Should I Use Multiple Tables or a Single Table with Partitions for MySQL Performance?

Optimizing MySQL Performance: Multiple Tables vs. Index on Single Table with Partitions

Databases often face the dilemma of whether to create multiple smaller tables or maintain a single larger table with an index for performance enhancement. This article explores this topic and offers an alternative solution through MySQL partitioning.

Multiple Tables vs. Indexed Single Table

In the case of a table with user statistics, creating multiple tables (one per user) may seem advantageous due to:

• Smaller table size, leading to faster INSERT operations
• Elimination of the index, simplifying SELECT queries

However, numerous tables can lead to operational complexities, such as:

• Metadata management overhead for a large number of tables
• Potential performance bottlenecks if the lookup for the appropriate user table becomes too computationally expensive

MySQL Partitioning

As an alternative, MySQL partitioning offers a flexible approach that combines the benefits of both multiple tables and an indexed single table. It allows you to divide a large table into smaller physical partitions based on a partitioning key (user_id in this case).

Using HASH partitioning, the rows are distributed evenly across multiple partitions, resulting in:

• Smaller partition sizes, reducing the impact of INSERT and SELECT operations
• Maintenance of a single logical table, simplifying data management

Partitioning Example

A query to retrieve user statistics would then target only the specific partition containing the user_id:

EXPLAIN PARTITIONS SELECT * FROM statistics WHERE user_id = 1\G
*************************** 1. row ***************************
           id: 1
  select_type: SIMPLE
        table: statistics
   partitions: p1    <--- this shows it touches only one partition 
         type: index
possible_keys: NULL
          key: PRIMARY
      key_len: 8
          ref: NULL
         rows: 2
        Extra: Using where; Using index

Determining Partition Count

For HASH partitioning, it is recommended to use a prime number of partitions. The optimal number depends on the total table size and the desired average partition size.

Partitioning Automation

Partition adjustments can be made using the ALTER TABLE command. However, it is not necessary to increase the partition count over time if HASH partitioning is used. Larger data volumes typically warrant a different architecture, such as sharding over multiple servers.

Conclusion

MySQL partitioning provides a robust solution to manage large tables without the drawbacks of numerous smaller tables. It effectively partitions the data based on a defined key, improving performance and simplifying data management. By understanding the benefits and limitations of both multiple tables and partitioning, you can optimize your MySQL database for maximum efficiency.

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