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

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MySQL中有四種主要的索引類型:B-Tree索引、哈希索引、全文索引和空間索引。 1.B-Tree索引適用於範圍查詢、排序和分組,適合在employees表的name列上創建。 2.哈希索引適用於等值查詢,適合在MEMORY存儲引擎的hash_table表的id列上創建。 3.全文索引用於文本搜索,適合在articles表的content列上創建。 4.空間索引用於地理空間查詢,適合在locations表的geom列上創建。

toCreateAnIndexinMysql,usethecReateIndexStatement.1)forasingLecolumn,使用“ createIndexIdx_lastNameEnemployees(lastName); 2)foracompositeIndex,使用“ createIndexIndexIndexIndexIndexDx_nameOmplayees(lastName,firstName,firstName);” 3)forauniqe instex,creationexexexexex,

MySQL和SQLite的主要區別在於設計理念和使用場景:1.MySQL適用於大型應用和企業級解決方案,支持高性能和高並發;2.SQLite適合移動應用和桌面軟件,輕量級且易於嵌入。

MySQL中的索引是數據庫表中一列或多列的有序結構,用於加速數據檢索。 1)索引通過減少掃描數據量提升查詢速度。 2)B-Tree索引利用平衡樹結構,適合範圍查詢和排序。 3)創建索引使用CREATEINDEX語句,如CREATEINDEXidx_customer_idONorders(customer_id)。 4)複合索引可優化多列查詢,如CREATEINDEXidx_customer_orderONorders(customer_id,order_date)。 5)使用EXPLAIN分析查詢計劃,避

在MySQL中使用事務可以確保數據一致性。 1)通過STARTTRANSACTION開始事務,執行SQL操作後用COMMIT提交或ROLLBACK回滾。 2)使用SAVEPOINT可以設置保存點,允許部分回滾。 3)性能優化建議包括縮短事務時間、避免大規模查詢和合理使用隔離級別。


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