刚刚我们说过了,生活中难免会有一些不如意,比如,我们用一个字符串类型的字段来作为主键,表面上,这太不如意了,然而,事实也证明这是有用的。
对于大型的系统而言,Oracle,SQLServer无疑是最好的选择,可看看现在越来越多的小网站,他们没有自己的服务器,只是买别人的空间和数据库,但这种小型的数据库在性能上当然和大型数据库没有对比性,但小型的数据库也要对自己的优化方式,今天和大家分享Mysql中加没加单引号的巨大区别,对于MYSQL性能优化很有意义。刚刚我们说过了,生活中难免会有一些不如意,比如,我们用一个字符串类型的字段来作为主键,表面上,这太不如意了,然而,事实也证明这是有用的。问题也就出来了,当在查询语句中对该字段值加上单引号和不加查询耗时相差百倍!
测试表:
代码如下:
CREATE TABLE `foo` ( `key` varchar(10) NOT NULL, `time` int(11) NOT NULL, PRIMARY KEY (`key`)) ENGINE=MyISAM DEFAULT CHARSET=utf8;
然后插入30多万条数据,然后执行下面的SQL语句:
代码如下:
SELECT *FROM `foo`WHERE `key` =1293322797
查询花费 0.1288 秒,大约花费这么久的时间,然后,给1293322797加上单引号:
代码如下:
SELECT *FROM `foo`WHERE `key` ='1293322797'
查询花费 0.0009 秒,基本上相差100倍!!!也就是说不加单引号MYSQL性能损失了100倍,很震撼的比例!
后来用EXPLAIN分别跑了一下上面两条语句,见下面两张图:
没有单引号时
有单引号时
很明显,不使用单引号没有用上主索引,并进行了全表扫描,使用单引号就能使用上索引了。
后来我用大于分别进行了测试,返回的结果集相同,而他们的耗时和上面一样,用EXPLAIN测试,也和上面一样
代码如下:
SELECT *FROM `foo`WHERE `key` >1293322797SELECT *FROM `foo`WHERE `key` >'1293322797'
加单引号和不加单引号就是这么大的差别!就是会对mysql性能产生这么大的影响。
再后来,我将字段`key`换成INT类型,这时候,加不加单引号,就没有什么差别了,EXPLAIN显示他们都同样能够用上主索引,只是key_len变短了。
就是这些,综上所述,我们在写SQL查询的时候还是不厌其烦的加上单引号吧,似乎那没有坏处。

InnoDB uses redologs and undologs to ensure data consistency and reliability. 1.redologs record data page modification to ensure crash recovery and transaction persistence. 2.undologs records the original data value and supports transaction rollback and MVCC.

Key metrics for EXPLAIN commands include type, key, rows, and Extra. 1) The type reflects the access type of the query. The higher the value, the higher the efficiency, such as const is better than ALL. 2) The key displays the index used, and NULL indicates no index. 3) rows estimates the number of scanned rows, affecting query performance. 4) Extra provides additional information, such as Usingfilesort prompts that it needs to be optimized.

Usingtemporary indicates that the need to create temporary tables in MySQL queries, which are commonly found in ORDERBY using DISTINCT, GROUPBY, or non-indexed columns. You can avoid the occurrence of indexes and rewrite queries and improve query performance. Specifically, when Usingtemporary appears in EXPLAIN output, it means that MySQL needs to create temporary tables to handle queries. This usually occurs when: 1) deduplication or grouping when using DISTINCT or GROUPBY; 2) sort when ORDERBY contains non-index columns; 3) use complex subquery or join operations. Optimization methods include: 1) ORDERBY and GROUPB

MySQL/InnoDB supports four transaction isolation levels: ReadUncommitted, ReadCommitted, RepeatableRead and Serializable. 1.ReadUncommitted allows reading of uncommitted data, which may cause dirty reading. 2. ReadCommitted avoids dirty reading, but non-repeatable reading may occur. 3.RepeatableRead is the default level, avoiding dirty reading and non-repeatable reading, but phantom reading may occur. 4. Serializable avoids all concurrency problems but reduces concurrency. Choosing the appropriate isolation level requires balancing data consistency and performance requirements.

MySQL is suitable for web applications and content management systems and is popular for its open source, high performance and ease of use. 1) Compared with PostgreSQL, MySQL performs better in simple queries and high concurrent read operations. 2) Compared with Oracle, MySQL is more popular among small and medium-sized enterprises because of its open source and low cost. 3) Compared with Microsoft SQL Server, MySQL is more suitable for cross-platform applications. 4) Unlike MongoDB, MySQL is more suitable for structured data and transaction processing.

MySQL index cardinality has a significant impact on query performance: 1. High cardinality index can more effectively narrow the data range and improve query efficiency; 2. Low cardinality index may lead to full table scanning and reduce query performance; 3. In joint index, high cardinality sequences should be placed in front to optimize query.

The MySQL learning path includes basic knowledge, core concepts, usage examples, and optimization techniques. 1) Understand basic concepts such as tables, rows, columns, and SQL queries. 2) Learn the definition, working principles and advantages of MySQL. 3) Master basic CRUD operations and advanced usage, such as indexes and stored procedures. 4) Familiar with common error debugging and performance optimization suggestions, such as rational use of indexes and optimization queries. Through these steps, you will have a full grasp of the use and optimization of MySQL.

MySQL's real-world applications include basic database design and complex query optimization. 1) Basic usage: used to store and manage user data, such as inserting, querying, updating and deleting user information. 2) Advanced usage: Handle complex business logic, such as order and inventory management of e-commerce platforms. 3) Performance optimization: Improve performance by rationally using indexes, partition tables and query caches.


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