MySQL中varchar(50)和varchar(500)区别是什么?

作者：向显

链接：https://juejin.cn/post/7350228838151847976

# 问题描述

我们在设计表结构的时候,设计规范里面有一条如下规则:

对于可变长度的字段，在满足条件的前提下，尽可能使用较短的变长字段长度。

为什么这么规定,我在网上查了一下,主要基于两个方面

基于存储空间的考虑

基于性能的考虑

网上说Varchar(50)和varchar(500)存储空间上是一样的,真的是这样吗?

基于性能考虑,是因为过长的字段会影响到查询性能?

本文我将带着这两个问题探讨验证一下

# 验证存储空间区别

CREATE TABLE `category_info_varchar_50` ( `id` bigint(20) NOT NULL AUTO_INCREMENT COMMENT '主键', `name` varchar(50) NOT NULL COMMENT '分类名称', `is_show` tinyint(4) NOT NULL DEFAULT '0' COMMENT '是否展示：0 禁用，1启用', `sort` int(11) NOT NULL DEFAULT '0' COMMENT '序号', `deleted` tinyint(1) DEFAULT '0' COMMENT '是否删除', `create_time` datetime NOT NULL COMMENT '创建时间', `update_time` datetime NOT NULL COMMENT '更新时间', PRIMARY KEY (`id`) USING BTREE, KEY `idx_name` (`name`) USING BTREE COMMENT '名称索引') ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='分类';

CREATE TABLE `category_info_varchar_500` ( `id` bigint(20) NOT NULL AUTO_INCREMENT COMMENT '主键', `name` varchar(500) NOT NULL COMMENT '分类名称', `is_show` tinyint(4) NOT NULL DEFAULT '0' COMMENT '是否展示：0 禁用，1启用', `sort` int(11) NOT NULL DEFAULT '0' COMMENT '序号', `deleted` tinyint(1) DEFAULT '0' COMMENT '是否删除', `create_time` datetime NOT NULL COMMENT '创建时间', `update_time` datetime NOT NULL COMMENT '更新时间', PRIMARY KEY (`id`) USING BTREE, KEY `idx_name` (`name`) USING BTREE COMMENT '名称索引') ENGINE=InnoDB AUTO_INCREMENT=288135 DEFAULT CHARSET=utf8mb4 COMMENT='分类';

2.准备数据

给每张表插入相同的数据,为了凸显不同,插入100万条数据

DELIMITER $$CREATE PROCEDURE batchInsertData(IN total INT)BEGIN DECLARE start_idx INT DEFAULT 1; DECLARE end_idx INT; DECLARE batch_size INT DEFAULT 500; DECLARE insert_values TEXT; SET end_idx = LEAST(total, start_idx + batch_size - 1); WHILE start_idx <= total DO SET insert_values = ''; WHILE start_idx <= end_idx DO SET insert_values = CONCAT(insert_values, CONCAT('(\'name', start_idx, '\', 0, 0, 0, NOW(), NOW()),')); SET start_idx = start_idx + 1; END WHILE; SET insert_values = LEFT(insert_values, LENGTH(insert_values) - 1); -- Remove the trailing comma SET @sql = CONCAT('INSERT INTO category_info_varchar_50 (name, is_show, sort, deleted, create_time, update_time) VALUES ', insert_values, ';'); PREPARE stmt FROM @sql; EXECUTE stmt; SET @sql = CONCAT('INSERT INTO category_info_varchar_500 (name, is_show, sort, deleted, create_time, update_time) VALUES ', insert_values, ';'); PREPARE stmt FROM @sql; EXECUTE stmt; SET end_idx = LEAST(total, start_idx + batch_size - 1); END WHILE;END$$DELIMITER ;

CALL batchInsertData(1000000);

3.验证存储空间

查询第一张表SQL

SELECT table_schema AS "数据库", table_name AS "表名", table_rows AS "记录数", TRUNCATE ( data_length / 1024 / 1024, 2 ) AS "数据容量（MB）", TRUNCATE ( index_length / 1024 / 1024, 2 ) AS "索引容量（MB）" FROM information_schema.TABLES WHERE table_schema = 'test_mysql_field' and TABLE_NAME = 'category_info_varchar_50'ORDER BY data_length DESC, index_length DESC;

查询结果

查询第二张表SQL

SELECT table_schema AS "数据库", table_name AS "表名", table_rows AS "记录数", TRUNCATE ( data_length / 1024 / 1024, 2 ) AS "数据容量（MB）", TRUNCATE ( index_length / 1024 / 1024, 2 ) AS "索引容量（MB）" FROM information_schema.TABLES WHERE table_schema = 'test_mysql_field' and TABLE_NAME = 'category_info_varchar_500'ORDER BY data_length DESC, index_length DESC;

查询结果

4.结论

两张表在占用空间上确实是一样的,并无差别

# 验证性能区别

1.验证索引覆盖查询

select name from category_info_varchar_50 where name = 'name100000'-- 耗时0.012sselect name from category_info_varchar_500 where name = 'name100000'-- 耗时0.012sselect name from category_info_varchar_50 order by name;-- 耗时0.370sselect name from category_info_varchar_500 order by name;-- 耗时0.379s

通过索引覆盖查询性能差别不大

2.验证索引查询

select * from category_info_varchar_50 where name = 'name100000'--耗时 0.012sselect * from category_info_varchar_500 where name = 'name100000'--耗时 0.012sselect * from category_info_varchar_50 where name in('name100','name1000','name100000','name10000','name1100000','name200','name2000','name200000','name20000','name2200000','name300','name3000','name300000','name30000','name3300000','name400','name4000','name400000','name40000','name4400000','name500','name5000','name500000','name50000','name5500000','name600','name6000','name600000','name60000','name6600000','name700','name7000','name700000','name70000','name7700000','name800','name8000','name800000','name80000','name6600000','name900','name9000','name900000','name90000','name9900000') -- 耗时 0.011s -0.014s -- 增加 order by name 耗时 0.012s - 0.015s

select * from category_info_varchar_50 where name in('name100','name1000','name100000','name10000','name1100000','name200','name2000','name200000','name20000','name2200000','name300','name3000','name300000','name30000','name3300000','name400','name4000','name400000','name40000','name4400000','name500','name5000','name500000','name50000','name5500000','name600','name6000','name600000','name60000','name6600000','name700','name7000','name700000','name70000','name7700000','name800','name8000','name800000','name80000','name6600000','name900','name9000','name900000','name90000','name9900000') -- 耗时 0.012s -0.014s -- 增加 order by name 耗时 0.014s - 0.017s

索引范围查询性能基本相同, 增加了order By后开始有一定性能差别;

3.验证全表查询和排序

全表无排序

全表有排序

select * from category_info_varchar_50 order by name ;--耗时 1.498sselect * from category_info_varchar_500 order by name ;--耗时 4.875s

结论:

全表扫描无排序情况下,两者性能无差异,在全表有排序的情况下, 两种性能差异巨大;

分析原因

varchar50 全表执行sql分析

我发现86%的时花在数据传输上,接下来我们看状态部分,关注Created_tmp_files和sort_merge_passes

Created_tmp_files为3

sort_merge_passes为95

varchar500 全表执行sql分析

增加了临时表排序

Created_tmp_files 为 4

sort_merge_passes为645

关于sort_merge_passes, Mysql给出了如下描述:

Number of merge passes that the sort algorithm has had to do. If this value is large, you may want to increase the value of the sort_buffer_size.

其实sort_merge_passes对应的就是MySQL做归并排序的次数，也就是说，如果sort_merge_passes值比较大，说明sort_buffer和要排序的数据差距越大，我们可以通过增大sort_buffer_size或者让填入sort_buffer_size的键值对更小来缓解sort_merge_passes归并排序的次数。

# 最终结论

至此,我们不难发现,当我们最该字段进行排序操作的时候,Mysql会根据该字段的设计的长度进行内存预估, 如果设计过大的可变长度, 会导致内存预估的值超出sort_buffer_size的大小, 导致mysql采用磁盘临时文件排序,最终影响查询性能;