Data storage optimization tips in MySQL

MySQL is currently the most widely used relational database management system. It has the advantages of stability, scalability and high performance. However, for applications that store big data, there are still some challenges in handling data storage. Therefore, this article will introduce some tips for optimizing data storage in MySQL to improve MySQL performance and reliability.

1. Choose the correct storage engine

A storage engine is a software component that provides basic functions for data storage management. MySQL provides multiple storage engines, including InnoDB, MyISAM, MEMORY, etc. When choosing a storage engine, you need to evaluate your application's requirements and characteristics. If the application requires high concurrency support and transaction processing, the InnoDB engine should be selected; if the application only requires simple read and write operations, the MyISAM engine can be selected.

2. Use compression technology

Compression technology is an important method to optimize data storage. MySQL provides a variety of compression technologies, such as compressed tables, compressed rows, etc. When compressing a table, you can enable compression using the ALTER TABLE statement or set the ROW_FORMAT option when creating the table.

3. Optimize the table structure

Optimization of the table structure can reduce the space occupied by the table and improve the efficiency of data access. Common optimization methods include:

(1) Try to use integer types

Integer types are better than other data types in terms of storage space and calculation efficiency. Try to use integer data types such as INT and BIGINT to save numerical data, rather than using floating-point types such as FLOAT and DOUBLE.

(2) Use ENUM and SET types

When you need to store fixed values, you can use the ENUM and SET types. Their storage space and query efficiency are higher than VARCHAR and other types.

(3) Avoid using TEXT and BLOB types

TEXT and BLOB types have larger storage space and are more time-consuming to query. If you can use VARCHAR and other types instead, you should try to avoid using TEXT and BLOB types.

(4) Avoid excessive use of NULL values

NULL values ​​require extra space and time to process when used, so you should try to avoid using NULL values ​​for columns in the table.

4. Partitioned table

Partitioned table is a technology that divides a table into multiple logical parts. MySQL supports horizontal partitioning and vertical partitioning. Horizontal partitioning groups tables by rows, and each partition has its own physical storage unit and can be managed independently. Vertical partitioning is grouping by column, dividing the columns in the table into multiple parts, each part being saved in a separate table.

Partitioned tables can effectively improve the efficiency of query and insertion operations and reduce system load when processing big data.

5. Use indexes

An index is a structure that sorts one or more columns in a database table, which can improve the efficiency of data access. MySQL provides multiple types of indexes, such as B-tree, hash table, full-text index, etc. When using indexes, you need to pay attention to the following points:

(1) Avoid creating too many indexes

Indexes can improve query efficiency, but creating too many indexes will take up too much storage space , reducing the efficiency of data modification. Therefore, when creating indexes, you should adjust them according to the needs of the application and try to avoid creating too many indexes.

(2) Avoid using long strings as indexes

Using long strings as indexes will take up a lot of storage space and calculation time, and reduce the efficiency of data modification. Therefore, when selecting index columns, you should try to choose shorter string or integer data types.

(3) Periodically maintain the index

When the amount of data is large, the index may become large and sparse, resulting in reduced query efficiency. Therefore, the index needs to be optimized and maintained periodically, such as reorganizing and rebuilding the index.

To sum up, data storage optimization skills in MySQL involve many aspects, including selecting the correct storage engine, using compression technology, optimizing table structure, partitioning tables, using indexes, etc. The above tips will help optimize MySQL's data storage method and improve the performance and reliability of the database to better meet the needs of the application.

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