Batch Inserts via saveAll(Iterable<S> entities) in MySQL
Description: Batch inserts via SimpleJpaRepository#saveAll(Iterable<S> entities) method in MySQL
Key points:
- in application.properties set spring.jpa.properties.hibernate.jdbc.batch_size
- in application.properties set spring.jpa.properties.hibernate.generate_statistics (just to check that batching is working)
- in application.properties set JDBC URL with rewriteBatchedStatements=true (optimization for MySQL)
- in application.properties set JDBC URL with cachePrepStmts=true (enable caching and is useful if you decide to set prepStmtCacheSize, prepStmtCacheSqlLimit, etc as well; without this setting the cache is disabled)
- in application.properties set JDBC URL with useServerPrepStmts=true (this way you switch to server-side prepared statements (may lead to signnificant performance boost))
- in case of using a parent-child relationship with cascade persist (e.g. one-to-many, many-to-many) then consider to set up spring.jpa.properties.hibernate.order_inserts=true to optimize the batching by ordering inserts
- in entity, use the assigned generator since MySQL IDENTITY will cause batching to be disabled
- in entity, add @Version property to avoid extra-SELECTs fired before batching (also prevent lost updates in multi-request transactions). Extra-SELECTs are the effect of using merge() instead of persist(); behind the scene, saveAll() uses save(), which in case of non-new entities (have IDs) will call merge(), which instruct Hibernate to fire a SELECT statement to make sure that there is no record in the database having the same identifier
- pay attention on the amount of inserts passed to saveAll() to not "overwhelm" the persistence context; normally the EntityManager should be flushed and cleared from time to time, but during the saveAll() execution you simply cannot do that, so if in saveAll() there is a list with a high amount of data, all that data will hit the persistence context (1st level cache) and will be in-memory until flush time. Using relatively small amount of data should be ok
Output example:
