Summary of some commonly used mysql optimization methods

1. Select the most applicable field attributes

MySQL can well support the access of large amounts of data, but generally speaking, the The smaller the table, the faster queries executed on it will be. Therefore, when creating a table, in order to obtain better performance, we can set the width of the fields in the table as small as possible. For example, when defining the postal code field, if you set it to CHAR(255), it will obviously add unnecessary space to the database. Even using the VARCHAR type is redundant, because CHAR(6) is fine. Mission accomplished. Likewise, if possible, we should use MEDIUMINT instead of BIGIN to define integer fields.
Another way to improve efficiency is to set fields to NOT NULL when possible, so that the database does not need to compare NULL values ​​when executing queries in the future.
For some text fields, such as "province" or "gender", we can define them as ENUM type. Because in MySQL, the ENUM type is treated as numeric data, and numeric data is processed much faster than text types. In this way, we can improve the performance of the database.
2. Use joins (JOIN) instead of sub-queries (Sub-Queries)
MySQL supports SQL subqueries starting from 4.1. This technique allows you to use a SELECT statement to create a single column of query results, and then use this result as a filter condition in another query. For example, if we want to delete customers who do not have any orders in the basic customer information table, we can use a subquery to first retrieve the IDs of all customers who issued orders from the sales information table, and then pass the results to the main query, as shown below :

DELETE FROM customerinfo WHERE CustomerID NOT in (SELECT CustomerID FROM salesinfo )

Using subqueries can complete many SQL operations that logically require multiple steps to complete at one time. It can also avoid transaction or table locks and write It's easy to get up too. However, in some cases, subqueries can be replaced by more efficient joins (JOIN).. For example, suppose we want to fetch all users who do not have order records, we can use the following query to complete:

SELECT * FROM customerinfo WHERE CustomerID NOT in (SELECT CustomerID FROM salesinfo )

If you use a connection (JOIN).. to complete this query, the speed will be faster a lot of. Especially when there is an index on CustomerID in the salesinfo table, the performance will be better. The query is as follows:

SELECT * FROM customerinfo LEFT JOIN salesinfoON customerinfo.CustomerID=salesinfo. CustomerID WHERE salesinfo.CustomerID IS NULL

Connection (JOIN).. The reason why it is more efficient , because MySQL does not need to create a temporary table in memory to complete this logical two-step query.
3. Use union (UNION) to replace manually created temporary tables
MySQL supports UNION query starting from version 4.0, which can combine two or more data that need to use temporary tables. SELECT queries are merged into one query. When the client's query session ends, the temporary table will be automatically deleted to ensure that the database is tidy and efficient. When using UNION to create a query, we only need to use UNION as the keyword to connect multiple SELECT statements. It should be noted that the number of fields in all SELECT statements must be the same. The following example demonstrates a query using UNION.

SELECT Name, Phone FROM client UNION SELECT Name, BirthDate FROM author 
UNION 
SELECT Name, Supplier FROM product

4. Locking tables
Although transactions are a very good way to maintain the integrity of the database, because of its exclusivity, it sometimes affects the performance of the database. performance, especially in large application systems. Since the database will be locked during the execution of the transaction, other user requests can only wait until the transaction ends. If a database system is used by only a few users, the impact of transactions will not become a big problem; but suppose there are thousands of users accessing a database system at the same time, such as accessing an e-commerce website, This will cause serious response delays.
In fact, in some cases we can obtain better performance by locking the table. The following example uses the lock table method to complete the transaction function in the previous example.

LOCK TABLE inventory WRITE 
SELECT Quantity FROM inventory 
WHEREItem='book'; 
... 
UPDATE inventory SET Quantity=11 
WHEREItem='book'; 
UNLOCK TABLES

5. Using foreign keys The method of locking the table can maintain the integrity of the data, but it cannot guarantee the relevance of the data. At this time we can use foreign keys. For example, a foreign key can ensure that each sales record points to an existing customer. Here, the foreign key can map the CustomerID in the customerinfo table to the CustomerID in the salesinfo table. Any record without a valid CustomerID will not be updated or inserted into salesinfo.

CREATE TABLE customerinfo 
( 
CustomerID INT NOT NULL , 
PRIMARY KEY ( CustomerID ) 
) TYPE = INNODB; 
CREATE TABLE salesinfo 
( 
SalesID INT NOT NULL, 
CustomerID INT NOT NULL, 
PRIMARY KEY(CustomerID, SalesID), 
FOREIGN KEY (CustomerID) REFERENCES customerinfo 
(CustomerID) ON DELETECASCADE 
) TYPE = INNODB;

注意例子中的参数“ON DELETE CASCADE”。该参数保证当 customerinfo 表中的一条客户记录被删除的时候，salesinfo 表中所有与该客户相关的记录也会被自动删除。如果要在 MySQL 中使用外键，一定要记住在创建表的时候将表的类型定义为事务安全表 InnoDB类型。该类型不是 MySQL 表的默认类型。定义的方法是在 CREATE TABLE 语句中加上 TYPE=INNODB。如例中所示。
6、使用索引
索引是提高数据库性能的常用方法，它可以令数据库服务器以比没有索引快得多的速度检索特定的行，尤其是在查询语句当中包含有MAX(), MIN()和ORDERBY这些命令的时候，性能提高更为明显。那该对哪些字段建立索引呢？一般说来，索引应建立在那些将用于JOIN, WHERE判断和ORDER BY排序的字段上。尽量不要对数据库中某个含有大量重复的值的字段建立索引。对于一个ENUM类型的字段来说，出现大量重复值是很有可能的情况，例如 customerinfo中的“province”.. 字段，在这样的字段上建立索引将不会有什么帮助；相反，还有可能降低数据库的性能。我们在创建表的时候可以同时创建合适的索引，也可以使用ALTER TABLE或CREATE INDEX在以后创建索引。此外，MySQL
从版本3.23.23开始支持全文索引和搜索。全文索引在MySQL 中是一个FULLTEXT类型索引，但仅能用于MyISAM 类型的表。对于一个大的数据库，将数据装载到一个没有FULLTEXT索引的表中，然后再使用ALTER TABLE或CREATE INDEX创建索引，将是非常快的。但如果将数据装载到一个已经有FULLTEXT索引的表中，执行过程将会非常慢。
7、优化的查询语句
绝大多数情况下，使用索引可以提高查询的速度，但如果SQL语句使用不恰当的话，索引将无法发挥它应有的作用。下面是应该注意的几个方面。首先，最好是在相同类型的字段间进行比较的操作。在MySQL 3.23版之前，这甚至是一个必须的条件。例如不能将一个建有索引的INT字段和BIGINT字段进行比较；但是作为特殊的情况，在CHAR类型的字段和 VARCHAR类型字段的字段大小相同的时候，可以将它们进行比较。其次，在建有索引的字段上尽量不要使用函数进行操作。
例如，在一个DATE类型的字段上使用YEAE()函数时，将会使索引不能发挥应有的作用。所以，下面的两个查询虽然返回的结果一样，但后者要比前者快得多。

SELECT * FROM order WHERE YEAR(OrderDate)<2021; 
SELECT * FROM order WHERE OrderDate<"2021-01-01";

同样的情形也会发生在对数值型字段进行计算的时候：

SELECT * FROM inventory WHERE Amount/7<24; 
SELECT * FROM inventory WHERE Amount<24*7;

上面的两个查询也是返回相同的结果，但后面的查询将比前面的一个快很多。第三，在搜索字符型字段时，我们有时会使用 LIKE 关键字和通配符，这种做法虽然简单，但却也是以牺牲系统性能为代价的。例如下面的查询将会比较表中的每一条记录。

SELECT * FROM books 
WHERE name like "MySQL%"

但是如果换用下面的查询，返回的结果一样，但速度就要快上很多：

SELECT * FROM books 
WHERE name>="MySQL"and name<"MySQM"

最后，应该注意避免在查询中让MySQL进行自动类型转换，因为转换过程也会使索引变得不起作用。

The above is the detailed content of Summary of some commonly used mysql optimization methods. For more information, please follow other related articles on the PHP Chinese website!