How to optimize MySQL through indexes

Indices can optimize MySQL. When the data in the data table is very large, you can solve this problem by creating an index. The index stores the data in the table in a separate location in alphabetical order to optimize database performance

The database index in MySQL can help us optimize performance. For small data tables, the difference may be very small, but for tables with a large amount of data, indexes have obvious advantages in improving performance. Next, in the article, I will introduce in detail how to optimize the database through indexing, which has a certain reference effect. I hope it will be helpful to everyone

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Database index

Database index is a A data structure that speeds up operations in a table. Every time an application runs a database query, the database looks at all the rows in the table to find rows that match the request. However, as database tables grow, more and more rows need to be checked each time, which degrades the overall performance of the database and application. But MySQL indexes solve this problem by taking the data from the columns in the table and storing it in alphabetical order in a separate location called the index.

Example: Suppose there is a data table named "demo" with only two rows "number" and "employee". When we run a simple SQL query, MySQL will check all the records and return only the records whose numerical value is set to 4.

SELECT * FROM sample WHERE number = 4;

However, when there are thousands of data in our database, this query will become particularly slow. In this case, an index is needed. In the table we can create an index through the "number" field. The index will create an internal register held by the MySQL service. This can be done using the following query

ALTER TABLE sample ADD INDEX (number);

For larger databases, the difference in load times can be significant. Indexing a database can significantly reduce web application load times.

In addition, we can also use another query to improve the loading speed of the database:

OPTIMIZE TABLE sample;

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