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MySQL5.6PERFORMANCE_SCHEMA说明
2025-07-22 09:58  点击:0

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：

view sourceprint?1.[mysqld]2.performance_schema=ON

查看是否开启：

view sourceprint?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：

view sourceprint?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。

view sourceprint?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。

view sourceprint?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：

view sourceprint?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：

view sourceprint?1.[mysqld]2.#performance_schema3.performance_schema_consumer_events_waits_current=on4.performance_schema_consumer_events_stages_current=on5.performance_schema_consumer_events_statements_current=on6.performance_schema_consumer_events_waits_history=on7.performance_schema_consumer_events_stages_history=on8.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：

view sourceprint?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：

view sourceprint?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：

view sourceprint?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。

view sourceprint?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）

view sourceprint?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。

view sourceprint?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：

view sourceprint?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：

view sourceprint?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：

view sourceprint?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

view sourceprint?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

view sourceprint?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 sourceprint?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 sourceprint?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 sourceprint?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 sourceprint?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 1G02.</strong>*************************** 1. row ***************************<strong>03.SCHEMA_NAME</strong>: dchat04.<strong>DIGEST_TEXT</strong>: SELECT ...05.<strong>COUNT_STAR</strong>: 116121010206.SUM_ROWS_SENT: 116120784207.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 sourceprint?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 1G02.</strong>*************************** 1. row ***************************<strong>03.SCHEMA_NAME</strong>: dchat04.<strong>DIGEST_TEXT</strong>: SELECT ...05.COUNT_STAR: 1<strong>06.AVG_TIMER_WAIT</strong>: 27323818396400007.SUM_ROWS_SENT: 5020808.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 sourceprint?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 2G02.</strong>*************************** 1. row ***************************03.FILE_NAME: /var/lib/mysql/<strong>ibdata1 #文件</strong>04.EVENT_NAME: wait/io/file/innodb/innodb_data_file05.COUNT_READ: 54406.SUM_NUMBER_OF_BYTES_READ: 1097728007.COUNT_WRITE: 370072908.SUM_NUMBER_OF_BYTES_WRITE: 143373421772809.*************************** 2. row ***************************10.FILE_NAME: /var/lib/mysql/dchat/<strong>fans.ibd #表</strong>11.EVENT_NAME: wait/io/file/innodb/innodb_data_file12.COUNT_READ: 937068013.SUM_NUMBER_OF_BYTES_READ: 15352918835214.COUNT_WRITE: 6757637615.SUM_NUMBER_OF_BYTES_WRITE: 1107815432192

8，哪个索引使用最多：

view sourceprint?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 sourceprint?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 sourceprint?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 sourceprint?001.比如分析包含count(*)的某条SQL语句，具体如下：002. 003.SELECT004.EVENT_ID,005.sql_text006.FROM events_statements_history007.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.SELECT017.event_id,018.EVENT_NAME,019.SOURCE,020.TIMER_END - TIMER_START021.FROM events_stages_history_long022.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.SELECT048.event_id,049.event_name,050.source,051.timer_wait,052.object_name,053.index_name,054.operation,055.nesting_event_id056.FROM events_waits_history_long057.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.SELECT073.statement.EVENT_ID,074.stages.event_id,075.statement.sql_text,076.stages.event_name,077.stages.timer_wait078.FROM events_statements_history_long statement079.join events_stages_history_long stages080.on statement.event_id=stages.nesting_event_id081.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.SELECT099.event_id,100.event_name,101.source,102.timer_wait,103.object_name,104.index_name,105.operation,106.nesting_event_id107.FROM events_waits_history_long108.WHERE nesting_event_id = 5832;109.*************************** 1. row ***************************110.event_id: 5832111.event_name: wait/io/table/sql/handler112.source: handler.cc:2782113.timer_wait: 6005946156624114.object_name: test_icp115.index_name: PRIMARY116.operation: fetch117.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.SELECT123.statement.EVENT_ID,124.stages.event_id,125.statement.sql_text,126.stages.event_name as stage_name,127.stages.timer_wait as stage_time128.FROM events_statements_history_long statement129.left join events_stages_history_long stages130.on statement.event_id=stages.nesting_event_id131.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/Waitingfor 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/Waitingfor 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/Waitingfor 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/Waitingfor 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/preparingfor 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.SELECT162.event_id,163.event_name,164.source,165.timer_wait,166.object_name,167.index_name,168.operation,169.nesting_event_id170.FROM events_waits_history_long171.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 sourceprint?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;