Optimizing Database Performance with Local Indexing in MySQL（mysql本地索引）

Database optimization is essential in designing fast-performing applications. Poorly designed databases can cause queries to run slowly, leading to long load times, unsatisfactory user experiences and lower conversions. To ensure the highest performance possible, one should choose the right database engine and optimize their queries whenever possible. One way to optimize MySQL databases is to use local indexing.

Local indexing in MySQL is the process of creating and maintaining an index of the columns in a table. The index stores the column’s data in a separate data structure, allowing the database to quickly access the columns without having to go through all the rows in the table. Using indexes can signifcantly improve the performance of queries that require multiple columns by reducing the amount of data scanned by the query engine.

Creating a local index in MySQL requires creating a unique index for each column in the table. Unique indexes ensure that no duplicate values exist for the considered column value. To create a unique index for a column, you can simply use the command CREATE UNIQUE INDEX. For example, to create a unique index for the email column in the users table, the command is as follows:

CREATE UNIQUE INDEX users_email_i ON users (email);

Once an index is created, the MySQL database engine will use it when executing queries that contain columns referenced in the index. This can lead to significant improvements in query performance by reducing the amount of data the query engine needs to inspect. To further optimize database performance, you may choose to create a combined index for multiple columns. Combined indexes allow the database engine to quickly access multiple columns without having to go through each column separately.

When developing a database application, it is important to consider the implications of local indexing on database performance. By leveraging indexes in the right way, database performance can be substantially improved. Specifically, creating unique and combined indexes can reduce the amount of data scanned by the query engine, resulting in faster query execution times and improved database performance.