mysql内存查阅 mysql内存分析

 【1】整体内存分析

该部分脚本转自:https://blog.csdn.net/weixin_36114835/article/details/113210288

效果如下

 

#!/bin/sh

# you might want to add some user authentication here
mysql -e "show variables; show status" | awk '
{undefined
VAR[$1]=$2
}

END {undefined
MAX_CONN = VAR["max_connections"]
MAX_USED_CONN = VAR["Max_used_connections"]
BASE_MEM=VAR["key_buffer_size"] + VAR["query_cache_size"] + VAR["innodb_buffer_pool_size"] + VAR["innodb_additional_mem_pool_size"] + VAR["innodb_log_buffer_size"]
MEM_PER_CONN=VAR["read_buffer_size"] + VAR["read_rnd_buffer_size"] + VAR["sort_buffer_size"] + VAR["join_buffer_size"] + VAR["binlog_cache_size"] + VAR["thread_stack"] + VAR["tmp_table_size"]
MEM_TOTAL_MIN=BASE_MEM + MEM_PER_CONN*MAX_USED_CONN
MEM_TOTAL_MAX=BASE_MEM + MEM_PER_CONN*MAX_CONN

printf "+------------------------------------------+--------------------+\n"
printf "| %40s | %15.3f MB |\n", "key_buffer_size", VAR["key_buffer_size"]/1048576
printf "| %40s | %15.3f MB |\n", "query_cache_size", VAR["query_cache_size"]/1048576
printf "| %40s | %15.3f MB |\n", "innodb_buffer_pool_size", VAR["innodb_buffer_pool_size"]/1048576
printf "| %40s | %15.3f MB |\n", "innodb_additional_mem_pool_size", VAR["innodb_additional_mem_pool_size"]/1048576
printf "| %40s | %15.3f MB |\n", "innodb_log_buffer_size", VAR["innodb_log_buffer_size"]/1048576

printf
"+------------------------------------------+--------------------+\n" printf "| %40s | %15.3f MB |\n", "BASE MEMORY", BASE_MEM/1048576 printf "+------------------------------------------+--------------------+\n"
printf "| %40s | %15.3f MB |\n", "sort_buffer_size", VAR["sort_buffer_size"]/1048576 printf "| %40s | %15.3f MB |\n", "read_buffer_size", VAR["read_buffer_size"]/1048576 printf "| %40s | %15.3f MB |\n", "read_rnd_buffer_size", VAR["read_rnd_buffer_size"]/1048576 printf "| %40s | %15.3f MB |\n", "join_buffer_size", VAR["join_buffer_size"]/1048576 printf "| %40s | %15.3f MB |\n", "thread_stack", VAR["thread_stack"]/1048576 printf "| %40s | %15.3f MB |\n", "binlog_cache_size", VAR["binlog_cache_size"]/1048576 printf "| %40s | %15.3f MB |\n", "tmp_table_size", VAR["tmp_table_size"]/1048576
printf
"+------------------------------------------+--------------------+\n" printf "| %40s | %15.3f MB |\n", "MEMORY PER CONNECTION", MEM_PER_CONN/1048576 printf "+------------------------------------------+--------------------+\n" printf "| %40s | %18d |\n", "Max_used_connections", MAX_USED_CONN printf "| %40s | %18d |\n", "max_connections", MAX_CONN printf "+------------------------------------------+--------------------+\n" printf "| %40s | %15.3f MB |\n", "TOTAL (MIN)", MEM_TOTAL_MIN/1048576 printf "| %40s | %15.3f MB |\n", "TOTAL (MAX)", MEM_TOTAL_MAX/1048576 printf "+------------------------------------------+--------------------+\n" }'

【2】具体内存分析

(2.1)连接内存

SELECT ( @@read_buffer_size
+ @@read_rnd_buffer_size
+ @@sort_buffer_size
+ @@join_buffer_size
+ @@binlog_cache_size
+ @@thread_stack
+ @@tmp_table_size
+ 2*@@net_buffer_length
) / (1024 * 1024) AS MEMORY_PER_CON_MB;

【3】整体内存占用分析

(3.1)查看渠道与角度

从哪里开始排除MySQL内存泄漏问题?

假设这是一个Linux服务器,首先我们要 

检查Linux操作系统和配置 :

  1. 检查mysql错误日志和Linux日志文件(即/ var / log / messages或/ var / log / syslog)来识别崩溃。你可能会看到OOM Killer杀死MySQL的条目,可以使用“dmesg”来显示相关的详细信息。

  2. 检查可用的RAM: free -g    cat / proc / meminfo

  3. 检查哪些应用程序正在使用RAM: “top”或“htop”

  4. 检查mysql配置: /etc/my.cnf 或general /etc/my* (including /etc/mysql/*等文件),MySQL可能正在运行不同的my.cnf(run ps  ax | grep mysql  )

  5. 运行 vmstat 5 5  以查看系统是否正在通过虚拟内存进行读/写以及是否正在进行交换

  6. 对于非生产环境,我们可以使用其他工具(如Valgrind,gdb等)来检查MySQL的使用情况.

(3.2)检查MySQL内部

我们也可以通过检查MySQL内部来发现潜在的MySQL内存泄露。MySQL在很多地方都会有内存分配,尤其是在以下情况下:

现在我们可以检查MySQL内部的东西来寻找潜在的MySQL内存泄漏。

MySQL在很多地方分配内存。特别:

  1. Table cache

  2. Performance_schema(运行: show engine performance_schema status ,并查看最后一行)。

  3. InnoDB(运行 show engine innodb status   并检查缓冲池部分,为buffer_pool和相关缓存分配的内存)

  4. RAM中的临时表(通过运行以下语句查找所有内存表: select * from information_schema .tables where engine ='MEMORY'  )

  5. Prepared statements。

不过,从MySQL 5.7版本开始,我们就可以在performance_schema中查看内存分配。那么,如何使用呢?

首先,我们需要启用收集内存指标。Run:

UPDATE performance_schema.setup_instruments SET ENABLED='YES'WHERE NAME LIKE 'memory/%';

(3.3)常见内存使用查询库表

常见表

-- sys 库
memory_by_host_by_current_bytes  
memory_by_thread_by_current_bytes
memory_by_user_by_current_bytes  
memory_global_by_current_bytes   
memory_global_total              

-- performance_schema 库
memory_summary_by_account_by_event_name:账号纬度的内存监控表
memory_summary_by_host_by_event_name:主机纬度的内存监控表
memory_summary_by_thread_by_event_name:线程维度的内存监控表
memory_summary_by_user_by_event_name:用户纬度的内存监控表
memory_summary_global_by_event_name:全局纬度的内存监控表

内存监控表
在performance_schema库下,提供多个维度的内存监控表,具体如下:

memory_summary_by_account_by_event_name:账号纬度的内存监控表
memory_summary_by_host_by_event_name:主机纬度的内存监控表
memory_summary_by_thread_by_event_name:线程维度的内存监控表
memory_summary_by_user_by_event_name:用户纬度的内存监控表
memory_summary_global_by_event_name:全局纬度的内存监控表
内存监控表均包括以下关键字段:

COUNT_ALLOC:内存分配次数
COUNT_FREE:内存回收次数
SUM_NUMBER_OF_BYTES_ALLOC:内存分配大小
SUM_NUMBER_OF_BYTES_FREE:内存回收大小
CURRENT_COUNT_USED:当前分配的内存,通过COUNT_ALLOC-COUNT_FREE计算得到
CURRENT_NUMBER_OF_BYTES_USED:当前分配的内存大小,通过SUM_NUMBER_OF_BYTES_ALLOC-SUM_NUMBER_OF_BYTES_FREE计算得到
LOW_COUNT_USED:CURRENT_COUNT_USED的最小值
HIGH_COUNT_USED:CURRENT_COUNT_USED的最大值
LOW_NUMBER_OF_BYTES_USED:CURRENT_NUMBER_OF_BYTES_USED的最小值
HIGH_NUMBER_OF_BYTES_USED:CURRENT_NUMBER_OF_BYTES_USED的最大值

(3.4)一个内存查询SQL

select event_name, current_alloc, high_alloc
from sys.memory_global_by_current_bytes
where current_count > 0;

    

通常,分配内存时会提供代码,所以在某些情况下搜索某些错误时,我们可能需要检查 MySQL 源代码。例如,对于在触发器中过度分配内存的错误:

某些情况下搜索某些错误时,我们可能需要检查MySQL源代码。

例如,对于在触发器中过度分配内存的错误

mysql> select event_name, current_alloc, high_alloc from memory_global_by_current_bytes where current_count > 0;

  

RAM中最大的块通常是缓冲池,但存储过程中的3G似乎也太高了。

根据MySQL源代码文档,SPHead表示存储程序的一个实例,该程序可能是任何类型(存储过程、函数、触发器、事件)。

在这种情况下,就会有潜在的内存泄漏。此外,如果我们想要更清楚的知道MySQL内存情况,还可以得到一个更高级别的总报告。

select  substring_index( substring_index(event_name, '/', 2),  '/', -1 )  as event_type,
round(sum(CURRENT_NUMBER_OF_BYTES_USED)/1024/1024, 2) as MB_CURRENTLY_USED
from performance_schema.memory_summary_global_by_event_name group by event_type having MB_CURRENTLY_USED>0;

【4】常用内存SQL查询

(4.1)总内存使用情况

SELECT SUBSTRING_INDEX(event_name,'/',2) AS code_area,
sys.format_bytes(SUM(current_alloc)) AS current_alloc FROM sys.x$memory_global_by_current_bytes
GROUP BY SUBSTRING_INDEX(event_name,'/',2)
ORDER BY SUM(current_alloc) DESC;

(4.2)查看线程占用

-- 具体线程
select THREAD_ID,EVENT_NAME,CURRENT_NUMBER_OF_BYTES_USED/1024/1024 'used_MB' 
from performance_schema.memory_summary_by_thread_by_event_name  
where CURRENT_NUMBER_OF_BYTES_USED>0 order by CURRENT_NUMBER_OF_BYTES_USED desc limit 30;

-- 线程总计
select sum(CURRENT_NUMBER_OF_BYTES_USED)/1024/1024 used_MB from memory_summary_by_thread_by_event_name;

 【5】

 

 

 

【参考文档】

叶金荣:https://cloud.tencent.com/developer/article/1005397

posted @ 2022-02-19 10:01  郭大侠1  阅读(2071)  评论(0编辑  收藏  举报