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Chapter 2. Transactions and concurrency control

2.1. Defining Transaction
2.2. Physical Transactions
2.2.1. Physical Transactions - JDBC
2.2.2. Physical Transactions - JTA
2.2.3. Physical Transactions - CMT
2.2.4. Physical Transactions - Custom
2.2.5. Physical Transactions - Legacy
2.3. Hibernate Transaction Usage
2.4. Transactional patterns (and anti-patterns)
2.4.1. Session-per-operation anti-pattern
2.4.2. Session-per-request pattern
2.4.3. Conversations
2.4.4. Session-per-application
2.5. Object identity
2.6. Common issues

It is important to understand that the term transaction has many different yet related meanings in regards to persistence and Object/Relational Mapping. In most use-cases these definitions align, but that is not always the case.

Hibernate uses the JDBC API for persistence. In the world of Java there are 2 well defined mechanism for dealing with transactions in JDBC: JDBC itself and JTA. Hibernate supports both mechanisms for integrating with transactions and allowing applications to manage physical transactions.

The first concept in understanding Hibernate transaction support is the org.hibernate.engine.transaction.spi.TransactionFactory interface which serves 2 main functions:

org.hibernate.engine.transaction.spi.TransactionFactory is a standard Hibernate service. See Section 7.5.16, “org.hibernate.engine.transaction.spi.TransactionFactory for details.

Hibernate uses JDBC connections and JTA resources directly, without adding any additional locking behavior. It is important for you to become familiar with the JDBC, ANSI SQL, and transaction isolation specifics of your database management system.

Hibernate does not lock objects in memory. The behavior defined by the isolation level of your database transactions does not change when you use Hibernate. The Hibernate org.hibernate.Session acts as a transaction-scoped cache providing repeatable reads for lookup by identifier and queries that result in loading entities.

Important

To reduce lock contention in the database, the physical database transaction needs to be as short as possible. Long database transactions prevent your application from scaling to a highly-concurrent load. Do not hold a database transaction open during end-user-level work, but open it after the end-user-level work is finished. This is concept is referred to as transactional write-behind.

This is the most common transaction pattern. The term request here relates to the concept of a system that reacts to a series of requests from a client/user. Web applications are a prime example of this type of system, though certainly not the only one. At the beginning of handling such a request, the application opens a Hibernate Session, starts a transaction, performs all data related work, ends the transaction and closes the Session. The crux of the pattern is the one-to-one relationship between the transaction and the Session.

Within this pattern there is a common technique of defining a current session to simplify the need of passing this Session around to all the application components that may need access to it. Hibernate provides support for this technique through the getCurrentSession method of the SessionFactory. The concept of a "current" session has to have a scope that defines the bounds in which the notion of "current" is valid. This is purpose of the org.hibernate.context.spi.CurrentSessionContext contract. There are 2 reliable defining scopes:

The session-per-request pattern is not the only valid way of designing units of work. Many business processes require a whole series of interactions with the user that are interleaved with database accesses. In web and enterprise applications, it is not acceptable for a database transaction to span a user interaction. Consider the following example:

Even though we have multiple databases access here, from the point of view of the user, this series of steps represents a single unit of work. There are many ways to implement this in your application.

A first naive implementation might keep the Session and database transaction open while the user is editing, using database-level locks to prevent other users from modifying the same data and to guarantee isolation and atomicity. This is an anti-pattern, because lock contention is a bottleneck which will prevent scalability in the future.

Several database transactions are used to implement the conversation. In this case, maintaining isolation of business processes becomes the partial responsibility of the application tier. A single conversation usually spans several database transactions. These multiple database accesses can only be atomic as a whole if only one of these database transactions (typically the last one) stores the updated data. All others only read data. A common way to receive this data is through a wizard-style dialog spanning several request/response cycles. Hibernate includes some features which make this easy to implement.

Automatic Versioning

Hibernate can perform automatic optimistic concurrency control for you. It can automatically detect if a concurrent modification occurred during user think time. Check for this at the end of the conversation.

Detached Objects

If you decide to use the session-per-request pattern, all loaded instances will be in the detached state during user think time. Hibernate allows you to reattach the objects and persist the modifications. The pattern is called session-per-request-with-detached-objects. Automatic versioning is used to isolate concurrent modifications.

Extended Session

The Hibernate Session can be disconnected from the underlying JDBC connection after the database transaction has been committed and reconnected when a new client request occurs. This pattern is known as session-per-conversation and makes even reattachment unnecessary. Automatic versioning is used to isolate concurrent modifications and the Session will not be allowed to flush automatically, only explicitly.

Session-per-request-with-detached-objects and session-per-conversation each have advantages and disadvantages.

An application can concurrently access the same persistent state (database row) in two different Sessions. However, an instance of a persistent class is never shared between two Session instances. Two different notions of identity exist and come into play here: Database identity and JVM identity.



For objects attached to a particular Session, the two notions are equivalent, and JVM identity for database identity is guaranteed by Hibernate. The application might concurrently access a business object with the same identity in two different sessions, the two instances are actually different, in terms of JVM identity. Conflicts are resolved using an optimistic approach and automatic versioning at flush/commit time.

This approach places responsibility for concurrency on Hibernate and the database. It also provides the best scalability, since expensive locking is not needed to guarantee identity in single-threaded units of work. The application does not need to synchronize on any business object, as long as it maintains a single thread per anti-patterns. While not recommended, within a Session the application could safely use the == operator to compare objects.

However, an application that uses the == operator outside of a Session may introduce problems.. If you put two detached instances into the same Set, they might use the same database identity, which means they represent the same row in the database. They would not be guaranteed to have the same JVM identity if they are in a detached state. Override the equals and hashCode methods in persistent classes, so that they have their own notion of object equality. Never use the database identifier to implement equality. Instead, use a business key that is a combination of unique, typically immutable, attributes. The database identifier changes if a transient object is made persistent. If the transient instance, together with detached instances, is held in a Set, changing the hash-code breaks the contract of the Set. Attributes for business keys can be less stable than database primary keys. You only need to guarantee stability as long as the objects are in the same Set.This is not a Hibernate issue, but relates to Java's implementation of object identity and equality.

Both the session-per-user-session and session-per-application anti-patterns are susceptible to the following issues. Some of the issues might also arise within the recommended patterns, so ensure that you understand the implications before making a design decision: