Chapter 11. Transactions And Concurrency - Hibernate reference 3.2.4 sp1 版英文参考手册

First, don't use the session-per-operation antipattern, that is, don't open and close a Session for every simple database call in a single thread! Of course, 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. (Note that this also means that auto-commit after every single SQL statement is useless in an application, this mode is intended for ad-hoc SQL console work. Hibernate disables, or expects the application server to do so, auto-commit mode immediately.) Database transactions are never optional, all communication with a database has to occur inside a transaction, no matter if you read or write data. As explained, 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 much 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 send 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. Once the work has been completed (and the response for the client has been prepared), the session is flushed and closed. You would also 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. All you have to do is start a transaction when a server request has to be processed, and end the transaction before the response is send to the client. You can do this in any way you like, 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 decide to use programmatic transaction demarcation, prefer the Hibernate Transaction API shown later in this chapter, for ease of use and code portability.

Your application code can access a "current session" to process the request by simply calling sessionFactory.getCurrentSession() anywhere and as often as needed. 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 2.5, “Contextual Sessions”.

Sometimes it is convenient to 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 complete is easy to do if you implement your own interceptor. However, it is not easily doable if you rely on EJBs with container-managed transactions, as 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 around this Open Session in View pattern.

The session-per-request pattern is not the only useful concept you can use to design units of work. Many business processes require a whole series of interactions with the user 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:

We call this unit of work, from the point of view of the user, a long running conversation (or application transaction). There are many ways how you can 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 of course an anti-pattern, since lock contention would not allow the application to scale with the number of concurrent users.

Clearly, we have to use several database transactions to implement the converastion. 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 (e.g. in a wizard-style dialog spanning several request/response cycles). This is easier to implement than it might sound, especially if you use Hibernate's features:

Both session-per-request-with-detached-objects and session-per-conversation have advantages and disadvantages, we discuss them later in this chapter in the context of optimistic concurrency control.

An application may concurrently access the same persistent state in two different Sessions. However, an instance of a persistent class is never shared between two Session instances. Hence there are two different notions of identity:

Then 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. However, 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 (automatic versioning) at flush/commit time, using an optimistic approach.

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 only doesn't need expensive locking or other means of synchronization. The application never needs to synchronize on any business object, as long as it sticks to a single thread per Session. Within a Session the application may safely use == to compare objects.

However, an application that uses == outside of a Session, might see 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), but JVM identity is by definition not guaranteed for instances in detached state. The developer has to override the equals() and hashCode() methods in persistent classes and implement his own notion of object equality. There is one caveat: Never use the database identifier to implement equality, use a business key, 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 don't 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. Also note that this is not a Hibernate issue, but simply how Java object identity and equality has to be implemented.

Never use the anti-patterns session-per-user-session or session-per-application (of course, there are rare exceptions to this rule). Note that some of the following issues might also appear with the recommended patterns, make sure you understand the implications before making a design decision:

If a Hibernate persistence layer runs in a non-managed environment, database connections are usually handled by simple (i.e. non-DataSource) connection pools from which Hibernate obtains connections as needed. The session/transaction handling idiom looks like this:

// Non-managed environment idiom
Session sess = factory.openSession();
Transaction tx = null;
try {
    tx = sess.beginTransaction();

    // do some work
    ...

    tx.commit();
}
catch (RuntimeException e) {
    if (tx != null) tx.rollback();
    throw e; // or display error message
}
finally {
    sess.close();
}

You don't have to flush() the Session explicitly - the call to commit() automatically triggers the synchronization (depending upon the Section 10.10, “Flushing the Session” for the session. A call to close() marks the end of a session. The main implication of close() is that the JDBC connection will be relinquished by the session. This Java code is portable and runs in both non-managed and JTA environments.

A much more flexible solution is Hibernate's built-in "current session" context management, as described earlier:

// Non-managed environment idiom with getCurrentSession()
try {
    factory.getCurrentSession().beginTransaction();

    // do some work
    ...

    factory.getCurrentSession().getTransaction().commit();
}
catch (RuntimeException e) {
    factory.getCurrentSession().getTransaction().rollback();
    throw e; // or display error message
}

You will very likely never see these code snippets in a regular application; fatal (system) exceptions should always be caught at the "top". In other words, the code that executes Hibernate calls (in the persistence layer) and the code that handles RuntimeException (and usually can only clean up and exit) are in different layers. The current context management by Hibernate can significantly simplify this design, as all you need is access to a SessionFactory. Exception handling is discussed later in this chapter.

Note that you should select org.hibernate.transaction.JDBCTransactionFactory (which is the default), and for the second example "thread" as your hibernate.current_session_context_class.

If your persistence layer runs in an application server (e.g. behind EJB session beans), every datasource connection obtained by Hibernate will automatically be part of the global JTA transaction. You can also install a standalone JTA implementation and use it without EJB. Hibernate offers two strategies for JTA integration.

If you use bean-managed transactions (BMT) Hibernate will tell the application server to start and end a BMT transaction if you use the Transaction API. So, the transaction management code is identical to the non-managed environment.

// BMT idiom
Session sess = factory.openSession();
Transaction tx = null;
try {
    tx = sess.beginTransaction();

    // do some work
    ...

    tx.commit();
}
catch (RuntimeException e) {
    if (tx != null) tx.rollback();
    throw e; // or display error message
}
finally {
    sess.close();
}

If you want to use a transaction-bound Session, that is, the getCurrentSession() functionality for easy context propagation, you will have to use the JTA UserTransaction API directly:

// BMT idiom with getCurrentSession()
try {
    UserTransaction tx = (UserTransaction)new InitialContext()
                            .lookup("java:comp/UserTransaction");

    tx.begin();

    // Do some work on Session bound to transaction
    factory.getCurrentSession().load(...);
    factory.getCurrentSession().persist(...);

    tx.commit();
}
catch (RuntimeException e) {
    tx.rollback();
    throw e; // or display error message
}

With CMT, transaction demarcation is done in session bean deployment descriptors, not programatically, hence, the code is reduced to:

// CMT idiom
 Session sess = factory.getCurrentSession();

 // do some work
 ...

In a CMT/EJB even rollback happens automatically, since an unhandled RuntimeException thrown by a session bean method tells the container to set the global transaction to rollback. This means you do not need to use the Hibernate Transaction API at all with BMT or CMT, and you get automatic propagation of the "current" Session bound to the transaction.

Note that you should choose org.hibernate.transaction.JTATransactionFactory if you use JTA directly (BMT), and org.hibernate.transaction.CMTTransactionFactory in a CMT session bean, when you configure Hibernate's transaction factory. Remember to also set hibernate.transaction.manager_lookup_class. Furthermore, make sure that your hibernate.current_session_context_class is either unset (backwards compatiblity), or set to "jta".

The getCurrentSession() operation has one downside in a JTA environment. There is one caveat to the use of after_statement connection release mode, which is then used by default. Due to a silly limitation of the JTA spec, it is not possible for Hibernate to automatically clean up any unclosed ScrollableResults or Iterator instances returned by scroll() or iterate(). You must release the underlying database cursor by calling ScrollableResults.close() or Hibernate.close(Iterator) explicity from a finally block. (Of course, most applications can easily avoid using scroll() or iterate() at all from the JTA or CMT code.)

If the Session throws an exception (including any SQLException), you should immediately rollback the database transaction, call Session.close() and discard the Session instance. Certain methods of Session will not leave the session in a consistent state. No exception thrown by Hibernate can be treated as recoverable. Ensure that the Session will be closed by calling close() in a finally block.

The HibernateException, which wraps most of the errors that can occur in a Hibernate persistence layer, is an unchecked exception (it wasn't in older versions of Hibernate). In our opinion, we shouldn't force the application developer to catch an unrecoverable exception at a low layer. In most systems, unchecked and fatal exceptions are handled in one of the first frames of the method call stack (i.e. in higher layers) and an error message is presented to the application user (or some other appropriate action is taken). Note that Hibernate might also throw other unchecked exceptions which are not a HibernateException. These are, again, not recoverable and appropriate action should be taken.

Hibernate wraps SQLExceptions thrown while interacting with the database in a JDBCException. In fact, Hibernate will attempt to convert the eexception into a more meningful subclass of JDBCException. The underlying SQLException is always available via JDBCException.getCause(). Hibernate converts the SQLException into an appropriate JDBCException subclass using the SQLExceptionConverter attached to the SessionFactory. By default, the SQLExceptionConverter is defined by the configured dialect; however, it is also possible to plug in a custom implementation (see the javadocs for the SQLExceptionConverterFactory class for details). The standard JDBCException subtypes are:

One extremely important feature provided by a managed environment like EJB that is never provided for non-managed code is transaction timeout. Transaction timeouts ensure that no misbehaving transaction can indefinitely tie up resources while returning no response to the user. Outside a managed (JTA) environment, Hibernate cannot fully provide this functionality. However, Hibernate can at least control data access operations, ensuring that database level deadlocks and queries with huge result sets are limited by a defined timeout. In a managed environment, Hibernate can delegate transaction timeout to JTA. This functioanlity is abstracted by the Hibernate Transaction object.

Session sess = factory.openSession();
try {
    //set transaction timeout to 3 seconds
    sess.getTransaction().setTimeout(3);
    sess.getTransaction().begin();

    // do some work
    ...

    sess.getTransaction().commit()
}
catch (RuntimeException e) {
    sess.getTransaction().rollback();
    throw e; // or display error message
}
finally {
    sess.close();
}

Note that setTimeout() may not be called in a CMT bean, where transaction timeouts must be defined declaratively.

In an implementation without much help from Hibernate, each interaction with the database occurs in a new Session and the developer is responsible for reloading all persistent instances from the database before manipulating them. This approach forces the application to carry out its own version checking to ensure conversation transaction isolation. This approach is the least efficient in terms of database access. It is the approach most similar to entity EJBs.

// foo is an instance loaded by a previous Session
session = factory.openSession();
Transaction t = session.beginTransaction();

int oldVersion = foo.getVersion();
session.load( foo, foo.getKey() ); // load the current state
if ( oldVersion!=foo.getVersion ) throw new StaleObjectStateException();
foo.setProperty("bar");

t.commit();
session.close();

The version property is mapped using <version>, and Hibernate will automatically increment it during flush if the entity is dirty.

Of course, if you are operating in a low-data-concurrency environment and don't require version checking, you may use this approach and just skip the version check. In that case, last commit wins will be the default strategy for your long conversations. Keep in mind that this might confuse the users of the application, as they might experience lost updates without error messages or a chance to merge conflicting changes.

Clearly, manual version checking is only feasible in very trivial circumstances and not practical for most applications. Often not only single instances, but complete graphs of modified ojects have to be checked. Hibernate offers automatic version checking with either an extended Session or detached instances as the design paradigm.

A single Session instance and its persistent instances are used for the whole conversation, known as session-per-conversation. Hibernate checks instance versions at flush time, throwing an exception if concurrent modification is detected. It's up to the developer to catch and handle this exception (common options are the opportunity for the user to merge changes or to restart the business conversation with non-stale data).

The Session is disconnected from any underlying JDBC connection when waiting for user interaction. This approach is the most efficient in terms of database access. The application need not concern itself with version checking or with reattaching detached instances, nor does it have to reload instances in every database transaction.

// foo is an instance loaded earlier by the old session
Transaction t = session.beginTransaction(); // Obtain a new JDBC connection, start transaction

foo.setProperty("bar");

session.flush();    // Only for last transaction in conversation
t.commit();         // Also return JDBC connection
session.close();    // Only for last transaction in conversation

The foo object still knows which Session it was loaded in. Beginning a new database transaction on an old session obtains a new connection and resumes the session. Committing a database transaction disconnects a session from the JDBC connection and returns the connection to the pool. After reconnection, to force a version check on data you aren't updating, you may call Session.lock() with LockMode.READ on any objects that might have been updated by another transaction. You don't need to lock any data that you are updating. Usually you would set FlushMode.NEVER on an extended Session, so that only the last database transaction cycle is allowed to actually persist all modifications made in this conversation. Hence, only this last database transaction would include the flush() operation, and then also close() the session to end the conversation.

This pattern is problematic if the Session is too big to be stored during user think time, e.g. an HttpSession should be kept as small as possible. As the Session is also the (mandatory) first-level cache and contains all loaded objects, we can probably use this strategy only for a few request/response cycles. You should use a Session only for a single conversation, as it will soon also have stale data.

(Note that earlier Hibernate versions required explicit disconnection and reconnection of a Session. These methods are deprecated, as beginning and ending a transaction has the same effect.)

Also note that you should keep the disconnected Session close to the persistence layer. In other words, use an EJB stateful session bean to hold the Session in a three-tier environment, and don't transfer it to the web layer (or even serialize it to a separate tier) to store it in the HttpSession.

The extended session pattern, or session-per-conversation, is more difficult to implement with automatic current session context management. You need to supply your own implementation of the CurrentSessionContext for this, see the Hibernate Wiki for examples.

Each interaction with the persistent store occurs in a new Session. However, the same persistent instances are reused for each interaction with the database. The application manipulates the state of detached instances originally loaded in another Session and then reattaches them using Session.update(), Session.saveOrUpdate(), or Session.merge().

// foo is an instance loaded by a previous Session
foo.setProperty("bar");
session = factory.openSession();
Transaction t = session.beginTransaction();
session.saveOrUpdate(foo); // Use merge() if "foo" might have been loaded already
t.commit();
session.close();

Again, Hibernate will check instance versions during flush, throwing an exception if conflicting updates occured.

You may also call lock() instead of update() and use LockMode.READ (performing a version check, bypassing all caches) if you are sure that the object has not been modified.

You may disable Hibernate's automatic version increment for particular properties and collections by setting the optimistic-lock mapping attribute to false. Hibernate will then no longer increment versions if the property is dirty.

Legacy database schemas are often static and can't be modified. Or, other applications might also access the same database and don't know how to handle version numbers or even timestamps. In both cases, versioning can't rely on a particular column in a table. To force a version check without a version or timestamp property mapping, with a comparison of the state of all fields in a row, turn on optimistic-lock="all" in the <class> mapping. Note that this concepetually only works if Hibernate can compare the old and new state, i.e. if you use a single long Session and not session-per-request-with-detached-objects.

Sometimes concurrent modification can be permitted as long as the changes that have been made don't overlap. If you set optimistic-lock="dirty" when mapping the <class>, Hibernate will only compare dirty fields during flush.

In both cases, with dedicated version/timestamp columns or with full/dirty field comparison, Hibernate uses a single UPDATE statement (with an appropriate WHERE clause) per entity to execute the version check and update the information. If you use transitive persistence to cascade reattachment to associated entities, Hibernate might execute uneccessary updates. This is usually not a problem, but on update triggers in the database might be executed even when no changes have been made to detached instances. You can customize this behavior by setting select-before-update="true" in the <class> mapping, forcing Hibernate to SELECT the instance to ensure that changes did actually occur, before updating the row.