MySQL table partitioning improves query performance and management efficiency by splitting big data into different physical storages. 1. Partition types include RANGE, LIST, HASH, and KEY, where RANGE is divided by value range and is suitable for time-class data; 2. To create a partition table, you need to specify a partition key (such as partitioning by year), and reasonably set the partition boundary; 3. You must use the partition key directly during query and avoid function wrapping to ensure that trigger partition cropping improves performance; 4. The partition key must be part of the primary key or unique index, otherwise the partition table cannot be created; 5. The partition structure needs to be maintained regularly, such as adding future years partitions to avoid data being concentrated in the bottom-up partition.
MySQL's Table Partitioning is an effective way to improve query performance and manage big data. If your data volume has reached millions or even tens of millions of records in a single table, the partition can help you "split" the data into different physical storage areas according to the rules, while maintaining a unified view of the logical table to the outside.

Here is a practical example to illustrate how table partitioning is used in MySQL, as well as its benefits and considerations.
What is table partitioning? Why use it?
Simply put, table partitioning is to divide a large table into multiple small pieces , each small piece is an independent physical subtable, but it is still a complete logical table for the user.

The benefits of using partitions include:
- Query performance improvement: especially for queries with time ranges or partition keys
- Faster data archiving or deletion: For example, clearing data for a certain month only requires deleting the corresponding partition
- Improve availability: If a partition has problems, it will not affect other partitions
Common partition types include RANGE, LIST, HASH, KEY, etc. We will demonstrate it with the most commonly used RANGE partition as an example.

How to create a RANGE partition table?
Suppose you have an order table orders
containing the order creation time field created_at
, and you want to partition by year.
CREATE TABLE orders ( id INT NOT NULL, order_no VARCHAR(50) NOT NULL, created_at DATE NOT NULL ) PARTITION BY RANGE (YEAR(created_at)) ( PARTITION p2021 VALUES LESS THAN (2022), PARTITION p2022 VALUES LESS THAN (2023), PARTITION p2023 VALUES LESS THAN (2024), PARTITION pmax VALUES LESS THAN MAXVALUE );
The above section of SQL creates a RANGE partition table divided by year:
- Each partition stores data for a specific year
-
pmax
is a bottom-up partition used to store all data larger than 2024
The advantage of this is that when you query the order for 2022, MySQL will only scan the p2022
partition, greatly reducing I/O and query time.
What points should be paid attention to when using partitions?
Although partitioning can bring performance improvements, it is not omnipotent. There are several key points to pay attention to:
? The partition key must be the primary key of the table or part of the unique index
If your table has primary keys or unique constraints, the fields used for partitioning must be included in these constraints. For example, if the primary key is (id, created_at)
, you can use created_at
as the partition key; but if the primary key is just id
, you cannot use created_at
to partition directly.
?? Not all queries can be partitioned and cropped (Partition Pruning)
MySQL can only scan relevant partitions if your query criteria contain partition keys and the format is appropriate. Otherwise, all areas will still be scanned, which is equivalent to no partition.
To give a counterexample:
SELECT * FROM orders WHERE DATE_FORMAT(created_at, '%Y') = '2022';
Although this query uses the created_at
field, it cannot trigger partition cropping due to function wrapping, and the performance will not be improved.
The correct way to write it should be:
SELECT * FROM orders WHERE created_at >= '2022-01-01' AND created_at < '2023-01-01';
? Regularly maintain the partition structure
Over time, the original partition may not be enough. For example, in the above example, when entering 2025, all new data will be placed in the pmax
partition. At this time, you need to manually add new partitions and adjust the old partition structure.
summary
Table partitioning is a very practical technology, especially suitable for processing large tables of time-class data. The following points should be paid attention to when designing partitioning strategies:
- The partition key should be reasonable and try to match the query conditions.
- Pay attention to the limitations of primary keys and unique indexes
- Avoid function operations on partition keys when writing query statements
- Regularly check and maintain partition structures
Basically that's it. Partitioning is not a once-for-all solution, but it does significantly improve performance in the right scenario.
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