Chapter 12. Transactions and Concurrency

First, let's define a unit of work. A unit of work is a design pattern described by Martin Fowler as “ [maintaining] a list of objects affected by a business transaction and coordinates the writing out of changes and the resolution of concurrency problems. ”[PoEAA] In other words, its a series of operations we wish to carry out against the database together. Basically, it is a transaction, though fulfilling a unit of work will often span multiple physical database transactions (see Section 12.1.2, “Long conversations”). So really we are talking about a more abstract notion of a transaction. The term "business transaction" is also sometimes used in lieu of unit of work.

Do not use the session-per-operation antipattern: do not open and close a Session for every simple database call in a single thread. The same is true for database transactions. Database calls in an application are made using a planned sequence; they are grouped into atomic units of work. This also means that auto-commit after every single SQL statement is useless in an application as this mode is intended for ad-hoc SQL console work. Hibernate disables, or expects the application server to disable, auto-commit mode immediately. Database transactions are never optional. All communication with a database has to occur inside a transaction. Auto-commit behavior for reading data should be avoided, as many small transactions are unlikely to perform better than one clearly defined unit of work. The latter is also more maintainable and extensible.

The most common pattern in a multi-user client/server application is session-per-request. In this model, a request from the client is sent to the server, where the Hibernate persistence layer runs. A new Hibernate Session is opened, and all database operations are executed in this unit of work. On completion of the work, and once the response for the client has been prepared, the session is flushed and closed. Use a single database transaction to serve the clients request, starting and committing it when you open and close the Session. The relationship between the two is one-to-one and this model is a perfect fit for many applications.

The challenge lies in the implementation. Hibernate provides built-in management of the "current session" to simplify this pattern. Start a transaction when a server request has to be processed, and end the transaction before the response is sent to the client. Common solutions are ServletFilter, AOP interceptor with a pointcut on the service methods, or a proxy/interception container. An EJB container is a standardized way to implement cross-cutting aspects such as transaction demarcation on EJB session beans, declaratively with CMT. If you use programmatic transaction demarcation, for ease of use and code portability use the Hibernate Transaction API shown later in this chapter.

Your application code can access a "current session" to process the request by calling sessionFactory.getCurrentSession(). You will always get a Session scoped to the current database transaction. This has to be configured for either resource-local or JTA environments, see Section 3.5, “Contextual sessions”.

You can extend the scope of a Session and database transaction until the "view has been rendered". This is especially useful in servlet applications that utilize a separate rendering phase after the request has been processed. Extending the database transaction until view rendering, is achieved by implementing your own interceptor. However, this will be difficult if you rely on EJBs with container-managed transactions. A transaction will be completed when an EJB method returns, before rendering of any view can start. See the Hibernate website and forum for tips and examples relating to this Open Session in View pattern.

The session-per-request pattern is not the only 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:

From the point of view of the user, we call this unit of work a long-running conversation or application transaction. There are many ways to implement this in your application.

A first naive implementation might keep the Session and database transaction open during user think time, with locks held in the database to prevent concurrent modification and to guarantee isolation and atomicity. This is an anti-pattern, since lock contention would not allow the application to scale with the number of concurrent users.

You have to use several database transactions 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. It will be atomic if only one of these database transactions (the last one) stores the updated data. All others simply read data (for example, in a wizard-style dialog spanning several request/response cycles). This is easier to implement than it might sound, especially if you utilize some of Hibernate's features:

Both session-per-request-with-detached-objects and session-per-conversation have advantages and disadvantages. These disadvantages are discussed later in this chapter in the context of optimistic concurrency control.

An application can concurrently access the same persistent state in two different Sessions. However, an instance of a persistent class is never shared between two Session instances. It is for this reason that there are two different notions of identity:

For objects attached to a particular Session (i.e., in the scope of a Session), the two notions are equivalent and JVM identity for database identity is guaranteed by Hibernate. While the application might concurrently access the "same" (persistent identity) business object in two different sessions, the two instances will actually be "different" (JVM identity). Conflicts are resolved using an optimistic approach and automatic versioning at flush/commit time.

This approach leaves Hibernate and the database to worry about concurrency. It also provides the best scalability, since guaranteeing identity in single-threaded units of work means that it does not need expensive locking or other means of synchronization. The application does not need to synchronize on any business object, as long as it maintains a single thread per Session. Within a Session the application can safely use == to compare objects.

However, an application that uses == outside of a Session might produce unexpected results. This might occur even in some unexpected places. For example, if you put two detached instances into the same Set, both might have the same database identity (i.e., they represent the same row). JVM identity, however, is by definition not guaranteed for instances in a detached state. The developer has to override the equals() and hashCode() methods in persistent classes and implement their own notion of object equality. There is one caveat: never use the database identifier to implement equality. Use a business key that is a combination of unique, usually immutable, attributes. The database identifier will change if a transient object is made persistent. If the transient instance (usually together with detached instances) is held in a Set, changing the hashcode breaks the contract of the Set. Attributes for business keys do not have to be as stable as database primary keys; you only have to guarantee stability as long as the objects are in the same Set. See the Hibernate website for a more thorough discussion of this issue. Please note that this is not a Hibernate issue, but simply how Java object identity and equality has to be implemented.

Do not use the anti-patterns session-per-user-session or session-per-application (there are, however, rare exceptions to this rule). Some of the following issues might also arise within the recommended patterns, so ensure that you understand the implications before making a design decision: