MySql’s partition table technology: How to implement MySQL’s partition table technology

MySQL's partitioned table technology is very common in large database applications, because with the increasing amount of data, the traditional table structure can no longer meet business needs. MySQL's partition table technology can help us divide a large table into several small tables, so that we can process data more efficiently and achieve more optimizations.

This article will introduce MySQL's partition table technology, including the concept of partition tables, implementation methods, advantages and disadvantages, and usage scenarios. I hope readers can learn about the basic knowledge and practical applications of MySQL partition table technology through this article.

1. The concept of partition table

The partition table of MySQL is to divide a large table into several sub-tables according to certain rules, and each sub-table can be operated independently. The main purpose of partitioning tables is to improve data query performance and reduce the data volume of a single table. Partition tables support two methods: horizontal partitioning and vertical partitioning.

Horizontal partitioning refers to dividing a large table into several small tables according to the value range of a certain field, and each small table contains a part of the data. For example, an order table can be divided into 12 sub-tables according to the order date, and each sub-table stores the order data for January. In this way, when we need to query the order data of a certain month, we only need to query the corresponding sub-table instead of scanning the entire large table.

Vertical partitioning refers to dividing a table into several small tables according to fields, and each small table contains a part of the fields. For example, a user table containing a large number of fields can be divided into two tables based on user basic information and user additional information. In this way, when querying the user's basic information, you only need to scan the basic information table instead of scanning all columns.

2. Methods of implementing partitioned tables

There are two main methods of implementing partitioned tables: table partitioning and partitioned table view. The following are the implementation steps and precautions for these two methods respectively.

1. Table partitioning

Table partitioning clearly specifies the specific range of each partition when creating the table, and specifies an independent storage method for each partition.

The steps are as follows:

(1) Create the table and specify the partition type

CREATE TABLE orders (
id int(11) NOT NULL AUTO_INCREMENT,
user_id int(11) NOT NULL,
product_id int(11) NOT NULL,
price decimal(10,2) NOT NULL,
order_date date NOT NULL,
PRIMARY KEY (id,order_date)
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4
PARTITION BY RANGE COLUMNS(order_date)(
PARTITION p01 VALUES LESS THAN ('2021-01-01'),
PARTITION p02 VALUES LESS THAN ('2021-02 -01'),
PARTITION p03 VALUES LESS THAN ('2021-03-01'),
PARTITION p04 VALUES LESS THAN ('2021-04-01'),
PARTITION p05 VALUES LESS THAN ( '2021-05-01')
);

The above example is horizontal partitioning based on order date, and the data can be divided into five sub-tables based on month.

（2）Insert data

INSERT INTO orders (user_id,product_id,price,order_date)
VALUES(1,1,1000.00,'2021-01-01');

When inserting data according to partition rules, MySQL will insert the data into the corresponding partition based on the value of order_date.

(3) Query data

SELECT * FROM orders WHERE order_date='2021-01-01';

When querying, MySQL will automatically route to the matching partition. And only scan the corresponding sub-table, thereby improving query efficiency.

2. Partitioned table view

Partitioned table view integrates data from multiple tables through views, and is externally presented as a partitioned table, and supports partitioning. operate. The advantage of the partitioned view is that a series of similar small tables can be maintained through the view for easy management.

The steps are as follows:

(1) Create a small table

CREATE TABLE orders01 (
id int(11 ) NOT NULL AUTO_INCREMENT,
user_id int(11) NOT NULL,
product_id int(11) NOT NULL,
price decimal (10,2) NOT NULL,
order_date date NOT NULL,
PRIMARY KEY (id)
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;

(2) Insert data

INSERT INTO orders01 (user_id, product_id, price, order_date)
VALUES(1,1,1000.00,'2021-01-01');

(3) Create a partitioned table view

CREATE VIEW orders AS
SELECT * FROM orders01 WHERE order_date <'2021-02-01' UNION ALL
SELECT * FROM orders02 WHERE order_date < ;'2021-03-01' UNION ALL
SELECT * FROM orders03 WHERE order_date <'2021-04-01' UNION ALL
SELECT * FROM orders04 WHERE order_date <'2021-05-01' UNION ALL
SELECT * FROM orders05 WHERE order_date <'2021-06-01';

The above steps will integrate orders divided into five sub-tables according to date through views. When the SELECT * FROM orders WHERE order_date='2021-01-01'; statement queries data, MySQL will automatically route to the corresponding sub-table and scan it to query the results.

3. Advantages and disadvantages of partition table technology

MySQL’s partition table technology has the following advantages and disadvantages:

Advantages:

(1) Improve data Query performance, reduce the amount of data in a single table, and reduce the read and write pressure on the database.

(2) Improve the reliability and maintainability of data, and manage data more flexibly.

(3) Choose horizontal partitioning and vertical partitioning according to actual business needs, which is more in line with actual needs.

Disadvantages:

(1) The implementation of partition tables will increase a certain amount of complexity and management workload.

(2) Data migration and backup operations require special configuration and processing.

(3) The implementation of partition table needs to consider the compatibility of database version and storage engine, which may affect upgrade and migration operations.

4. Usage Scenarios

MySQL’s partition table technology is more suitable in the following scenarios:

(1) Systems that need to process large amounts of data, such as logs, orders, members Information etc.

(2) A system that needs to flexibly respond to business changes and demand modifications.

(3) A system that requires efficient data query and statistical analysis.

In short, MySQL's partition table technology can help us process large amounts of data more efficiently and improve the reliability and maintainability of the system. However, before using partition table technology, we need to carefully analyze and plan the business and choose the appropriate partitioning method and implementation method.

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