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11장. Transactions and Concurrency

11.1. 세션 영역과 트랜잭션 영역
11.1.1. 작업 단위
11.1.2. 장기간의 대화
11.1.3. 객체 identity 고려하기
11.1.4. 공통된 쟁점들
11.2. 데이터베이스 트랜잭션 경계 설정
11.2.1. 관리되지 않는 환경
11.2.2. JTA 사용하기
11.2.3. 예외상황 처리
11.2.4. 트랜잭션 타임아웃
11.3. Optimistic 동시성 제어
11.3.1. 어플리케이션 버전 체킹
11.3.2. 확장된 세션과 자동적인 버전화
11.3.3. Detached 객체들과 자동적인 버전화
11.3.4. 자동적인 버전화를 맞춤화 시키기
11.4. Pessimistic locking
11.5. Connection release modes

The most important point about Hibernate and concurrency control is that it is easy to understand. Hibernate directly uses JDBC connections and JTA resources without adding any additional locking behavior. It is recommended that you spend some time with the JDBC, ANSI, and transaction isolation specification of your database management system.

Hibernate does not lock objects in memory. Your application can expect the behavior as defined by the isolation level of your database transactions. Through Session, which is also a transaction-scoped cache, Hibernate provides repeatable reads for lookup by identifier and entity queries and not reporting queries that return scalar values.

In addition to versioning for automatic optimistic concurrency control, Hibernate also offers, using the SELECT FOR UPDATE syntax, a (minor) API for pessimistic locking of rows. Optimistic concurrency control and this API are discussed later in this chapter.

The discussion of concurrency control in Hibernate begins with the granularity of Configuration, SessionFactory, and Session, as well as database transactions and long conversations.

A SessionFactory is an expensive-to-create, threadsafe object, intended to be shared by all application threads. It is created once, usually on application startup, from a Configuration instance.

A Session is an inexpensive, non-threadsafe object that should be used once and then discarded for: a single request, a conversation or a single unit of work. A Session will not obtain a JDBC Connection, or a Datasource, unless it is needed. It will not consume any resources until used.

In order to reduce lock contention in the database, a database transaction has to be as short as possible. Long database transactions will prevent your application from scaling to a highly concurrent load. It is not recommended that you hold a database transaction open during user think time until the unit of work is complete.

What is the scope of a unit of work? Can a single Hibernate Session span several database transactions, or is this a one-to-one relationship of scopes? When should you open and close a Session and how do you demarcate the database transaction boundaries? These questions are addressed in the following sections.

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 11.1.2절. “장기간의 대화”). 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 2.5절. “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:

Database, or system, transaction boundaries are always necessary. No communication with the database can occur outside of a database transaction (this seems to confuse many developers who are used to the auto-commit mode). Always use clear transaction boundaries, even for read-only operations. Depending on your isolation level and database capabilities this might not be required, but there is no downside if you always demarcate transactions explicitly. Certainly, a single database transaction is going to perform better than many small transactions, even for reading data.

A Hibernate application can run in non-managed (i.e., standalone, simple Web- or Swing applications) and managed J2EE environments. In a non-managed environment, Hibernate is usually responsible for its own database connection pool. The application developer has to manually set transaction boundaries (begin, commit, or rollback database transactions) themselves. A managed environment usually provides container-managed transactions (CMT), with the transaction assembly defined declaratively (in deployment descriptors of EJB session beans, for example). Programmatic transaction demarcation is then no longer necessary.

However, it is often desirable to keep your persistence layer portable between non-managed resource-local environments, and systems that can rely on JTA but use BMT instead of CMT. In both cases use programmatic transaction demarcation. Hibernate offers a wrapper API called Transaction that translates into the native transaction system of your deployment environment. This API is actually optional, but we strongly encourage its use unless you are in a CMT session bean.

Ending a Session usually involves four distinct phases:

We discussed Flushing the session earlier, so we will now have a closer look at transaction demarcation and exception handling in both managed and non-managed environments.

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

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

You do not have to flush() the Session explicitly: the call to commit() automatically triggers the synchronization depending on the FlushMode 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.

As outlined earlier, a much more flexible solution is Hibernate's built-in "current session" context management:

// Non-managed environment idiom with getCurrentSession()
try {

    // do some work

catch (RuntimeException e) {
    throw e; // or display error message

You will not 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 by accessing a SessionFactory. Exception handling is discussed later in this chapter.

You should select org.hibernate.transaction.JDBCTransactionFactory, which is the default, and for the second example select "thread" as your hibernate.current_session_context_class.

If your persistence layer runs in an application server (for example, 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. 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

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

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

// BMT idiom with getCurrentSession()
try {
    UserTransaction tx = (UserTransaction)new InitialContext()


    // Do some work on Session bound to transaction

catch (RuntimeException e) {
    throw e; // or display error message

With CMT, transaction demarcation is completed in session bean deployment descriptors, not programmatically. The code is reduced to:

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

 // do some work

In a CMT/EJB, even rollback happens automatically. An unhandled RuntimeException thrown by a session bean method tells the container to set the global transaction to rollback. 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.

When configuring Hibernate's transaction factory, choose org.hibernate.transaction.JTATransactionFactory if you use JTA directly (BMT), and org.hibernate.transaction.CMTTransactionFactory in a CMT session bean. Remember to also set hibernate.transaction.manager_lookup_class. Ensure that your hibernate.current_session_context_class is either unset (backwards compatibility), or is 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 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) explicitly from a finally block. Most applications can easily avoid using scroll() or iterate() from the JTA or CMT code.)

If the Session throws an exception, including any SQLException, 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 was not in older versions of Hibernate. In our opinion, we should not 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 either 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 that are not a HibernateException. These are 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 exception into a more meaningful 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:

The only approach that is consistent with high concurrency and high scalability, is optimistic concurrency control with versioning. Version checking uses version numbers, or timestamps, to detect conflicting updates and to prevent lost updates. Hibernate provides three possible approaches to writing application code that uses optimistic concurrency. The use cases we discuss are in the context of long conversations, but version checking also has the benefit of preventing lost updates in single database transactions.

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. The application is forced 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();


version 프로퍼티는 <version>을 사용하여 매핑되고, Hibernate는 만일 엔티티가 dirty일 경우 flush 동안에 그것을 자동적으로 증가시킬 것이다.

If you are operating in a low-data-concurrency environment, and do not require version checking, you can use this approach and skip the version check. In this case, last commit wins is the default strategy for long conversations. Be aware 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.

Manual version checking is only feasible in trivial circumstances and not practical for most applications. Often not only single instances, but complete graphs of modified objects, 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 that are used for the whole conversation are known as session-per-conversation. Hibernate checks instance versions at flush time, throwing an exception if concurrent modification is detected. It is 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 does not version check or reattach 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


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 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 are not updating, you can call Session.lock() with LockMode.READ on any objects that might have been updated by another transaction. You do not need to lock any data that you are updating. Usually you would set FlushMode.MANUAL on an extended Session, so that only the last database transaction cycle is allowed to actually persist all modifications made in this conversation. Only this last database transaction will include the flush() operation, and then close() the session to end the conversation.

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

Keep the disconnected Session close to the persistence layer. Use an EJB stateful session bean to hold the Session in a three-tier environment. Do not 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.

You can 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 cannot be modified. Or, other applications might access the same database and will not know how to handle version numbers or even timestamps. In both cases, versioning cannot rely on a particular column in a table. To force a version check with a comparison of the state of all fields in a row but without a version or timestamp property mapping, turn on optimistic-lock="all" in the <class> mapping. This conceptually only works if Hibernate can compare the old and the new state (i.e., if you use a single long Session and not session-per-request-with-detached-objects).

Concurrent modification can be permitted in instances where the changes that have been made do not 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 a 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 may execute unnecessary 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 occur before updating the row.

It is not intended that users spend much time worrying about locking strategies. It is usually enough to specify an isolation level for the JDBC connections and then simply let the database do all the work. However, advanced users may wish to obtain exclusive pessimistic locks or re-obtain locks at the start of a new transaction.

Hibernate will always use the locking mechanism of the database; it never lock objects in memory.

The LockMode class defines the different lock levels that can be acquired by Hibernate. A lock is obtained by the following mechanisms:

"명시적인 사용자 요청"은 다음 방법들 중 하나로 표현된다:

만일 Session.load()UPGRADE 또는 UPGRADE_NOWAIT 모드로 호출되고 ,요청된 객체가 아직 이 세션에 의해 로드되지 않았다면, 그 객체는 SELECT ... FOR UPDATE를 사용하여 로드된다. 만일 요청된 것이 아닌 다소 제한적인 잠금으로 이미 로드되어 있는 객체에 대해 load()가 호출될 경우, Hibernate는 그 객체에 대해 lock()을 호출한다.

Session.lock() performs a version number check if the specified lock mode is READ, UPGRADE or UPGRADE_NOWAIT. In the case of UPGRADE or UPGRADE_NOWAIT, SELECT ... FOR UPDATE is used.

If the requested lock mode is not supported by the database, Hibernate uses an appropriate alternate mode instead of throwing an exception. This ensures that applications are portable.

One of the legacies of Hibernate 2.x JDBC connection management meant that a Session would obtain a connection when it was first required and then maintain that connection until the session was closed. Hibernate 3.x introduced the notion of connection release modes that would instruct a session how to handle its JDBC connections. The following discussion is pertinent only to connections provided through a configured ConnectionProvider. User-supplied connections are outside the breadth of this discussion. The different release modes are identified by the enumerated values of org.hibernate.ConnectionReleaseMode:

The configuration parameter hibernate.connection.release_mode is used to specify which release mode to use. The possible values are as follows: