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KEY partitioning is very similar to HASH partitioning, but with one important difference:
MySQL chooses which column(s) to use for distributing data—usually the primary key or a unique key.
This means you don’t have to specify a column manually. MySQL internally applies its own hashing algorithm to the selected key columns and decides which partition each row belongs to.
This automatic handling makes KEY partitioning especially useful when:
You have tables with a primary key
You want even data distribution without thinking about ranges or categories
You prefer MySQL to decide the hashing logic instead of writing it yourself
Because it relies on indexed columns, KEY partitioning is often more consistent and stable than manually defined hash functions.
CREATE TABLE student_key ( student_id INT PRIMARY KEY, student_name VARCHAR(50), department VARCHAR(50) ) PARTITION BY KEY() PARTITIONS 4;
How this works:
Since no column is specified, MySQL automatically uses student_id (the primary key).
MySQL applies its internal hashing algorithm to the key.
The output decides which of the 4 partitions the row goes into.
If you later add a new unique key, MySQL can use that too.
No need to define ranges or lists—everything is automatic.
This approach makes partition management simple while maintaining high performance for large datasets.
KEY partitioning works best when the table is frequently accessed using primary or unique keys. Some ideal scenarios include:
1. Primary-Key-Based Workloads
When most queries involve lookups like:
SELECT * FROM student_key WHERE student_id = 101;
Partitioning ensures quick access because only one partition needs to be checked.
2. Auto-Incrementing IDs
Tables with sequential IDs (e.g., order_id, user_id) can benefit from balanced distribution without manual logic.
3. Simplified Load Balancing
Because MySQL handles the hashing automatically:
Data is evenly spread across all partitions
Storage and CPU usage are more balanced
Performance does not degrade as the table grows
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