How to use PHP to implement MySQL table partitioning to improve query efficiency

1. What is a sub-table?

In MySQL, tables are the main form of data storage. If millions of records are stored in a table, querying the data becomes very slow because MySQL needs to scan the entire table to find the required data. In order to speed up queries, it helps to split a large table into multiple small tables, each small table stores a corresponding part of the data. This technique is called sharding.

2. Why divide the table?

In large websites, it is very common to have tables with millions or hundreds of millions of records. Not only do these tables require a lot of storage space, but they are also very slow to query. The main purpose of table sharding is to improve database query speed and response time by storing data dispersedly in multiple small tables, thereby solving related problems.

3. How to divide the table?

Before splitting the table, you should first determine how to split the data. Data can be segmented according to time, region, user and other methods. For example, the data can be split by region and stored in different tables, or the data can be split into multiple tables of different months based on time. In order to better organize and manage data, it is a best practice to divide the data into chunks with similar attributes.

After determining the division method, you can start to divide the tables. The specific steps are as follows:

Step 1: Create the database and table structure of the sub-table.

First, a new table structure needs to be created in the database to store scattered data. The table structure should be the same as the original table structure. For example, if the original table name is user, then the split table names can be named user_1, user_2, etc.

Step 2: Insert data into scattered tables.

After creating the table structure, you can insert data into the split table. Various methods can be used to split data blocks depending on how they are split. By dividing the data by time, you can copy the data from the original table to the corresponding timetable.

Step 3: Query data.

In order to query data, you need to send query requests to all sub-tables and summarize the results. In PHP, you can use the UNION operator to combine query results. The following is an example of a query command that can be used to retrieve data registered by all users in August 2021:

SELECT * FROM user_202108
UNION
SELECT * FROM user_202109 ;

4. The impact of table partitioning on query efficiency

Split tables can significantly improve query efficiency. For example, there are 10 million records in the original table, but only 1 million records in each sub-table. Doing this allows MySQL to only scan 1 million records in each split table when querying the data, instead of scanning all the records in the original table. This improves query efficiency and spreads the database load well.

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