Home >Database >Mysql Tutorial >Single Table Index vs. Multiple Small Tables: Is Partitioning the Optimal Solution for Large Datasets?
Database Optimization: Evaluate Single Table Indexing vs. Multiple Small Tables without Indexes
In the realm of database optimization, the debate between utilizing a single table with an index or multiple smaller tables without indexes often arises. To shed light on this topic, let's delve into a specific scenario.
Scenario:
Consider a table named 'statistics' with 20,000 users and 30 million rows, featuring columns for user_id, actions, timestamps, etc. Primary query operations involve inserting data based on user_id and retrieving data for specific user_ids.
Question:
Would it be more efficient to leverage an index on a single 'statistics' table or opt for a separate 'statistics' table for each user, eliminating the need for indexes?
Answer:
Using 20,000 tables is not recommended, as it leads to maintenance issues and performance bottlenecks. Instead, MySQL Partitioning provides a solution to optimize performance without sacrificing data integrity.
MySQL Partitioning:
<code class="sql">CREATE TABLE statistics ( id INT AUTO_INCREMENT NOT NULL, user_id INT NOT NULL, PRIMARY KEY (id, user_id) ) PARTITION BY HASH(user_id) PARTITIONS 101;</code>
Benefits of Partitioning:
Considerations:
The above is the detailed content of Single Table Index vs. Multiple Small Tables: Is Partitioning the Optimal Solution for Large Datasets?. For more information, please follow other related articles on the PHP Chinese website!