MySQL Thread Pool: Problem Definition
A new thread pool plugin is now a part of the MySQL Enterprise Edition.
In this blog we will cover the problem that the thread pool is solving
and some high-level description of how it solves this problem.
In the traditional MySQL server model there is a one-to-one mapping between
thread and connection. Even the MySQL server has lots of code where thread
or some abbreviation of thread is actually representing a connection.
Obviously this mapping has served MySQL very well over the years, but there
are some cases where this model don't work so well.
One such case is where there are much more connections executing queries
simultaneously compared to the number of CPUs available in the server. The
MySQL Server also have scalability bottlenecks where performance suffers
when too many connections execute in parallel.
So effectively there are two reasons that can make performance suffer in
the original MySQL Server model.
The first is that many connections executing in parallel means that the
amount of data that the CPUs work on increases. This will decrease the
CPU cache hit rates. Lowering the CPU cache hit rate can have a significant
negative impact on server performance. Actually in some cases the amount
of memory allocated by the connections executing in parallel could at times
even supersede the memory available in the server. In this case we enter a
state called swapping which is very detrimental to performance.
The second problem is that the number of parallel queries and transactions
can have a negative impact on the throughput through the "critical sections"
of the MySQL Server (critical section is where mutexes are applied to
ensure only one CPU changes a certain data structure at a time, when such
a critical section becomes a scalability problem we call it a hot spot).
Statements that writes are more affected since they use more critical
sections.
Neither of those problems can be solved in the operating system scheduler.
However there are some operating systems that have attempted solving this
problem for generic applications on a higher level in the operating system.
Both of those problems have the impact that performance suffers more and
more as the number of statements executed in parallel increases.
In addition there are hot spots where the mutex is held for a longer time
when many concurrent statements and/or transactions are executed in
parallel. One such example is the transaction list in InnoDB where each
transaction is listed in a linked list. Thus when the number of concurrent
transactions increases the time to scan the list increases and the time
holding the lock increases and thus the hot spot becomes even hotter
as the concurrency increases.
Current solutions to these issues exist in InnoDB through use of the
configuration parameter --innodb-thread-concurrency. When this parameter
is set to a nonzero value, this indicates how many threads are
able to run through InnoDB code concurrently. This solution have its
use cases where it works well. It does however have the drawback that
the solution itself contains a hot spot that limits the MySQL server
scalability. It does also not contain any solution to limiting the
number of concurrent transactions.
In a previous alpha version of the MySQL Server (MySQL 6.0) a thread
pool was developed. This thread pool solved the problem with limiting
the number of concurrent threads executing. It did nothing to solve
the problem with limiting the number of concurrent transactions.
It was also a scalability bottleneck in itself. Finally it didn't
solve all issues regarding long queries and blocked queries.
This made it possible for the MySQL Server to become completely
blocked.
When developing the thread pool extension now available in the MySQL
Enterprise Edition we decided to start from a clean plate with the
following requirements:
1) Limit the number of concurrently executing statements to ensure
that each statement execution has sufficient CPU and memory resources
to fulfill its task.
2) Split threads and connection into thread groups that are
independently managed. This is to ensure that the thread pool
plugin itself doesn't become a scalability bottleneck. The
aim is that each thread group has one or zero active threads
at any point in time.
3) Limit the number of concurrently executing transactions
through prioritizing queued connections dependent on if
they have started a transaction or not.
4) Avoid deadlocks when a statement execution becomes long or
when the statement is blocked for some reason for an extended
time.
If you are interested in knowing more details of how the new
thread pool solves these requirements there will be a
webinar on Thursday 20 Oct 2011 at 9.00 PDT. Check here
for details on how to access it.
If you want to try out the thread pool go here.
参考:
http://mikaelronstrom.blogspot.ae/2011/10/mysql-thread-pool-problem-definition.html

热AI工具

Undresser.AI Undress
人工智能驱动的应用程序,用于创建逼真的裸体照片

AI Clothes Remover
用于从照片中去除衣服的在线人工智能工具。

Undress AI Tool
免费脱衣服图片

Clothoff.io
AI脱衣机

Video Face Swap
使用我们完全免费的人工智能换脸工具轻松在任何视频中换脸!

热门文章

热工具

记事本++7.3.1
好用且免费的代码编辑器

SublimeText3汉化版
中文版,非常好用

禅工作室 13.0.1
功能强大的PHP集成开发环境

Dreamweaver CS6
视觉化网页开发工具

SublimeText3 Mac版
神级代码编辑软件(SublimeText3)

热门话题

全表扫描在MySQL中可能比使用索引更快,具体情况包括:1)数据量较小时;2)查询返回大量数据时;3)索引列不具备高选择性时;4)复杂查询时。通过分析查询计划、优化索引、避免过度索引和定期维护表,可以在实际应用中做出最优选择。

InnoDB的全文搜索功能非常强大,能够显着提高数据库查询效率和处理大量文本数据的能力。 1)InnoDB通过倒排索引实现全文搜索,支持基本和高级搜索查询。 2)使用MATCH和AGAINST关键字进行搜索,支持布尔模式和短语搜索。 3)优化方法包括使用分词技术、定期重建索引和调整缓存大小,以提升性能和准确性。

是的,可以在 Windows 7 上安装 MySQL,虽然微软已停止支持 Windows 7,但 MySQL 仍兼容它。不过,安装过程中需要注意以下几点:下载适用于 Windows 的 MySQL 安装程序。选择合适的 MySQL 版本(社区版或企业版)。安装过程中选择适当的安装目录和字符集。设置 root 用户密码,并妥善保管。连接数据库进行测试。注意 Windows 7 上的兼容性问题和安全性问题,建议升级到受支持的操作系统。

聚集索引和非聚集索引的区别在于:1.聚集索引将数据行存储在索引结构中,适合按主键查询和范围查询。2.非聚集索引存储索引键值和数据行的指针,适用于非主键列查询。

文章讨论了流行的MySQL GUI工具,例如MySQL Workbench和PhpMyAdmin,比较了它们对初学者和高级用户的功能和适合性。[159个字符]

MySQL是一个开源的关系型数据库管理系统。1)创建数据库和表:使用CREATEDATABASE和CREATETABLE命令。2)基本操作:INSERT、UPDATE、DELETE和SELECT。3)高级操作:JOIN、子查询和事务处理。4)调试技巧:检查语法、数据类型和权限。5)优化建议:使用索引、避免SELECT*和使用事务。

MySQL 数据库中,用户和数据库的关系通过权限和表定义。用户拥有用户名和密码,用于访问数据库。权限通过 GRANT 命令授予,而表由 CREATE TABLE 命令创建。要建立用户和数据库之间的关系,需创建数据库、创建用户,然后授予权限。
