Partitioned tables in MySQL: detailed introduction and optimization techniques

As the amount of data continues to grow, it becomes increasingly difficult to store and query data in MySQL. Partition table is a function of MySQL database, which can solve the problem of large data volume and slow query speed. This article will introduce the partition table in MySQL in detail and provide several optimization tips.

1. What is MySQL partition table?

MySQL partition table is a function introduced after MySQL 5.1 version. It allows a large table to be divided into several small sub-tables. The data of each sub-table can be separated, stored and queried according to specified conditions. For example, a user's transaction data can be separated into different subtables by year or month. Each sub-table can be maintained independently, greatly improving the efficiency of query and maintenance.

2. Why do you need to use MySQL partition table?

1. Improve query efficiency

Normally, low query efficiency occurs when large tables store data. When the amount of data is large, the query operation will take a long time and occupy a large amount of system resources. Using partitioned tables allows query operations to be performed only on specific subtables, thereby greatly improving query efficiency.

2. Reduce storage costs

Using partition tables can separate data into different sub-tables for storage, reducing the storage space of each data table. This reduces storage costs.

3. Convenient maintenance

Each sub-table can be maintained independently without the need to operate the entire table, which makes maintenance more convenient.

3. How to create a MySQL partition table?

The process of creating a partitioned table is similar to creating a normal table. The difference lies in the need to specify the partitioning method and fields. For example, we create a transaction record table partitioned by date. The code is as follows:

CREATE TABLE trade_records
(
id INT(11) NOT NULL AUTO_INCREMENT,
trade_time DATETIME NOT NULL,
trade_amount INT(11) NOT NULL,
PRIMARY KEY (id, trade_time)
)
PARTITION BY RANGE (YEAR(trade_time))
(
PARTITION p0 VALUES LESS THAN (2015),
PARTITION p1 VALUES LESS THAN (2016),
PARTITION p2 VALUES LESS THAN (2017),
PARTITION p3 VALUES LESS THAN (2018),
PARTITION p4 VALUES LESS THAN MAXVALUE
);

In this code, when we create the table, we use the PARTITION BY RANGE clause and specify the trade_time field as the benchmark. , partitioned according to year. And five subtables are used for partitioning, from 2015 to unlimited time. In addition, a joint primary key is specified in the code to ensure the uniqueness between the partition key field and the primary key.

In addition to partitioning by range, you can also partition by list or hash. Taking list mode as an example, we create a transaction record table partitioned by region. The code is as follows:

CREATE TABLE trade_records
(
    id INT(11) NOT NULL AUTO_INCREMENT,
    trade_time DATETIME NOT NULL,
    trade_amount INT(11) NOT NULL,
    location VARCHAR(50) NOT NULL,
    PRIMARY KEY (id, trade_time)
)
PARTITION BY LIST (location)
(
    PARTITION p_domestic VALUES IN ('Shanghai', 'Beijing'),
    PARTITION p_hongkong VALUES IN ('Hong Kong'),
    PARTITION p_others VALUES IN (DEFAULT)
);

In this code, we use the PARTITION BY LIST clause when creating the table, specifying The location field is used as the basis and is partitioned according to region. Three subtables are used for partitioning. Among them, the default sub-table p_others can receive regions other than named partitions.

4. Optimization skills of MySQL partition table

1. Reasonable number of partitions

When dividing partitions, it should be determined based on the actual situation. Generally recommended Control it to around 10-20. Too many subtables increase maintenance costs and require more time to perform queries.

2. Use the appropriate partition key

Choosing the appropriate partition key can improve query efficiency. If the selected partition key can divide the data into different sub-tables, then only the corresponding sub-tables need to be accessed during the query, which can greatly reduce the query time. However, if you choose a partition key that does not partition the data efficiently, query time will increase.

3. Avoid cross-partition queries

Cross-partition queries may involve multiple sub-tables, which will reduce efficiency. Therefore, when making queries, avoid cross-partition queries whenever possible.

4. Regularly maintain the partition table

Although the partition table can reduce storage costs and facilitate maintenance, due to the use of multiple sub-tables, the query time will also increase accordingly. Therefore, the table needs to be maintained before querying, such as deleting unnecessary data or optimizing the index to improve query efficiency.

5. Use the official tools provided by MySQL for optimization

The official MySQL provides many tools and tips that can be used to optimize the performance of partitioned tables. For example, use the officially provided EXPLAIN tool to analyze performance issues in query statements; use the pt-online-schema-change tool to modify the partition table to avoid the impact on the table during the modification process.

In short, partitioning tables is an important method for MySQL optimization. By reasonably dividing sub-tables, selecting appropriate partition keys and regularly maintaining tables, query efficiency can be greatly improved and storage costs can be reduced. However, using partition tables also has its disadvantages, and at the same time, you need to follow some principles and precautions to ensure its normal operation.

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