How does LockModeType.OPTIMISTIC work in JPA and Hibernate
Explicit optimistic locking In my previous post, I introduced the basic concepts of Java Persistence locking. The implicit locking mechanism prevents lost updates and it’s suitable for entities that we can actively modify. While implicit optimistic locking is a widespread technique, few happen to understand the inner workings of explicit optimistic lock mode. Explicit optimistic locking may prevent data integrity anomalies when the locked entities are always modified by some external mechanism.
A beginner’s guide to Java Persistence locking
Implicit locking In concurrency theory, locking is used for protecting mutable shared data against hazardous data integrity anomalies. Because lock management is a very complex problem, most applications rely on their data provider implicit locking techniques. Delegating the whole locking responsibility to the database system can both simplify application development and prevent concurrency issues, such as deadlocking. Deadlocks can still occur, but the database can detect and take safety measures (arbitrarily releasing one of the two competing locks).
Book review – How Linux Works 2nd edition
The book The book’s author is Brian Ward, who has a Ph.D. in computer science and has written several books about Linux Kernel, Vim, and VMware. The book has 17 Chapters and covers many Linux aspects, from the Operating System architecture to Bash scripting and Package Managers.
A beginner’s guide to transaction isolation levels in enterprise Java
Introduction A relational database strong consistency model is based on ACID transaction properties. In this post we are going to unravel the reasons behind using different transaction isolation levels and various configuration patterns for both resource local and JTA transactions. Isolation and consistency In a relational database system, atomicity and durability are strict properties, while consistency and isolation are more or less configurable. We cannot even separate consistency from isolation as these two properties are always related. The lower the isolation level, the less consistent the system will get. From the least… Read More
JPA and Hibernate FetchType EAGER is a code smell
Introduction Hibernate fetching strategies can really make a difference between an application that barely crawls and a highly responsive one. In this post, I’ll explain why you should prefer query-based fetching instead of global fetch plans. Fetching 101 Hibernate defines four association retrieving strategies: Fetching Strategy Description Join The association is OUTER JOINED in the original SELECT statement Select An additional SELECT statement is used to retrieve the associated entity(entities) Subselect An additional SELECT statement is used to retrieve the whole associated collection. This mode is meant for to-many associations Batch An… Read More
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 address the OptimisticLockException in JPA and Hibernate
Introduction Application-level repeatable reads are suitable for preventing lost updates in web conversations. Enabling entity-level optimistic locking is fairly easy. You just have to mark one logical-clock property (usually an integer counter) with the JPA @Version annotation and Hibernate takes care of the rest. The catch Optimistic locking discards all incoming changes that are relative to an older entity version. But everything has a cost and optimistic locking makes no difference. The optimistic concurrency control mechanism takes an all-or-nothing approach even for non-overlapping changes. If two concurrent transactions are changing distinct entity… Read More
Hibernate collections optimistic locking
Introduction Hibernate provides an optimistic locking mechanism to prevent lost updates even for long-conversations. In conjunction with an entity storage, spanning over multiple user requests (extended persistence context or detached entities) Hibernate can guarantee application-level repeatable-reads. The dirty checking mechanism detects entity state changes and increments the entity version. While basic property changes are always taken into consideration, Hibernate collections are more subtle in this regard. Owned vs Inverse collections In relational databases, two records are associated with a foreign key reference. In this relationship, the referenced record is the parent while… Read More
How does Hibernate guarantee application-level repeatable reads
Introduction In my previous post I described how application-level transactions offer a suitable concurrency control mechanism for long conversations. All entities are loaded within the context of a Hibernate Session, acting as a transactional write-behind cache. A Hibernate persistence context can hold one and only one reference to a given entity. The first level cache guarantees session-level repeatable reads. If the conversation spans over multiple requests we can have application-level repeatable reads. Long conversations are inherently stateful so we can opt for detached objects or long persistence contexts. But application-level repeatable reads… Read More
