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Achieve a high-speed InnoDB purge on Amazon RDS for MySQL and Amazon Aurora MySQL
- Purge is essential for a MySQL database to clean up delete-marked table records and undo logs that are no longer needed for multiversion concurrency control (MVCC) or rollback operations.
- The slow advancement of purge in the background compared to numerous data changes causes poor database performance.
- InnoDB uses undo logs as the key data structure to support MVCC and rollback operations and purge to clean them up.
- The most heavy-duty part of the purge operation is identifying delete-marked table records including those in clustered indexes, secondary indexes, and BLOB columns.
- The number of purge threads, the workload characteristics, and database resource utilization can significantly impact the performance of purge operation.
- Choosing the right instance class, partitioning and sharding strategies can improve the efficiency of the purge operation.
- Using the schema_unused_indexes view in SYS schema to identify and drop the unused secondary indexes is a recommended optimization.
- Monitoring and setting up alarms for the rollback segment history list length metric can warn of the need to optimize database capacity and workload characteristics.
- Purge operation can be an essential tool to optimize a MySQL database's performance.
- Optimizing purge operation needs careful consideration of workload optimization, database capacity planning, and configurations.
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