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HomeBackend DevelopmentPHP TutorialHow to improve MySQL performance by vertically partitioning tables

How to improve MySQL performance by vertically partitioning tables

May 10, 2023 pm 09:31 PM
vertical partitionmysql performance optimizationDatabase table design

With the rapid development of the Internet, the scale of data continues to expand, and the demand for database storage and query efficiency is also getting higher and higher. As the most commonly used open source database, MySQL's performance optimization has always been the focus of developers. This article will introduce an effective MySQL performance optimization technology - vertical partition table, and explain in detail how to implement and apply it.

1. What is a vertical partition table?

Vertically partitioned tables refer to dividing a table according to column characteristics and storing different columns on different physical storage devices to improve query efficiency. In a vertically partitioned table, the columns in a table can be logically grouped, and a physical table is created for each group of columns. Each physical table contains the group of columns and other columns that need to be queried.

For example, an order table can be divided vertically into two tables: the order details table and the order summary table. The order details table contains detailed information about the order, such as product name, quantity, price, etc.; the order summary table contains summary information about the order, such as order number, order time, total amount, etc. In this way, when querying order details, you only need to query the order details table, and when querying order summary information, you only need to query the order summary table, without reading the entire order table, thus improving query efficiency.

2. Why use vertical partition table?

Normally, the structure of a database table is flat and contains all columns. When the amount of data in the table is large, querying all columns will cause large IO overhead, increase query time and system overhead. The vertical partitioning table technology can divide the columns of the table according to their characteristics, and store frequently used columns and infrequently used columns separately, thereby reducing IO operations. Vertically partitioned tables can bring the following advantages:

  1. Improve IO efficiency: After partitioning the columns of the table according to their characteristics, unnecessary IO operations can be reduced, thereby improving query efficiency and performance.
  2. Reduce the width of the table: Compared with the table with a flat structure, the width of the table after vertical partitioning is smaller, and the size of each row of data is more compact, which reduces the storage overhead of data in memory.
  3. Reduce the amount of query data: When the query does not need to use all columns, only query the columns of the relevant partitions, which can reduce the amount of data retrieved and improve query efficiency.
  4. Better maintainability: Vertically partitioned tables can group related columns in the table, reduce redundant data storage, and better maintain data integrity.

3. How to implement a vertical partition table?

MySQL provides two methods to implement vertical partitioning tables:

  1. Split table: all columns of a table are divided into different physical tables, each table contains the Group columns and other columns that need to be queried. Split tables are suitable for tables with fewer columns and lower complexity.
  2. Split view: Copy a table containing related column groups to different physical tables, create a view to combine the partitioned tables into one table, so that all columns can be queried during query. Split view is suitable for scenarios where partitioning is complex and all columns need to be queried.

Choose different partitioning methods based on specific scenarios and needs.

4. How to select the partition field?

Choosing the appropriate partition field is very critical. Improper selection will result in reduced query efficiency. The following points are worth noting:

  1. Data uniformity: For numeric-based fields, such as order amount, product ID, etc., you need to consider whether the amount of data contained in each partition after partitioning is even. If a certain partition contains a large amount of data and other partitions have very little data, all partitions will need to be read during the query and the optimization effect will be lost.
  2. Access frequency: It is necessary to select frequently accessed columns as partition fields according to the actual query scenario. If the data is relatively average, you can use multiple partition fields. For multiple partition fields, consider the combination of data.
  3. Update frequency of partition fields: Consider the update frequency of partition fields and select more stable fields for partitioning.

5. Notes

  1. The planning of the partition table should be completed when designing the database, and the data growth should be taken into consideration to prevent the table from being too wide. performance issues.
  2. The data distribution of the partition table should be even, ensuring that the data size of each partition is roughly equal, otherwise query performance will be greatly affected.
  3. It will be more difficult when the partition table needs to be backed up and restored, because multiple tables need to be backed up and restored.
  4. Partitioned tables are more friendly for query operations, but operations such as update and delete may not be as efficient as ordinary tables due to the need to operate multiple tables.
  5. The partition field of the partitioned table does not support operations such as foreign keys, indexes, and SQL functions.

6. Summary

Vertically partitioned tables are an effective way to optimize MySQL performance. By rationally selecting partition fields and allocating data to different physical tables, MySQL query efficiency can be further improved. However, in actual applications, it is necessary to select appropriate partitioning methods and partitioning fields according to specific scenarios to avoid performance problems caused by improper partitioning.

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