如何为 MySQL 表添加索引?

How do I add indexes to MySQL tables?(如何为 MySQL 表添加索引?)
本文介绍了如何为 MySQL 表添加索引?的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

I've got a very large MySQL table with about 150,000 rows of data. Currently, when I try and run

SELECT * FROM table WHERE id = '1';

the code runs fine as the ID field is the primary index. However, for a recent development in the project, I have to search the database by another field. For example:

SELECT * FROM table WHERE product_id = '1';

This field was not previously indexed; however, I've added one, so mysql now indexes the field, but when I try to run the above query, it runs very slowly. An EXPLAIN query reveals that there is no index for the product_id field when I've already added one, and as a result the query takes any where from 20 minutes to 30 minutes to return a single row.

My full EXPLAIN results are:

| id | select_type | table | type | possible_keys| key  | key_len | ref  | rows  | Extra       |
+----+-------------+-------+------+--------------+------+---------+------+-------+------------------+
|  1 | SIMPLE      | table | ALL  | NULL         | NULL | NULL    | NULL |157211 | Using where |
+----+-------------+-------+------+--------------+------+---------+------+-------+------------------+

It might be helpful to note that I've just taken a look, and ID field is stored as INT whereas the PRODUCT_ID field is stored as VARCHAR. Could this be the source of the problem?

解决方案

ALTER TABLE `table` ADD INDEX `product_id_index` (`product_id`)

Never compare integer to strings in MySQL. If id is int, remove the quotes.

这篇关于如何为 MySQL 表添加索引?的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持编程学习网!

本站部分内容来源互联网,如果有图片或者内容侵犯您的权益请联系我们删除!

相关文档推荐

Hibernate reactive No Vert.x context active in aws rds(AWS RDS中的休眠反应性非Vert.x上下文处于活动状态)
Bulk insert with mysql2 and NodeJs throws 500(使用mysql2和NodeJS的大容量插入抛出500)
Flask + PyMySQL giving error no attribute #39;settimeout#39;(FlASK+PyMySQL给出错误,没有属性#39;setTimeout#39;)
auto_increment column for a group of rows?(一组行的AUTO_INCREMENT列?)
Sort by ID DESC(按ID代码排序)
SQL/MySQL: split a quantity value into multiple rows by date(SQL/MySQL:按日期将数量值拆分为多行)