背景：
MySQL 5.5開(kāi)始新增一個(gè)數據庫：PERFORMANCE_SCHEMA，主要用于收集數據庫服務(wù)器性能參數。并且庫里表的存儲引擎均為PERFORMANCE_SCHEMA，而用戶(hù)是不能創(chuàng )建存儲引擎為PERFORMANCE_SCHEMA的表。MySQL5.5默認是關(guān)閉的，需要手動(dòng)開(kāi)啟，在配置文件里添加：
[mysqld]performance_schema=ON
查看是否開(kāi)啟：
mysql>show variables like 'performance_schema';+--------------------+-------+| Variable_name | Value |+--------------------+-------+| performance_schema | ON |+--------------------+-------+
從MySQL5.6開(kāi)始，默認打開(kāi)，本文就從MySQL5.6來(lái)說(shuō)明，在數據庫使用當中PERFORMANCE_SCHEMA的一些比較常用的功能。具體的信息可以查看官方文檔。
相關(guān)表信息：
一：配置（setup）表：
zjy@performance_schema 10:16:56>show tables like '%setup%';+----------------------------------------+| Tables_in_performance_schema (%setup%) |+----------------------------------------+| setup_actors || setup_consumers || setup_instruments || setup_objects || setup_timers |+----------------------------------------+
1，setup_actors：配置用戶(hù)緯度的監控，默認監控所有用戶(hù)。
zjy@performance_schema 10:19:11>select * from setup_actors;+------+------+------+| HOST | USER | ROLE |+------+------+------+| % | % | % |+------+------+------+
2，setup_consumers：配置events的消費者類(lèi)型，即收集的events寫(xiě)入到哪些統計表中。
zjy@: performance_schema 10:23:35>select * from setup_consumers;+--------------------------------+---------+| NAME | ENABLED |+--------------------------------+---------+| events_stages_current | NO || events_stages_history | NO || events_stages_history_long | NO || events_statements_current | YES || events_statements_history | NO || events_statements_history_long | NO || events_waits_current | NO || events_waits_history | NO || events_waits_history_long | NO || global_instrumentation | YES || thread_instrumentation | YES || statements_digest | YES |+--------------------------------+---------+
這里需要說(shuō)明的是需要查看哪個(gè)就更新其ENABLED列為YES。如：
zjy@performance_schema 10:25:02>update setup_consumers set ENABLED='YES' where NAME in ('events_stages_current','events_waits_current');Query OK, 2 rows affected (0.00 sec)
更新完后立即生效，但是服務(wù)器重啟之后又會(huì )變回默認值，要永久生效需要在配置文件里添加：
[mysqld]#performance_schemaperformance_schema_consumer_events_waits_current=onperformance_schema_consumer_events_stages_current=onperformance_schema_consumer_events_statements_current=onperformance_schema_consumer_events_waits_history=onperformance_schema_consumer_events_stages_history=onperformance_schema_consumer_events_statements_history=on
即在這些表的前面加上：performance_schema_consumer_xxx。表setup_consumers里面的值有個(gè)層級關(guān)系：
global_instrumentation > thread_instrumentation = statements_digest > events_stages_current = events_statements_current = events_waits_current > events_stages_history = events_statements_history = events_waits_history > events_stages_history_long = events_statements_history_long = events_waits_history_long
只有上一層次的為YES，才會(huì )繼續檢查該本層為YES or NO。global_instrumentation是最高級別consumer，如果它設置為NO，則所有的consumer都會(huì )忽略。其中history和history_long存的是current表的歷史記錄條數，history表記錄了每個(gè)線(xiàn)程最近等待的10個(gè)事件，而history_long表則記錄了最近所有線(xiàn)程產(chǎn)生的10000個(gè)事件，這里的10和10000都是可以配置的。這三個(gè)表表結構相同，history和history_long表數據都來(lái)源于current表。長(cháng)度通過(guò)控制參數：
zjy@performance_schema 11:10:03>show variables like 'performance_schema%history%size';+--------------------------------------------------------+-------+| Variable_name | Value |+--------------------------------------------------------+-------+| performance_schema_events_stages_history_long_size | 10000 || performance_schema_events_stages_history_size | 10 || performance_schema_events_statements_history_long_size | 10000 || performance_schema_events_statements_history_size | 10 || performance_schema_events_waits_history_long_size | 10000 || performance_schema_events_waits_history_size | 10 |+--------------------------------------------------------+-------+
3，setup_instruments：配置具體的instrument，主要包含4大類(lèi)：idle、stage/xxx、statement/xxx、wait/xxx：
zjy@performance_schema 10:56:35>select name,count(*) from setup_instruments group by LEFT(name,5);+---------------------------------+----------+| name | count(*) |+---------------------------------+----------+| idle | 1 || stage/sql/After create | 111 || statement/sql/select | 179 || wait/synch/mutex/sql/PAGE::lock | 296 |+---------------------------------+----------+
idle表示socket空閑的時(shí)間，stage類(lèi)表示語(yǔ)句的每個(gè)執行階段的統計，statement類(lèi)統計語(yǔ)句維度的信息，wait類(lèi)統計各種等待事件，比如IO，mutux，spin_lock,condition等。
4，setup_objects：配置監控對象，默認對mysql，performance_schema和information_schema中的表都不監控，而其它DB的所有表都監控。
zjy@performance_schema 11:00:18>select * from setup_objects;+-------------+--------------------+-------------+---------+-------+| OBJECT_TYPE | OBJECT_SCHEMA | OBJECT_NAME | ENABLED | TIMED |+-------------+--------------------+-------------+---------+-------+| TABLE | mysql | % | NO | NO || TABLE | performance_schema | % | NO | NO || TABLE | information_schema | % | NO | NO || TABLE | % | % | YES | YES |+-------------+--------------------+-------------+---------+-------+
5，setup_timers：配置每種類(lèi)型指令的統計時(shí)間單位。MICROSECOND表示統計單位是微妙，CYCLE表示統計單位是時(shí)鐘周期，時(shí)間度量與CPU的主頻有關(guān)，NANOSECOND表示統計單位是納秒。但無(wú)論采用哪種度量單位，最終統計表中統計的時(shí)間都會(huì )裝換到皮秒。（1秒＝1000000000000皮秒）
zjy@performance_schema 11:05:12>select * from setup_timers;+-----------+-------------+| NAME | TIMER_NAME |+-----------+-------------+| idle | MICROSECOND || wait | CYCLE || stage | NANOSECOND || statement | NANOSECOND |+-----------+-------------+
二：instance表
1，cond_instances：條件等待對象實(shí)例
表中記錄了系統中使用的條件變量的對象，OBJECT_INSTANCE_BEGIN為對象的內存地址。
2，file_instances：文件實(shí)例
表中記錄了系統中打開(kāi)了文件的對象，包括ibdata文件，redo文件，binlog文件，用戶(hù)的表文件等，open_count顯示當前文件打開(kāi)的數目，如果重來(lái)沒(méi)有打開(kāi)過(guò)，不會(huì )出現在表中。
zjy@performance_schema 11:20:04>select * from file_instances limit 2,5;+---------------------------------+--------------------------------------+------------+| FILE_NAME | EVENT_NAME | OPEN_COUNT |+---------------------------------+--------------------------------------+------------+| /var/lib/mysql/mysql/plugin.frm | wait/io/file/sql/FRM | 0 || /var/lib/mysql/mysql/plugin.MYI | wait/io/file/myisam/kfile | 1 || /var/lib/mysql/mysql/plugin.MYD | wait/io/file/myisam/dfile | 1 || /var/lib/mysql/ibdata1 | wait/io/file/innodb/innodb_data_file | 2 || /var/lib/mysql/ib_logfile0 | wait/io/file/innodb/innodb_log_file | 2 |+---------------------------------+--------------------------------------+------------+
3，mutex_instances：互斥同步對象實(shí)例
表中記錄了系統中使用互斥量對象的所有記錄，其中name為：wait/synch/mutex/*。LOCKED_BY_THREAD_ID顯示哪個(gè)線(xiàn)程正持有mutex，若沒(méi)有線(xiàn)程持有，則為NULL。
4，rwlock_instances： 讀寫(xiě)鎖同步對象實(shí)例
表中記錄了系統中使用讀寫(xiě)鎖對象的所有記錄，其中name為 wait/synch/rwlock/*。WRITE_LOCKED_BY_THREAD_ID為正在持有該對象的thread_id，若沒(méi)有線(xiàn)程持有，則為NULL。READ_LOCKED_BY_COUNT為記錄了同時(shí)有多少個(gè)讀者持有讀鎖。（通過(guò) events_waits_current 表可以知道，哪個(gè)線(xiàn)程在等待鎖；通過(guò)rwlock_instances知道哪個(gè)線(xiàn)程持有鎖。rwlock_instances的缺陷是，只能記錄持有寫(xiě)鎖的線(xiàn)程，對于讀鎖則無(wú)能為力）。
5，socket_instances：活躍會(huì )話(huà)對象實(shí)例
表中記錄了thread_id,socket_id,ip和port，其它表可以通過(guò)thread_id與socket_instance進(jìn)行關(guān)聯(lián)，獲取IP-PORT信息，能夠與應用對接起來(lái)。
event_name主要包含3類(lèi)：
wait/io/socket/sql/server_unix_socket，服務(wù)端unix監聽(tīng)socket
wait/io/socket/sql/server_tcpip_socket，服務(wù)端tcp監聽(tīng)socket
wait/io/socket/sql/client_connection，客戶(hù)端socket
三：Wait表
1，events_waits_current：記錄了當前線(xiàn)程等待的事件
2，events_waits_history：記錄了每個(gè)線(xiàn)程最近等待的10個(gè)事件
3，events_waits_history_long：記錄了最近所有線(xiàn)程產(chǎn)生的10000個(gè)事件
表結構定義如下：
CREATE TABLE `events_waits_current` ( `THREAD_ID` bigint(20) unsigned NOT NULL COMMENT '線(xiàn)程ID', `EVENT_ID` bigint(20) unsigned NOT NULL COMMENT '當前線(xiàn)程的事件ID，和THREAD_ID確定唯一', `END_EVENT_ID` bigint(20) unsigned DEFAULT NULL COMMENT '當事件開(kāi)始時(shí)，這一列被設置為NULL。當事件結束時(shí)，再更新為當前的事件ID', `EVENT_NAME` varchar(128) NOT NULL COMMENT '事件名稱(chēng)', `SOURCE` varchar(64) DEFAULT NULL COMMENT '該事件產(chǎn)生時(shí)的源碼文件', `TIMER_START` bigint(20) unsigned DEFAULT NULL COMMENT '事件開(kāi)始時(shí)間（皮秒）', `TIMER_END` bigint(20) unsigned DEFAULT NULL COMMENT '事件結束結束時(shí)間（皮秒）', `TIMER_WAIT` bigint(20) unsigned DEFAULT NULL COMMENT '事件等待時(shí)間（皮秒）', `SPINS` int(10) unsigned DEFAULT NULL COMMENT '', `OBJECT_SCHEMA` varchar(64) DEFAULT NULL COMMENT '庫名', `OBJECT_NAME` varchar(512) DEFAULT NULL COMMENT '文件名、表名、IP:SOCK值', `OBJECT_TYPE` varchar(64) DEFAULT NULL COMMENT 'FILE、TABLE、TEMPORARY TABLE', `INDEX_NAME` varchar(64) DEFAULT NULL COMMENT '索引名', `OBJECT_INSTANCE_BEGIN` bigint(20) unsigned NOT NULL COMMENT '內存地址', `NESTING_EVENT_ID` bigint(20) unsigned DEFAULT NULL COMMENT '該事件對應的父事件ID', `NESTING_EVENT_TYPE` enum('STATEMENT','STAGE','WAIT') DEFAULT NULL COMMENT '父事件類(lèi)型(STATEMENT, STAGE, WAIT)', `OPERATION` varchar(32) NOT NULL COMMENT '操作類(lèi)型（lock, read, write）', `NUMBER_OF_BYTES` bigint(20) DEFAULT NULL COMMENT '', `FLAGS` int(10) unsigned DEFAULT NULL COMMENT '標記') ENGINE=PERFORMANCE_SCHEMA DEFAULT CHARSET=utf8
四：Stage 表
1，events_stages_current：記錄了當前線(xiàn)程所處的執行階段
2，events_stages_history：記錄了當前線(xiàn)程所處的執行階段10條歷史記錄
3，events_stages_history_long：記錄了當前線(xiàn)程所處的執行階段10000條歷史記錄
表結構定義如下：
CREATE TABLE `events_stages_current` ( `THREAD_ID` bigint(20) unsigned NOT NULL COMMENT '線(xiàn)程ID', `EVENT_ID` bigint(20) unsigned NOT NULL COMMENT '事件ID', `END_EVENT_ID` bigint(20) unsigned DEFAULT NULL COMMENT '結束事件ID', `EVENT_NAME` varchar(128) NOT NULL COMMENT '事件名稱(chēng)', `SOURCE` varchar(64) DEFAULT NULL COMMENT '源碼位置', `TIMER_START` bigint(20) unsigned DEFAULT NULL COMMENT '事件開(kāi)始時(shí)間（皮秒）', `TIMER_END` bigint(20) unsigned DEFAULT NULL COMMENT '事件結束結束時(shí)間（皮秒）', `TIMER_WAIT` bigint(20) unsigned DEFAULT NULL COMMENT '事件等待時(shí)間（皮秒）', `NESTING_EVENT_ID` bigint(20) unsigned DEFAULT NULL COMMENT '該事件對應的父事件ID', `NESTING_EVENT_TYPE` enum('STATEMENT','STAGE','WAIT') DEFAULT NULL COMMENT '父事件類(lèi)型(STATEMENT, STAGE, WAIT)') ENGINE=PERFORMANCE_SCHEMA DEFAULT CHARSET=utf8
五：Statement 表
1，events_statements_current：通過(guò) thread_id+event_id可以唯一確定一條記錄。Statments表只記錄最頂層的請求，SQL語(yǔ)句或是COMMAND，每條語(yǔ)句一行。event_name形式為statement/sql/*，或statement/com/*
2，events_statements_history
3，events_statements_history_long
表結構定義如下：
CREATE TABLE `events_statements_current` ( `THREAD_ID` bigint(20) unsigned NOT NULL COMMENT '線(xiàn)程ID', `EVENT_ID` bigint(20) unsigned NOT NULL COMMENT '事件ID', `END_EVENT_ID` bigint(20) unsigned DEFAULT NULL COMMENT '結束事件ID', `EVENT_NAME` varchar(128) NOT NULL COMMENT '事件名稱(chēng)', `SOURCE` varchar(64) DEFAULT NULL COMMENT '源碼位置', `TIMER_START` bigint(20) unsigned DEFAULT NULL COMMENT '事件開(kāi)始時(shí)間（皮秒）', `TIMER_END` bigint(20) unsigned DEFAULT NULL COMMENT '事件結束結束時(shí)間（皮秒）', `TIMER_WAIT` bigint(20) unsigned DEFAULT NULL COMMENT '事件等待時(shí)間（皮秒）', `LOCK_TIME` bigint(20) unsigned NOT NULL COMMENT '鎖時(shí)間', `SQL_TEXT` longtext COMMENT '記錄SQL語(yǔ)句', `DIGEST` varchar(32) DEFAULT NULL COMMENT '對SQL_TEXT做MD5產(chǎn)生的32位字符串', `DIGEST_TEXT` longtext COMMENT '將語(yǔ)句中值部分用問(wèn)號代替，用于SQL語(yǔ)句歸類(lèi)', `CURRENT_SCHEMA` varchar(64) DEFAULT NULL COMMENT '默認的數據庫名', `OBJECT_TYPE` varchar(64) DEFAULT NULL COMMENT '保留字段', `OBJECT_SCHEMA` varchar(64) DEFAULT NULL COMMENT '保留字段', `OBJECT_NAME` varchar(64) DEFAULT NULL COMMENT '保留字段', `OBJECT_INSTANCE_BEGIN` bigint(20) unsigned DEFAULT NULL COMMENT '內存地址', `MYSQL_ERRNO` int(11) DEFAULT NULL COMMENT '', `RETURNED_SQLSTATE` varchar(5) DEFAULT NULL COMMENT '', `MESSAGE_TEXT` varchar(128) DEFAULT NULL COMMENT '信息', `ERRORS` bigint(20) unsigned NOT NULL COMMENT '錯誤數目', `WARNINGS` bigint(20) unsigned NOT NULL COMMENT '警告數目', `ROWS_AFFECTED` bigint(20) unsigned NOT NULL COMMENT '影響的數目', `ROWS_SENT` bigint(20) unsigned NOT NULL COMMENT '返回的記錄數', `ROWS_EXAMINED` bigint(20) unsigned NOT NULL COMMENT '讀取掃描的記錄數目', `CREATED_TMP_DISK_TABLES` bigint(20) unsigned NOT NULL COMMENT '創(chuàng )建磁盤(pán)臨時(shí)表數目', `CREATED_TMP_TABLES` bigint(20) unsigned NOT NULL COMMENT '創(chuàng )建臨時(shí)表數目', `SELECT_FULL_JOIN` bigint(20) unsigned NOT NULL COMMENT 'join時(shí)，第一個(gè)表為全表掃描的數目', `SELECT_FULL_RANGE_JOIN` bigint(20) unsigned NOT NULL COMMENT '引用表采用range方式掃描的數目', `SELECT_RANGE` bigint(20) unsigned NOT NULL COMMENT 'join時(shí)，第一個(gè)表采用range方式掃描的數目', `SELECT_RANGE_CHECK` bigint(20) unsigned NOT NULL COMMENT '', `SELECT_SCAN` bigint(20) unsigned NOT NULL COMMENT 'join時(shí)，第一個(gè)表位全表掃描的數目', `SORT_MERGE_PASSES` bigint(20) unsigned NOT NULL COMMENT '', `SORT_RANGE` bigint(20) unsigned NOT NULL COMMENT '范圍排序數目', `SORT_ROWS` bigint(20) unsigned NOT NULL COMMENT '排序的記錄數目', `SORT_SCAN` bigint(20) unsigned NOT NULL COMMENT '全表排序數目', `NO_INDEX_USED` bigint(20) unsigned NOT NULL COMMENT '沒(méi)有使用索引數目', `NO_GOOD_INDEX_USED` bigint(20) unsigned NOT NULL COMMENT '', `NESTING_EVENT_ID` bigint(20) unsigned DEFAULT NULL COMMENT '該事件對應的父事件ID', `NESTING_EVENT_TYPE` enum('STATEMENT','STAGE','WAIT') DEFAULT NULL COMMENT '父事件類(lèi)型(STATEMENT, STAGE, WAIT)') ENGINE=PERFORMANCE_SCHEMA DEFAULT CHARSET=utf8
六：Connection 表
1，users：記錄用戶(hù)連接數信息
2，hosts：記錄了主機連接數信息
3，accounts：記錄了用戶(hù)主機連接數信息
七：Summary 表： Summary表聚集了各個(gè)維度的統計信息包括表維度，索引維度，會(huì )話(huà)維度，語(yǔ)句維度和鎖維度的統計信息
1，events_waits_summary_global_by_event_name：按等待事件類(lèi)型聚合，每個(gè)事件一條記錄
CREATE TABLE `events_waits_summary_global_by_event_name` ( `EVENT_NAME` varchar(128) NOT NULL COMMENT '事件名稱(chēng)', `COUNT_STAR` bigint(20) unsigned NOT NULL COMMENT '事件計數', `SUM_TIMER_WAIT` bigint(20) unsigned NOT NULL COMMENT '總的等待時(shí)間', `MIN_TIMER_WAIT` bigint(20) unsigned NOT NULL COMMENT '最小等待時(shí)間', `AVG_TIMER_WAIT` bigint(20) unsigned NOT NULL COMMENT '平均等待時(shí)間', `MAX_TIMER_WAIT` bigint(20) unsigned NOT NULL COMMENT '最大等待時(shí)間') ENGINE=PERFORMANCE_SCHEMA DEFAULT CHARSET=utf8
2，events_waits_summary_by_instance：按等待事件對象聚合，同一種等待事件，可能有多個(gè)實(shí)例，每個(gè)實(shí)例有不同的內存地址，因此
event_name+object_instance_begin唯一確定一條記錄。
CREATE TABLE `events_waits_summary_by_instance` ( `EVENT_NAME` varchar(128) NOT NULL COMMENT '事件名稱(chēng)', `OBJECT_INSTANCE_BEGIN` bigint(20) unsigned NOT NULL COMMENT '內存地址', `COUNT_STAR` bigint(20) unsigned NOT NULL COMMENT '事件計數', `SUM_TIMER_WAIT` bigint(20) unsigned NOT NULL COMMENT '總的等待時(shí)間', `MIN_TIMER_WAIT` bigint(20) unsigned NOT NULL COMMENT '最小等待時(shí)間', `AVG_TIMER_WAIT` bigint(20) unsigned NOT NULL COMMENT '平均等待時(shí)間', `MAX_TIMER_WAIT` bigint(20) unsigned NOT NULL COMMENT '最大等待時(shí)間') ENGINE=PERFORMANCE_SCHEMA DEFAULT CHARSET=utf8
3，events_waits_summary_by_thread_by_event_name：按每個(gè)線(xiàn)程和事件來(lái)統計，thread_id+event_name唯一確定一條記錄。
CREATE TABLE `events_waits_summary_by_thread_by_event_name` ( `THREAD_ID` bigint(20) unsigned NOT NULL COMMENT '線(xiàn)程ID', `EVENT_NAME` varchar(128) NOT NULL COMMENT '事件名稱(chēng)', `COUNT_STAR` bigint(20) unsigned NOT NULL COMMENT '事件計數', `SUM_TIMER_WAIT` bigint(20) unsigned NOT NULL COMMENT '總的等待時(shí)間', `MIN_TIMER_WAIT` bigint(20) unsigned NOT NULL COMMENT '最小等待時(shí)間', `AVG_TIMER_WAIT` bigint(20) unsigned NOT NULL COMMENT '平均等待時(shí)間', `MAX_TIMER_WAIT` bigint(20) unsigned NOT NULL COMMENT '最大等待時(shí)間') ENGINE=PERFORMANCE_SCHEMA DEFAULT CHARSET=utf8
4，events_stages_summary_global_by_event_name：按事件階段類(lèi)型聚合，每個(gè)事件一條記錄，表結構同上。
5，events_stages_summary_by_thread_by_event_name：按每個(gè)線(xiàn)程和事件來(lái)階段統計，表結構同上。
6，events_statements_summary_by_digest：按照事件的語(yǔ)句進(jìn)行聚合。
CREATE TABLE `events_statements_summary_by_digest` ( `SCHEMA_NAME` varchar(64) DEFAULT NULL COMMENT '庫名', `DIGEST` varchar(32) DEFAULT NULL COMMENT '對SQL_TEXT做MD5產(chǎn)生的32位字符串。如果為consumer表中沒(méi)有打開(kāi)statement_digest選項，則為NULL', `DIGEST_TEXT` longtext COMMENT '將語(yǔ)句中值部分用問(wèn)號代替，用于SQL語(yǔ)句歸類(lèi)。如果為consumer表中沒(méi)有打開(kāi)statement_digest選項，則為NULL。', `COUNT_STAR` bigint(20) unsigned NOT NULL COMMENT '事件計數', `SUM_TIMER_WAIT` bigint(20) unsigned NOT NULL COMMENT '總的等待時(shí)間', `MIN_TIMER_WAIT` bigint(20) unsigned NOT NULL COMMENT '最小等待時(shí)間', `AVG_TIMER_WAIT` bigint(20) unsigned NOT NULL COMMENT '平均等待時(shí)間', `MAX_TIMER_WAIT` bigint(20) unsigned NOT NULL COMMENT '最大等待時(shí)間', `SUM_LOCK_TIME` bigint(20) unsigned NOT NULL COMMENT '鎖時(shí)間總時(shí)長(cháng)', `SUM_ERRORS` bigint(20) unsigned NOT NULL COMMENT '錯誤數的總', `SUM_WARNINGS` bigint(20) unsigned NOT NULL COMMENT '警告的總數', `SUM_ROWS_AFFECTED` bigint(20) unsigned NOT NULL COMMENT '影響的總數目', `SUM_ROWS_SENT` bigint(20) unsigned NOT NULL COMMENT '返回總數目', `SUM_ROWS_EXAMINED` bigint(20) unsigned NOT NULL COMMENT '總的掃描的數目', `SUM_CREATED_TMP_DISK_TABLES` bigint(20) unsigned NOT NULL COMMENT '創(chuàng )建磁盤(pán)臨時(shí)表的總數目', `SUM_CREATED_TMP_TABLES` bigint(20) unsigned NOT NULL COMMENT '創(chuàng )建臨時(shí)表的總數目', `SUM_SELECT_FULL_JOIN` bigint(20) unsigned NOT NULL COMMENT '第一個(gè)表全表掃描的總數目', `SUM_SELECT_FULL_RANGE_JOIN` bigint(20) unsigned NOT NULL COMMENT '總的采用range方式掃描的數目', `SUM_SELECT_RANGE` bigint(20) unsigned NOT NULL COMMENT '第一個(gè)表采用range方式掃描的總數目', `SUM_SELECT_RANGE_CHECK` bigint(20) unsigned NOT NULL COMMENT '', `SUM_SELECT_SCAN` bigint(20) unsigned NOT NULL COMMENT '第一個(gè)表位全表掃描的總數目', `SUM_SORT_MERGE_PASSES` bigint(20) unsigned NOT NULL COMMENT '', `SUM_SORT_RANGE` bigint(20) unsigned NOT NULL COMMENT '范圍排序總數', `SUM_SORT_ROWS` bigint(20) unsigned NOT NULL COMMENT '排序的記錄總數目', `SUM_SORT_SCAN` bigint(20) unsigned NOT NULL COMMENT '第一個(gè)表排序掃描總數目', `SUM_NO_INDEX_USED` bigint(20) unsigned NOT NULL COMMENT '沒(méi)有使用索引總數', `SUM_NO_GOOD_INDEX_USED` bigint(20) unsigned NOT NULL COMMENT '', `FIRST_SEEN` timestamp NOT NULL DEFAULT '0000-00-00 00:00:00' COMMENT '第一次執行時(shí)間', `LAST_SEEN` timestamp NOT NULL DEFAULT '0000-00-00 00:00:00' COMMENT '最后一次執行時(shí)間') ENGINE=PERFORMANCE_SCHEMA DEFAULT CHARSET=utf8
7，events_statements_summary_global_by_event_name：按照事件的語(yǔ)句進(jìn)行聚合。表結構同上。
8，events_statements_summary_by_thread_by_event_name：按照線(xiàn)程和事件的語(yǔ)句進(jìn)行聚合，表結構同上。
9，file_summary_by_instance：按事件類(lèi)型統計（物理IO維度）
10，file_summary_by_event_name：具體文件統計（物理IO維度）
9和10一起說(shuō)明：
統計IO操作：COUNT_STAR，SUM_TIMER_WAIT,MIN_TIMER_WAIT,AVG_TIMER_WAIT,MAX_TIMER_WAIT
統計讀 ：COUNT_READ,SUM_TIMER_READ,MIN_TIMER_READ,AVG_TIMER_READ,MAX_TIMER_READ, SUM_NUMBER_OF_BYTES_READ
統計寫(xiě) ：COUNT_WRITE,SUM_TIMER_WRITE,MIN_TIMER_WRITE,AVG_TIMER_WRITE,MAX_TIMER_WRITE, SUM_NUMBER_OF_BYTES_WRITE
統計其他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：根據wait/io/table/sql/handler，聚合每個(gè)表的I/O操作（邏輯IO緯度）
統計IO操作：COUNT_STAR,SUM_TIMER_WAIT,MIN_TIMER_WAIT,AVG_TIMER_WAIT,MAX_TIMER_WAIT
統計讀 ：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
統計寫(xiě) ：COUNT_WRITE,SUM_TIMER_WRITE,MIN_TIMER_WRITE,AVG_TIMER_WRITE,MAX_TIMER_WRITE
INSERT統計，相應的還有DELETE和UPDATE統計：COUNT_INSERT,SUM_TIMER_INSERT,MIN_TIMER_INSERT,AVG_TIMER_INSERT,MAX_TIMER_INSERT
12，table_io_waits_summary_by_index_usage：與table_io_waits_summary_by_table類(lèi)似，按索引維度統計
13，table_lock_waits_summary_by_table：聚合了表鎖等待事件，包括internal lock 和 external lock
internal lock通過(guò)SQL層函數thr_lock調用，OPERATION值為：
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則通過(guò)接口函數handler::external_lock調用存儲引擎層，OPERATION列的值為：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聚合統計表。
八：其他相關(guān)表
1，performance_timers：系統支持的統計時(shí)間單位
2，threads：監視服務(wù)端的當前運行的線(xiàn)程
統計應用：
關(guān)于SQL維度的統計信息主要集中在events_statements_summary_by_digest表中，通過(guò)將SQL語(yǔ)句抽象出digest，可以統計某類(lèi)SQL語(yǔ)句在各個(gè)維度的統計信息
1，哪個(gè)SQL執行最多：
zjy@performance_schema 11:36:22>SELECT SCHEMA_NAME,DIGEST_TEXT,COUNT_STAR,SUM_ROWS_SENT,SUM_ROWS_EXAMINED,FIRST_SEEN,LAST_SEEN FROM events_statements_summary_by_digest ORDER BY COUNT_STAR desc LIMIT 1\G*************************** 1. row *************************** SCHEMA_NAME: dchat DIGEST_TEXT: SELECT ... COUNT_STAR: 1161210102 SUM_ROWS_SENT: 1161207842SUM_ROWS_EXAMINED: 0 FIRST_SEEN: 2016-02-17 00:36:46 LAST_SEEN: 2016-03-07 11:36:29
各個(gè)字段的注釋可以看上面的表結構說(shuō)明：從2月17號到3月7號該SQL執行了1161210102次。
2，哪個(gè)SQL平均響應時(shí)間最多：
zjy@performance_schema 11:36:28>SELECT SCHEMA_NAME,DIGEST_TEXT,COUNT_STAR,AVG_TIMER_WAIT,SUM_ROWS_SENT,SUM_ROWS_EXAMINED,FIRST_SEEN,LAST_SEEN FROM events_statements_summary_by_digest ORDER BY AVG_TIMER_WAIT desc LIMIT 1\G*************************** 1. row *************************** SCHEMA_NAME: dchat DIGEST_TEXT: SELECT ... COUNT_STAR: 1 AVG_TIMER_WAIT: 273238183964000 SUM_ROWS_SENT: 50208SUM_ROWS_EXAMINED: 5565651 FIRST_SEEN: 2016-02-22 13:27:33 LAST_SEEN: 2016-02-22 13:27:33
各個(gè)字段的注釋可以看上面的表結構說(shuō)明：從2月17號到3月7號該SQL平均響應時(shí)間273238183964000皮秒（1000000000000皮秒=1秒）
3，哪個(gè)SQL掃描的行數最多：
SUM_ROWS_EXAMINED
4，哪個(gè)SQL使用的臨時(shí)表最多：
SUM_CREATED_TMP_DISK_TABLES、SUM_CREATED_TMP_TABLES
5，哪個(gè)SQL返回的結果集最多：
SUM_ROWS_SENT
6，哪個(gè)SQL排序數最多：
SUM_SORT_ROWS
通過(guò)上述指標我們可以間接獲得某類(lèi)SQL的邏輯IO(SUM_ROWS_EXAMINED)，CPU消耗(SUM_SORT_ROWS)，網(wǎng)絡(luò )帶寬(SUM_ROWS_SENT)的對比。
通過(guò)file_summary_by_instance表，可以獲得系統運行到現在，哪個(gè)文件(表)物理IO最多，這可能意味著(zhù)這個(gè)表經(jīng)常需要訪(fǎng)問(wèn)磁盤(pán)IO。
7，哪個(gè)表、文件邏輯IO最多（熱數據）：
zjy@performance_schema 12:16:18>SELECT FILE_NAME,EVENT_NAME,COUNT_READ,SUM_NUMBER_OF_BYTES_READ,COUNT_WRITE,SUM_NUMBER_OF_BYTES_WRITE FROM file_summary_by_instance ORDER BY SUM_NUMBER_OF_BYTES_READ+SUM_NUMBER_OF_BYTES_WRITE DESC LIMIT 2\G*************************** 1. row *************************** FILE_NAME: /var/lib/mysql/ibdata1 #文件 EVENT_NAME: wait/io/file/innodb/innodb_data_file COUNT_READ: 544 SUM_NUMBER_OF_BYTES_READ: 10977280 COUNT_WRITE: 3700729SUM_NUMBER_OF_BYTES_WRITE: 1433734217728*************************** 2. row *************************** FILE_NAME: /var/lib/mysql/dchat/fans.ibd #表 EVENT_NAME: wait/io/file/innodb/innodb_data_file COUNT_READ: 9370680 SUM_NUMBER_OF_BYTES_READ: 153529188352 COUNT_WRITE: 67576376SUM_NUMBER_OF_BYTES_WRITE: 1107815432192
8，哪個(gè)索引使用最多：
zjy@performance_schema 12:18:42>SELECT OBJECT_NAME, INDEX_NAME, COUNT_FETCH, COUNT_INSERT, COUNT_UPDATE, COUNT_DELETE FROM table_io_waits_summary_by_index_usage ORDER BY SUM_TIMER_WAIT DESC limit 1;+-------------+------------+-------------+--------------+--------------+--------------+| OBJECT_NAME | INDEX_NAME | COUNT_FETCH | COUNT_INSERT | COUNT_UPDATE | COUNT_DELETE |+-------------+------------+-------------+--------------+--------------+--------------+| fans | PRIMARY | 29002695158 | 0 | 296373434 | 0 |+-------------+------------+-------------+--------------+--------------+--------------+1 row in set (0.29 sec)
通過(guò)table_io_waits_summary_by_index_usage表，可以獲得系統運行到現在，哪個(gè)表的具體哪個(gè)索引(包括主鍵索引，二級索引)使用最多。
9，哪個(gè)索引沒(méi)有使用過(guò)：
zjy@performance_schema 12:23:22>SELECT OBJECT_SCHEMA, OBJECT_NAME, INDEX_NAME FROM table_io_waits_summary_by_index_usage WHERE INDEX_NAME IS NOT NULL AND COUNT_STAR = 0 AND OBJECT_SCHEMA <> 'mysql' ORDER BY OBJECT_SCHEMA,OBJECT_NAME;
10，哪個(gè)等待事件消耗的時(shí)間最多：
zjy@performance_schema 12:25:22>SELECT EVENT_NAME, COUNT_STAR, SUM_TIMER_WAIT, AVG_TIMER_WAIT FROM events_waits_summary_global_by_event_name WHERE event_name != 'idle' ORDER BY SUM_TIMER_WAIT DESC LIMIT 1;
11，類(lèi)似profiling功能：
分析具體某條SQL，該SQL在執行各個(gè)階段的時(shí)間消耗，通過(guò)events_statements_xxx表和events_stages_xxx表，就可以達到目的。兩個(gè)表通過(guò)event_id與nesting_event_id關(guān)聯(lián)，stages表的nesting_event_id為對應statements表的event_id；針對每個(gè)stage可能出現的鎖等待，一個(gè)stage會(huì )對應一個(gè)或多個(gè)wait，通過(guò)stage_xxx表的event_id字段與waits_xxx表的nesting_event_id進(jìn)行關(guān)聯(lián)。如：
比如分析包含count(*)的某條SQL語(yǔ)句，具體如下：SELECTEVENT_ID,sql_textFROM events_statements_historyWHERE sql_text LIKE '%count(*)%';+----------+--------------------------------------+| EVENT_ID | sql_text |+----------+--------------------------------------+| 1690 | select count(*) from chuck.test_slow |+----------+--------------------------------------+首先得到了語(yǔ)句的event_id為1690，通過(guò)查找events_stages_xxx中nesting_event_id為1690的記錄，可以達到目的。a.查看每個(gè)階段的時(shí)間消耗：SELECTevent_id,EVENT_NAME,SOURCE,TIMER_END - TIMER_STARTFROM events_stages_history_longWHERE NESTING_EVENT_ID = 1690;+----------+--------------------------------+----------------------+-----------------------+| event_id | EVENT_NAME | SOURCE | TIMER_END-TIMER_START |+----------+--------------------------------+----------------------+-----------------------+| 1691 | stage/sql/init | mysqld.cc:990 | 316945000 || 1693 | stage/sql/checking permissions | sql_parse.cc:5776 | 26774000 || 1695 | stage/sql/Opening tables | sql_base.cc:4970 | 41436934000 || 2638 | stage/sql/init | sql_select.cc:1050 | 85757000 || 2639 | stage/sql/System lock | lock.cc:303 | 40017000 || 2643 | stage/sql/optimizing | sql_optimizer.cc:138 | 38562000 || 2644 | stage/sql/statistics | sql_optimizer.cc:362 | 52845000 || 2645 | stage/sql/preparing | sql_optimizer.cc:485 | 53196000 || 2646 | stage/sql/executing | sql_executor.cc:112 | 3153000 || 2647 | stage/sql/Sending data | sql_executor.cc:192 | 7369072089000 || 4304138 | stage/sql/end | sql_select.cc:1105 | 19920000 || 4304139 | stage/sql/query end | sql_parse.cc:5463 | 44721000 || 4304145 | stage/sql/closing tables | sql_parse.cc:5524 | 61723000 || 4304152 | stage/sql/freeing items | sql_parse.cc:6838 | 455678000 || 4304155 | stage/sql/logging slow query | sql_parse.cc:2258 | 83348000 || 4304159 | stage/sql/cleaning up | sql_parse.cc:2163 | 4433000 |+----------+--------------------------------+----------------------+-----------------------+通過(guò)間接關(guān)聯(lián)，我們能分析得到SQL語(yǔ)句在每個(gè)階段的時(shí)間消耗，時(shí)間單位以皮秒表示。這里展示的結果很類(lèi)似profiling功能，有了performance schema，就不再需要profiling這個(gè)功能了。另外需要注意的是，由于默認情況下events_stages_history表中只為每個(gè)連接記錄了最近10條記錄，為了確保獲取所有記錄，需要訪(fǎng)問(wèn)events_stages_history_long表b.查看某個(gè)階段的鎖等待情況針對每個(gè)stage可能出現的鎖等待，一個(gè)stage會(huì )對應一個(gè)或多個(gè)wait，events_waits_history_long這個(gè)表容易爆滿(mǎn)[默認閥值10000]。由于select count(*)需要IO(邏輯IO或者物理IO)，所以在stage/sql/Sending data階段會(huì )有io等待的統計。通過(guò)stage_xxx表的event_id字段與waits_xxx表的nesting_event_id進(jìn)行關(guān)聯(lián)。SELECTevent_id,event_name,source,timer_wait,object_name,index_name,operation,nesting_event_idFROM events_waits_history_longWHERE nesting_event_id = 2647;+----------+---------------------------+-----------------+------------+-------------+------------+-----------+------------------+| event_id | event_name | source | timer_wait | object_name | index_name | operation | nesting_event_id |+----------+---------------------------+-----------------+------------+-------------+------------+-----------+------------------+| 190607 | wait/io/table/sql/handler | handler.cc:2842 | 1845888 | test_slow | idx_c1 | fetch | 2647 || 190608 | wait/io/table/sql/handler | handler.cc:2842 | 1955328 | test_slow | idx_c1 | fetch | 2647 || 190609 | wait/io/table/sql/handler | handler.cc:2842 | 1929792 | test_slow | idx_c1 | fetch | 2647 | | 190610 | wait/io/table/sql/handler | handler.cc:2842 | 1869600 | test_slow | idx_c1 | fetch | 2647 || 190611 | wait/io/table/sql/handler | handler.cc:2842 | 1922496 | test_slow | idx_c1 | fetch | 2647 |+----------+---------------------------+-----------------+------------+-------------+------------+-----------+------------------+通過(guò)上面的實(shí)驗，我們知道了statement,stage,wait的三級結構，通過(guò)nesting_event_id進(jìn)行關(guān)聯(lián)，它表示某個(gè)事件的父event_id。(2).模擬innodb行鎖等待的例子會(huì )話(huà)A執行語(yǔ)句update test_icp set y=y+1 where x=1(x為primary key)，不commit；會(huì )話(huà)B執行同樣的語(yǔ)句update test_icp set y=y+1 where x=1，會(huì )話(huà)B堵塞，并最終報錯。通過(guò)連接連接查詢(xún)events_statements_history_long和events_stages_history_long，可以看到在updating階段花了大約60s的時(shí)間。這主要因為實(shí)例上的innodb_lock_wait_timeout設置為60，等待60s后超時(shí)報錯了。SELECTstatement.EVENT_ID,stages.event_id,statement.sql_text,stages.event_name,stages.timer_waitFROM events_statements_history_long statement join events_stages_history_long stages on statement.event_id=stages.nesting_event_id WHERE statement.sql_text = 'update test_icp set y=y+1 where x=1';+----------+----------+-------------------------------------+--------------------------------+----------------+| EVENT_ID | event_id | sql_text | event_name | timer_wait |+----------+----------+-------------------------------------+--------------------------------+----------------+| 5816 | 5817 | update test_icp set y=y+1 where x=1 | stage/sql/init | 195543000 || 5816 | 5819 | update test_icp set y=y+1 where x=1 | stage/sql/checking permissions | 22730000 || 5816 | 5821 | update test_icp set y=y+1 where x=1 | stage/sql/Opening tables | 66079000 || 5816 | 5827 | update test_icp set y=y+1 where x=1 | stage/sql/init | 89116000 || 5816 | 5828 | update test_icp set y=y+1 where x=1 | stage/sql/System lock | 218744000 || 5816 | 5832 | update test_icp set y=y+1 where x=1 | stage/sql/updating | 6001362045000 || 5816 | 5968 | update test_icp set y=y+1 where x=1 | stage/sql/end | 10435000 || 5816 | 5969 | update test_icp set y=y+1 where x=1 | stage/sql/query end | 85979000 || 5816 | 5983 | update test_icp set y=y+1 where x=1 | stage/sql/closing tables | 56562000 || 5816 | 5990 | update test_icp set y=y+1 where x=1 | stage/sql/freeing items | 83563000 || 5816 | 5992 | update test_icp set y=y+1 where x=1 | stage/sql/cleaning up | 4589000 |+----------+----------+-------------------------------------+--------------------------------+----------------+查看wait事件：SELECTevent_id,event_name,source,timer_wait,object_name,index_name,operation,nesting_event_idFROM events_waits_history_longWHERE nesting_event_id = 5832;*************************** 1. row ***************************event_id: 5832event_name: wait/io/table/sql/handlersource: handler.cc:2782timer_wait: 6005946156624object_name: test_icpindex_name: PRIMARYoperation: fetch從結果來(lái)看，waits表中記錄了一個(gè)fetch等待事件，但并沒(méi)有更細的innodb行鎖等待事件統計。(3).模擬MDL鎖等待的例子會(huì )話(huà)A執行一個(gè)大查詢(xún)select count(*) from test_slow，會(huì )話(huà)B執行表結構變更alter table test_slow modify c2 varchar(152);通過(guò)如下語(yǔ)句可以得到alter語(yǔ)句的執行過(guò)程，重點(diǎn)關(guān)注“stage/sql/Waiting for table metadata lock”階段。SELECTstatement.EVENT_ID,stages.event_id,statement.sql_text,stages.event_name as stage_name,stages.timer_wait as stage_timeFROM events_statements_history_long statement left join events_stages_history_long stages on statement.event_id=stages.nesting_event_idWHERE statement.sql_text = 'alter table test_slow modify c2 varchar(152)';+-----------+-----------+----------------------------------------------+----------------------------------------------------+---------------+| EVENT_ID | event_id | sql_text | stage_name | stage_time |+-----------+-----------+----------------------------------------------+----------------------------------------------------+---------------+| 326526744 | 326526745 | alter table test_slow modify c2 varchar(152) | stage/sql/init | 216662000 || 326526744 | 326526747 | alter table test_slow modify c2 varchar(152) | stage/sql/checking permissions | 18183000 || 326526744 | 326526748 | alter table test_slow modify c2 varchar(152) | stage/sql/checking permissions | 10294000 || 326526744 | 326526750 | alter table test_slow modify c2 varchar(152) | stage/sql/init | 4783000 || 326526744 | 326526751 | alter table test_slow modify c2 varchar(152) | stage/sql/Opening tables | 140172000 || 326526744 | 326526760 | alter table test_slow modify c2 varchar(152) | stage/sql/setup | 157643000 || 326526744 | 326526769 | alter table test_slow modify c2 varchar(152) | stage/sql/creating table | 8723217000 || 326526744 | 326526803 | alter table test_slow modify c2 varchar(152) | stage/sql/After create | 257332000 || 326526744 | 326526832 | alter table test_slow modify c2 varchar(152) | stage/sql/Waiting for table metadata lock | 1000181831000 || 326526744 | 326526835 | alter table test_slow modify c2 varchar(152) | stage/sql/After create | 33483000 || 326526744 | 326526838 | alter table test_slow modify c2 varchar(152) | stage/sql/Waiting for table metadata lock | 1000091810000 || 326526744 | 326526841 | alter table test_slow modify c2 varchar(152) | stage/sql/After create | 17187000 || 326526744 | 326526844 | alter table test_slow modify c2 varchar(152) | stage/sql/Waiting for table metadata lock | 1000126464000 || 326526744 | 326526847 | alter table test_slow modify c2 varchar(152) | stage/sql/After create | 27472000 || 326526744 | 326526850 | alter table test_slow modify c2 varchar(152) | stage/sql/Waiting for table metadata lock | 561996133000 || 326526744 | 326526853 | alter table test_slow modify c2 varchar(152) | stage/sql/After create | 124876000 || 326526744 | 326526877 | alter table test_slow modify c2 varchar(152) | stage/sql/System lock | 30659000 || 326526744 | 326526881 | alter table test_slow modify c2 varchar(152) | stage/sql/preparing for alter table | 40246000 || 326526744 | 326526889 | alter table test_slow modify c2 varchar(152) | stage/sql/altering table | 36628000 || 326526744 | 326528280 | alter table test_slow modify c2 varchar(152) | stage/sql/end | 43824000 || 326526744 | 326528281 | alter table test_slow modify c2 varchar(152) | stage/sql/query end | 112557000 || 326526744 | 326528299 | alter table test_slow modify c2 varchar(152) | stage/sql/closing tables | 27707000 || 326526744 | 326528305 | alter table test_slow modify c2 varchar(152) | stage/sql/freeing items | 201614000 || 326526744 | 326528308 | alter table test_slow modify c2 varchar(152) | stage/sql/cleaning up | 3584000 |+-----------+-----------+----------------------------------------------+----------------------------------------------------+---------------+從結果可以看到，出現了多次stage/sql/Waiting for table metadata lock階段，并且間隔1s，說(shuō)明每隔1s鐘會(huì )重試判斷。找一個(gè)該階段的event_id,通過(guò)nesting_event_id關(guān)聯(lián)，確定到底在等待哪個(gè)wait事件。SELECTevent_id,event_name,source,timer_wait,object_name,index_name,operation,nesting_event_idFROM events_waits_history_longWHERE nesting_event_id = 326526850;+-----------+---------------------------------------------------+------------------+--------------+-------------+------------+------------+------------------+| event_id | event_name | source | timer_wait | object_name | index_name | operation | nesting_event_id |+-----------+---------------------------------------------------+------------------+--------------+-------------+------------+------------+------------------+| 326526851 | wait/synch/cond/sql/MDL_context::COND_wait_status | mdl.cc:1327 | 562417991328 | NULL | NULL | timed_wait | 326526850 || 326526852 | wait/synch/mutex/mysys/my_thread_var::mutex | sql_class.h:3481 | 733248 | NULL | NULL | lock | 326526850 |+-----------+---------------------------------------------------+------------------+--------------+-------------+------------+------------+------------------+通過(guò)結果可以知道，產(chǎn)生阻塞的是條件變量MDL_context::COND_wait_status，并且顯示了代碼的位置。
總結：
本文通過(guò)對Performance Schema數據庫的介紹，主要用于收集數據庫服務(wù)器性能參數：①提供進(jìn)程等待的詳細信息，包括鎖、互斥變量、文件信息；②保存歷史的事件匯總信息，為提供MySQL服務(wù)器性能做出詳細的判斷；③對于新增和刪除監控事件點(diǎn)都非常容易，并可以改變mysql服務(wù)器的監控周期，例如（CYCLE、MICROSECOND）。通過(guò)該庫得到數據庫運行的統計信息，更好分析定位問(wèn)題和完善監控信息。類(lèi)似的監控還有：
打開(kāi)標準的innodb監控：CREATE TABLE innodb_monitor (a INT) ENGINE=INNODB;打開(kāi)innodb的鎖監控：CREATE TABLE innodb_lock_monitor (a INT) ENGINE=INNODB;打開(kāi)innodb表空間監控：CREATE TABLE innodb_tablespace_monitor (a INT) ENGINE=INNODB;打開(kāi)innodb表監控：CREATE TABLE innodb_table_monitor (a INT) ENGINE=INNODB;
參考文章：
https://dev.mysql.com/doc/refman/5.6/en/performance-schema.html
http://www.cnblogs.com/cchust/p/5022148.html
http://www.cnblogs.com/cchust/p/5057498.html
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