MySQL5.6 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。[MySQL][]5.5默认是关闭的，需要手动开启，在配置文件里添加：
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1. [mysqld]
2. performance_schema=ON
查看是否开启：
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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：
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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。
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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。
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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：
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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：
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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：
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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：
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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：
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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。
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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）
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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。
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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：
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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：
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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：
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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
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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
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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。
view source print ?
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。
view source print ?
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。
view source print ?
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：
view source print ?
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：
view source print ?
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）：
view source print ?
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：
view source print ?
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：
view source print ?
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：
view source print ?
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：
view source print ?
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：
view source print ?
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;
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