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user_summary_by_statement_latency,x$user_summary_by_statement_latency
xiaoboluo768 edited this page Jun 9, 2020
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2 revisions
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按照用户分组的总体语句统计信息,默认情况下按照语句总延迟时间(执行时间)降序排序。数据来源:events_statements_summary_by_user_by_event_name
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user_summary_by_statement_latency和x$user_summary_by_statement_latency视图字段含义如下:
- user:客户端用户名。如果在performance_schema表中user列为NULL,则假定为后台线程,该字段为'background',如果为前台线程,则该字段对应具体的用户名
- total:对应用户的语句总数量
- total_latency:对应用户的语句总等待时间(执行时间)
- max_latency:对应用户的语句单次最大等待时间(执行时间)
- lock_latency:对应用户的语句锁等待的总时间
- rows_sent:对应用户的语句返回给客户端的总数据行数
- rows_examined:对应用户的语句从存储引擎读取的总数据行数
- rows_affected:对应用户的语句影响的总数据行数
- full_scans:对应用户的语句的全表扫描总次数
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视图定义语句
# user_summary_by_statement_latency
CREATE OR REPLACE
ALGORITHM = TEMPTABLE
DEFINER = 'root'@'localhost'
SQL SECURITY INVOKER
VIEW user_summary_by_statement_latency (
user, total, total_latency, max_latency, lock_latency, rows_sent, rows_examined, rows_affected, full_scans
) AS
SELECT IF(user IS NULL, 'background', user) AS user,
SUM(count_star) AS total,
sys.format_time(SUM(sum_timer_wait)) AS total_latency,
sys.format_time(SUM(max_timer_wait)) AS max_latency,
sys.format_time(SUM(sum_lock_time)) AS lock_latency,
SUM(sum_rows_sent) AS rows_sent,
SUM(sum_rows_examined) AS rows_examined,
SUM(sum_rows_affected) AS rows_affected,
SUM(sum_no_index_used) + SUM(sum_no_good_index_used) AS full_scans
FROM performance_schema.events_statements_summary_by_user_by_event_name
GROUP BY IF(user IS NULL, 'background', user)
ORDER BY SUM(sum_timer_wait) DESC;
# x$user_summary_by_statement_latency
CREATE OR REPLACE
ALGORITHM = TEMPTABLE
DEFINER = 'root'@'localhost'
SQL SECURITY INVOKER
VIEW x$user_summary_by_statement_latency (
user, total, total_latency, max_latency, lock_latency, rows_sent, rows_examined, rows_affected, full_scans
) AS
SELECT IF(user IS NULL, 'background', user) AS user,
SUM(count_star) AS total,
SUM(sum_timer_wait) AS total_latency,
SUM(max_timer_wait) AS max_latency,
SUM(sum_lock_time) AS lock_latency,
SUM(sum_rows_sent) AS rows_sent,
SUM(sum_rows_examined) AS rows_examined,
SUM(sum_rows_affected) AS rows_affected,
SUM(sum_no_index_used) + SUM(sum_no_good_index_used) AS full_scans
FROM performance_schema.events_statements_summary_by_user_by_event_name
GROUP BY IF(user IS NULL, 'background', user)
ORDER BY SUM(sum_timer_wait) DESC;
- 视图查询信息示例
admin@localhost : sys 12:57:13> select * from user_summary_by_statement_latency limit 3;
+------------+-------+---------------+-------------+--------------+-----------+---------------+---------------+------------+
| user | total | total_latency | max_latency | lock_latency | rows_sent | rows_examined | rows_affected | full_scans |
+------------+-------+---------------+-------------+--------------+-----------+---------------+---------------+------------+
| admin | 45487 | 1.05 h | 45.66 m | 19.02 s | 6065 | 17578842 | 1544 | 258 |
| qfsys | 9 | 929.43 ms | 928.68 ms | 0 ps | 5 | 0 | 0 | 0 |
| background | 0 | 0 ps | 0 ps | 0 ps | 0 | 0 | 0 | 0 |
+------------+-------+---------------+-------------+--------------+-----------+---------------+---------------+------------+
3 rows in set (0.00 sec)
admin@localhost : sys 12:57:34> select * from x$user_summary_by_statement_latency limit 3;
+------------+-------+------------------+------------------+----------------+-----------+---------------+---------------+------------+
| user | total | total_latency | max_latency | lock_latency | rows_sent | rows_examined | rows_affected | full_scans |
+------------+-------+------------------+------------------+----------------+-----------+---------------+---------------+------------+
| admin | 45562 | 3762457232413000 | 2739502018445000 | 19019928000000 | 6068 | 17579421 | 1544 | 259 |
| qfsys | 9 | 929429421000 | 928682487000 | 0 | 5 | 0 | 0 | 0 |
| background | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
+------------+-------+------------------+------------------+----------------+-----------+---------------+---------------+------------+
3 rows in set (0.00 sec)
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- 提示:本系列文章的主体结构遵循Oracle MySQL 官方 5.7 手册中,关于information_schema、mysql schema、performance_schema、sys schema的章节结构体系,并额外添加了一些验证、测试数据。鉴于本人精力和能力有限,难免出现一些纰漏,欢迎大家踊跃指正!