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HomeJavajavaTutorialHow does Hibernate handle optimistic locking and pessimistic locking?

How does Hibernate handle optimistic locking and pessimistic locking?

Apr 17, 2024 pm 10:18 PM
pessimistic lockconcurrent accessdata lostoptimistic locking

In a multi-user environment, Hibernate provides optimistic locking and pessimistic locking to ensure data integrity. Optimistic locking assumes that when a transaction modifies data, other transactions will not conflict. It is implemented through version field checking and has high performance and scalability, but may cause data loss. Pessimistic locking assumes conflicts between transactions and is implemented through database locks, which can prevent concurrent modifications, but has lower performance and scalability. The specific choice depends on the frequency of concurrent modifications and the importance of data integrity.

Hibernate 如何处理乐观锁和悲观锁?

Optimistic locking and pessimistic locking in Hibernate

In a multi-user environment, data integrity is crucial. Hibernate provides two locking mechanisms to ensure the integrity of concurrent access: optimistic locking and pessimistic locking.

Optimistic lock

Optimistic lock is based on the assumption that when a transaction modifies data, other transactions will not make conflicting modifications at the same time. If this assumption holds, then transactions can commit quickly without causing any lock contention.

Implementation method: Hibernate uses the version field to implement optimistic locking. Every time an entity is modified, the version field is incremented. When a transaction attempts to commit, Hibernate checks whether the current version field matches the version field in the database. If the version field does not match, the transaction will be rolled back and a StaleObjectStateException exception will be thrown.

Advantages:

  • High performance: no additional lock overhead, so it is fast.
  • Scalability: Since there are no locks, it scales well to high-concurrency systems.

Disadvantages:

  • Possible data loss: If another transaction modifies data before the current transaction commits, the current transaction will cause the data to be lost. lost.
  • Can only detect concurrent modifications, not prevent them.

Pessimistic lock

Pessimistic lock is based on the assumption that when a transaction modifies data, other transactions may make conflicting modifications to the same data at the same time. . Therefore, pessimistic locking acquires the lock immediately to prevent concurrent access.

Implementation method: Hibernate mainly uses database-level locks to implement pessimistic locks. When a transaction begins, it acquires a read or write lock to prevent concurrent modifications to the data by other transactions.

Advantages:

  • Reliability: Concurrent modifications can be absolutely prevented, thereby ensuring data integrity.

Disadvantages:

  • Low performance: The existence of locks will introduce overhead, thus reducing performance.
  • Scalability: In highly concurrent systems, lock contention may result, limiting scalability.

Practical case:

Consider an e-commerce website where multiple users browse the same product details page at the same time. To prevent concurrent purchases from causing inventory errors, optimistic locking can be used:

@Entity
public class Product {

    @Id
    @GeneratedValue(strategy = GenerationType.IDENTITY)
    private Long id;

    private String name;

    private int quantity;

    @Version
    private long version;
}

When a user attempts to purchase the item, Hibernate will increment the version field. If another user also attempts to purchase at this time, when the first user commits the transaction, Hibernate will detect a mismatch in the version field and roll back the first user's purchase.

Other considerations:

  • For data that is frequently modified concurrently, pessimistic locking is more appropriate. For data that is not frequently modified concurrently, optimistic locking performs better.
  • Hibernate also supports using LockModeEnum to explicitly specify the lock type.
  • The type and behavior of database locks may vary, which may affect the performance and behavior of pessimistic locks.

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