
|
14.
| backup |
0
|
15
|
15.
| cacti |
0
|
4312
|
16.
| kol |
10
|
172414
|
17.
+------------------+---------------------+-------------------+
18.
12
rows in set (
0.00
sec)
19.
20.
zjy
@performance_schema
12
:
03
:
34
>select * from hosts;
21.
+-----------------+---------------------+-------------------+
22.
| HOST | CURRENT_CONNECTIONS | TOTAL_CONNECTIONS |
23.
+-----------------+---------------------+-------------------+
24.
|
192.168
.
100.218
|
150
|
2499422
|
25.
|
192.168
.
100.240
|
10
|
172429
|
26.
|
192.168
.
100.139
|
0
|
698
|
27.
|
192.168
.
100.21
|
0
|
2
|
28.
|
192.168
.
100.220
|
150
|
2526136
|
29.
|
192.168
.
100.25
|
1
|
7
|
30.
| NULL |
0
|
15867
|
31.
|
192.168
.
100.241
|
0
|
21558
|
32.
|
192.168
.
100.191
|
1
|
34
|
33.
| localhost |
0
|
10807
|
34.
|
192.168
.
100.118
|
1
|
2
|
35.
|
192.168
.
100.251
|
0
|
4312
|
36.
|
192.168
.
100.23
|
1
|
31
|
37.
|
192.168
.
100.193
|
0
|
15
|
38.
+-----------------+---------------------+-------------------+
39.
14
rows in set (
0.01
sec)
40.
41.
zjy
@performance_schema
12
:
05
:
21
>select * from accounts;
42.
+------------------+-----------------+---------------------+-------------------+
43.
| USER | HOST | CURRENT_CONNECTIONS | TOTAL_CONNECTIONS |
44.
+------------------+-----------------+---------------------+-------------------+
45.
| cacti |
192.168
.
100.251
|
0
|
4313
|
46.
| debian-sys-maint | localhost |
0
|
36
|
47.
| backup |
192.168
.
100.193
|
0
|
15
|
48.
| dchat_api |
192.168
.
100.220
|
80
|
1382585
|
49.
| dchat_php |
192.168
.
100.220
|
0
|
20292
|
50.
| zjy |
192.168
.
100.139
|
0
|
698
|
51.
| zjy |
192.168
.
100.241
|
0
|
21558
|
52.
| mha_data |
192.168
.
100.191
|
1
|
34
|
53.
| dxyslave |
192.168
.
100.118
|
1
|
2
|
54.
| kol |
192.168
.
100.240
|
10
|
172431
|
55.
| dxyslave |
192.168
.
100.25
|
1
|
7
|
56.
| dchat_data |
192.168
.
100.218
|
70
|
1109974
|
57.
| zjy |
192.168
.
100.23
|
1
|
31
|
58.
| dchat_php |
192.168
.
100.218
|
0
|
17572
|
59.
| dchat_data |
192.168
.
100.220
|
70
|
1123306
|
60.
| NULL | NULL |
0
|
15868
|
61.
| mha_data |
192.168
.
100.21
|
0
|
2
|
62.
| dchat_api |
192.168
.
100.218
|
80
|
1371918
|
63.
| nagios | localhost |
0
|
10771
|
64.
+------------------+-----------------+---------------------+-------------------+
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
1.
CREATE TABLE `events_waits_summary_global_by_event_name` (
2.
`EVENT_NAME` varchar(
128
) NOT NULL COMMENT
'事件名称'
,
3.
`COUNT_STAR` bigint(
20
) unsigned NOT NULL COMMENT
'事件计数'
,
4.
`SUM_TIMER_WAIT` bigint(
20
) unsigned NOT NULL COMMENT
'总的等待时间'
,
5.
`MIN_TIMER_WAIT` bigint(
20
) unsigned NOT NULL COMMENT
'最小等待时间'
,
6.
`AVG_TIMER_WAIT` bigint(
20
) unsigned NOT NULL COMMENT
'平均等待时间'
,
7.
`MAX_TIMER_WAIT` bigint(
20
) unsigned NOT NULL COMMENT
'最大等待时间'
8.
) ENGINE=PERFORMANCE_SCHEMA DEFAULT CHARSET=utf8
2,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。
01.
CREATE TABLE `events_waits_summary_by_instance` (
02.
`EVENT_NAME` varchar(
128
) NOT NULL COMMENT
'事件名称'
,
03.
`OBJECT_INSTANCE_BEGIN` bigint(
20
) unsigned NOT NULL COMMENT
'内存地址'
,
04.
`COUNT_STAR` bigint(
20
) unsigned NOT NULL COMMENT
'事件计数'
,
05.
`SUM_TIMER_WAIT` bigint(
20
) unsigned NOT NULL COMMENT
'总的等待时间'
,
06.
`MIN_TIMER_WAIT` bigint(
20
) unsigned NOT NULL COMMENT
'最小等待时间'
,
07.
`AVG_TIMER_WAIT` bigint(
20
) unsigned NOT NULL COMMENT
'平均等待时间'
,
08.
`MAX_TIMER_WAIT` bigint(
20
) unsigned NOT NULL COMMENT
'最大等待时间'
09.
) ENGINE=PERFORMANCE_SCHEMA DEFAULT CHARSET=utf8
3,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。
01.
CREATE TABLE `events_waits_summary_by_thread_by_event_name` (
02.
`THREAD_ID` bigint(
20
) unsigned NOT NULL COMMENT
'线程ID'
,
03.
`EVENT_NAME` varchar(
128
) NOT NULL COMMENT
'事件名称'
,
04.
`COUNT_STAR` bigint(
20
) unsigned NOT NULL COMMENT
'事件计数'
,
05.
`SUM_TIMER_WAIT` bigint(
20
) unsigned NOT NULL COMMENT
'总的等待时间'
,
06.
`MIN_TIMER_WAIT` bigint(
20
) unsigned NOT NULL COMMENT
'最小等待时间'
,
07.
`AVG_TIMER_WAIT` bigint(
20
) unsigned NOT NULL COMMENT
'平均等待时间'
,
08.
`MAX_TIMER_WAIT` bigint(
20
) unsigned NOT NULL COMMENT
'最大等待时间'
09.
) ENGINE=PERFORMANCE_SCHEMA DEFAULT CHARSET=utf8
4,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。
01.
CREATE TABLE `events_statements_summary_by_digest` (
02.
`SCHEMA_NAME` varchar(
64
) DEFAULT NULL COMMENT
'库名'
,
03.
`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'
,
04.
`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。'
,
05.
`COUNT_STAR` bigint(
20
) unsigned NOT NULL COMMENT
'事件计数'
,
06.
`SUM_TIMER_WAIT` bigint(
20
) unsigned NOT NULL COMMENT
'总的等待时间'
,
07.
`MIN_TIMER_WAIT` bigint(
20
) unsigned NOT NULL COMMENT
'最小等待时间'
,
08.
`AVG_TIMER_WAIT` bigint(
20
) unsigned NOT NULL COMMENT
'平均等待时间'
,
09.
`MAX_TIMER_WAIT` bigint(
20
) unsigned NOT NULL COMMENT
'最大等待时间'
,
10.
`SUM_LOCK_TIME` bigint(
20
) unsigned NOT NULL COMMENT
'锁时间总时长'
,
11.
`SUM_ERRORS` bigint(
20
) unsigned NOT NULL COMMENT
'错误数的总'
,
12.
`SUM_WARNINGS` bigint(
20
) unsigned NOT NULL COMMENT
'警告的总数'
,
13.
`SUM_ROWS_AFFECTED` bigint(
20
) unsigned NOT NULL COMMENT
'影响的总数目'
,
14.
`SUM_ROWS_SENT` bigint(
20
) unsigned NOT NULL COMMENT
'返回总数目'
,
15.
`SUM_ROWS_EXAMINED` bigint(
20
) unsigned NOT NULL COMMENT
'总的扫描的数目'
,
16.
`SUM_CREATED_TMP_DISK_TABLES` bigint(
20
) unsigned NOT NULL COMMENT
'创建磁盘临时表的总数目'
,
17.
`SUM_CREATED_TMP_TABLES` bigint(
20
) unsigned NOT NULL COMMENT
'创建临时表的总数目'
,
18.
`SUM_SELECT_FULL_JOIN` bigint(
20
) unsigned NOT NULL COMMENT
'第一个表全表扫描的总数目'
,
19.
`SUM_SELECT_FULL_RANGE_JOIN` bigint(
20
) unsigned NOT NULL COMMENT
'总的采用range方式扫描的数目'
,
20.
`SUM_SELECT_RANGE` bigint(
20
) unsigned NOT NULL COMMENT
'第一个表采用range方式扫描的总数目'
,
21.
`SUM_SELECT_RANGE_CHECK` bigint(
20
) unsigned NOT NULL COMMENT
''
,
22.
`SUM_SELECT_SCAN` bigint(
20
) unsigned NOT NULL COMMENT
'第一个表位全表扫描的总数目'
,
23.
`SUM_SORT_MERGE_PASSES` bigint(
20
) unsigned NOT NULL COMMENT
''
,
24.
`SUM_SORT_RANGE` bigint(
20
) unsigned NOT NULL COMMENT
'范围排序总数'
,
25.
`SUM_SORT_ROWS` bigint(
20
) unsigned NOT NULL COMMENT
'排序的记录总数目'
,
26.
`SUM_SORT_SCAN` bigint(
20
) unsigned NOT NULL COMMENT
'第一个表排序扫描总数目'
,
27.
`SUM_NO_INDEX_USED` bigint(
20
) unsigned NOT NULL COMMENT
'没有使用索引总数'
,
28.
`SUM_NO_GOOD_INDEX_USED` bigint(
20
) unsigned NOT NULL COMMENT
''
,
29.
`FIRST_SEEN` timestamp NOT NULL DEFAULT
'0000-00-00 00:00:00'
COMMENT
'第一次执行时间'
,
30.
`LAST_SEEN` timestamp NOT NULL DEFAULT
'0000-00-00 00:00:00'
COMMENT
'最后一次执行时间'
31.
) ENGINE=PERFORMANCE_SCHEMA DEFAULT CHARSET=utf8
7,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_MISC
11,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_WRITE
INSERT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_INSERT
12,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 lock
internal 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 external
14,Connection Summaries表:account、user、host
events_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_name
15,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:
01.
zjy
@performance_schema
11
:
36
:
22
><strong>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
02.
</strong>***************************
1
. row ***************************<strong>
03.
SCHEMA_NAME</strong>: dchat
04.
<strong>DIGEST_TEXT</strong>: SELECT ...
05.
<strong>COUNT_STAR</strong>:
1161210102
06.
SUM_ROWS_SENT:
1161207842
07.
SUM_ROWS_EXAMINED:
0
<strong>
08.
FIRST_SEEN</strong>:
2016
-
02
-
17
00
:
36
:
46
<strong>
09.
LAST_SEEN</strong>:
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:
01.
zjy
@performance_schema
11
:
36
:
28
><strong>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
02.
</strong>***************************
1
. row ***************************<strong>
03.
SCHEMA_NAME</strong>: dchat
04.
<strong>DIGEST_TEXT</strong>: SELECT ...
05.
COUNT_STAR:
1
<strong>
06.
AVG_TIMER_WAIT</strong>:
273238183964000
07.
SUM_ROWS_SENT:
50208
08.
SUM_ROWS_EXAMINED:
5565651
<strong>
09.
FIRST_SEEN</strong>:
2016
-
02
-
22
13
:
27
:
33
<strong>
10.
LAST_SEEN</strong>:
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_EXAMINED
4,哪个SQL使用的临时表最多:
SUM_CREATED_TMP_DISK_TABLES、SUM_CREATED_TMP_TABLES
5,哪个SQL返回的结果集最多:
SUM_ROWS_SENT
6,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):
01.
zjy
@performance_schema
12
:
16
:
18
><strong>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
02.
</strong>***************************
1
. row ***************************
03.
FILE_NAME: /var/lib/mysql/<strong>ibdata1 #文件</strong>
04.
EVENT_NAME: wait/io/file/innodb/innodb_data_file
05.
COUNT_READ:
544
06.
SUM_NUMBER_OF_BYTES_READ:
10977280
07.
COUNT_WRITE:
3700729
08.
SUM_NUMBER_OF_BYTES_WRITE:
1433734217728
09.
***************************
2
. row ***************************
10.
FILE_NAME: /var/lib/mysql/dchat/<strong>fans.ibd #表</strong>
11.
EVENT_NAME: wait/io/file/innodb/innodb_data_file
12.
COUNT_READ:
9370680
13.
SUM_NUMBER_OF_BYTES_READ:
153529188352
14.
COUNT_WRITE:
67576376
15.
SUM_NUMBER_OF_BYTES_WRITE:
1107815432192
8,哪个索引使用最多:
1.
zjy
@performance_schema
12
:
18
:
42
><strong>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
;
2.
</strong>+-------------+------------+-------------+--------------+--------------+--------------+
3.
| OBJECT_NAME | INDEX_NAME | COUNT_FETCH | COUNT_INSERT | COUNT_UPDATE | COUNT_DELETE |
4.
+-------------+------------+-------------+--------------+--------------+--------------+
5.
| <strong>fans</strong> | <strong>PRIMARY</strong> |
29002695158
|
0
|
296373434
|
0
|
6.
+-------------+------------+-------------+--------------+--------------+--------------+
7.
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:
1.
zjy
@performance_schema
12
:
23
:
22
><strong>SELECT OBJECT_SCHEMA, OBJECT_NAME, INDEX_NAME FROM table_io_waits_summary_by_index_usage WHERE INDEX_NAME IS NOT NULL AND COUNT_STAR =
0
AND OBJECT_SCHEMA <>
'mysql'
ORDER BY OBJECT_SCHEMA,OBJECT_NAME;</strong>
10,哪个等待事件消耗的时间最多:
1.
zjy
@performance_schema
12
:
25
:
22
><strong>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
;</strong>
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:
001.
比如分析包含count(*)的某条SQL语句,具体如下:
002.
003.
SELECT
004.
EVENT_ID,
005.
sql_text
006.
FROM events_statements_history
007.
WHERE sql_text LIKE
'%count(*)%'
;
008.
+----------+--------------------------------------+
009.
| EVENT_ID | sql_text |
010.
+----------+--------------------------------------+
011.
|
1690
| select count(*) from chuck.test_slow |
012.
+----------+--------------------------------------+
013.
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。
014.
015.
a.查看每个阶段的时间消耗:
016.
SELECT
017.
event_id,
018.
EVENT_NAME,
019.
SOURCE,
020.
TIMER_END - TIMER_START
021.
FROM events_stages_history_long
022.
WHERE NESTING_EVENT_ID =
1690
;
023.
+----------+--------------------------------+----------------------+-----------------------+
024.
| event_id | EVENT_NAME | SOURCE | TIMER_END-TIMER_START |
025.
+----------+--------------------------------+----------------------+-----------------------+
026.
|
1691
| stage/sql/init | mysqld.cc:
990
|
316945000
|
027.
|
1693
| stage/sql/checking permissions | sql_parse.cc:
5776
|
26774000
|
028.
|
1695
| stage/sql/Opening tables | sql_base.cc:
4970
|
41436934000
|
029.
|
2638
| stage/sql/init | sql_select.cc:
1050
|
85757000
|
030.
|
2639
| stage/sql/System lock | lock.cc:
303
|
40017000
|
031.
|
2643
| stage/sql/optimizing | sql_optimizer.cc:
138
|
38562000
|
032.
|
2644
| stage/sql/statistics | sql_optimizer.cc:
362
|
52845000
|
033.
|
2645
| stage/sql/preparing | sql_optimizer.cc:
485
|
53196000
|
034.
|
2646
| stage/sql/executing | sql_executor.cc:
112
|
3153000
|
035.
|
2647
| stage/sql/Sending data | sql_executor.cc:
192
|
7369072089000
|
036.
|
4304138
| stage/sql/end | sql_select.cc:
1105
|
19920000
|
037.
|
4304139
| stage/sql/query end | sql_parse.cc:
5463
|
44721000
|
038.
|
4304145
| stage/sql/closing tables | sql_parse.cc:
5524
|
61723000
|
039.
|
4304152
| stage/sql/freeing items | sql_parse.cc:
6838
|
455678000
|
040.
|
4304155
| stage/sql/logging slow query | sql_parse.cc:
2258
|
83348000
|
041.
|
4304159
| stage/sql/cleaning up | sql_parse.cc:
2163
|
4433000
|
042.
+----------+--------------------------------+----------------------+-----------------------+
043.
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
044.
045.
b.查看某个阶段的锁等待情况
046.
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。
047.
SELECT
048.
event_id,
049.
event_name,
050.
source,
051.
timer_wait,
052.
object_name,
053.
index_name,
054.
operation,
055.
nesting_event_id
056.
FROM events_waits_history_long
057.
WHERE nesting_event_id =
2647
;
058.
+----------+---------------------------+-----------------+------------+-------------+------------+-----------+------------------+
059.
| event_id | event_name | source | timer_wait | object_name | index_name | operation | nesting_event_id |
060.
+----------+---------------------------+-----------------+------------+-------------+------------+-----------+------------------+
061.
|
190607
| wait/io/table/sql/handler | handler.cc:
2842
|
1845888
| test_slow | idx_c1 | fetch |
2647
|
062.
|
190608
| wait/io/table/sql/handler | handler.cc:
2842
|
1955328
| test_slow | idx_c1 | fetch |
2647
|
063.
|
190609
| wait/io/table/sql/handler | handler.cc:
2842
|
1929792
| test_slow | idx_c1 | fetch |
2647
|
064.
|
190610
| wait/io/table/sql/handler | handler.cc:
2842
|
1869600
| test_slow | idx_c1 | fetch |
2647
|
065.
|
190611
| wait/io/table/sql/handler | handler.cc:
2842
|
1922496
| test_slow | idx_c1 | fetch |
2647
|
066.
+----------+---------------------------+-----------------+------------+-------------+------------+-----------+------------------+
067.
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。
068.
069.
(
2
).模拟innodb行锁等待的例子
070.
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。
071.
072.
SELECT
073.
statement.EVENT_ID,
074.
stages.event_id,
075.
statement.sql_text,
076.
stages.event_name,
077.
stages.timer_wait
078.
FROM events_statements_history_long statement
079.
join events_stages_history_long stages
080.
on statement.event_id=stages.nesting_event_id
081.
WHERE statement.sql_text =
'update test_icp set y=y+1 where x=1'
;
082.
+----------+----------+-------------------------------------+--------------------------------+----------------+
083.
| EVENT_ID | event_id | sql_text | event_name | timer_wait |
084.
+----------+----------+-------------------------------------+--------------------------------+----------------+
085.
|
5816
|
5817
| update test_icp set y=y+
1
where x=
1
| stage/sql/init |
195543000
|
086.
|
5816
|
5819
| update test_icp set y=y+
1
where x=
1
| stage/sql/checking permissions |
22730000
|
087.
|
5816
|
5821
| update test_icp set y=y+
1
where x=
1
| stage/sql/Opening tables |
66079000
|
088.
|
5816
|
5827
| update test_icp set y=y+
1
where x=
1
| stage/sql/init |
89116000
|
089.
|
5816
|
5828
| update test_icp set y=y+
1
where x=
1
| stage/sql/System lock |
218744000
|
090.
|
5816
|
5832
| update test_icp set y=y+
1
where x=
1
| stage/sql/updating |
6001362045000
|
091.
|
5816
|
5968
| update test_icp set y=y+
1
where x=
1
| stage/sql/end |
10435000
|
092.
|
5816
|
5969
| update test_icp set y=y+
1
where x=
1
| stage/sql/query end |
85979000
|
093.
|
5816
|
5983
| update test_icp set y=y+
1
where x=
1
| stage/sql/closing tables |
56562000
|
094.
|
5816
|
5990
| update test_icp set y=y+
1
where x=
1
| stage/sql/freeing items |
83563000
|
095.
|
5816
|
5992
| update test_icp set y=y+
1
where x=
1
| stage/sql/cleaning up |
4589000
|
096.
+----------+----------+-------------------------------------+--------------------------------+----------------+
097.
查看wait事件:
098.
SELECT
099.
event_id,
100.
event_name,
101.
source,
102.
timer_wait,
103.
object_name,
104.
index_name,
105.
operation,
106.
nesting_event_id
107.
FROM events_waits_history_long
108.
WHERE nesting_event_id =
5832
;
109.
***************************
1
. row ***************************
110.
event_id:
5832
111.
event_name: wait/io/table/sql/handler
112.
source: handler.cc:
2782
113.
timer_wait:
6005946156624
114.
object_name: test_icp
115.
index_name: PRIMARY
116.
operation: fetch
117.
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。
118.
119.
(
3
).模拟MDL锁等待的例子
120.
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。
121.
122.
SELECT
123.
statement.EVENT_ID,
124.
stages.event_id,
125.
statement.sql_text,
126.
stages.event_name as stage_name,
127.
stages.timer_wait as stage_time
128.
FROM events_statements_history_long statement
129.
left join events_stages_history_long stages
130.
on statement.event_id=stages.nesting_event_id
131.
WHERE statement.sql_text =
'alter table test_slow modify c2 varchar(152)'
;
132.
+-----------+-----------+----------------------------------------------+----------------------------------------------------+---------------+
133.
| EVENT_ID | event_id | sql_text | stage_name | stage_time |
134.
+-----------+-----------+----------------------------------------------+----------------------------------------------------+---------------+
135.
|
326526744
|
326526745
| alter table test_slow modify c2 varchar(
152
) | stage/sql/init |
216662000
|
136.
|
326526744
|
326526747
| alter table test_slow modify c2 varchar(
152
) | stage/sql/checking permissions |
18183000
|
137.
|
326526744
|
326526748
| alter table test_slow modify c2 varchar(
152
) | stage/sql/checking permissions |
10294000
|
138.
|
326526744
|
326526750
| alter table test_slow modify c2 varchar(
152
) | stage/sql/init |
4783000
|
139.
|
326526744
|
326526751
| alter table test_slow modify c2 varchar(
152
) | stage/sql/Opening tables |
140172000
|
140.
|
326526744
|
326526760
| alter table test_slow modify c2 varchar(
152
) | stage/sql/setup |
157643000
|
141.
|
326526744
|
326526769
| alter table test_slow modify c2 varchar(
152
) | stage/sql/creating table |
8723217000
|
142.
|
326526744
|
326526803
| alter table test_slow modify c2 varchar(
152
) | stage/sql/After create |
257332000
|
143.
|
326526744
|
326526832
| alter table test_slow modify c2 varchar(
152
) | stage/sql/Waiting
for
table metadata lock |
1000181831000
|
144.
|
326526744
|
326526835
| alter table test_slow modify c2 varchar(
152
) | stage/sql/After create |
33483000
|
145.
|
326526744
|
326526838
| alter table test_slow modify c2 varchar(
152
) | stage/sql/Waiting
for
table metadata lock |
1000091810000
|
146.
|
326526744
|
326526841
| alter table test_slow modify c2 varchar(
152
) | stage/sql/After create |
17187000
|
147.
|
326526744
|
326526844
| alter table test_slow modify c2 varchar(
152
) | stage/sql/Waiting
for
table metadata lock |
1000126464000
|
148.
|
326526744
|
326526847
| alter table test_slow modify c2 varchar(
152
) | stage/sql/After create |
27472000
|
149.
|
326526744
|
326526850
| alter table test_slow modify c2 varchar(
152
) | stage/sql/Waiting
for
table metadata lock |
561996133000
|
150.
|
326526744
|
326526853
| alter table test_slow modify c2 varchar(
152
) | stage/sql/After create |
124876000
|
151.
|
326526744
|
326526877
| alter table test_slow modify c2 varchar(
152
) | stage/sql/System lock |
30659000
|
152.
|
326526744
|
326526881
| alter table test_slow modify c2 varchar(
152
) | stage/sql/preparing
for
alter table |
40246000
|
153.
|
326526744
|
326526889
| alter table test_slow modify c2 varchar(
152
) | stage/sql/altering table |
36628000
|
154.
|
326526744
|
326528280
| alter table test_slow modify c2 varchar(
152
) | stage/sql/end |
43824000
|
155.
|
326526744
|
326528281
| alter table test_slow modify c2 varchar(
152
) | stage/sql/query end |
112557000
|
156.
|
326526744
|
326528299
| alter table test_slow modify c2 varchar(
152
) | stage/sql/closing tables |
27707000
|
157.
|
326526744
|
326528305
| alter table test_slow modify c2 varchar(
152
) | stage/sql/freeing items |
201614000
|
158.
|
326526744
|
326528308
| alter table test_slow modify c2 varchar(
152
) | stage/sql/cleaning up |
3584000
|
159.
+-----------+-----------+----------------------------------------------+----------------------------------------------------+---------------+
160.
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。
161.
SELECT
162.
event_id,
163.
event_name,
164.
source,
165.
timer_wait,
166.
object_name,
167.
index_name,
168.
operation,
169.
nesting_event_id
170.
FROM events_waits_history_long
171.
WHERE nesting_event_id =
326526850
;
172.
+-----------+---------------------------------------------------+------------------+--------------+-------------+------------+------------+------------------+
173.
| event_id | event_name | source | timer_wait | object_name | index_name | operation | nesting_event_id |
174.
+-----------+---------------------------------------------------+------------------+--------------+-------------+------------+------------+------------------+
175.
|
326526851
| wait/synch/cond/sql/MDL_context::COND_wait_status | mdl.cc:
1327
|
562417991328
| NULL | NULL | timed_wait |
326526850
|
176.
|
326526852
| wait/synch/mutex/mysys/my_thread_var::mutex | sql_class.h:
3481
|
733248
| NULL | NULL | lock |
326526850
|
177.
+-----------+---------------------------------------------------+------------------+--------------+-------------+------------+------------+------------------+
178.
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。
总结:
本文通过对Performance Schema数据库的介绍,主要用于收集数据库服务器性能参数:①提供进程等待的详细信息,包括锁、互斥变量、文件信息;②保存历史的事件汇总信息,为提供MySQL服务器性能做出详细的判断;③对于新增和删除监控事件点都非常容易,并可以改变mysql服务器的监控周期,例如(CYCLE、MICROSECOND)。通过该库得到数据库运行的统计信息,更好分析定位问题和完善监控信息。类似的监控还有:
1.
打开标准的innodb监控:
2.
CREATE TABLE innodb_monitor (a INT) ENGINE=INNODB;
3.
打开innodb的锁监控:
4.
CREATE TABLE innodb_lock_monitor (a INT) ENGINE=INNODB;
5.
打开innodb表空间监控:
6.
CREATE TABLE innodb_tablespace_monitor (a INT) ENGINE=INNODB;
7.
打开innodb表监控:
8.
CREATE TABLE innodb_table_monitor (a INT) ENGINE=INNODB;
来源:CSDN
作者:isoleo
链接:https://blog.csdn.net/isoleo/article/details/51180593