The World of MySQL & MariaDB

MySQL Partitioning Guide: Basics to Performance Boost

Table Management
目次

1. What is MySQL partitioning? Overview and benefits

Introduction

As the size of a database grows, performance optimization becomes crucial. Especially in environments handling large-scale data like MySQL, the partitioning feature is useful. Partitioning is a technique that improves query execution efficiency by dividing a table into multiple partitions. Here, we will take a detailed look at the basic concepts of MySQL partitions and their benefits.

2. Basics of MySQL Partitioning

MySQL provides horizontal partitioning, which splits data based on specific rules. For example by using a record’s “creation date” or “ID”, you can divide an entire table into multiple partitions, allowing you to efficiently retrieve only the data you need. This section introduces the basic partitioning settings supported by MySQL and their relationship with storage engines.

3. Types of Partitioning and How to Apply Them

RANGE Partitioning

RANGE partitioning splits data based on a specified range (e.g., a date range). For example, with YEAR(created_at) based RANGE partitioning, you can partition data by each specific year.

LIST Partitioning

LIST partitioning uses a list of specific values (e.g., data per category) to split data. This method is suitable when classifying data into predefined categories or ranges.

HASH Partitioning

HASH partitioning uses a hash function to distribute data. It is typically used to evenly split large volumes of data and is suitable when efficient data access is required.

KEY Partitioning

KEY partitioning automatically splits data using MySQL’s internal functions. It is widely used to ensure an even data distribution and remains effective even when multiple complex conditions are involved.

4. Partition Management and Maintenance

Adding, dropping, and redistributing partitions play a crucial role in performance management. By using ALTER TABLE, you can flexibly modify the partition layout. However, when you use the DROP PARTITION command, all data within the affected partition is also deleted, so caution is required. When dropping partitions or migrating data, you need to understand the risk of data loss.

5. Partition Pruning and Optimization

How Partition Pruning Works

Partition pruning is a technique that reduces access to unnecessary partitions and accesses only the specific partitions needed. By leveraging MySQL’s query optimization features, you can quickly extract only the data that matches the conditions. For example, when referencing data for a particular date, the optimization can search only the partition for the relevant year.

6. Using Partitions and Indexes Together

Synergistic Effects with Indexes

Combining partitions with indexes enables even more efficient data access. In particular, for databases with many conditional queries, properly pairing partitions and indexes can improve query performance. When adding indexes to each partition, it’s important to configure them while considering the impact on performance.

7. Partitioning Best Practices

Choosing the Right Partitioning Strategy

Partitioning is not suitable for every table and should be chosen based on data characteristics and usage goals. For example, if there is a subset of data that is accessed extremely frequently, it is recommended to split the data into specific ranges so you can focus on the high‑frequency data. Also, increasing the number of partitions impacts memory usage, so it’s important to design the configuration with memory constraints in mind.

8. Summary

In this article, we explained MySQL’s partitioning feature from basics to advanced usage. Partitions are an important feature for improving database performance and enabling efficient management. However, they are not applicable to every case, and a proper strategy is required.