MySQL查询优化:连接查询排序limit(join、order by、limit语句)_MySQL
bitsCN.com
MySQL查询优化:连接查询排序limit(join、order by、limit语句)
不知道有没有人碰到过这样恶心的问题:两张表连接查询并limit,SQL效率很高,
但是加上order by以后,语句的执行时间变的巨长,效率巨低。
www.bitsCN.com
情况是这么一个情况:现在有两张表,team表和people表,每个people属于一个
team,people中有个字段team_id。
下面给出建表语句:
[sql]
create table t_team
(
id int primary key,
tname varchar(100)
);
create table t_people
(
id int primary key,
pname varchar(100),
team_id int,
foreign key (team_id) references t_team(id)
);
下面我要连接两张表查询出前10个people,按tname排序。
于是,一个SQL语句诞生了:select * from t_people p left join t_team t onp.
team_id=t.id order by p.pname limit 10; [语句①]
这个是我第一反应写的SQL,通俗易懂,也是大多数人的第一反应。
然后来测试一下这个语句的执行时间。
首先要准备数据。我用存储过程在t_team表中生成1000条数据,在t_people表中
生成100000条数据。(存储过程在本文最后)
执行上面那条SQL语句,执行了好几次,耗时在3秒左右。
再换两个语句对比一下:
1.把order by子句去掉:select * from t_people p left join t_team t on p.team_id=
t.id limit10; [语句②]
耗时0.00秒,忽略不计。
2.还是使用order by,但是把连接t_team表去掉:select * from t_people p order
by p.pname limit 10; [语句③]
耗时0.15秒左右。
对比发现[语句①]的效率巨低。
为什么效率这么低呢。[语句②]和[语句③]执行都很快,[语句①]不过是二者的结合。
如果先执行[语句③]得到排序好的10条people结果后,再连接查询出各个people的
team,效率不会这么低。那么只有一个解释:MySQL先执行连接查询,再进行排序。
解决方法:如果想提高效率,就要修改SQL语句,让MySQL先排序取前10条再连接查询。
SQL语句:
select * from (select * from t_people p order by p.pname limit 10) p left join t_team
t on p.team_id=t.id limit 10; [语句④]
[语句④]和[语句①]功能一样,虽然有子查询,虽然看起来很别扭,但是效率提高了很多,
它的执行时间只要0.16秒左右,比之前的[语句①]提高了20倍。
这两个表的结构很简单,如果遇到复杂的表结构…我在实际开发中就碰到了这样的
问题,使用[语句①]的方式耗时80多秒,但使用[语句④]只需1秒以内。
最后给出造数据的存储过程:
[sql]
CREATE PROCEDURE createdata()
BEGIN
DECLARE i INT;
START TRANSACTION;
SET i=0;
WHILE i
INSERT INTO t_team VALUES(i+1,CONCAT('team',i+1));
SET i=i+1;
END WHILE;
SET i=0;
WHILE i
INSERT INTO t_people VALUES(i+1,CONCAT('people',i+1),i%1000+1);
SET i=i+1;
END WHILE;
COMMIT;
END
来源 http://blog.csdn.net/xiao__gui/article/details/8616224
bitsCN.com

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

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

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











Full table scanning may be faster in MySQL than using indexes. Specific cases include: 1) the data volume is small; 2) when the query returns a large amount of data; 3) when the index column is not highly selective; 4) when the complex query. By analyzing query plans, optimizing indexes, avoiding over-index and regularly maintaining tables, you can make the best choices in practical applications.

Yes, MySQL can be installed on Windows 7, and although Microsoft has stopped supporting Windows 7, MySQL is still compatible with it. However, the following points should be noted during the installation process: Download the MySQL installer for Windows. Select the appropriate version of MySQL (community or enterprise). Select the appropriate installation directory and character set during the installation process. Set the root user password and keep it properly. Connect to the database for testing. Note the compatibility and security issues on Windows 7, and it is recommended to upgrade to a supported operating system.

MySQL is an open source relational database management system. 1) Create database and tables: Use the CREATEDATABASE and CREATETABLE commands. 2) Basic operations: INSERT, UPDATE, DELETE and SELECT. 3) Advanced operations: JOIN, subquery and transaction processing. 4) Debugging skills: Check syntax, data type and permissions. 5) Optimization suggestions: Use indexes, avoid SELECT* and use transactions.

MySQL and MariaDB can coexist, but need to be configured with caution. The key is to allocate different port numbers and data directories to each database, and adjust parameters such as memory allocation and cache size. Connection pooling, application configuration, and version differences also need to be considered and need to be carefully tested and planned to avoid pitfalls. Running two databases simultaneously can cause performance problems in situations where resources are limited.

In MySQL database, the relationship between the user and the database is defined by permissions and tables. The user has a username and password to access the database. Permissions are granted through the GRANT command, while the table is created by the CREATE TABLE command. To establish a relationship between a user and a database, you need to create a database, create a user, and then grant permissions.

Data Integration Simplification: AmazonRDSMySQL and Redshift's zero ETL integration Efficient data integration is at the heart of a data-driven organization. Traditional ETL (extract, convert, load) processes are complex and time-consuming, especially when integrating databases (such as AmazonRDSMySQL) with data warehouses (such as Redshift). However, AWS provides zero ETL integration solutions that have completely changed this situation, providing a simplified, near-real-time solution for data migration from RDSMySQL to Redshift. This article will dive into RDSMySQL zero ETL integration with Redshift, explaining how it works and the advantages it brings to data engineers and developers.

LaravelEloquent Model Retrieval: Easily obtaining database data EloquentORM provides a concise and easy-to-understand way to operate the database. This article will introduce various Eloquent model search techniques in detail to help you obtain data from the database efficiently. 1. Get all records. Use the all() method to get all records in the database table: useApp\Models\Post;$posts=Post::all(); This will return a collection. You can access data using foreach loop or other collection methods: foreach($postsas$post){echo$post->

MySQL is suitable for beginners because it is simple to install, powerful and easy to manage data. 1. Simple installation and configuration, suitable for a variety of operating systems. 2. Support basic operations such as creating databases and tables, inserting, querying, updating and deleting data. 3. Provide advanced functions such as JOIN operations and subqueries. 4. Performance can be improved through indexing, query optimization and table partitioning. 5. Support backup, recovery and security measures to ensure data security and consistency.
