How to prevent OptimisticLockException with Hibernate versionless optimistic locking

Introduction In my previous post I demonstrated how you can scale optimistic locking through write-concerns splitting. Version-less optimistic locking is one lesser-known Hibernate feature. In this post, I’ll explain both the good and the bad parts of this approach. Version-less optimistic locking Optimistic locking is commonly associated with a logical or physical clocking sequence, for both performance and consistency reasons. The clocking sequence points to an absolute entity state version for all entity state transitions. To support legacy database schema optimistic locking, Hibernate added a version-less concurrency control mechanism. To enable this… Read More

How to prevent lost updates in long conversations

Introduction All database statements are executed within the context of a physical transaction, even when we don’t explicitly declare transaction boundaries (BEGIN/COMMIT/ROLLBACK). Data integrity is enforced by the ACID properties of database transactions. Logical vs Physical transactions A logical transaction is an application-level unit of work that may span over multiple physical (database) transactions. Holding the database connection open throughout several user requests, including user think time, is definitely an anti-pattern. A database server can accommodate a limited number of physical connections, and often those are reused by using connection pooling. Holding… Read More

A beginner’s guide to database locking and the lost update phenomena

Introduction A database is highly concurrent system. There’s always a chance of update conflicts, like when two concurring transactions try to update the same record. If there would be only one database transaction at any time then all operations would be executed sequentially. The challenge comes when multiple transactions try to update the same database rows as we still have to ensure consistent data state transitions. The SQL standard defines three consistency anomalies (phenomena): Dirty reads, prevented by Read Committed, Repeatable Read and Serializable isolation levels Non-repeatable reads, prevented by Repeatable Read… Read More

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