FreeBSD下提高MySQL使用效率
测试的结论是,FreeBSD现在缺乏稳定而且高效率的Filesystem让MySQL MyISAM使用。 先解释一下现在的环境,有两台Tyan Server,
测试的结论是,FreeBSD现在缺乏稳定而且高效率的Filesystem让MySQL MyISAM使用。
先解释一下现在的环境,有两台Tyan Server,上面都是Dual Quad Core与12GB RAM (6*2GB),接两颗73GB SCSI硬碟,两台的差异在于CPU,新进的这台是E5410 ( 2333Mhz,2*6144KB L2),旧的是E5320 (1866Mhz,2*4096KB L2)。
旧的是目前PIXNET production的MySQL database,跑Debian/amd64,kernel是2.6.22,档案系统是XFS。另外一台则是前阵子另外进的,装了FreeBSD/amd64 7.0-BETA2,然后透过make kernel & make world升级到7.0-PRERELEASE,跑SCHED_ULE,档案系统是UFS2。依照惯例,noatime与nodiratime之类的参数都会设上去,两台都是跑MySQL 5.1.22-rc,都是MySQL slave。
要复制slave很简单,,把production停机(利用使用者比较少的时候,其他的slave会负责这台本来的事情),整个目录复制一份到新的FreeBSD上,改server_id后跑起来后MySQL会跟master更新。
然后用databases/mytop看replication delay的情况(原版的mytop没有这个讯息,这是FreeBSD ports patch的功能),发现即使是放着跑replication sync,某些时候UPDATE的速度反而会跟不上master,跟不上时的I/O是满载的(透过gstat看的)
目前测过最好的情况是这样跑:gstripe -s 16384将da{0,1}串起来,用async + noatime。其他的情况包括:
gstripe -s 16384 + gjournal + async + noatime:日志类的Filesystem在DB这类用法的速度不会提升,与预料的差不多。
gstripe -s 16384 + soft updates + noatime:毕竟要维持consistent,速度慢一些。
单颗硬碟+ async + noatime:也如同预期的,速度只有一半。
以效率来看,短期内还是会跑Debian/amd64养MySQL。
另外补充一点,本来是在开启gjournal的情况下用rsync把资料复制到本机,结果发生kernel panic,后来是先复制完再使用gjournal,这个部份还要到其他机器看看到底是怎么一回事。

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics

Big data structure processing skills: Chunking: Break down the data set and process it in chunks to reduce memory consumption. Generator: Generate data items one by one without loading the entire data set, suitable for unlimited data sets. Streaming: Read files or query results line by line, suitable for large files or remote data. External storage: For very large data sets, store the data in a database or NoSQL.

MySQL query performance can be optimized by building indexes that reduce lookup time from linear complexity to logarithmic complexity. Use PreparedStatements to prevent SQL injection and improve query performance. Limit query results and reduce the amount of data processed by the server. Optimize join queries, including using appropriate join types, creating indexes, and considering using subqueries. Analyze queries to identify bottlenecks; use caching to reduce database load; optimize PHP code to minimize overhead.

Backing up and restoring a MySQL database in PHP can be achieved by following these steps: Back up the database: Use the mysqldump command to dump the database into a SQL file. Restore database: Use the mysql command to restore the database from SQL files.

How to insert data into MySQL table? Connect to the database: Use mysqli to establish a connection to the database. Prepare the SQL query: Write an INSERT statement to specify the columns and values to be inserted. Execute query: Use the query() method to execute the insertion query. If successful, a confirmation message will be output.

One of the major changes introduced in MySQL 8.4 (the latest LTS release as of 2024) is that the "MySQL Native Password" plugin is no longer enabled by default. Further, MySQL 9.0 removes this plugin completely. This change affects PHP and other app

To use MySQL stored procedures in PHP: Use PDO or the MySQLi extension to connect to a MySQL database. Prepare the statement to call the stored procedure. Execute the stored procedure. Process the result set (if the stored procedure returns results). Close the database connection.

Creating a MySQL table using PHP requires the following steps: Connect to the database. Create the database if it does not exist. Select a database. Create table. Execute the query. Close the connection.

Oracle database and MySQL are both databases based on the relational model, but Oracle is superior in terms of compatibility, scalability, data types and security; while MySQL focuses on speed and flexibility and is more suitable for small to medium-sized data sets. . ① Oracle provides a wide range of data types, ② provides advanced security features, ③ is suitable for enterprise-level applications; ① MySQL supports NoSQL data types, ② has fewer security measures, and ③ is suitable for small to medium-sized applications.
