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reference: add documentation for statement summary #1939
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Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,148 @@ | ||
--- | ||
title: Statement Summary Table | ||
category: reference | ||
--- | ||
|
||
# Statement Summary Table | ||
|
||
针对 SQL 性能相关的问题,MySQL 在 `performance_schema` 提供了 [statement summary tables](https://dev.mysql.com/doc/refman/5.6/en/statement-summary-tables.html),用来监控和统计 SQL。例如其中的一张表 `events_statements_summary_by_digest`,提供了丰富的字段,包括延迟、执行次数、扫描行数、全表扫描次数等,有助于用户定位 SQL 问题。 | ||
|
||
为此,从 3.0.4 版本开始,TiDB 也提供系统表 `events_statements_summary_by_digest`。本文将详细介绍 `events_statements_summary_by_digest`,以及如何利用它来排查 SQL 性能问题。 | ||
|
||
## events_statements_summary_by_digest 介绍 | ||
|
||
`events_statement_summary_by_digest` 是 `performance_schema` 里的一张系统表。顾名思义,它把 SQL 按 digest 分组,统计每一组的 SQL 信息。 | ||
|
||
此处的 digest 与 slow log 里的 digest 一样,是把 SQL 规范化后算出的唯一标识符。 | ||
SQL 的规范化会忽略常量、空白符、大小写的差别。也就是说,只要语法一致,就会归到同一类。 | ||
|
||
例如: | ||
|
||
```sql | ||
SELECT * FROM employee WHERE id IN (1, 2, 3) AND salary BETWEEN 1000 AND 2000; | ||
select * from EMPLOYEE where ID in (4, 5) and SALARY between 3000 and 4000; | ||
``` | ||
|
||
规范化后都是: | ||
|
||
```sql | ||
select * from employee where id in (...) and salary between ? and ?; | ||
``` | ||
|
||
接下来详细看一下 `events_statements_summary_by_digest` 的表结构。 | ||
因为 TiDB 中的很多概念不同于 MySQL,所以 `events_statements_summary_by_digest` 也与 MySQL 有一些区别。 | ||
|
||
查询 `events_statements_summary_by_digest` 的输出示例: | ||
|
||
``` | ||
SCHEMA_NAME: test | ||
DIGEST: 0611cc2fe792f8c146cc97d39b31d9562014cf15f8d41f23a4938ca341f54182 | ||
DIGEST_TEXT: select * from employee where id = ? | ||
EXEC_COUNT: 3 | ||
SUM_LATENCY: 1035161 | ||
MAX_LATENCY: 399594 | ||
MIN_LATENCY: 301353 | ||
AVG_LATENCY: 345053 | ||
SUM_ROWS_AFFECTED: 0 | ||
FIRST_SEEN: 2019-09-12 18:47:14 | ||
LAST_SEEN: 2019-09-12 18:47:16 | ||
QUERY_SAMPLE_TEXT: select * from employee where id=3100 | ||
``` | ||
|
||
以下是各个字段的含义: | ||
|
||
| 列名 | 含义 | | ||
|:----------------- |:-------------------------------- | | ||
| SCHEMA_NAME | 执行这类 SQL 的当前 schema | | ||
| DIGEST | SQL 的 digest | | ||
| DIGEST_TEXT | 规范化后的 SQL | | ||
| EXEC_COUNT | 这类 SQL 执行的总次数 | | ||
| SUM_LATENCY | 这类 SQL 执行的总延迟,单位 ns | | ||
| MAX_LATENCY | 这类 SQL 执行的最大延迟,单位 ns | | ||
| MIN_LATENCY | 这类 SQL 执行的最小延迟,单位 ns | | ||
| AVG_LATENCY | 这类 SQL 执行的平均延迟,单位 ns | | ||
| SUM_ROWS_AFFECTED | 这类 SQL 的总影响行数 | | ||
| FIRST_SEEN | 这类 SQL 第一次执行的时间 | | ||
| LAST_SEEN | 这类 SQL 最后一次执行的时间 | | ||
| QUERY_SAMPLE_TEXT | 这类 SQL 首次出现的原 SQL 语句 | | ||
|
||
## 排查示例 | ||
|
||
下面来两个示例问题演示如何利用 statement summary 来排查。 | ||
|
||
### SQL 延迟比较大,是不是服务端的问题? | ||
|
||
例如客户端显示 employee 表的点查比较慢,那么可以按 SQL 文本来模糊查询: | ||
|
||
```sql | ||
SELECT avg_latency, exec_count, query_sample_text | ||
FROM performance_schema.events_statements_summary_by_digest | ||
WHERE digest_text LIKE ‘select * from employee%’; | ||
``` | ||
|
||
结果如下,`avg_latency` 是 1 ms 和 0.3 ms,在正常范围,所以可以判定不是服务端的问题,继而排查客户端或网络问题。 | ||
|
||
``` | ||
+-------------+------------+------------------------------------------+ | ||
| avg_latency | exec_count | query_sample_text | | ||
+-------------+------------+------------------------------------------+ | ||
| 1042040 | 2 | select * from employee where name='eric' | | ||
| 345053 | 3 | select * from employee where id=3100 | | ||
+-------------+------------+------------------------------------------+ | ||
2 rows in set (0.00 sec) | ||
``` | ||
|
||
### 哪类 SQL 的总耗时最高? | ||
|
||
如果要对系统调优,可以找出耗时最高的 3 类 SQL: | ||
|
||
```sql | ||
SELECT sum_latency, avg_latency, exec_count, query_sample_text | ||
FROM performance_schema.events_statements_summary_by_digest | ||
ORDER BY sum_latency DESC LIMIT 3; | ||
``` | ||
|
||
结果显示以下三类 SQL 的总延迟最高,所以这些 SQL 需要重点优化。 | ||
|
||
``` | ||
+-------------+-------------+------------+-----------------------------------------------------------------------+ | ||
| sum_latency | avg_latency | exec_count | query_sample_text | | ||
+-------------+-------------+------------+-----------------------------------------------------------------------+ | ||
| 7855660 | 1122237 | 7 | select avg(salary) from employee where company_id=2013 | | ||
| 7241960 | 1448392 | 5 | select * from employee join company on employee.company_id=company.id | | ||
| 2084081 | 1042040 | 2 | select * from employee where name='eric' | | ||
+-------------+-------------+------------+-----------------------------------------------------------------------+ | ||
3 rows in set (0.00 sec) | ||
``` | ||
|
||
## 参数配置 | ||
|
||
statement summary 功能默认关闭,通过设置系统变量打开,例如: | ||
|
||
```sql | ||
set global tidb_enable_stmt_summary = true; | ||
``` | ||
|
||
`tidb_enable_stmt_summary` 有 global 和 session 两种作用域,它们的生效方式与其他系统变量不一样: | ||
|
||
- 设置 global 变量后整个集群立即生效 | ||
- 设置 session 变量后当前 TiDB-Server 立即生效,这对于调试单个 TiDB-Server 比较有用 | ||
- 优先读 session 变量,没有设置过 session 变量才会读 global 变量 | ||
- 把 session 变量设为空字符串,将会重新读 global 变量 | ||
|
||
statement summary 关闭后,系统表里的数据会被清空,下次打开后重新统计。经测试,打开后对性能几乎没有影响。 | ||
|
||
由于 `events_statements_summary_by_digest` 是内存表,为了防止内存问题,需要限制保存的 SQL 条数和 SQL 的最大显示长度。这两个参数都在 config.toml 的 [stmt-summary] 类别下配置: | ||
|
||
- 通过 `max-stmt-count` 更改保存的 SQL 种类数量,默认 100 条。当 SQL 种类超过 `max-stmt-count` 时,会移除最近没有使用的 SQL。 | ||
- 通过 `max-sql-length` 更改 `DIGEST_TEXT` 和 `QUERY_SAMPLE_TEXT` 的最大显示长度,默认是 4096。 | ||
|
||
这两个参数建议根据实际情况调整,不宜设置得过大。 | ||
|
||
## 目前的限制 | ||
|
||
`events_statements_summary_by_digest` 现在还存在一些限制: | ||
|
||
- 查询 `events_statements_summary_by_digest` 时,只会显示当前 TiDB-Server 的 statement summary,而不是整个集群的 statement summary。 | ||
- statement summary 不会滚动更新。一旦 `tidb_enable_stmt_summary` 打开,SQL 信息就开始统计。随着时间的推移,statement summary 累加,所以无法查看最近一段时间内的 statement summary。所以最佳实践是,需要排查问题的时候再打开,查看一段时间内的 statement summary。 | ||
- TiDB Server 重启后 statement summary 丢失。因为 `events_statements_summary_by_digest` 是内存表,不会持久化数据,所以一旦 Server 被重启,statement summary 随之丢失。 |
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Learn more about bidirectional Unicode characters
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Learn more about bidirectional Unicode characters
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Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,148 @@ | ||
--- | ||
title: Statement Summary Table | ||
category: reference | ||
--- | ||
|
||
# Statement Summary Table | ||
|
||
针对 SQL 性能相关的问题,MySQL 在 `performance_schema` 提供了 [statement summary tables](https://dev.mysql.com/doc/refman/5.6/en/statement-summary-tables.html),用来监控和统计 SQL。例如其中的一张表 `events_statements_summary_by_digest`,提供了丰富的字段,包括延迟、执行次数、扫描行数、全表扫描次数等,有助于用户定位 SQL 问题。 | ||
|
||
为此,从 3.0.4 版本开始,TiDB 也提供系统表 `events_statements_summary_by_digest`。本文将详细介绍 `events_statements_summary_by_digest`,以及如何利用它来排查 SQL 性能问题。 | ||
|
||
## events_statements_summary_by_digest 介绍 | ||
|
||
`events_statement_summary_by_digest` 是 `performance_schema` 里的一张系统表。顾名思义,它把 SQL 按 digest 分组,统计每一组的 SQL 信息。 | ||
|
||
此处的 digest 与 slow log 里的 digest 一样,是把 SQL 规范化后算出的唯一标识符。 | ||
SQL 的规范化会忽略常量、空白符、大小写的差别。也就是说,只要语法一致,就会归到同一类。 | ||
|
||
例如: | ||
|
||
```sql | ||
SELECT * FROM employee WHERE id IN (1, 2, 3) AND salary BETWEEN 1000 AND 2000; | ||
select * from EMPLOYEE where ID in (4, 5) and SALARY between 3000 and 4000; | ||
``` | ||
|
||
规范化后都是: | ||
|
||
```sql | ||
select * from employee where id in (...) and salary between ? and ?; | ||
``` | ||
|
||
接下来详细看一下 `events_statements_summary_by_digest` 的表结构。 | ||
因为 TiDB 中的很多概念不同于 MySQL,所以 `events_statements_summary_by_digest` 也与 MySQL 有一些区别。 | ||
|
||
查询 `events_statements_summary_by_digest` 的输出示例: | ||
|
||
``` | ||
SCHEMA_NAME: test | ||
DIGEST: 0611cc2fe792f8c146cc97d39b31d9562014cf15f8d41f23a4938ca341f54182 | ||
DIGEST_TEXT: select * from employee where id = ? | ||
EXEC_COUNT: 3 | ||
SUM_LATENCY: 1035161 | ||
MAX_LATENCY: 399594 | ||
MIN_LATENCY: 301353 | ||
AVG_LATENCY: 345053 | ||
SUM_ROWS_AFFECTED: 0 | ||
FIRST_SEEN: 2019-09-12 18:47:14 | ||
LAST_SEEN: 2019-09-12 18:47:16 | ||
QUERY_SAMPLE_TEXT: select * from employee where id=3100 | ||
``` | ||
|
||
以下是各个字段的含义: | ||
|
||
| 列名 | 含义 | | ||
|:----------------- |:-------------------------------- | | ||
| SCHEMA_NAME | 执行这类 SQL 的当前 schema | | ||
| DIGEST | SQL 的 digest | | ||
| DIGEST_TEXT | 规范化后的 SQL | | ||
| EXEC_COUNT | 这类 SQL 执行的总次数 | | ||
| SUM_LATENCY | 这类 SQL 执行的总延迟,单位 ns | | ||
| MAX_LATENCY | 这类 SQL 执行的最大延迟,单位 ns | | ||
| MIN_LATENCY | 这类 SQL 执行的最小延迟,单位 ns | | ||
| AVG_LATENCY | 这类 SQL 执行的平均延迟,单位 ns | | ||
| SUM_ROWS_AFFECTED | 这类 SQL 的总影响行数 | | ||
| FIRST_SEEN | 这类 SQL 第一次执行的时间 | | ||
| LAST_SEEN | 这类 SQL 最后一次执行的时间 | | ||
| QUERY_SAMPLE_TEXT | 这类 SQL 首次出现的原 SQL 语句 | | ||
|
||
## 排查示例 | ||
|
||
下面来两个示例问题演示如何利用 statement summary 来排查。 | ||
|
||
### SQL 延迟比较大,是不是服务端的问题? | ||
|
||
例如客户端显示 employee 表的点查比较慢,那么可以按 SQL 文本来模糊查询: | ||
|
||
```sql | ||
SELECT avg_latency, exec_count, query_sample_text | ||
FROM performance_schema.events_statements_summary_by_digest | ||
WHERE digest_text LIKE ‘select * from employee%’; | ||
``` | ||
|
||
结果如下,`avg_latency` 是 1 ms 和 0.3 ms,在正常范围,所以可以判定不是服务端的问题,继而排查客户端或网络问题。 | ||
|
||
``` | ||
+-------------+------------+------------------------------------------+ | ||
| avg_latency | exec_count | query_sample_text | | ||
+-------------+------------+------------------------------------------+ | ||
| 1042040 | 2 | select * from employee where name='eric' | | ||
| 345053 | 3 | select * from employee where id=3100 | | ||
+-------------+------------+------------------------------------------+ | ||
2 rows in set (0.00 sec) | ||
``` | ||
|
||
### 哪类 SQL 的总耗时最高? | ||
|
||
如果要对系统调优,可以找出耗时最高的 3 类 SQL: | ||
|
||
```sql | ||
SELECT sum_latency, avg_latency, exec_count, query_sample_text | ||
FROM performance_schema.events_statements_summary_by_digest | ||
ORDER BY sum_latency DESC LIMIT 3; | ||
``` | ||
|
||
结果显示以下三类 SQL 的总延迟最高,所以这些 SQL 需要重点优化。 | ||
|
||
``` | ||
+-------------+-------------+------------+-----------------------------------------------------------------------+ | ||
| sum_latency | avg_latency | exec_count | query_sample_text | | ||
+-------------+-------------+------------+-----------------------------------------------------------------------+ | ||
| 7855660 | 1122237 | 7 | select avg(salary) from employee where company_id=2013 | | ||
| 7241960 | 1448392 | 5 | select * from employee join company on employee.company_id=company.id | | ||
| 2084081 | 1042040 | 2 | select * from employee where name='eric' | | ||
+-------------+-------------+------------+-----------------------------------------------------------------------+ | ||
3 rows in set (0.00 sec) | ||
``` | ||
|
||
## 参数配置 | ||
|
||
statement summary 功能默认关闭,通过设置系统变量打开,例如: | ||
|
||
```sql | ||
set global tidb_enable_stmt_summary = true; | ||
``` | ||
|
||
`tidb_enable_stmt_summary` 有 global 和 session 两种作用域,它们的生效方式与其他系统变量不一样: | ||
|
||
- 设置 global 变量后整个集群立即生效 | ||
- 设置 session 变量后当前 TiDB-Server 立即生效,这对于调试单个 TiDB-Server 比较有用 | ||
- 优先读 session 变量,没有设置过 session 变量才会读 global 变量 | ||
- 把 session 变量设为空字符串,将会重新读 global 变量 | ||
|
||
statement summary 关闭后,系统表里的数据会被清空,下次打开后重新统计。经测试,打开后对性能几乎没有影响。 | ||
|
||
由于 `events_statements_summary_by_digest` 是内存表,为了防止内存问题,需要限制保存的 SQL 条数和 SQL 的最大显示长度。这两个参数都在 config.toml 的 [stmt-summary] 类别下配置: | ||
|
||
- 通过 `max-stmt-count` 更改保存的 SQL 种类数量,默认 100 条。当 SQL 种类超过 `max-stmt-count` 时,会移除最近没有使用的 SQL。 | ||
- 通过 `max-sql-length` 更改 `DIGEST_TEXT` 和 `QUERY_SAMPLE_TEXT` 的最大显示长度,默认是 4096。 | ||
|
||
这两个参数建议根据实际情况调整,不宜设置得过大。 | ||
|
||
## 目前的限制 | ||
|
||
`events_statements_summary_by_digest` 现在还存在一些限制: | ||
|
||
- 查询 `events_statements_summary_by_digest` 时,只会显示当前 TiDB-Server 的 statement summary,而不是整个集群的 statement summary。 | ||
- statement summary 不会滚动更新。一旦 `tidb_enable_stmt_summary` 打开,SQL 信息就开始统计。随着时间的推移,statement summary 累加,所以无法查看最近一段时间内的 statement summary。所以最佳实践是,需要排查问题的时候再打开,查看一段时间内的 statement summary。 | ||
- TiDB Server 重启后 statement summary 丢失。因为 `events_statements_summary_by_digest` 是内存表,不会持久化数据,所以一旦 Server 被重启,statement summary 随之丢失。 |
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Addressed.