--- title: Primary Key Design description: Primary key patterns tags: mysql, primary-keys, auto-increment, uuid, innodb --- # Primary Keys InnoDB stores rows in primary key order (clustered index). This means: - **Sequential keys = optimal inserts**: new rows append, minimizing page splits and fragmentation. - **Random keys = fragmentation**: random inserts cause page splits to maintain PK order, wasting space and slowing inserts. - **Secondary index lookups**: secondary indexes store the PK value and use it to fetch the full row from the clustered index. ## INT vs BIGINT for Primary Keys - **INT UNSIGNED**: 4 bytes, max ~4.3B rows. - **BIGINT UNSIGNED**: 8 bytes, max ~18.4 quintillion rows. Guideline: default to **BIGINT UNSIGNED** unless you're certain the table will never approach the INT limit. The extra 4 bytes is usually cheaper than the risk of exhausting INT. ## Avoid Random UUID as Clustered PK - UUID PK stored as `BINARY(16)`: 16 bytes (vs 8 for BIGINT). Random inserts cause page splits, and every secondary index entry carries the PK. - UUID stored as `CHAR(36)`/`VARCHAR(36)`: 36 bytes (+ overhead) and is generally worse for storage and index size. - If external identifiers are required, store UUID as `BINARY(16)` in a secondary unique column: ```sql CREATE TABLE users ( id BIGINT UNSIGNED NOT NULL AUTO_INCREMENT PRIMARY KEY, public_id BINARY(16) NOT NULL, UNIQUE KEY idx_public_id (public_id) ); -- UUID_TO_BIN(uuid, 1) reorders UUIDv1 bytes to be roughly time-sorted (reduces fragmentation) -- MySQL's UUID() returns UUIDv4 (random). For time-ordered IDs, use app-generated UUIDv7/ULID/Snowflake. INSERT INTO users (public_id) VALUES (UUID_TO_BIN(?, 1)); -- app provides UUID string ``` If UUIDs are required, prefer time-ordered variants such as UUIDv7 (app-generated) to reduce index fragmentation. ## Secondary Indexes Include the Primary Key InnoDB secondary indexes store the primary key value with each index entry. Implications: - **Larger secondary indexes**: a secondary index entry includes (indexed columns + PK bytes). - **Covering reads**: `SELECT id FROM users WHERE email = ?` can often be satisfied from `INDEX(email)` because `id` (PK) is already present in the index entry. - **UUID penalty**: a `BINARY(16)` PK makes every secondary index entry 8 bytes larger than a BIGINT PK. ## Auto-Increment Considerations - **Hot spot**: inserts target the end of the clustered index (usually fine; can bottleneck at extreme insert rates). - **Gaps are normal**: rollbacks or failed inserts can leave gaps. - **Locking**: auto-increment allocation can introduce contention under very high concurrency. ## Alternative Ordered IDs (Snowflake / ULID / UUIDv7) If you need globally unique IDs generated outside the database: - **Snowflake-style**: 64-bit integers (fits in BIGINT), time-ordered, compact. - **ULID / UUIDv7**: 128-bit (store as `BINARY(16)`), time-ordered, better insert locality than random UUIDv4. Recommendation: prefer `BIGINT AUTO_INCREMENT` unless you need distributed ID generation or externally meaningful identifiers. ## Replication Considerations - Random-key insert patterns (UUIDv4) can amplify page splits and I/O on replicas too, increasing lag. - Time-ordered IDs reduce fragmentation and tend to replicate more smoothly under heavy insert workloads. ## Composite Primary Keys Use for join/many-to-many tables. Most-queried column first: ```sql CREATE TABLE user_roles ( user_id BIGINT UNSIGNED NOT NULL, role_id BIGINT UNSIGNED NOT NULL, PRIMARY KEY (user_id, role_id) ); ```