Home Database Mysql Tutorial How to implement MySQL underlying optimization: horizontal and vertical splitting strategies for data tables

How to implement MySQL underlying optimization: horizontal and vertical splitting strategies for data tables

Nov 08, 2023 pm 06:57 PM
mysql data sheet Low-level optimization

How to implement MySQL underlying optimization: horizontal and vertical splitting strategies for data tables

How to implement MySQL underlying optimization: horizontal and vertical splitting strategies for data tables, specific code examples are required

Introduction:
In large-scale application scenarios, MySQL database Often faced with the pressure of storing and querying massive data. In order to solve this problem, MySQL provides data table partitioning strategies, including horizontal partitioning (Horizontal Partitioning) and vertical partitioning (Vertical Partitioning). This article will introduce how to implement MySQL underlying optimization, focusing on the data table segmentation strategy, and will also give specific code examples.

1. Horizontal splitting strategy for data tables
Horizontal splitting refers to dividing the data originally stored in the same table into multiple tables according to certain conditions, and each table only contains part of the data. The core of horizontal splitting is to disperse data into different physical tables based on the value of a certain column, which can reduce the amount of data in a single table and improve query efficiency.

The following takes an order table as an example, assuming that it needs to be divided horizontally according to the order date. First create an original order table:

CREATE TABLE orders (
  order_id INT PRIMARY KEY,
  customer_id INT,
  order_date DATE,
  total_amount DECIMAL(10,2),
  ...
);
Copy after login
Copy after login

Next, use the following code example to implement the function of horizontal splitting by order date:

-- 创建分表orders_2020、orders_2021
CREATE TABLE orders_2020 LIKE orders;
CREATE TABLE orders_2021 LIKE orders;

-- 将订单数据插入到对应的分表中
INSERT INTO orders_2020 SELECT * FROM orders WHERE order_date BETWEEN '2020-01-01' AND '2020-12-31';
INSERT INTO orders_2021 SELECT * FROM orders WHERE order_date BETWEEN '2021-01-01' AND '2021-12-31';

-- 删除原始订单表
DROP TABLE orders;
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With the above code, we create two sub-tables orders_2020 and orders_2021, and split and insert the order data according to the conditions of the order date. Finally the original order form is deleted.

2. Vertical segmentation strategy of data tables
Vertical segmentation refers to dividing the columns originally stored in the same table into multiple tables according to a certain rule, and each table only contains some columns. The purpose of vertical splitting is to separate frequently queried columns from infrequently queried columns to improve query efficiency.

Continuing to take the order table as an example, assume that the order table is divided vertically according to the order amount, and the basic information of the order and the order amount are stored in two tables respectively. First create an original order table:

CREATE TABLE orders (
  order_id INT PRIMARY KEY,
  customer_id INT,
  order_date DATE,
  total_amount DECIMAL(10,2),
  ...
);
Copy after login
Copy after login

Next, use the following code example to implement vertical splitting of the order table:

-- 创建分表orders_info和orders_amount
CREATE TABLE orders_info (
  order_id INT PRIMARY KEY,
  customer_id INT,
  order_date DATE,
  ...
);

CREATE TABLE orders_amount (
  order_id INT PRIMARY KEY,
  total_amount DECIMAL(10,2)
);

-- 将数据插入到对应的分表中
INSERT INTO orders_info SELECT order_id, customer_id, order_date FROM orders;
INSERT INTO orders_amount SELECT order_id, total_amount FROM orders;

-- 删除原始订单表
DROP TABLE orders;
Copy after login

With the above code, we create two sub-tables orders_info and orders_amount, and split and insert the order data according to basic information and order amount. Finally the original order form is deleted.

Summary:
Through horizontal and vertical segmentation strategies, we can optimize the underlying MySQL and improve query efficiency. Horizontal splitting can disperse data into multiple tables, reducing the amount of data in a single table; vertical splitting can separate frequently queried columns from infrequently queried columns, improving query efficiency. In actual applications, select an appropriate segmentation strategy based on specific business scenarios and write corresponding code to implement the segmentation function.

Note: The above code examples are for demonstration purposes only, and need to be appropriately modified and improved according to specific needs in actual applications.

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