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Updated on 2025-04-14

Implementation of partitioning and database partitioning of MySQL large table data

With the development of business and the increasing amount of data, a single MySQL database table may not be able to meet the needs of high performance and high availability, resulting in reduced query efficiency, insufficient storage space, and even database downtime. To solve these problems, the databasePartitionandLibrary and tableThese are two commonly used technical solutions.

This article will be fromPartition of MySQL large table dataandLibrary and tableIn-depth analysis of two aspects helps developers understand how to effectively deal with the challenges brought by large data volumes.

1. Partition of MySQL large table data

1.1 What is partition?

PartitioningIt is a technology to divide the logical data of a single table into multiple physical partitions. Each partition can store a portion of data, which can be stored on different physical storage devices. MySQL partition is based on certain columns of a table, which are calledPartition key。

MySQL's partitioning technology improves query efficiency and management flexibility by splitting large tables into multiple smaller physical partitions. Partitioning can reduce the amount of data in a single partition, thereby increasing the speed of data access.

1.2 Partition type

MySQL supports several common partitioning methods, and the applicable scenarios of each partitioning method are different:

  • RANGE partition: Partition according to the range of a certain field. For example, you can partition the data based on the date field, and the monthly data can be placed in a different partition.

    CREATE TABLE orders (
    order_id INT,
    order_date DATE
)
PARTITION BY RANGE (YEAR(order_date)) (
    PARTITION p0 VALUES LESS THAN (2022),
    PARTITION p1 VALUES LESS THAN (2023),
    PARTITION p2 VALUES LESS THAN (2024)
);

  • LIST partition: Partition according to the specific value list of a certain field. Applicable to discrete distributions of certain field values, such as partitioning based on regions, countries, etc.

    CREATE TABLE orders (
    order_id INT,
    region VARCHAR(20)
)
PARTITION BY LIST (region) (
    PARTITION p0 VALUES IN ('Asia', 'Europe'),
    PARTITION p1 VALUES IN ('America', 'Africa')
);

  • HASH partition: Partitioning according to the hash value of a certain field, which is suitable for scenes where the field values ​​are relatively uniform. Hash partitions can evenly distribute data in each partition.

    CREATE TABLE orders (
    order_id INT,
    customer_id INT
)
PARTITION BY HASH(customer_id)
PARTITIONS 4;

  • KEY Partition: Similar to HASH partition, but using MySQL's internal hash function for partitioning is suitable for scenarios where the values ​​of fields are evenly distributed.

    CREATE TABLE orders (
    order_id INT,
    customer_id INT
)
PARTITION BY KEY(customer_id)
PARTITIONS 4;

1.3 Advantages of Partition

  • Query performance improvement: Through partitioning, MySQL can only scan related partitions, not the entire table, thereby improving query performance. In particular, the optimization effect of range queries (such as date range queries) is significant.
  • Easy to manage: Partitioning makes data management more flexible. For example, some partitions can be archived, backed up, or deleted without affecting other partitions.
  • Even distribution of data: For hash partitions and key partitions, MySQL can evenly distribute data to different partitions, avoiding performance bottlenecks caused by concentrating data in a certain partition.

1.4 Disadvantages and limitations of partitions

  • Not applicable to all scenarios: Partitioning technology is suitable for situations where the data volume is large and the queries are concentrated in certain fields, but for tables that are frequently updated or inserted, partitioning may bring additional management overhead.
  • Complex partitioning strategies: The selection of partitioning strategies requires the query characteristics of the data, so it needs to be carefully considered during design.
  • Only certain operations are supported: MySQL's partition table has restrictions on certain operations (such as foreign key constraints), so you should reasonably choose whether to use partitions according to business needs.

2. MySQL library and table

2.1 What is a library and table?

ShardingIt is a technology that divides a logical database or table into multiple physical databases or tables. In the schema of sub-databases and tables, data is stored in multiple databases or tables according to a certain strategy (such as ID, time, etc.), thus solving the problem of performance bottlenecks of a single database.

2.2 Common strategies for dividing databases and tables

Horizontal Table: Spread the data in the table into multiple tables based on a certain field (such as ID). The amount of data stored in each table is small, which improves query and insertion efficiency.

For example, spread data into multiple tables according to the range of user ID:

CREATE TABLE orders_1 (
    order_id INT,
    customer_id INT,
    order_date DATE
);

CREATE TABLE orders_2 (
    order_id INT,
    customer_id INT,
    order_date DATE
);

Vertical table: Spread different fields in a table into multiple tables according to business needs, which is suitable for situations where the table structure is relatively complex.

For example, the user table contains personal information and account information, and the data of these two parts can be stored separately:

CREATE TABLE user_info (
    user_id INT,
    name VARCHAR(100),
    email VARCHAR(100)
);

CREATE TABLE user_account (
    user_id INT,
    account_balance DECIMAL
);

Distribution: Spread data into different database instances according to certain rules (such as user ID, region, etc.) to reduce the load on a single database.

CREATE DATABASE db1;
CREATE DATABASE db2;

2.3 Implementation of library and tables

  • Application layer library division: The application is responsible for processing data routing, querying and other operations, and writes data to different databases or tables according to business needs. This approach is highly flexible, but it increases the complexity of the application layer.
  • Middleware library division: Automatic database partition and table division logic is implemented through database middleware (such as Sharding-JDBC, Mycat, etc.). Applications do not need to care about specific database partition and table division policies. The middleware will route and access data according to preset rules.

2.4 Advantages of sub-store and table

  • Performance improvement: By dividing databases and tables, splitting large tables into multiple small tables or multiple databases, thereby improving the performance of query and writing and reducing the load of a single database.
  • Strong scalability: According to the increase in the amount of data, it can be horizontally expanded at any time, and more databases or tables are added to store data, solving the bottlenecks in database capacity and performance.
  • High availability: By dispersing data in multiple databases, the risk of a single point of failure is reduced, and the high availability of the system is improved.

2.5 Disadvantages and challenges of sub-repository

  • Complex transaction management: After dividing the database and table, the transaction processing across libraries and tables becomes complicated, and distributed transaction management mechanisms may be required (such as 2PC, TCC, etc.).
  • Increased complexity of data query: When querying data across multiple tables or databases, you may need to do a concatenated table operation, which will increase the complexity and performance burden of the query.
  • Complex routing strategies: Designing a reasonable library and table division strategy requires careful planning based on business needs. Incorrect library and table division strategy may lead to uneven data distribution, hot issues, etc.

3. Summary

In MySQL, two common technical solutions for processing large table data arePartitionandLibrary and table. Through partitioning, the data of large tables can be split into multiple partitions according to some rules, thereby improving query performance and management flexibility. The database and table partitioning improves the performance and scalability of the system by scattering data in multiple databases or tables.

When choosing to use partitions or databases and tables, comprehensive considerations need to be made based on actual business needs and data characteristics. For example, partitioning is suitable for certain fields with clear scope query requirements, while library partitioning is suitable for high-load systems that need to handle a large number of concurrent requests. By rationally designing partition or database partitioning strategies, we can effectively deal with the challenges brought by MySQL large table data and improve the performance and stability of the database.

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