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Hibernate example source code file (transactions.xml)
This example Hibernate source code file (transactions.xml) is included in the DevDaily.com
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The Hibernate transactions.xml source code
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<chapter id="transactions" revision="2">
<title>Transactions and Concurrency
<para>
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.
</para>
<para>
Hibernate does not lock objects in memory. Your application can expect the behavior as
defined by the isolation level of your database transactions. Through
<literal>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.
</para>
<para>
In addition to versioning for automatic optimistic concurrency control, Hibernate also
offers, using the
<literal>SELECT FOR UPDATE syntax, a (minor) API for pessimistic locking of rows. Optimistic concurrency control and
this API are discussed later in this chapter.
</para>
<para>
The discussion of concurrency control in Hibernate begins with the granularity of
<literal>Configuration, SessionFactory, and
<literal>Session, as well as database transactions and long conversations.
</para>
<section id="transactions-basics" revision="1">
<title>Session and transaction scopes
<para>
A <literal>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 <literal>Configuration instance.
</para>
<para>
A <literal>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 <literal>Session will not obtain a JDBC Connection,
or a <literal>Datasource, unless it is needed. It will not consume any
resources until used.
</para>
<para>
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.
</para>
<para>
What is the scope of a unit of work? Can a single Hibernate <literal>Session
span several database transactions, or is this a one-to-one relationship of scopes? When
should you open and close a <literal>Session and how do you demarcate the
database transaction boundaries? These questions are addressed in the following sections.
</para>
<section id="transactions-basics-uow" revision="1">
<title>Unit of work
<para>
First, let's define a unit of work. A unit of work is a
design pattern described by Martin Fowler as
<quote>
[maintaining] a list of objects affected by a business
transaction and coordinates the writing out of changes
and the resolution of concurrency problems.
</quote>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 <xref linkend="transactions-basics-apptx"/>).
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.
</para>
<para>
Do not use the <emphasis>session-per-operation antipattern:
do not open and close a <literal>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.
</para>
<para>
The most common pattern in a multi-user client/server application is
<emphasis>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
<literal>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
<literal>Session. The relationship between the two is one-to-one and this
model is a perfect fit for many applications.
</para>
<para>
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 <literal>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 <literal>Transaction
API shown later in this chapter.
</para>
<para>
Your application code can access a "current session" to process the request
by calling <literal>sessionFactory.getCurrentSession().
You will always get a <literal>Session scoped
to the current database transaction. This has to be configured for either
resource-local or JTA environments, see <xref linkend="architecture-current-session"/>.
</para>
<para>
You can extend the scope of a <literal>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 <emphasis>Open Session in View pattern.
</para>
</section>
<section id="transactions-basics-apptx" revision="1">
<title>Long conversations
<para>
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:
</para>
<itemizedlist>
<listitem>
<para>
The first screen of a dialog opens. The data seen by the user has been loaded in
a particular <literal>Session and database transaction. The user is free to
modify the objects.
</para>
</listitem>
<listitem>
<para>
The user clicks "Save" after 5 minutes and expects their modifications to be made
persistent. The user also expects that they were the only person editing this information and
that no conflicting modification has occurred.
</para>
</listitem>
</itemizedlist>
<para>
From the point of view of the user, we call this unit of work a long-running
<emphasis>conversation or application transaction.
There are many ways to implement this in your application.
</para>
<para>
A first naive implementation might keep the <literal>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.
</para>
<para>
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:
</para>
<itemizedlist>
<listitem>
<para>
<emphasis>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.
</para>
</listitem>
<listitem>
<para>
<emphasis>Detached Objects: if you decide to use the
<emphasis>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
<emphasis>session-per-request-with-detached-objects. Automatic
versioning is used to isolate concurrent modifications.
</para>
</listitem>
<listitem>
<para>
<emphasis>Extended (or Long) Session: the Hibernate
<literal>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
<emphasis>session-per-conversation and makes
even reattachment unnecessary. Automatic versioning is used to isolate
concurrent modifications and the <literal>Session will not
be allowed to be flushed automatically, but explicitly.
</para>
</listitem>
</itemizedlist>
<para>
Both <emphasis>session-per-request-with-detached-objects and
<emphasis>session-per-conversation have advantages and disadvantages.
These disadvantages are discussed later in this chapter in the context of optimistic concurrency control.
</para>
</section>
<section id="transactions-basics-identity">
<title>Considering object identity
<para>
An application can concurrently access the same persistent state in two
different <literal>Sessions. However, an instance of a persistent class
is never shared between two <literal>Session instances. It is for this reason that there are
two different notions of identity:
</para>
<variablelist spacing="compact">
<varlistentry>
<term>Database Identity
<listitem>
<para>
<literal>foo.getId().equals( bar.getId() )
</para>
</listitem>
</varlistentry>
<varlistentry>
<term>JVM Identity
<listitem>
<para>
<literal>foo==bar
</para>
</listitem>
</varlistentry>
</variablelist>
<para>
For objects attached to a <emphasis>particular Session
(i.e., in the scope of a <literal>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.
</para>
<para>
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
<literal>Session. Within a Session the application can safely use
<literal>== to compare objects.
</para>
<para>
However, an application that uses <literal>== 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 <literal>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 <literal>equals()
and <literal>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
<literal>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 <literal>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.
</para>
</section>
<section id="transactions-basics-issues">
<title>Common issues
<para>
Do not use the anti-patterns <emphasis>session-per-user-session or
<emphasis>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:
</para>
<itemizedlist>
<listitem>
<para>
A <literal>Session is not thread-safe. Things that work
concurrently, like HTTP requests, session beans, or Swing workers, will cause race
conditions if a <literal>Session instance is shared. If you keep your
Hibernate <literal>Session in your HttpSession (this is discussed
later in the chapter), you should consider synchronizing access to your Http session. Otherwise,
a user that clicks reload fast enough can use the same <literal>Session in
two concurrently running threads.
</para>
</listitem>
<listitem>
<para>
An exception thrown by Hibernate means you have to rollback your database transaction
and close the <literal>Session immediately (this is discussed in more detail later in the chapter).
If your <literal>Session is bound to the application, you have to stop
the application. Rolling back the database transaction does not put your business
objects back into the state they were at the start of the transaction. This means that the
database state and the business objects will be out of sync. Usually this is not a
problem, because exceptions are not recoverable and you will have to start over after
rollback anyway.
</para>
</listitem>
<listitem>
<para>
The <literal>Session caches every object that is in a persistent state (watched
and checked for dirty state by Hibernate). If you keep it open for a long time or simply load too
much data, it will grow endlessly until you
get an OutOfMemoryException. One solution is to call <literal>clear() and evict()
to manage the <literal>Session cache, but you should consider a
Stored Procedure if you need mass data operations. Some solutions are shown in
<xref linkend="batch"/>. Keeping a Session open for the duration
of a user session also means a higher probability of stale data.
</para>
</listitem>
</itemizedlist>
</section>
</section>
<section id="transactions-demarcation">
<title>Database transaction demarcation
<para>
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.
</para>
<para>
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.
</para>
<para>
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 <literal>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.
</para>
<para>
Ending a <literal>Session usually involves four distinct phases:
</para>
<itemizedlist spacing="compact">
<listitem>
<para>
flush the session
</para>
</listitem>
<listitem>
<para>
commit the transaction
</para>
</listitem>
<listitem>
<para>
close the session
</para>
</listitem>
<listitem>
<para>
handle exceptions
</para>
</listitem>
</itemizedlist>
<para>
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.
</para>
<section id="transactions-demarcation-nonmanaged" revision="2">
<title>Non-managed environment
<para>
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:
</para>
<programlisting role="JAVA">
<para>
You do not have to <literal>flush() the Session explicitly:
the call to <literal>commit() automatically triggers the synchronization depending
on the <link linkend="objectstate-flushing">FlushMode for the session.
A call to <literal>close() marks the end of a session. The main implication
of <literal>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.
</para>
<para>
As outlined earlier, a much more flexible solution is Hibernate's built-in "current session" context
management:
</para>
<programlisting role="JAVA">
<para>
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
<literal>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 <literal>SessionFactory.
Exception handling is discussed later in this chapter.
</para>
<para>
You should select <literal>org.hibernate.transaction.JDBCTransactionFactory,
which is the default, and for the second example select <literal>"thread" as your
<literal>hibernate.current_session_context_class.
</para>
</section>
<section id="transactions-demarcation-jta" revision="3">
<title>Using JTA
<para>
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.
</para>
<para>
If you use bean-managed transactions (BMT), Hibernate will tell the application server to start
and end a BMT transaction if you use the <literal>Transaction API. The
transaction management code is identical to the non-managed environment.
</para>
<programlisting role="JAVA">
<para>
If you want to use a transaction-bound <literal>Session, that is, the
<literal>getCurrentSession() functionality for easy context propagation,
use the JTA <literal>UserTransaction API directly:
</para>
<programlisting role="JAVA">
<para>
With CMT, transaction demarcation is completed in session bean deployment descriptors, not programmatically.
The code is reduced to:
</para>
<programlisting role="JAVA">
<para>
In a CMT/EJB, even rollback happens automatically. An unhandled <literal>RuntimeException
thrown by a session bean method tells the container to set the global transaction to rollback.
<emphasis>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.</emphasis>
</para>
<para>
When configuring Hibernate's transaction factory, choose <literal>org.hibernate.transaction.JTATransactionFactory
if you use JTA directly (BMT), and <literal>org.hibernate.transaction.CMTTransactionFactory
in a CMT session bean. Remember to also set
<literal>hibernate.transaction.manager_lookup_class. Ensure
that your <literal>hibernate.current_session_context_class is either unset (backwards
compatibility), or is set to <literal>"jta".
</para>
<para>
The <literal>getCurrentSession() operation has one downside in a JTA environment.
There is one caveat to the use of <literal>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 <literal>ScrollableResults or
<literal>Iterator instances returned by scroll() or
<literal>iterate(). You must release the underlying database
cursor by calling <literal>ScrollableResults.close() or
<literal>Hibernate.close(Iterator) explicitly from a finally
block. Most applications can easily avoid using <literal>scroll() or
<literal>iterate() from the JTA or CMT code.)
</para>
</section>
<section id="transactions-demarcation-exceptions">
<title>Exception handling
<para>
If the <literal>Session throws an exception, including any
<literal>SQLException, immediately rollback the database
transaction, call <literal>Session.close() and discard the
<literal>Session instance. Certain methods of Session
will <emphasis>not leave the session in a consistent state. No
exception thrown by Hibernate can be treated as recoverable. Ensure that the
<literal>Session will be closed by calling close()
in a <literal>finally block.
</para>
<para>
The <literal>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 <literal>HibernateException. These
are not recoverable and appropriate action should be taken.
</para>
<para>
Hibernate wraps <literal>SQLExceptions thrown while interacting with the database
in a <literal>JDBCException. In fact, Hibernate will attempt to convert the exception
into a more meaningful subclass of <literal>JDBCException. The underlying
<literal>SQLException is always available via JDBCException.getCause().
Hibernate converts the <literal>SQLException into an appropriate
<literal>JDBCException subclass using the SQLExceptionConverter
attached to the <literal>SessionFactory. By default, the
<literal>SQLExceptionConverter is defined by the configured dialect. However, it is
also possible to plug in a custom implementation. See the javadocs for the
<literal>SQLExceptionConverterFactory class for details. The standard
<literal>JDBCException subtypes are:
</para>
<itemizedlist spacing="compact">
<listitem>
<para>
<literal>JDBCConnectionException: indicates an error
with the underlying JDBC communication.
</para>
</listitem>
<listitem>
<para>
<literal>SQLGrammarException: indicates a grammar
or syntax problem with the issued SQL.
</para>
</listitem>
<listitem>
<para>
<literal>ConstraintViolationException: indicates some
form of integrity constraint violation.
</para>
</listitem>
<listitem>
<para>
<literal>LockAcquisitionException: indicates an error
acquiring a lock level necessary to perform the requested operation.
</para>
</listitem>
<listitem>
<para>
<literal>GenericJDBCException: a generic exception
which did not fall into any of the other categories.
</para>
</listitem>
</itemizedlist>
</section>
<section id="transactions-demarcation-timeout">
<title>Transaction timeout
<para>
An 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 functionality is abstracted by the Hibernate
<literal>Transaction object.
</para>
<programlisting role="JAVA">
<para>
<literal>setTimeout() cannot be called in a CMT bean,
where transaction timeouts must be defined declaratively.
</para>
</section>
</section>
<section id="transactions-optimistic">
<title>Optimistic concurrency control
<para>
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.
</para>
<section id="transactions-optimistic-manual">
<title>Application version checking
<para>
In an implementation without much help from Hibernate, each interaction with the
database occurs in a new <literal>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.
</para>
<programlisting role="JAVA">
<para>
The <literal>version property is mapped using <version>,
and Hibernate will automatically increment it during flush if the entity is
dirty.
</para>
<para>
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, <emphasis>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.
</para>
<para>
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 <literal>Session or detached instances
as the design paradigm.
</para>
</section>
<section id="transactions-optimistic-longsession">
<title>Extended session and automatic versioning
<para>
A single <literal>Session instance and its persistent instances that are
used for the whole conversation are known as <emphasis>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.
</para>
<para>
The <literal>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.
</para>
<programlisting role="JAVA">
<para>
The <literal>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 <literal>Session.lock()
with <literal>LockMode.READ on any objects that might have been updated by another
transaction. You do not need to lock any data that you <emphasis>are updating.
Usually you would set <literal>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 <literal>flush() operation, and then
<literal>close() the session to end the conversation.
</para>
<para>
This pattern is problematic if the <literal>Session is too big to
be stored during user think time (for example, an <literal>HttpSession should
be kept as small as possible). As the <literal>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
<literal>Session only for a single conversation as it will soon
have stale data.
</para>
<note>
<title>Note
<para>Earlier versions of Hibernate required explicit disconnection and reconnection
of a <literal>Session. These methods are deprecated, as beginning and
ending a transaction has the same effect.
</para>
</note>
<para>
Keep the disconnected <literal>Session close
to the persistence layer. Use an EJB stateful session bean to
hold the <literal>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
<literal>HttpSession.
</para>
<para>
The extended session pattern, or <emphasis>session-per-conversation, is
more difficult to implement with automatic current session context management.
You need to supply your own implementation of the <literal>CurrentSessionContext
for this. See the Hibernate Wiki for examples.
</para>
</section>
<section id="transactions-optimistic-detached">
<title>Detached objects and automatic versioning
<para>
Each interaction with the persistent store occurs in a new <literal>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
<literal>Session and then reattaches them using Session.update(),
<literal>Session.saveOrUpdate(), or Session.merge().
</para>
<programlisting role="JAVA">
<para>
Again, Hibernate will check instance versions during flush, throwing an
exception if conflicting updates occurred.
</para>
<para>
You can also call <literal>lock() instead of update(),
and use <literal>LockMode.READ (performing a version check and bypassing all
caches) if you are sure that the object has not been modified.
</para>
</section>
<section id="transactions-optimistic-customizing">
<title>Customizing automatic versioning
<para>
You can disable Hibernate's automatic version increment for particular properties and
collections by setting the <literal>optimistic-lock mapping attribute to
<literal>false. Hibernate will then no longer increment versions if the
property is dirty.
</para>
<para>
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 <literal>optimistic-lock="all"
in the <literal><class> mapping. This conceptually only works
if Hibernate can compare the old and the new state (i.e., if you use a single long
<literal>Session and not session-per-request-with-detached-objects).
</para>
<para>
Concurrent modification can be permitted in instances where the changes that have been
made do not overlap. If you set <literal>optimistic-lock="dirty" when mapping the
<literal><class>, Hibernate will only compare dirty fields during flush.
</para>
<para>
In both cases, with dedicated version/timestamp columns or with a full/dirty field
comparison, Hibernate uses a single <literal>UPDATE statement, with an
appropriate <literal>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 <emphasis>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 <literal>select-before-update="true" in the
<literal><class> mapping, forcing Hibernate to SELECT
the instance to ensure that changes did occur before updating the row.
</para>
</section>
</section>
<section id="transactions-locking">
<title>Pessimistic locking
<para>
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.
</para>
<para>
Hibernate will always use the locking mechanism of the database; it never lock objects
in memory.
</para>
<para>
The <literal>LockMode class defines the different lock levels that can be acquired
by Hibernate. A lock is obtained by the following mechanisms:
</para>
<itemizedlist spacing="compact">
<listitem>
<para>
<literal>LockMode.WRITE is acquired automatically when Hibernate updates or inserts
a row.
</para>
</listitem>
<listitem>
<para>
<literal>LockMode.UPGRADE can be acquired upon explicit user request using
<literal>SELECT ... FOR UPDATE on databases which support that syntax.
</para>
</listitem>
<listitem>
<para>
<literal>LockMode.UPGRADE_NOWAIT can be acquired upon explicit user request using a
<literal>SELECT ... FOR UPDATE NOWAIT under Oracle.
</para>
</listitem>
<listitem>
<para>
<literal>LockMode.READ is acquired automatically when Hibernate reads data
under Repeatable Read or Serializable isolation level. It can be re-acquired by explicit user
request.
</para>
</listitem>
<listitem>
<para>
<literal>LockMode.NONE represents the absence of a lock. All objects switch to this
lock mode at the end of a <literal>Transaction. Objects associated with the session
via a call to <literal>update() or saveOrUpdate() also start out
in this lock mode.
</para>
</listitem>
</itemizedlist>
<para>
The "explicit user request" is expressed in one of the following ways:
</para>
<itemizedlist spacing="compact">
<listitem>
<para>
A call to <literal>Session.load(), specifying a LockMode.
</para>
</listitem>
<listitem>
<para>
A call to <literal>Session.lock().
</para>
</listitem>
<listitem>
<para>
A call to <literal>Query.setLockMode().
</para>
</listitem>
</itemizedlist>
<para>
If <literal>Session.load() is called with UPGRADE or
<literal>UPGRADE_NOWAIT, and the requested object was not yet loaded by
the session, the object is loaded using <literal>SELECT ... FOR UPDATE.
If <literal>load() is called for an object that is already loaded with
a less restrictive lock than the one requested, Hibernate calls
<literal>lock() for that object.
</para>
<para>
<literal>Session.lock() performs a version number check if the specified lock
mode is <literal>READ, UPGRADE or
<literal>UPGRADE_NOWAIT. In the case of UPGRADE or
<literal>UPGRADE_NOWAIT, SELECT ... FOR UPDATE is used.
</para>
<para>
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.
</para>
</section>
<section id="transactions-connection-release">
<title>Connection release modes
<para>
One of the legacies of Hibernate 2.x JDBC connection management
meant that a <literal>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 <literal>ConnectionProvider.
User-supplied connections are outside the breadth of this discussion. The different
release modes are identified by the enumerated values of
<literal>org.hibernate.ConnectionReleaseMode:
</para>
<itemizedlist spacing="compact">
<listitem>
<para>
<literal>ON_CLOSE: is the legacy behavior described above. The
Hibernate session obtains a connection when it first needs to perform some JDBC access
and maintains that connection until the session is closed.
</para>
</listitem>
<listitem>
<para>
<literal>AFTER_TRANSACTION: releases connections after a
<literal>org.hibernate.Transaction has been completed.
</para>
</listitem>
<listitem>
<para>
<literal>AFTER_STATEMENT (also referred to as aggressive release):
releases connections after every statement execution. This aggressive releasing
is skipped if that statement leaves open resources associated with the given session.
Currently the only situation where this occurs is through the use of
<literal>org.hibernate.ScrollableResults.
</para>
</listitem>
</itemizedlist>
<para>
The configuration parameter <literal>hibernate.connection.release_mode is used
to specify which release mode to use. The possible values are as follows:
</para>
<itemizedlist spacing="compact">
<listitem>
<para>
<literal>auto (the default): this choice delegates to the release mode
returned by the <literal>org.hibernate.transaction.TransactionFactory.getDefaultReleaseMode()
method. For JTATransactionFactory, this returns ConnectionReleaseMode.AFTER_STATEMENT; for
JDBCTransactionFactory, this returns ConnectionReleaseMode.AFTER_TRANSACTION. Do not
change this default behavior as failures due to the value of this setting
tend to indicate bugs and/or invalid assumptions in user code.
</para>
</listitem>
<listitem>
<para>
<literal>on_close: uses ConnectionReleaseMode.ON_CLOSE. This setting
is left for backwards compatibility, but its use is discouraged.
</para>
</listitem>
<listitem>
<para>
<literal>after_transaction: uses ConnectionReleaseMode.AFTER_TRANSACTION.
This setting should not be used in JTA environments. Also note that with
ConnectionReleaseMode.AFTER_TRANSACTION, if a session is considered to be in auto-commit
mode, connections will be released as if the release mode were AFTER_STATEMENT.
</para>
</listitem>
<listitem>
<para>
<literal>after_statement: uses ConnectionReleaseMode.AFTER_STATEMENT. Additionally,
the configured <literal>ConnectionProvider is consulted to see if it supports this
setting (<literal>supportsAggressiveRelease()). If not, the release mode is reset
to ConnectionReleaseMode.AFTER_TRANSACTION. This setting is only safe in environments where
we can either re-acquire the same underlying JDBC connection each time you make a call into
<literal>ConnectionProvider.getConnection() or in auto-commit environments where
it does not matter if we re-establish the same connection.
</para>
</listitem>
</itemizedlist>
</section>
</chapter>
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