Introduction In this article, we are going to see how we can adjust a bulk update statement so that it takes optimistic locking into consideration. While Hibernate has been supporting versioned HQL queries for a very long time, it’s actually very easy to achieve this goal even with standard JPQL or JPA Criteria API.
Introduction In this article, we are going to see what is the best way to map the entity version property with JPA and Hibernate. Most often, we overlook the basic entity type mappings, focusing more on associations or querying options. However, basic types can also have a significant impact on application performance, especially if the type in question is used in many entity mappings.
Introduction In this article, we are going to see how optimistic locking version property works when using JPA and Hibernate. Most often, we overlook basic concepts and focus only on more advanced topics such as associations or queries, without realizing that basic mappings can also have a significant impact when it comes to persistence effectiveness and efficiency.
Introduction In this article, I’m going to show you how the JPA @Version entity property works when using Hibernate. The most significant benefit of adding a version property to a JPA entity is that we can prevent the lost update anomaly, therefore ensuring that data integrity is not compromised.
How to increment the parent entity version whenever a child entity gets modified with JPA and Hibernate
Introduction StackOverflow and the Hibernate forum are gold mines. Yesterday, I bumped on the following question on our forum: Usually, the rationale behind clustering objects together is to form a transactional boundary inside which business invariants are protected. I’ve noticed that with the OPTIMISTIC locking mode changes to a child entity will not cause a version increment on the root. This behavior makes it quite useless to cluster objects together in the first place. Is there a way to configure Hibernate so that any changes to an object cluster will cause the… Read More
Introduction In my previous post, I introduced the OPTIMISTIC_FORCE_INCREMENT Lock Mode and we applied it for propagating a child entity version change to a locked parent entity. In this post, I am going to reveal the PESSIMISTIC_FORCE_INCREMENT Lock Mode and compare it with its optimistic counterpart.
Introduction In my previous post, I explained how OPTIMISTIC Lock Mode works and how it can help us synchronize external entity state changes. In this post, we are going to unravel the OPTIMISTIC_FORCE_INCREMENT Lock Mode usage patterns. With LockModeType.OPTIMISTIC, the locked entity version is checked towards the end of the current running transaction, to make sure we don’t use a stale entity state. Because of the application-level validation nature, this strategy is susceptible to race-conditions, therefore requiring an additional pessimistic lock . The LockModeType.OPTIMISTIC_FORCE_INCREMENT not only it checks the expected locked entity… Read More
Recap In my previous post, I explained the benefits of using explicit optimistic locking. As we then discovered, there’s a very short time window in which a concurrent transaction can still commit a Product price change right before our current transaction gets committed. This issue can be depicted as follows: Alice fetches a Product She then decides to order it The Product optimistic lock is acquired The Order is inserted in the current transaction database session The Product version is checked by the Hibernate explicit optimistic locking routine The price engine manages… Read More
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.
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).