hibernate-orm/reference/en/modules/transactions.xml

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<chapter id="transactions" revision="1">
<title>Transactions And Concurrency</title>
<para>
The most important point about Hibernate and concurrency control is that it is very
easy to understand. Hibernate directly uses JDBC connections and JTA resources without
adding any additional locking behavior. We highly recommend you spend some time with the
JDBC, ANSI, and transaction isolation specification of your database management system.
Hibernate only adds automatic versioning but does not lock objects in memory or change the
isolation level of your database transactions. Basically, use Hibernate like you would
use direct JDBC (or JTA/CMT) with your database resources.
</para>
<para>
However, in addition to automatic versioning, Hibernate also offers a (minor) API for
pessimistic locking of rows, using the <literal>SELECT FOR UPDATE</literal> syntax. This API
is discussed later in this chapter.
</para>
<para>
We start the discussion of concurrency control in Hibernate with the granularity of
<literal>Configuration</literal>, <literal>SessionFactory</literal>, and
<literal>Session</literal>, as well as database and long application transactions.
</para>
<sect1 id="transactions-basics">
<title>Session and transaction scopes</title>
<para>
A <literal>SessionFactory</literal> 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</literal> instance.
</para>
<para>
A <literal>Session</literal> is an inexpensive, non-threadsafe object that should be
used once, for a single business process, a single unit of work, and then discarded.
A <literal>Session</literal> will not obtain a JDBC <literal>Connection</literal>
(or a <literal>Datasource</literal>) unless it is needed, so you may safely open
and close a <literal>Session</literal> even if you are not sure that data access will
be needed to serve a particular request. (This becomes important as soon as you are
implementing some of the following patterns using request interception.)
</para>
<para>
To complete this picture you also have to think about database transactions. A
database transaction has to be as short as possible, to reduce lock contention in
the database. Long database transactions will prevent your application from scaling
to highly concurrent load.
</para>
<para>
What is the scope of a unit of work? Can a single Hibernate <literal>Session</literal>
span several database transactions or is this a one-to-one relationship of scopes? When
should you open and close a <literal>Session</literal> and how do you demarcate the
database transaction boundaries?
</para>
<sect2 id="transactions-basics-uow">
<title>Unit of work</title>
<para>
First, don't use the <emphasis>session-per-operation</emphasis> antipattern, that is,
don't open and close a <literal>Session</literal> 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.)
</para>
<para>
The most common pattern in a multi-user client/server application is
<emphasis>session-per-request</emphasis>. In this model, a request from the client
is send to the server (where the Hibernate persistence layer runs), a new Hibernate
<literal>Session</literal> 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
<literal>Session</literal>. 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: not only has the <literal>Session</literal>
and transaction to be started and ended correctly, but they also have to be accessible for
data access operations. The demarcation of a unit of work is ideally implemented using an
interceptor that runs when a request hits the server and before the response will be send (i.e.
a <literal>ServletFilter</literal>). We recommend to bind the <literal>Session</literal> to
the thread that serves the request, using a <literal>ThreadLocal</literal> variable. This allows
easy access (like accessing a static variable) in all code that runs in this thread. Depending
on the database transaction demarcation mechanism you chose, you might also keep the transaction
context in a <literal>ThreadLocal</literal> variable. The implementation patterns for this
are known as <emphasis>ThreadLocal Session</emphasis> and <emphasis>Open Session in View</emphasis>.
You can easily extend the <literal>HibernateUtil</literal> helper class shown earlier in this
documentation to implement this. Of course, you'd have to find a way to implement an interceptor
and set it up in your environment. See the Hibernate website for tips and examples.
</para>
</sect2>
<sect2 id="transactions-basics-apptx">
<title>Application transactions</title>
<para>
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:
</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</literal> and database transaction. The user is free to
modify the objects.
</para>
</listitem>
<listitem>
<para>
The user clicks "Save" after 5 minutes and expects his modifications to be made
persistent; he also expects that he was the only person editing this information and
that no conflicting modification can occur.
</para>
</listitem>
</itemizedlist>
<para>
We call this unit of work, from the point of view of the user, a long running
<emphasis>application transaction</emphasis>. There are many ways how you can implement
this in your application.
</para>
<para>
A first naive implementation might keep the <literal>Session</literal> 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.
</para>
<para>
Clearly, we have to use several database transactions to implement the application
transaction. In this case, maintaining isolation of business processes becomes the
partial responsibility of the application tier. A single application transaction
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:
</para>
<itemizedlist>
<listitem>
<para>
<emphasis>Automatic Versioning</emphasis> - Hibernate can do automatic
optimistic concurrency control for you, it can automatically detect
if a concurrent modification occured during user think time.
</para>
</listitem>
<listitem>
<para>
<emphasis>Detached Objects</emphasis> - If you decide to use the already
discussed <emphasis>session-per-request</emphasis> pattern, all loaded instances
will be in 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</emphasis>. Automatic
versioning is used to isolate concurrent modifications.
</para>
</listitem>
<listitem>
<para>
<emphasis>Long Session</emphasis> - The Hibernate <literal>Session</literal> may
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-application-transaction</emphasis> and makes
even reattachment unnecessary. Automatic versioning is used to isolate
concurrent modifications.
</para>
</listitem>
</itemizedlist>
<para>
Both <emphasis>session-per-request-with-detached-objects</emphasis> and
<emphasis>session-per-application-transaction</emphasis> have advantages and disadvantages,
we discuss them later in this chapter in the context of optimistic concurrency control.
</para>
</sect2>
<sect2 id="transactions-basics-identity">
<title>Considering object identity</title>
<para>
An application may concurrently access the same persistent state in two
different <literal>Session</literal>s. However, an instance of a persistent class
is never shared between two <literal>Session</literal> instances. Hence there are
two different notions of identity:
</para>
<variablelist spacing="compact">
<varlistentry>
<term>Database Identity</term>
<listitem>
<para>
<literal>foo.getId().equals( bar.getId() )</literal>
</para>
</listitem>
</varlistentry>
<varlistentry>
<term>JVM Identity</term>
<listitem>
<para>
<literal>foo==bar</literal>
</para>
</listitem>
</varlistentry>
</variablelist>
<para>
Then for objects attached to a <emphasis>particular</emphasis> <literal>Session</literal>
(i.e. in the scope of a <literal>Session</literal>) 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.
</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 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
<literal>Session</literal>. Within a <literal>Session</literal> the application may safely use
<literal>==</literal> to compare objects.
</para>
<para>
However, an application that uses <literal>==</literal> outside of a <literal>Session</literal>,
might see unexpected results. This might occur even in some unexpected places, for example,
if you put two detached instances into the same <literal>Set</literal>. 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 <literal>equals()</literal>
and <literal>hashCode()</literal> 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
<literal>Set</literal>, changing the hashcode breaks the contract of the <literal>Set</literal>.
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 <literal>Set</literal>. 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.
</para>
</sect2>
<sect2 id="transactions-basics-issues">
<title>Common issues</title>
<para>
Never use the anti-patterns <emphasis>session-per-user-session</emphasis> or
<emphasis>session-per-application</emphasis> (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:
</para>
<itemizedlist>
<listitem>
<para>
A <literal>Session</literal> is not thread-safe. Things which are supposed to work
concurrently, like HTTP requests, session beans, or Swing workers, will cause race
conditions if a <literal>Session</literal> instance would be shared. If you keep your
Hibernate <literal>Session</literal> in your <literal>HttpSession</literal> (discussed
later), you should consider synchronizing access to your Http session. Otherwise,
a user that clicks reload fast enough may use the same <literal>Session</literal> 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</literal> immediately (discussed later in more detail).
If your <literal>Session</literal> is bound to the application, you have to stop
the application. Rolling back the database transaction doesn't put your business
objects back into the state they were at the start of the transaction. This means the
database state and the business objects do get out of sync. Usually this is not a
problem, because exceptions are not recoverable and you have to start over after
rollback anyway.
</para>
</listitem>
<listitem>
<para>
The <literal>Session</literal> caches every object that is in persistent state (watched
and checked for dirty state by Hibernate). This means it grows endlessly until you
get an OutOfMemoryException, if you keep it open for a long time or simply load too
much data. One solution for this is to call <literal>clear()</literal> and <literal>evict()</literal>
to manage the <literal>Session</literal> cache, but you most likely should consider a
Stored Procedure if you need mass data operations. Some solutions are shown in
<xref linkend="batch"/>. Keeping a <literal>Session</literal> open for the duration
of a user session also means a high probability of stale data.
</para>
</listitem>
</itemizedlist>
</sect2>
</sect1>
<sect1 id="transactions-demarcation">
<title>Database transaction demarcation</title>
<para>
Datatabase (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.
</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, in other words, begin, commit, or rollback database transactions himself. A managed environment
usually provides container-managed transactions, with the transaction assembly defined declaratively
in deployment descriptors of EJB session beans, for example. Programmatic transaction demarcation is
then no longer necessary, even flushing the <literal>Session</literal> is done automatically.
</para>
<para>
However, it is often desirable to keep your persistence layer portable. Hibernate offers a wrapper
API called <literal>Transaction</literal> 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>
Usually, ending a <literal>Session</literal> 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>
Flushing the session has been discussed earlier, we'll now have a closer look at transaction
demarcation and exception handling in both managed- and non-managed environments.
</para>
<sect2 id="transactions-demarcation-nonmanaged">
<title>Non-managed environment</title>
<para>
If a Hibernate persistence layer runs in a non-managed environment, database connections
are usually handled by Hibernate's pooling mechanism. The session/transaction handling
idiom looks like this:
</para>
<programlisting><![CDATA[//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();
}]]></programlisting>
<para>
You don't have to <literal>flush()</literal> the <literal>Session</literal> explicitly -
the call to <literal>commit()</literal> automatically triggers the synchronization.
</para>
<para>
A call to <literal>close()</literal> marks the end of a session. The main implication
of <literal>close()</literal> is that the JDBC connection will be relinquished by the
session.
</para>
<para>
This Java code is portable and runs in both non-managed and JTA environments.
</para>
<para>
You will very likely never see this idiom in business code in a normal 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</literal> (and usually can only clean up and exit) are in
different layers. This can be a challenge to design yourself and you should use J2EE/EJB
container services whenever they are available. Exception handling is discussed later in
this chapter.
</para>
<para>
Note that you should select <literal>org.hibernate.transaction.JDBCTransactionFactory</literal>
(which is the default).
</para>
</sect2>
<sect2 id="transactions-demarcation-jta">
<title>Using JTA</title>
<para>
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. Hibernate offers two strategies for this 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</literal> API. So, the
transaction management code is identical to the non-managed environment.
</para>
<programlisting><![CDATA[// 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();
}]]></programlisting>
<para>
With CMT, transaction demarcation is done in session bean deployment descriptors, not programatically.
If you don't want to manually flush and close the <literal>Session</literal> yourself, just set
<literal>hibernate.transaction.flush_before_completion</literal> to <literal>true</literal>,
<literal>hibernate.connection.release_mode</literal> to <literal>after_statement</literal> or
<literal>auto</literal> and <literal>hibernate.transaction.auto_close_session</literal> to
<literal>true</literal>. Hibernate will then automatically flush and close the <literal>Session</literal>
for you. The only thing left is to rollback the transaction when an exception occurs. Fortunately, in a
CMT bean, even this happens automatically, since an unhandled <literal>RuntimeException</literal> thrown
by a session bean method tells the container to set the global transaction to rollback. <emphasis>This
means you do not need to use the Hibernate <literal>Transaction</literal> API at all in CMT.</emphasis>
</para>
<para>
Note that you should choose <literal>org.hibernate.transaction.JTATransactionFactory</literal>
in a BMT session bean, and <literal>org.hibernate.transaction.CMTTransactionFactory</literal>
in a CMT session bean, when you configure Hibernate's transaction factory. Remember to also set
<literal>org.hibernate.transaction.manager_lookup_class</literal>.
</para>
<para>
If you work in a CMT environment, and use automatic flushing and closing of the session, you
might also want to use the same session in different parts of your code. Typically, in a non-managed
environment you would use a <literal>ThreadLocal</literal> variable to hold the session, but a
single EJB request might execute in different threads (e.g. session bean calling another session bean).
If you don't want to bother passing your <literal>Session</literal> instance around, the
<literal>SessionFactory</literal> provides the <literal>getCurrentSession()</literal>
method, which returns a session that is bound to the JTA transaction context. This is the
easiest way to integrate Hibernate into an application! The "current" session always has
auto-flush, auto-close and auto-connection-release enabled (regardless of the above property
settings). Our session/transaction management idiom is reduced to this:
</para>
<programlisting><![CDATA[// CMT idiom
Session sess = factory.getCurrentSession();
// do some work
...
]]></programlisting>
<para>
In other words, all you have to do in a managed environment is call
<literal>SessionFactory.getCurrentSession()</literal>, do your data access work, and leave
the rest to the container. Transaction boundaries are set declaratively in the deployment
descriptors of your session bean. The lifecycle of the session is completely managed by
Hibernate.
</para>
<para>
There is one caveat to the use of <literal>after_statement</literal> connection release
mode. Due to a silly limitation of the JTA spec, it is not possible for Hibernate to
automatically clean up any unclosed <literal>ScrollableResults</literal> or
<literal>Iterator</literal> instances returned by <literal>scroll()</literal> or
<literal>iterate()</literal>. You <emphasis>must</emphasis> release the underlying database
cursor by calling <literal>ScrollableResults.close()</literal> or
<literal>Hibernate.close(Iterator)</literal> explicity from a <literal>finally</literal>
block. (Of course, most applications can easily avoid using <literal>scroll()</literal> or
<literal>iterate()</literal> at all from the CMT code.)
</para>
</sect2>
<sect2 id="transactions-demarcation-exceptions">
<title>Exception handling</title>
<para>
If the <literal>Session</literal> throws an exception (including any
<literal>SQLException</literal>), you should immediately rollback the database
transaction, call <literal>Session.close()</literal> and discard the
<literal>Session</literal> instance. Certain methods of <literal>Session</literal>
will <emphasis>not</emphasis> leave the session in a consistent state. No
exception thrown by Hibernate can be treated as recoverable. Ensure that the
<literal>Session</literal> will be closed by calling <literal>close()</literal>
in a <literal>finally</literal> block.
</para>
<para>
The <literal>HibernateException</literal>, 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 <literal>HibernateException</literal>. These
are, again, not recoverable and appropriate action should be taken.
</para>
<para>
Hibernate wraps <literal>SQLException</literal>s thrown while interacting with the database
in a <literal>JDBCException</literal>. In fact, Hibernate will attempt to convert the eexception
into a more meningful subclass of <literal>JDBCException</literal>. The underlying
<literal>SQLException</literal> is always available via <literal>JDBCException.getCause()</literal>.
Hibernate converts the <literal>SQLException</literal> into an appropriate
<literal>JDBCException</literal> subclass using the <literal>SQLExceptionConverter</literal>
attached to the <literal>SessionFactory</literal>. By default, the
<literal>SQLExceptionConverter</literal> is defined by the configured dialect; however, it is
also possible to plug in a custom implementation (see the javadocs for the
<literal>SQLExceptionConverterFactory</literal> class for details). The standard
<literal>JDBCException</literal> subtypes are:
</para>
<itemizedlist spacing="compact">
<listitem>
<para>
<literal>JDBCConnectionException</literal> - indicates an error
with the underlying JDBC communication.
</para>
</listitem>
<listitem>
<para>
<literal>SQLGrammarException</literal> - indicates a grammar
or syntax problem with the issued SQL.
</para>
</listitem>
<listitem>
<para>
<literal>ConstraintViolationException</literal> - indicates some
form of integrity constraint violation.
</para>
</listitem>
<listitem>
<para>
<literal>LockAcquisitionException</literal> - indicates an error
acquiring a lock level necessary to perform the requested operation.
</para>
</listitem>
<listitem>
<para>
<literal>GenericJDBCException</literal> - a generic exception
which did not fall into any of the other categories.
</para>
</listitem>
</itemizedlist>
</sect2>
</sect1>
<sect1 id="transactions-optimistic">
<title>Optimistic concurrency control</title>
<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 for three possible approaches
to writing application code that uses optimistic concurrency. The use cases
we show are in the context of long application transactions but version checking
also has the benefit of preventing lost updates in single database transactions.
</para>
<sect2 id="transactions-optimistic-manual">
<title>Application version checking</title>
<para>
In an implementation without much help from Hibernate, each interaction with the
database occurs in a new <literal>Session</literal> 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
application transaction isolation. This approach is the least efficient in terms of
database access. It is the approach most similar to entity EJBs.
</para>
<programlisting><![CDATA[// 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();]]></programlisting>
<para>
The <literal>version</literal> property is mapped using <literal>&lt;version&gt;</literal>,
and Hibernate will automatically increment it during flush if the entity is
dirty.
</para>
<para>
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, <emphasis>last commit wins</emphasis> will be the default
strategy for your long application transactions. 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.
</para>
<para>
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 long <literal>Session</literal> or detached instances
as the design paradigm.
</para>
</sect2>
<sect2 id="transactions-optimistic-longsession">
<title>Long session and automatic versioning</title>
<para>
A single <literal>Session</literal> instance and its persistent instances are
used for the whole application transaction. 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
process with non-stale data).
</para>
<para>
The <literal>Session</literal> 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.
</para>
<programlisting><![CDATA[// foo is an instance loaded earlier by the Session
session.reconnect(); // Obtain a new JDBC connection
Transaction t = session.beginTransaction();
foo.setProperty("bar");
t.commit(); // End database transaction, flushing the change and checking the version
session.disconnect(); // Return JDBC connection ]]></programlisting>
<para>
The <literal>foo</literal> object still knows which <literal>Session</literal> it was
loaded in. <literal>Session.reconnect()</literal> obtains a new connection (or you
may supply one) and resumes the session. The method <literal>Session.disconnect()</literal>
will disconnect the session from the JDBC connection and return the connection to the pool
(unless you provided the connection). After reconnection, to force a version check on data
you aren't updating, you may call <literal>Session.lock()</literal> with
<literal>LockMode.READ</literal> on any objects that might have been updated by another
transaction. You don't need to lock any data that you <emphasis>are</emphasis> updating.
</para>
<para>
If the explicit calls to <literal>disconnect()</literal> and <literal>reconnect()</literal>
are too onerous, you may instead use <literal>hibernate.connection.release_mode</literal>.
</para>
<para>
This pattern is problematic if the <literal>Session</literal> is too big to
be stored during user think time, e.g. an <literal>HttpSession</literal> should
be kept as small as possible. As the <literal>Session</literal> 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. This is indeed
recommended, as the <literal>Session</literal> will soon also have stale data.
</para>
<para>
Also note that you should keep the disconnected <literal>Session</literal> close
to the persistence layer. In other words, use an EJB stateful session bean to
hold the <literal>Session</literal> and don't transfer it to the web layer (or
even serialize it to a separate tier) to store it in the <literal>HttpSession</literal>.
</para>
</sect2>
<sect2 id="transactions-optimistic-detached">
<title>Detached objects and automatic versioning</title>
<para>
Each interaction with the persistent store occurs in a new <literal>Session</literal>.
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</literal> and then reattaches them using <literal>Session.update()</literal>,
<literal>Session.saveOrUpdate()</literal>, or <literal>Session.merge()</literal>.
</para>
<programlisting><![CDATA[// 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();]]></programlisting>
<para>
Again, Hibernate will check instance versions during flush, throwing an
exception if conflicting updates occured.
</para>
<para>
You may also call <literal>lock()</literal> instead of <literal>update()</literal>
and use <literal>LockMode.READ</literal> (performing a version check, bypassing all
caches) if you are sure that the object has not been modified.
</para>
</sect2>
<sect2 id="transactions-optimistic-customizing">
<title>Customizing automatic versioning</title>
<para>
You may disable Hibernate's automatic version increment for particular properties and
collections by setting the <literal>optimistic-lock</literal> mapping attribute to
<literal>false</literal>. Hibernate will then no longer increment versions if the
property is dirty.
</para>
<para>
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 <literal>optimistic-lock="all"</literal>
in the <literal>&lt;class&gt;</literal> mapping. Note that this concepetually only works
if Hibernate can compare the old and new state, i.e. if you use a single long
<literal>Session</literal> and not session-per-request-with-detached-objects.
</para>
<para>
Sometimes concurrent modification can be permitted as long as the changes that have been
made don't overlap. If you set <literal>optimistic-lock="dirty"</literal> when mapping the
<literal>&lt;class&gt;</literal>, Hibernate will only compare dirty fields during flush.
</para>
<para>
In both cases, with dedicated version/timestamp columns or with full/dirty field
comparison, Hibernate uses a single <literal>UPDATE</literal> statement (with an
appropriate <literal>WHERE</literal> 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 <emphasis>on update</emphasis> 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"</literal> in the
<literal>&lt;class&gt;</literal> mapping, forcing Hibernate to <literal>SELECT</literal>
the instance to ensure that changes did actually occur, before updating the row.
</para>
</sect2>
</sect1>
<sect1 id="transactions-locking">
<title>Pessimistic Locking</title>
<para>
It is not intended that users spend much time worring about locking strategies. Its 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 sometimes 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, never lock objects
in memory!
</para>
<para>
The <literal>LockMode</literal> class defines the different lock levels that may be acquired
by Hibernate. A lock is obtained by the following mechanisms:
</para>
<itemizedlist spacing="compact">
<listitem>
<para>
<literal>LockMode.WRITE</literal> is acquired automatically when Hibernate updates or inserts
a row.
</para>
</listitem>
<listitem>
<para>
<literal>LockMode.UPGRADE</literal> may be acquired upon explicit user request using
<literal>SELECT ... FOR UPDATE</literal> on databases which support that syntax.
</para>
</listitem>
<listitem>
<para>
<literal>LockMode.UPGRADE_NOWAIT</literal> may be acquired upon explicit user request using a
<literal>SELECT ... FOR UPDATE NOWAIT</literal> under Oracle.
</para>
</listitem>
<listitem>
<para>
<literal>LockMode.READ</literal> is acquired automatically when Hibernate reads data
under Repeatable Read or Serializable isolation level. May be re-acquired by explicit user
request.
</para>
</listitem>
<listitem>
<para>
<literal>LockMode.NONE</literal> represents the absence of a lock. All objects switch to this
lock mode at the end of a <literal>Transaction</literal>. Objects associated with the session
via a call to <literal>update()</literal> or <literal>saveOrUpdate()</literal> 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()</literal>, specifying a <literal>LockMode</literal>.
</para>
</listitem>
<listitem>
<para>
A call to <literal>Session.lock()</literal>.
</para>
</listitem>
<listitem>
<para>
A call to <literal>Query.setLockMode()</literal>.
</para>
</listitem>
</itemizedlist>
<para>
If <literal>Session.load()</literal> is called with <literal>UPGRADE</literal> or
<literal>UPGRADE_NOWAIT</literal>, and the requested object was not yet loaded by
the session, the object is loaded using <literal>SELECT ... FOR UPDATE</literal>.
If <literal>load()</literal> is called for an object that is already loaded with
a less restrictive lock than the one requested, Hibernate calls
<literal>lock()</literal> for that object.
</para>
<para>
<literal>Session.lock()</literal> performs a version number check if the specified lock
mode is <literal>READ</literal>, <literal>UPGRADE</literal> or
<literal>UPGRADE_NOWAIT</literal>. (In the case of <literal>UPGRADE</literal> or
<literal>UPGRADE_NOWAIT</literal>, <literal>SELECT ... FOR UPDATE</literal> is used.)
</para>
<para>
If the database does not support the requested lock mode, Hibernate will use an appropriate
alternate mode (instead of throwing an exception). This ensures that applications will
be portable.
</para>
</sect1>
</chapter>