Analyzing and reducing disk space usage in MySQL
Jul 08, 2025 am 01:45 AM
To reduce MySQL disk usage, first find the table that takes up the most space by querying information_schema; secondly, clean up unnecessary historical data and delete or archive it in batches; then optimize the table structure and indexes, such as deleting redundant indexes, adjusting field types, splitting large field tables, and performing OPTIMIZE TABLE to reclaim free space; finally, consider enabling InnoDB table compression or using partitioned tables to further save storage space.
MySQL often swells quietly, especially when data volumes grow rapidly or without regular maintenance. If left uncontrolled, it may result in disk full load, performance degradation and even service interruption. To reduce MySQL disk usage, deleting data is not enough, and you also need to start from multiple aspects.
See which tables take up the most space
The first step is to figure out who is "eating" the disk. You can find out the tables that take up the largest space by querying information_schema :
SELECT table_schema AS `Database`, table_name AS `Table`, round((data_length index_length) / 1024 / 1024, 2) AS `Size (MB)` FROM information_schema.tables ORDER BY (data_length index_length) DESC LIMIT 10;
This statement can help you quickly locate the big table. Usually, data tables of log and history are most likely to become "big investors". After finding it, you can focus on analyzing whether these tables really need to retain so much data.
Clean up unnecessary data
For those historical data that are not really needed, the most direct way is to delete (DELETE) or archive (Archive). But there are a few points to note:
Don't delete too much at once : For example, if you plan to delete the log from a year ago, if you directly execute
DELETE FROM logs WHERE created_at < '2023-01-01', the table locking time may be too long, affecting the business.It is recommended to delete in batches : you can use a script to loop the delete, delete several thousand pieces each time, and add a sleep in the middle, for example:
DELETE FROM logs WHERE created_at < '2023-01-01' LIMIT 10000; -- Wait for a few seconds
Consider archives instead of deleting them directly : If you are not sure whether they will be used in the future, you can export and save the data first, and then delete it from the main library.
In addition, some tables may have a large amount of "soft delete" marking data (such as status=deleted), and you can also consider cleaning this part.
Optimize table structure and index
Sometimes, space waste is not because of the large amount of data, but because of the unreasonable structural design. for example:
- Used too large field types, such as
TEXTorVARCHAR(1000)and only use a few dozen characters; - Store duplicate data without standardization;
- Too many indexes have been built, especially for fields with frequent updates, which not only occupy space but also affects the writing speed.
The following points can be considered:
- Drop unnecessary indexes;
- Change certain fields to more appropriate data types;
- For large fields that are frequently queried but rarely modified, they can be split into separate tables and join on demand.
Another operation that is often ignored is: OPTIMIZE TABLE . When you delete a large amount of data, the space of the InnoDB table will not be automatically released to the system. You need to manually run this command to rebuild the table and recycle the empty space.
Enable compression or use partition tables (advanced)
If your data itself is difficult to reduce, consider enabling InnoDB table compression, which is a good choice for storage-intensive tables. The setup method is relatively simple, you only need to add:
ROW_FORMAT=COMPRESSED KEY_BLOCK_SIZE=8
However, be careful that compression will increase the CPU burden and decompress it when reading.
Another way is to use partition tables to separate historical data from current data. For example, partitioning by time, old data is placed in a separate partition, which is easy to manage and facilitates later archiving or migration.
Basically that's it. Reasonably clean up data, optimize structure, and appropriate compression can effectively alleviate MySQL's disk pressure. What is not complicated but easy to ignore is: regular inspection and maintenance.
The above is the detailed content of Analyzing and reducing disk space usage in MySQL. For more information, please follow other related articles on the PHP Chinese website!
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