Data Access

Table of Contents

Transaction Management
DAO Support
- Consistent Exception Hierarchy
- Annotations Used to Configure DAO or Repository Classes
Data Access with JDBC
Object Relational Mapping (ORM) Data Access
Marshalling XML by Using Object-XML Mappers

This part of the reference documentation is concerned with data access and the interaction between the data access layer and the business or service layer.

Spring’s comprehensive transaction management support is covered in some detail, followed by thorough coverage of the various data access frameworks and technologies with which the Spring Framework integrates.

Transaction Management

Comprehensive transaction support is among the most compelling reasons to use the Spring Framework. The Spring Framework provides a consistent abstraction for transaction management that delivers the following benefits:

A consistent programming model across different transaction APIs, such as Java Transaction API (JTA), JDBC, Hibernate, and the Java Persistence API (JPA).
Support for declarative transaction management.
A simpler API for programmatic transaction management than complex transaction APIs, such as JTA.
Excellent integration with Spring’s data access abstractions.

The following sections describe the Spring Framework’s transaction features and technologies:

Advantages of the Spring Framework’s transaction support model describes why you would use the Spring Framework’s transaction abstraction instead of EJB Container-Managed Transactions (CMT) or choosing to drive local transactions through a proprietary API, such as Hibernate.
Understanding the Spring Framework transaction abstraction outlines the core classes and describes how to configure and obtain DataSource instances from a variety of sources.
Synchronizing resources with transactions describes how the application code ensures that resources are created, reused, and cleaned up properly.
Declarative transaction management describes support for declarative transaction management.
Programmatic transaction management covers support for programmatic (that is, explicitly coded) transaction management.
Transaction bound event describes how you could use application events within a transaction.

The chapter also includes discussions of best practices, application server integration, and solutions to common problems.

Advantages of the Spring Framework’s Transaction Support Model

Traditionally, Java EE developers have had two choices for transaction management: global or local transactions, both of which have profound limitations. Global and local transaction management is reviewed in the next two sections, followed by a discussion of how the Spring Framework’s transaction management support addresses the limitations of the global and local transaction models.

Global Transactions

Global transactions let you work with multiple transactional resources, typically relational databases and message queues. The application server manages global transactions through the JTA, which is a cumbersome API (partly due to its exception model). Furthermore, a JTA UserTransaction normally needs to be sourced from JNDI, meaning that you also need to use JNDI in order to use JTA. The use of global transactions limits any potential reuse of application code, as JTA is normally only available in an application server environment.

Previously, the preferred way to use global transactions was through EJB CMT (Container Managed Transaction). CMT is a form of declarative transaction management (as distinguished from programmatic transaction management). EJB CMT removes the need for transaction-related JNDI lookups, although the use of EJB itself necessitates the use of JNDI. It removes most but not all of the need to write Java code to control transactions. The significant downside is that CMT is tied to JTA and an application server environment. Also, it is only available if one chooses to implement business logic in EJBs (or at least behind a transactional EJB facade). The negatives of EJB in general are so great that this is not an attractive proposition, especially in the face of compelling alternatives for declarative transaction management.

Local Transactions

Local transactions are resource-specific, such as a transaction associated with a JDBC connection. Local transactions may be easier to use but have a significant disadvantage: They cannot work across multiple transactional resources. For example, code that manages transactions by using a JDBC connection cannot run within a global JTA transaction. Because the application server is not involved in transaction management, it cannot help ensure correctness across multiple resources. (It is worth noting that most applications use a single transaction resource.) Another downside is that local transactions are invasive to the programming model.

Spring Framework’s Consistent Programming Model

Spring resolves the disadvantages of global and local transactions. It lets application developers use a consistent programming model in any environment. You write your code once, and it can benefit from different transaction management strategies in different environments. The Spring Framework provides both declarative and programmatic transaction management. Most users prefer declarative transaction management, which we recommend in most cases.

With programmatic transaction management, developers work with the Spring Framework transaction abstraction, which can run over any underlying transaction infrastructure. With the preferred declarative model, developers typically write little or no code related to transaction management and, hence, do not depend on the Spring Framework transaction API or any other transaction API.

Do you need an application server for transaction management?

The Spring Framework’s transaction management support changes traditional rules as to when an enterprise Java application requires an application server.

In particular, you do not need an application server purely for declarative transactions through EJBs. In fact, even if your application server has powerful JTA capabilities, you may decide that the Spring Framework’s declarative transactions offer more power and a more productive programming model than EJB CMT.

Typically, you need an application server’s JTA capability only if your application needs to handle transactions across multiple resources, which is not a requirement for many applications. Many high-end applications use a single, highly scalable database (such as Oracle RAC) instead. Stand-alone transaction managers (such as Atomikos Transactions and JOTM) are other options. Of course, you may need other application server capabilities, such as Java Message Service (JMS) and Java EE Connector Architecture (JCA).

The Spring Framework gives you the choice of when to scale your application to a fully loaded application server. Gone are the days when the only alternative to using EJB CMT or JTA was to write code with local transactions (such as those on JDBC connections) and face a hefty rework if you need that code to run within global, container-managed transactions. With the Spring Framework, only some of the bean definitions in your configuration file need to change (rather than your code).

Understanding the Spring Framework Transaction Abstraction

The key to the Spring transaction abstraction is the notion of a transaction strategy. A transaction strategy is defined by the org.springframework.transaction.PlatformTransactionManager interface, which the following listing shows:

Java

public interface PlatformTransactionManager {

    TransactionStatus getTransaction(TransactionDefinition definition) throws TransactionException;

    void commit(TransactionStatus status) throws TransactionException;

    void rollback(TransactionStatus status) throws TransactionException;
}

Kotlin

interface PlatformTransactionManager {

    @Throws(TransactionException::class)
    fun getTransaction(definition: TransactionDefinition): TransactionStatus

    @Throws(TransactionException::class)
    fun commit(status: TransactionStatus)

    @Throws(TransactionException::class)
    fun rollback(status: TransactionStatus)
}

This is primarily a service provider interface (SPI), although you can use it programmatically from your application code. Because PlatformTransactionManager is an interface, it can be easily mocked or stubbed as necessary. It is not tied to a lookup strategy, such as JNDI. PlatformTransactionManager implementations are defined like any other object (or bean) in the Spring Framework IoC container. This benefit alone makes Spring Framework transactions a worthwhile abstraction, even when you work with JTA. You can test transactional code much more easily than if it used JTA directly.

Again, in keeping with Spring’s philosophy, the TransactionException that can be thrown by any of the PlatformTransactionManager interface’s methods is unchecked (that is, it extends the java.lang.RuntimeException class). Transaction infrastructure failures are almost invariably fatal. In rare cases where application code can actually recover from a transaction failure, the application developer can still choose to catch and handle TransactionException. The salient point is that developers are not forced to do so.

The getTransaction(..) method returns a TransactionStatus object, depending on a TransactionDefinition parameter. The returned TransactionStatus might represent a new transaction or can represent an existing transaction, if a matching transaction exists in the current call stack. The implication in this latter case is that, as with Java EE transaction contexts, a TransactionStatus is associated with a thread of execution.

The TransactionDefinition interface specifies:

Propagation: Typically, all code executed within a transaction scope runs in that transaction. However, you can specify the behavior if a transactional method is executed when a transaction context already exists. For example, code can continue running in the existing transaction (the common case), or the existing transaction can be suspended and a new transaction created. Spring offers all of the transaction propagation options familiar from EJB CMT. To read about the semantics of transaction propagation in Spring, see Transaction Propagation.
Isolation: The degree to which this transaction is isolated from the work of other transactions. For example, can this transaction see uncommitted writes from other transactions?
Timeout: How long this transaction runs before timing out and being automatically rolled back by the underlying transaction infrastructure.
Read-only status: You can use a read-only transaction when your code reads but does not modify data. Read-only transactions can be a useful optimization in some cases, such as when you use Hibernate.

These settings reflect standard transactional concepts. If necessary, refer to resources that discuss transaction isolation levels and other core transaction concepts. Understanding these concepts is essential to using the Spring Framework or any transaction management solution.

The TransactionStatus interface provides a simple way for transactional code to control transaction execution and query transaction status. The concepts should be familiar, as they are common to all transaction APIs. The following listing shows the TransactionStatus interface:

Java

public interface TransactionStatus extends SavepointManager {

    boolean isNewTransaction();

    boolean hasSavepoint();

    void setRollbackOnly();

    boolean isRollbackOnly();

    void flush();

    boolean isCompleted();
}

Kotlin

interface TransactionStatus : SavepointManager {

    fun isNewTransaction(): Boolean

    fun hasSavepoint(): Boolean

    fun setRollbackOnly()

    fun isRollbackOnly(): Boolean

    fun flush()

    fun isCompleted(): Boolean
}

Regardless of whether you opt for declarative or programmatic transaction management in Spring, defining the correct PlatformTransactionManager implementation is absolutely essential. You typically define this implementation through dependency injection.

PlatformTransactionManager implementations normally require knowledge of the environment in which they work: JDBC, JTA, Hibernate, and so on. The following examples show how you can define a local PlatformTransactionManager implementation (in this case, with plain JDBC.)

You can define a JDBC DataSource by creating a bean similar to the following:

<bean id="dataSource" class="org.apache.commons.dbcp.BasicDataSource" destroy-method="close">
    <property name="driverClassName" value="${jdbc.driverClassName}" />
    <property name="url" value="${jdbc.url}" />
    <property name="username" value="${jdbc.username}" />
    <property name="password" value="${jdbc.password}" />
</bean>

The related PlatformTransactionManager bean definition then has a reference to the DataSource definition. It should resemble the following example:

<bean id="txManager" class="org.springframework.jdbc.datasource.DataSourceTransactionManager">
    <property name="dataSource" ref="dataSource"/>
</bean>

If you use JTA in a Java EE container, then you use a container DataSource, obtained through JNDI, in conjunction with Spring’s JtaTransactionManager. The following example shows what the JTA and JNDI lookup version would look like:

<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
    xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
    xmlns:jee="http://www.springframework.org/schema/jee"
    xsi:schemaLocation="
        http://www.springframework.org/schema/beans
        https://www.springframework.org/schema/beans/spring-beans.xsd
        http://www.springframework.org/schema/jee
        https://www.springframework.org/schema/jee/spring-jee.xsd">

    <jee:jndi-lookup id="dataSource" jndi-name="jdbc/jpetstore"/>

    <bean id="txManager" class="org.springframework.transaction.jta.JtaTransactionManager" />

    <!-- other <bean/> definitions here -->

</beans>

The JtaTransactionManager does not need to know about the DataSource (or any other specific resources) because it uses the container’s global transaction management infrastructure.

Note	The preceding definition of the `dataSource` bean uses the `<jndi-lookup/>` tag from the `jee` namespace. For more information see The JEE Schema.

You can also use easily Hibernate local transactions, as shown in the following examples. In this case, you need to define a Hibernate LocalSessionFactoryBean, which your application code can use to obtain Hibernate Session instances.

The DataSource bean definition is similar to the local JDBC example shown previously and, thus, is not shown in the following example.

Note	If the `DataSource` (used by any non-JTA transaction manager) is looked up through JNDI and managed by a Java EE container, it should be non-transactional, because the Spring Framework (rather than the Java EE container) manages the transactions.

The txManager bean in this case is of the HibernateTransactionManager type. In the same way as the DataSourceTransactionManager needs a reference to the DataSource, the HibernateTransactionManager needs a reference to the SessionFactory. The following example declares sessionFactory and txManager beans:

<bean id="sessionFactory" class="org.springframework.orm.hibernate5.LocalSessionFactoryBean">
    <property name="dataSource" ref="dataSource"/>
    <property name="mappingResources">
        <list>
            <value>org/springframework/samples/petclinic/hibernate/petclinic.hbm.xml</value>
        </list>
    </property>
    <property name="hibernateProperties">
        <value>
            hibernate.dialect=${hibernate.dialect}
        </value>
    </property>
</bean>

<bean id="txManager" class="org.springframework.orm.hibernate5.HibernateTransactionManager">
    <property name="sessionFactory" ref="sessionFactory"/>
</bean>

If you use Hibernate and Java EE container-managed JTA transactions, you should use the same JtaTransactionManager as in the previous JTA example for JDBC, as the following example shows:

<bean id="txManager" class="org.springframework.transaction.jta.JtaTransactionManager"/>

Note

If you use JTA, your transaction manager definition should look the same, regardless of what data access technology you use, be it JDBC, Hibernate JPA, or any other supported technology. This is due to the fact that JTA transactions are global transactions, which can enlist any transactional resource.

In all these cases, application code does not need to change. You can change how transactions are managed merely by changing configuration, even if that change means moving from local to global transactions or vice versa.

Synchronizing Resources with Transactions

How to create different transaction managers and how they are linked to related resources that need to be synchronized to transactions (for example DataSourceTransactionManager to a JDBC DataSource, HibernateTransactionManager to a Hibernate SessionFactory, and so forth) should now be clear. This section describes how the application code (directly or indirectly, by using a persistence API such as JDBC, Hibernate, or JPA) ensures that these resources are created, reused, and cleaned up properly. The section also discusses how transaction synchronization is (optionally) triggered through the relevant PlatformTransactionManager.

High-level Synchronization Approach

The preferred approach is to use Spring’s highest-level template based persistence integration APIs or to use native ORM APIs with transaction-aware factory beans or proxies for managing the native resource factories. These transaction-aware solutions internally handle resource creation and reuse, cleanup, optional transaction synchronization of the resources, and exception mapping. Thus, user data access code does not have to address these tasks but can focus purely on non-boilerplate persistence logic. Generally, you use the native ORM API or take a template approach for JDBC access by using the JdbcTemplate. These solutions are detailed in subsequent chapters of this reference documentation.

Low-level Synchronization Approach

Classes such as DataSourceUtils (for JDBC), EntityManagerFactoryUtils (for JPA), SessionFactoryUtils (for Hibernate), and so on exist at a lower level. When you want the application code to deal directly with the resource types of the native persistence APIs, you use these classes to ensure that proper Spring Framework-managed instances are obtained, transactions are (optionally) synchronized, and exceptions that occur in the process are properly mapped to a consistent API.

For example, in the case of JDBC, instead of the traditional JDBC approach of calling the getConnection() method on the DataSource, you can instead use Spring’s org.springframework.jdbc.datasource.DataSourceUtils class, as follows:

Connection conn = DataSourceUtils.getConnection(dataSource);

If an existing transaction already has a connection synchronized (linked) to it, that instance is returned. Otherwise, the method call triggers the creation of a new connection, which is (optionally) synchronized to any existing transaction and made available for subsequent reuse in that same transaction. As mentioned earlier, any SQLException is wrapped in a Spring Framework CannotGetJdbcConnectionException, one of the Spring Framework’s hierarchy of unchecked DataAccessException types. This approach gives you more information than can be obtained easily from the SQLException and ensures portability across databases and even across different persistence technologies.

This approach also works without Spring transaction management (transaction synchronization is optional), so you can use it whether or not you use Spring for transaction management.

Of course, once you have used Spring’s JDBC support, JPA support, or Hibernate support, you generally prefer not to use DataSourceUtils or the other helper classes, because you are much happier working through the Spring abstraction than directly with the relevant APIs. For example, if you use the Spring JdbcTemplate or jdbc.object package to simplify your use of JDBC, correct connection retrieval occurs behind the scenes and you need not write any special code.

`TransactionAwareDataSourceProxy`

At the very lowest level exists the TransactionAwareDataSourceProxy class. This is a proxy for a target DataSource, which wraps the target DataSource to add awareness of Spring-managed transactions. In this respect, it is similar to a transactional JNDI DataSource, as provided by a Java EE server.

You should almost never need or want to use this class, except when existing code must be called and passed a standard JDBC DataSource interface implementation. In that case, it is possible that this code is usable but is participating in Spring-managed transactions. You can write your new code by using the higher-level abstractions mentioned earlier.

Declarative transaction management

Note	Most Spring Framework users choose declarative transaction management. This option has the least impact on application code and, hence, is most consistent with the ideals of a non-invasive lightweight container.

The Spring Framework’s declarative transaction management is made possible with Spring aspect-oriented programming (AOP). However, as the transactional aspects code comes with the Spring Framework distribution and may be used in a boilerplate fashion, AOP concepts do not generally have to be understood to make effective use of this code.

The Spring Framework’s declarative transaction management is similar to EJB CMT, in that you can specify transaction behavior (or lack of it) down to the individual method level. You can make a setRollbackOnly() call within a transaction context, if necessary. The differences between the two types of transaction management are:

Unlike EJB CMT, which is tied to JTA, the Spring Framework’s declarative transaction management works in any environment. It can work with JTA transactions or local transactions by using JDBC, JPA, or Hibernate by adjusting the configuration files.
You can apply the Spring Framework declarative transaction management to any class, not merely special classes such as EJBs.
The Spring Framework offers declarative rollback rules, a feature with no EJB equivalent. Both programmatic and declarative support for rollback rules is provided.
The Spring Framework lets you customize transactional behavior by using AOP. For example, you can insert custom behavior in the case of transaction rollback. You can also add arbitrary advice, along with transactional advice. With EJB CMT, you cannot influence the container’s transaction management, except with setRollbackOnly().
The Spring Framework does not support propagation of transaction contexts across remote calls, as high-end application servers do. If you need this feature, we recommend that you use EJB. However, consider carefully before using such a feature, because, normally, one does not want transactions to span remote calls.

The concept of rollback rules is important. They let you specify which exceptions (and throwables) should cause automatic rollback. You can specify this declaratively, in configuration, not in Java code. So, although you can still call setRollbackOnly() on the TransactionStatus object to roll back the current transaction back, most often you can specify a rule that MyApplicationException must always result in rollback. The significant advantage to this option is that business objects do not depend on the transaction infrastructure. For example, they typically do not need to import Spring transaction APIs or other Spring APIs.

Although EJB container default behavior automatically rolls back the transaction on a system exception (usually a runtime exception), EJB CMT does not roll back the transaction automatically on an application exception (that is, a checked exception other than java.rmi.RemoteException). While the Spring default behavior for declarative transaction management follows EJB convention (roll back is automatic only on unchecked exceptions), it is often useful to customize this behavior.

Understanding the Spring Framework’s Declarative Transaction Implementation

It is not sufficient merely to tell you to annotate your classes with the @Transactional annotation, add @EnableTransactionManagement to your configuration, and expect you to understand how it all works. To provide a deeper understanding, this section explains the inner workings of the Spring Framework’s declarative transaction infrastructure in the event of transaction-related issues.

The most important concepts to grasp with regard to the Spring Framework’s declarative transaction support are that this support is enabled via AOP proxies and that the transactional advice is driven by metadata (currently XML- or annotation-based). The combination of AOP with transactional metadata yields an AOP proxy that uses a TransactionInterceptor in conjunction with an appropriate PlatformTransactionManager implementation to drive transactions around method invocations.

Note	Spring AOP is covered in the AOP section.

The following images shows a Conceptual view of calling a method on a transactional proxy:

Example of Declarative Transaction Implementation

Consider the following interface and its attendant implementation. This example uses Foo and Bar classes as placeholders so that you can concentrate on the transaction usage without focusing on a particular domain model. For the purposes of this example, the fact that the DefaultFooService class throws UnsupportedOperationException instances in the body of each implemented method is good. That behavior lets you see transactions be created and then rolled back in response to the UnsupportedOperationException instance. The following listing shows the FooService interface:

Java

// the service interface that we want to make transactional

package x.y.service;

public interface FooService {

    Foo getFoo(String fooName);

    Foo getFoo(String fooName, String barName);

    void insertFoo(Foo foo);

    void updateFoo(Foo foo);

}

Kotlin

// the service interface that we want to make transactional

package x.y.service

interface FooService {

    fun getFoo(fooName: String): Foo

    fun getFoo(fooName: String, barName: String): Foo

    fun insertFoo(foo: Foo)

    fun updateFoo(foo: Foo)
}

The following example shows an implementation of the preceding interface:

Java

package x.y.service;

public class DefaultFooService implements FooService {

    @Override
    public Foo getFoo(String fooName) {
        // ...
    }

    @Override
    public Foo getFoo(String fooName, String barName) {
        // ...
    }

    @Override
    public void insertFoo(Foo foo) {
        // ...
    }

    @Override
    public void updateFoo(Foo foo) {
        // ...
    }
}

Kotlin

package x.y.service

class DefaultFooService : FooService {

    override fun getFoo(fooName: String): Foo {
        // ...
    }

    override fun getFoo(fooName: String, barName: String): Foo {
        // ...
    }

    override fun insertFoo(foo: Foo) {
        // ...
    }

    override fun updateFoo(foo: Foo) {
        // ...
    }
}

Assume that the first two methods of the FooService interface, getFoo(String) and getFoo(String, String), must execute in the context of a transaction with read-only semantics, and that the other methods, insertFoo(Foo) and updateFoo(Foo), must execute in the context of a transaction with read-write semantics. The following configuration is explained in detail in the next few paragraphs:

<!-- from the file 'context.xml' -->
<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
    xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
    xmlns:aop="http://www.springframework.org/schema/aop"
    xmlns:tx="http://www.springframework.org/schema/tx"
    xsi:schemaLocation="
        http://www.springframework.org/schema/beans
        https://www.springframework.org/schema/beans/spring-beans.xsd
        http://www.springframework.org/schema/tx
        https://www.springframework.org/schema/tx/spring-tx.xsd
        http://www.springframework.org/schema/aop
        https://www.springframework.org/schema/aop/spring-aop.xsd">

    <!-- this is the service object that we want to make transactional -->
    <bean id="fooService" class="x.y.service.DefaultFooService"/>

    <!-- the transactional advice (what 'happens'; see the <aop:advisor/> bean below) -->
    <tx:advice id="txAdvice" transaction-manager="txManager">
        <!-- the transactional semantics... -->
        <tx:attributes>
            <!-- all methods starting with 'get' are read-only -->
            <tx:method name="get*" read-only="true"/>
            <!-- other methods use the default transaction settings (see below) -->
            <tx:method name="*"/>
        </tx:attributes>
    </tx:advice>

    <!-- ensure that the above transactional advice runs for any execution
        of an operation defined by the FooService interface -->
    <aop:config>
        <aop:pointcut id="fooServiceOperation" expression="execution(* x.y.service.FooService.*(..))"/>
        <aop:advisor advice-ref="txAdvice" pointcut-ref="fooServiceOperation"/>
    </aop:config>

    <!-- don't forget the DataSource -->
    <bean id="dataSource" class="org.apache.commons.dbcp.BasicDataSource" destroy-method="close">
        <property name="driverClassName" value="oracle.jdbc.driver.OracleDriver"/>
        <property name="url" value="jdbc:oracle:thin:@rj-t42:1521:elvis"/>
        <property name="username" value="scott"/>
        <property name="password" value="tiger"/>
    </bean>

    <!-- similarly, don't forget the PlatformTransactionManager -->
    <bean id="txManager" class="org.springframework.jdbc.datasource.DataSourceTransactionManager">
        <property name="dataSource" ref="dataSource"/>
    </bean>

    <!-- other <bean/> definitions here -->

</beans>

Examine the preceding configuration. It assumes that you want to make a service object, the fooService bean, transactional. The transaction semantics to apply are encapsulated in the <tx:advice/> definition. The <tx:advice/> definition reads as “all methods, on starting with get, are to execute in the context of a read-only transaction, and all other methods are to execute with the default transaction semantics”. The transaction-manager attribute of the <tx:advice/> tag is set to the name of the PlatformTransactionManager bean that is going to drive the transactions (in this case, the txManager bean).

Tip

You can omit the transaction-manager attribute in the transactional advice (<tx:advice/>) if the bean name of the PlatformTransactionManager that you want to wire in has the name transactionManager. If the PlatformTransactionManager bean that you want to wire in has any other name, you must use the transaction-manager attribute explicitly, as in the preceding example.

The <aop:config/> definition ensures that the transactional advice defined by the txAdvice bean executes at the appropriate points in the program. First, you define a pointcut that matches the execution of any operation defined in the FooService interface (fooServiceOperation). Then you associate the pointcut with the txAdvice by using an advisor. The result indicates that, at the execution of a fooServiceOperation, the advice defined by txAdvice is run.

The expression defined within the <aop:pointcut/> element is an AspectJ pointcut expression. See the AOP section for more details on pointcut expressions in Spring.

A common requirement is to make an entire service layer transactional. The best way to do this is to change the pointcut expression to match any operation in your service layer. The following example shows how to do so:

<aop:config>
    <aop:pointcut id="fooServiceMethods" expression="execution(* x.y.service.*.*(..))"/>
    <aop:advisor advice-ref="txAdvice" pointcut-ref="fooServiceMethods"/>
</aop:config>

Note	In the preceding example, it is assumed that all your service interfaces are defined in the `x.y.service` package. See the AOP section for more details.

Now that we have analyzed the configuration, you may be asking yourself, “What does all this configuration actually do?”

The configuration shown earlier is used to create a transactional proxy around the object that is created from the fooService bean definition. The proxy is configured with the transactional advice so that, when an appropriate method is invoked on the proxy, a transaction is started, suspended, marked as read-only, and so on, depending on the transaction configuration associated with that method. Consider the following program that test drives the configuration shown earlier:

Java

public final class Boot {

    public static void main(final String[] args) throws Exception {
        ApplicationContext ctx = new ClassPathXmlApplicationContext("context.xml", Boot.class);
        FooService fooService = (FooService) ctx.getBean("fooService");
        fooService.insertFoo (new Foo());
    }
}

Kotlin

import org.springframework.beans.factory.getBean

fun main() {
    val ctx = ClassPathXmlApplicationContext("context.xml")
    val fooService = ctx.getBean<FooService>("fooService")
    fooService.insertFoo(Foo())
}

The output from running the preceding program should resemble the following (the Log4J output and the stack trace from the UnsupportedOperationException thrown by the insertFoo(..) method of the DefaultFooService class have been truncated for clarity):

<!-- the Spring container is starting up... -->
[AspectJInvocationContextExposingAdvisorAutoProxyCreator] - Creating implicit proxy for bean 'fooService' with 0 common interceptors and 1 specific interceptors

<!-- the DefaultFooService is actually proxied -->
[JdkDynamicAopProxy] - Creating JDK dynamic proxy for [x.y.service.DefaultFooService]

<!-- ... the insertFoo(..) method is now being invoked on the proxy -->
[TransactionInterceptor] - Getting transaction for x.y.service.FooService.insertFoo

<!-- the transactional advice kicks in here... -->
[DataSourceTransactionManager] - Creating new transaction with name [x.y.service.FooService.insertFoo]
[DataSourceTransactionManager] - Acquired Connection [org.apache.commons.dbcp.PoolableConnection@a53de4] for JDBC transaction

<!-- the insertFoo(..) method from DefaultFooService throws an exception... -->
[RuleBasedTransactionAttribute] - Applying rules to determine whether transaction should rollback on java.lang.UnsupportedOperationException
[TransactionInterceptor] - Invoking rollback for transaction on x.y.service.FooService.insertFoo due to throwable [java.lang.UnsupportedOperationException]

<!-- and the transaction is rolled back (by default, RuntimeException instances cause rollback) -->
[DataSourceTransactionManager] - Rolling back JDBC transaction on Connection [org.apache.commons.dbcp.PoolableConnection@a53de4]
[DataSourceTransactionManager] - Releasing JDBC Connection after transaction
[DataSourceUtils] - Returning JDBC Connection to DataSource

Exception in thread "main" java.lang.UnsupportedOperationException at x.y.service.DefaultFooService.insertFoo(DefaultFooService.java:14)
<!-- AOP infrastructure stack trace elements removed for clarity -->
at $Proxy0.insertFoo(Unknown Source)
at Boot.main(Boot.java:11)

Rolling Back a Declarative Transaction

The previous section outlined the basics of how to specify transactional settings for classes, typically service layer classes, declaratively in your application. This section describes how you can control the rollback of transactions in a simple, declarative fashion.

The recommended way to indicate to the Spring Framework’s transaction infrastructure that a transaction’s work is to be rolled back is to throw an Exception from code that is currently executing in the context of a transaction. The Spring Framework’s transaction infrastructure code catches any unhandled Exception as it bubbles up the call stack and makes a determination whether to mark the transaction for rollback.

In its default configuration, the Spring Framework’s transaction infrastructure code marks a transaction for rollback only in the case of runtime, unchecked exceptions. That is, when the thrown exception is an instance or subclass of RuntimeException. ( Error instances also, by default, result in a rollback). Checked exceptions that are thrown from a transactional method do not result in rollback in the default configuration.

You can configure exactly which Exception types mark a transaction for rollback, including checked exceptions. The following XML snippet demonstrates how you configure rollback for a checked, application-specific Exception type:

<tx:advice id="txAdvice" transaction-manager="txManager">
    <tx:attributes>
    <tx:method name="get*" read-only="true" rollback-for="NoProductInStockException"/>
    <tx:method name="*"/>
    </tx:attributes>
</tx:advice>

If you do not want a transaction rolled back when an exception is thrown, you can also specify 'no rollback rules'. The following example tells the Spring Framework’s transaction infrastructure to commit the attendant transaction even in the face of an unhandled InstrumentNotFoundException:

<tx:advice id="txAdvice">
    <tx:attributes>
    <tx:method name="updateStock" no-rollback-for="InstrumentNotFoundException"/>
    <tx:method name="*"/>
    </tx:attributes>
</tx:advice>

When the Spring Framework’s transaction infrastructure catches an exception and it consults the configured rollback rules to determine whether to mark the transaction for rollback, the strongest matching rule wins. So, in the case of the following configuration, any exception other than an InstrumentNotFoundException results in a rollback of the attendant transaction:

<tx:advice id="txAdvice">
    <tx:attributes>
    <tx:method name="*" rollback-for="Throwable" no-rollback-for="InstrumentNotFoundException"/>
    </tx:attributes>
</tx:advice>

You can also indicate a required rollback programmatically. Although simple, this process is quite invasive and tightly couples your code to the Spring Framework’s transaction infrastructure. The following example shows how to programmatically indicate a required rollback:

Java

public void resolvePosition() {
    try {
        // some business logic...
    } catch (NoProductInStockException ex) {
        // trigger rollback programmatically
        TransactionAspectSupport.currentTransactionStatus().setRollbackOnly();
    }
}

Kotlin

fun resolvePosition() {
    try {
        // some business logic...
    } catch (ex: NoProductInStockException) {
        // trigger rollback programmatically
        TransactionAspectSupport.currentTransactionStatus().setRollbackOnly();
    }
}

You are strongly encouraged to use the declarative approach to rollback, if at all possible. Programmatic rollback is available should you absolutely need it, but its usage flies in the face of achieving a clean POJO-based architecture.

Configuring Different Transactional Semantics for Different Beans

Consider the scenario where you have a number of service layer objects, and you want to apply a totally different transactional configuration to each of them. You can do so by defining distinct <aop:advisor/> elements with differing pointcut and advice-ref attribute values.

As a point of comparison, first assume that all of your service layer classes are defined in a root x.y.service package. To make all beans that are instances of classes defined in that package (or in subpackages) and that have names ending in Service have the default transactional configuration, you could write the following:

<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
    xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
    xmlns:aop="http://www.springframework.org/schema/aop"
    xmlns:tx="http://www.springframework.org/schema/tx"
    xsi:schemaLocation="
        http://www.springframework.org/schema/beans
        https://www.springframework.org/schema/beans/spring-beans.xsd
        http://www.springframework.org/schema/tx
        https://www.springframework.org/schema/tx/spring-tx.xsd
        http://www.springframework.org/schema/aop
        https://www.springframework.org/schema/aop/spring-aop.xsd">

    <aop:config>

        <aop:pointcut id="serviceOperation"
                expression="execution(* x.y.service..*Service.*(..))"/>

        <aop:advisor pointcut-ref="serviceOperation" advice-ref="txAdvice"/>

    </aop:config>

    <!-- these two beans will be transactional... -->
    <bean id="fooService" class="x.y.service.DefaultFooService"/>
    <bean id="barService" class="x.y.service.extras.SimpleBarService"/>

    <!-- ... and these two beans won't -->
    <bean id="anotherService" class="org.xyz.SomeService"/> <!-- (not in the right package) -->
    <bean id="barManager" class="x.y.service.SimpleBarManager"/> <!-- (doesn't end in 'Service') -->

    <tx:advice id="txAdvice">
        <tx:attributes>
            <tx:method name="get*" read-only="true"/>
            <tx:method name="*"/>
        </tx:attributes>
    </tx:advice>

    <!-- other transaction infrastructure beans such as a PlatformTransactionManager omitted... -->

</beans>

The following example shows how to configure two distinct beans with totally different transactional settings:

<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
    xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
    xmlns:aop="http://www.springframework.org/schema/aop"
    xmlns:tx="http://www.springframework.org/schema/tx"
    xsi:schemaLocation="
        http://www.springframework.org/schema/beans
        https://www.springframework.org/schema/beans/spring-beans.xsd
        http://www.springframework.org/schema/tx
        https://www.springframework.org/schema/tx/spring-tx.xsd
        http://www.springframework.org/schema/aop
        https://www.springframework.org/schema/aop/spring-aop.xsd">

    <aop:config>

        <aop:pointcut id="defaultServiceOperation"
                expression="execution(* x.y.service.*Service.*(..))"/>

        <aop:pointcut id="noTxServiceOperation"
                expression="execution(* x.y.service.ddl.DefaultDdlManager.*(..))"/>

        <aop:advisor pointcut-ref="defaultServiceOperation" advice-ref="defaultTxAdvice"/>

        <aop:advisor pointcut-ref="noTxServiceOperation" advice-ref="noTxAdvice"/>

    </aop:config>

    <!-- this bean will be transactional (see the 'defaultServiceOperation' pointcut) -->
    <bean id="fooService" class="x.y.service.DefaultFooService"/>

    <!-- this bean will also be transactional, but with totally different transactional settings -->
    <bean id="anotherFooService" class="x.y.service.ddl.DefaultDdlManager"/>

    <tx:advice id="defaultTxAdvice">
        <tx:attributes>
            <tx:method name="get*" read-only="true"/>
            <tx:method name="*"/>
        </tx:attributes>
    </tx:advice>

    <tx:advice id="noTxAdvice">
        <tx:attributes>
            <tx:method name="*" propagation="NEVER"/>
        </tx:attributes>
    </tx:advice>

    <!-- other transaction infrastructure beans such as a PlatformTransactionManager omitted... -->

</beans>

<tx:advice/> Settings

This section summarizes the various transactional settings that you can specify by using the <tx:advice/> tag. The default <tx:advice/> settings are:

The propagation setting is REQUIRED.
The isolation level is DEFAULT.
The transaction is read-write.
The transaction timeout defaults to the default timeout of the underlying transaction system or none if timeouts are not supported.
Any RuntimeException triggers rollback, and any checked Exception does not.

You can change these default settings. The following table summarizes the various attributes of the <tx:method/> tags that are nested within <tx:advice/> and <tx:attributes/> tags:

Table 1. <tx:method/> settings

Attribute	Required?	Default	Description
`name`	Yes		Method names with which the transaction attributes are to be associated. The wildcard () character can be used to associate the same transaction attribute settings with a number of methods (for example, `get`, `handle`, `onEvent`, and so forth).
`propagation`	No	`REQUIRED`	Transaction propagation behavior.
`isolation`	No	`DEFAULT`	Transaction isolation level. Only applicable to propagation settings of `REQUIRED` or `REQUIRES_NEW`.
`timeout`	No	-1	Transaction timeout (seconds). Only applicable to propagation `REQUIRED` or `REQUIRES_NEW`.
`read-only`	No	false	Read-write versus read-only transaction. Applies only to `REQUIRED` or `REQUIRES_NEW`.
`rollback-for`	No		Comma-delimited list of `Exception` instances that trigger rollback. For example, `com.foo.MyBusinessException,ServletException.`
`no-rollback-for`	No		Comma-delimited list of `Exception` instances that do not trigger rollback. For example, `com.foo.MyBusinessException,ServletException.`

Using `@Transactional`

In addition to the XML-based declarative approach to transaction configuration, you can use an annotation-based approach. Declaring transaction semantics directly in the Java source code puts the declarations much closer to the affected code. There is not much danger of undue coupling, because code that is meant to be used transactionally is almost always deployed that way anyway.

Note	The standard `javax.transaction.Transactional` annotation is also supported as a drop-in replacement to Spring’s own annotation. Please refer to JTA 1.2 documentation for more details.

The ease-of-use afforded by the use of the @Transactional annotation is best illustrated with an example, which is explained in the text that follows. Consider the following class definition:

Java

// the service class that we want to make transactional
@Transactional
public class DefaultFooService implements FooService {

    Foo getFoo(String fooName) {
        // ...
    }

    Foo getFoo(String fooName, String barName) {
        // ...
    }

    void insertFoo(Foo foo) {
        // ...
    }

    void updateFoo(Foo foo) {
        // ...
    }
}

Kotlin

// the service class that we want to make transactional
@Transactional
class DefaultFooService : FooService {

    override fun getFoo(fooName: String): Foo {
        // ...
    }

    override fun getFoo(fooName: String, barName: String): Foo {
        // ...
    }

    override fun insertFoo(foo: Foo) {
        // ...
    }

    override fun updateFoo(foo: Foo) {
        // ...
    }
}

Used at the class level as above, the annotation indicates a default for all methods of the declaring class (as well as its subclasses). Alternatively, each method can get annotated individually. Note that a class-level annotation does not apply to ancestor classes up the class hierarchy; in such a scenario, methods need to be locally redeclared in order to participate in a subclass-level annotation.

When a POJO class such as the one above is defined as a bean in a Spring context, you can make the bean instance transactional through an @EnableTransactionManagement annotation in a @Configuration class. See the javadoc for full details.

In XML configuration, the <tx:annotation-driven/> tag provides similar convenience:

<!-- from the file 'context.xml' -->
<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
    xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
    xmlns:aop="http://www.springframework.org/schema/aop"
    xmlns:tx="http://www.springframework.org/schema/tx"
    xsi:schemaLocation="
        http://www.springframework.org/schema/beans
        https://www.springframework.org/schema/beans/spring-beans.xsd
        http://www.springframework.org/schema/tx
        https://www.springframework.org/schema/tx/spring-tx.xsd
        http://www.springframework.org/schema/aop
        https://www.springframework.org/schema/aop/spring-aop.xsd">

    <!-- this is the service object that we want to make transactional -->
    <bean id="fooService" class="x.y.service.DefaultFooService"/>

    <!-- enable the configuration of transactional behavior based on annotations -->
    <tx:annotation-driven transaction-manager="txManager"/><!-- a PlatformTransactionManager is still required --> (1)

    <bean id="txManager" class="org.springframework.jdbc.datasource.DataSourceTransactionManager">
        <!-- (this dependency is defined somewhere else) -->
        <property name="dataSource" ref="dataSource"/>
    </bean>

    <!-- other <bean/> definitions here -->

</beans>

The line that makes the bean instance transactional.

Tip

You can omit the transaction-manager attribute in the <tx:annotation-driven/> tag if the bean name of the PlatformTransactionManager that you want to wire in has the name, transactionManager. If the PlatformTransactionManager bean that you want to dependency-inject has any other name, you have to use the transaction-manager attribute, as in the preceding example.

Method visibility and @Transactional

When you use proxies, you should apply the @Transactional annotation only to methods with public visibility. If you do annotate protected, private or package-visible methods with the @Transactional annotation, no error is raised, but the annotated method does not exhibit the configured transactional settings. If you need to annotate non-public methods, consider using AspectJ (described later).

You can apply the @Transactional annotation to an interface definition, a method on an interface, a class definition, or a public method on a class. However, the mere presence of the @Transactional annotation is not enough to activate the transactional behavior. The @Transactional annotation is merely metadata that can be consumed by some runtime infrastructure that is @Transactional-aware and that can use the metadata to configure the appropriate beans with transactional behavior. In the preceding example, the <tx:annotation-driven/> element switches on the transactional behavior.

Tip

The Spring team recommends that you annotate only concrete classes (and methods of concrete classes) with the @Transactional annotation, as opposed to annotating interfaces. You certainly can place the @Transactional annotation on an interface (or an interface method), but this works only as you would expect it to if you use interface-based proxies. The fact that Java annotations are not inherited from interfaces means that, if you use class-based proxies (proxy-target-class="true") or the weaving-based aspect (mode="aspectj"), the transaction settings are not recognized by the proxying and weaving infrastructure, and the object is not wrapped in a transactional proxy.

Note

In proxy mode (which is the default), only external method calls coming in through the proxy are intercepted. This means that self-invocation (in effect, a method within the target object calling another method of the target object) does not lead to an actual transaction at runtime even if the invoked method is marked with @Transactional. Also, the proxy must be fully initialized to provide the expected behavior, so you should not rely on this feature in your initialization code (that is, @PostConstruct).

Consider using of AspectJ mode (see the mode attribute in the following table) if you expect self-invocations to be wrapped with transactions as well. In this case, there no proxy in the first place. Instead, the target class is woven (that is, its byte code is modified) to turn @Transactional into runtime behavior on any kind of method.

Table 2. Annotation driven transaction settings

XML Attribute	Annotation Attribute	Default	Description
`transaction-manager`	N/A (see `TransactionManagementConfigurer` javadoc)	`transactionManager`	Name of the transaction manager to use. Required only if the name of the transaction manager is not `transactionManager`, as in the preceding example.
`mode`	`mode`	`proxy`	The default mode (`proxy`) processes annotated beans to be proxied by using Spring’s AOP framework (following proxy semantics, as discussed earlier, applying to method calls coming in through the proxy only). The alternative mode (`aspectj`) instead weaves the affected classes with Spring’s AspectJ transaction aspect, modifying the target class byte code to apply to any kind of method call. AspectJ weaving requires `spring-aspects.jar` in the classpath as well as having load-time weaving (or compile-time weaving) enabled. (See Spring configuration for details on how to set up load-time weaving.)
`proxy-target-class`	`proxyTargetClass`	`false`	Applies to `proxy` mode only. Controls what type of transactional proxies are created for classes annotated with the `@Transactional` annotation. If the `proxy-target-class` attribute is set to `true`, class-based proxies are created. If `proxy-target-class` is `false` or if the attribute is omitted, then standard JDK interface-based proxies are created. (See Proxying Mechanisms for a detailed examination of the different proxy types.)
`order`	`order`	`Ordered.LOWEST_PRECEDENCE`	Defines the order of the transaction advice that is applied to beans annotated with `@Transactional`. (For more information about the rules related to ordering of AOP advice, see Advice Ordering.) No specified ordering means that the AOP subsystem determines the order of the advice.

Note

The default advice mode for processing @Transactional annotations is proxy, which allows for interception of calls through the proxy only. Local calls within the same class cannot get intercepted that way. For a more advanced mode of interception, consider switching to aspectj mode in combination with compile-time or load-time weaving.

Note

The proxy-target-class attribute controls what type of transactional proxies are created for classes annotated with the @Transactional annotation. If proxy-target-class is set to true, class-based proxies are created. If proxy-target-class is false or if the attribute is omitted, standard JDK interface-based proxies are created. (See [aop-proxying] for a discussion of the different proxy types.)

Note

@EnableTransactionManagement and <tx:annotation-driven/> looks for @Transactional only on beans in the same application context in which they are defined. This means that, if you put annotation-driven configuration in a WebApplicationContext for a DispatcherServlet, it checks for @Transactional beans only in your controllers and not your services. See MVC for more information.

The most derived location takes precedence when evaluating the transactional settings for a method. In the case of the following example, the DefaultFooService class is annotated at the class level with the settings for a read-only transaction, but the @Transactional annotation on the updateFoo(Foo) method in the same class takes precedence over the transactional settings defined at the class level.

Java

@Transactional(readOnly = true)
public class DefaultFooService implements FooService {

    public Foo getFoo(String fooName) {
        // ...
    }

    // these settings have precedence for this method
    @Transactional(readOnly = false, propagation = Propagation.REQUIRES_NEW)
    public void updateFoo(Foo foo) {
        // ...
    }
}

Kotlin

@Transactional(readOnly = true)
class DefaultFooService : FooService {

    override fun getFoo(fooName: String): Foo {
        // ...
    }

    // these settings have precedence for this method
    @Transactional(readOnly = false, propagation = Propagation.REQUIRES_NEW)
    override fun updateFoo(foo: Foo) {
        // ...
    }
}

`@Transactional` Settings

The @Transactional annotation is metadata that specifies that an interface, class, or method must have transactional semantics (for example, “start a brand new read-only transaction when this method is invoked, suspending any existing transaction”). The default @Transactional settings are as follows:

The propagation setting is PROPAGATION_REQUIRED.
The isolation level is ISOLATION_DEFAULT.
The transaction is read-write.
The transaction timeout defaults to the default timeout of the underlying transaction system, or to none if timeouts are not supported.
Any RuntimeException triggers rollback, and any checked Exception does not.

You can change these default settings. The following table summarizes the various properties of the @Transactional annotation:

Table 3. @Transactional Settings

Property	Type	Description
value	`String`	Optional qualifier that specifies the transaction manager to be used.
propagation	`enum`: `Propagation`	Optional propagation setting.
`isolation`	`enum`: `Isolation`	Optional isolation level. Applies only to propagation values of `REQUIRED` or `REQUIRES_NEW`.
`timeout`	`int` (in seconds of granularity)	Optional transaction timeout. Applies only to propagation values of `REQUIRED` or `REQUIRES_NEW`.
`readOnly`	`boolean`	Read-write versus read-only transaction. Only applicable to values of `REQUIRED` or `REQUIRES_NEW`.
`rollbackFor`	Array of `Class` objects, which must be derived from `Throwable.`	Optional array of exception classes that must cause rollback.
`rollbackForClassName`	Array of class names. The classes must be derived from `Throwable.`	Optional array of names of exception classes that must cause rollback.
`noRollbackFor`	Array of `Class` objects, which must be derived from `Throwable.`	Optional array of exception classes that must not cause rollback.
`noRollbackForClassName`	Array of `String` class names, which must be derived from `Throwable.`	Optional array of names of exception classes that must not cause rollback.

Currently, you cannot have explicit control over the name of a transaction, where 'name' means the transaction name that appears in a transaction monitor, if applicable (for example, WebLogic’s transaction monitor), and in logging output. For declarative transactions, the transaction name is always the fully-qualified class name + . + the method name of the transactionally advised class. For example, if the handlePayment(..) method of the BusinessService class started a transaction, the name of the transaction would be: com.example.BusinessService.handlePayment.

Multiple Transaction Managers with `@Transactional`

Most Spring applications need only a single transaction manager, but there may be situations where you want multiple independent transaction managers in a single application. You can use the value attribute of the @Transactional annotation to optionally specify the identity of the PlatformTransactionManager to be used. This can either be the bean name or the qualifier value of the transaction manager bean. For example, using the qualifier notation, you can combine the following Java code with the following transaction manager bean declarations in the application context:

Java

public class TransactionalService {

    @Transactional("order")
    public void setSomething(String name) { ... }

    @Transactional("account")
    public void doSomething() { ... }
}

Kotlin

class TransactionalService {

    @Transactional("order")
    fun setSomething(name: String) {
        // ...
    }

    @Transactional("account")
    fun doSomething() {
        // ...
    }
}

The following listing shows the bean declarations:

<tx:annotation-driven/>

    <bean id="transactionManager1" class="org.springframework.jdbc.datasource.DataSourceTransactionManager">
        ...
        <qualifier value="order"/>
    </bean>

    <bean id="transactionManager2" class="org.springframework.jdbc.datasource.DataSourceTransactionManager">
        ...
        <qualifier value="account"/>
    </bean>

In this case, the two methods on TransactionalService run under separate transaction managers, differentiated by the order and account qualifiers. The default <tx:annotation-driven> target bean name, transactionManager, is still used if no specifically qualified PlatformTransactionManager bean is found.

Custom Shortcut Annotations

If you find you repeatedly use the same attributes with @Transactional on many different methods, Spring’s meta-annotation support lets you define custom shortcut annotations for your specific use cases. For example, consider the following annotation definitions:

Java

@Target({ElementType.METHOD, ElementType.TYPE})
@Retention(RetentionPolicy.RUNTIME)
@Transactional("order")
public @interface OrderTx {
}

@Target({ElementType.METHOD, ElementType.TYPE})
@Retention(RetentionPolicy.RUNTIME)
@Transactional("account")
public @interface AccountTx {
}

Kotlin

@Target(AnnotationTarget.FUNCTION, AnnotationTarget.TYPE)
@Retention(AnnotationRetention.RUNTIME)
@Transactional("order")
annotation class OrderTx

@Target(AnnotationTarget.FUNCTION, AnnotationTarget.TYPE)
@Retention(AnnotationRetention.RUNTIME)
@Transactional("account")
annotation class AccountTx

The preceding annotations lets us write the example from the previous section as follows:

Java

public class TransactionalService {

    @OrderTx
    public void setSomething(String name) {
        // ...
    }

    @AccountTx
    public void doSomething() {
        // ...
    }
}

Kotlin

class TransactionalService {

    @OrderTx
    fun setSomething(name: String) {
        // ...
    }

    @AccountTx
    fun doSomething() {
        // ...
    }
}

In the preceding example, we used the syntax to define the transaction manager qualifier, but we could also have included propagation behavior, rollback rules, timeouts, and other features.

Transaction Propagation

This section describes some semantics of transaction propagation in Spring. Note that this section is not an introduction to transaction propagation proper. Rather, it details some of the semantics regarding transaction propagation in Spring.

In Spring-managed transactions, be aware of the difference between physical and logical transactions, and how the propagation setting applies to this difference.

Understanding `PROPAGATION_REQUIRED`

PROPAGATION_REQUIRED enforces a physical transaction, either locally for the current scope if no transaction exists yet or participating in an existing 'outer' transaction defined for a larger scope. This is a fine default in common call stack arrangements within the same thread (for example, a service facade that delegates to several repository methods where all the underlying resources have to participate in the service-level transaction).

Note

By default, a participating transaction joins the characteristics of the outer scope, silently ignoring the local isolation level, timeout value, or read-only flag (if any). Consider switching the validateExistingTransactions flag to true on your transaction manager if you want isolation level declarations to be rejected when participating in an existing transaction with a different isolation level. This non-lenient mode also rejects read-only mismatches (that is, an inner read-write transaction that tries to participate in a read-only outer scope).

When the propagation setting is PROPAGATION_REQUIRED, a logical transaction scope is created for each method upon which the setting is applied. Each such logical transaction scope can determine rollback-only status individually, with an outer transaction scope being logically independent from the inner transaction scope. In the case of standard PROPAGATION_REQUIRED behavior, all these scopes are mapped to the same physical transaction. So a rollback-only marker set in the inner transaction scope does affect the outer transaction’s chance to actually commit.

However, in the case where an inner transaction scope sets the rollback-only marker, the outer transaction has not decided on the rollback itself, so the rollback (silently triggered by the inner transaction scope) is unexpected. A corresponding UnexpectedRollbackException is thrown at that point. This is expected behavior so that the caller of a transaction can never be misled to assume that a commit was performed when it really was not. So, if an inner transaction (of which the outer caller is not aware) silently marks a transaction as rollback-only, the outer caller still calls commit. The outer caller needs to receive an UnexpectedRollbackException to indicate clearly that a rollback was performed instead.

Understanding `PROPAGATION_REQUIRES_NEW`

PROPAGATION_REQUIRES_NEW, in contrast to PROPAGATION_REQUIRED, always uses an independent physical transaction for each affected transaction scope, never participating in an existing transaction for an outer scope. In such an arrangement, the underlying resource transactions are different and, hence, can commit or roll back independently, with an outer transaction not affected by an inner transaction’s rollback status and with an inner transaction’s locks released immediately after its completion. Such an independent inner transaction can also declare its own isolation level, timeout, and read-only settings and not inherit an outer transaction’s characteristics.

Understanding `PROPAGATION_NESTED`

PROPAGATION_NESTED uses a single physical transaction with multiple savepoints that it can roll back to. Such partial rollbacks let an inner transaction scope trigger a rollback for its scope, with the outer transaction being able to continue the physical transaction despite some operations having been rolled back. This setting is typically mapped onto JDBC savepoints, so it works only with JDBC resource transactions. See Spring’s DataSourceTransactionManager.

Advising Transactional Operations

Suppose you want to execute both transactional operations and some basic profiling advice. How do you effect this in the context of <tx:annotation-driven/>?

When you invoke the updateFoo(Foo) method, you want to see the following actions:

The configured profiling aspect starts.
The transactional advice executes.
The method on the advised object executes.
The transaction commits.
The profiling aspect reports the exact duration of the whole transactional method invocation.

Note	This chapter is not concerned with explaining AOP in any great detail (except as it applies to transactions). See AOP for detailed coverage of the AOP configuration and AOP in general.

The following code shows the simple profiling aspect discussed earlier:

Java

package x.y;

import org.aspectj.lang.ProceedingJoinPoint;
import org.springframework.util.StopWatch;
import org.springframework.core.Ordered;

public class SimpleProfiler implements Ordered {

    private int order;

    // allows us to control the ordering of advice
    public int getOrder() {
        return this.order;
    }

    public void setOrder(int order) {
        this.order = order;
    }

    // this method is the around advice
    public Object profile(ProceedingJoinPoint call) throws Throwable {
        Object returnValue;
        StopWatch clock = new StopWatch(getClass().getName());
        try {
            clock.start(call.toShortString());
            returnValue = call.proceed();
        } finally {
            clock.stop();
            System.out.println(clock.prettyPrint());
        }
        return returnValue;
    }
}

Kotlin

class SimpleProfiler : Ordered {

    private var order: Int = 0

    // allows us to control the ordering of advice
    override fun getOrder(): Int {
        return this.order
    }

    fun setOrder(order: Int) {
        this.order = order
    }

    // this method is the around advice
    fun profile(call: ProceedingJoinPoint): Any {
        var returnValue: Any
        val clock = StopWatch(javaClass.name)
        try {
            clock.start(call.toShortString())
            returnValue = call.proceed()
        } finally {
            clock.stop()
            println(clock.prettyPrint())
        }
        return returnValue
    }
}

The ordering of advice is controlled through the Ordered interface. For full details on advice ordering, see Advice ordering.

The following configuration creates a fooService bean that has profiling and transactional aspects applied to it in the desired order:

<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
    xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
    xmlns:aop="http://www.springframework.org/schema/aop"
    xmlns:tx="http://www.springframework.org/schema/tx"
    xsi:schemaLocation="
        http://www.springframework.org/schema/beans
        https://www.springframework.org/schema/beans/spring-beans.xsd
        http://www.springframework.org/schema/tx
        https://www.springframework.org/schema/tx/spring-tx.xsd
        http://www.springframework.org/schema/aop
        https://www.springframework.org/schema/aop/spring-aop.xsd">

    <bean id="fooService" class="x.y.service.DefaultFooService"/>

    <!-- this is the aspect -->
    <bean id="profiler" class="x.y.SimpleProfiler">
        <!-- execute before the transactional advice (hence the lower order number) -->
        <property name="order" value="1"/>
    </bean>

    <tx:annotation-driven transaction-manager="txManager" order="200"/>

    <aop:config>
            <!-- this advice will execute around the transactional advice -->
            <aop:aspect id="profilingAspect" ref="profiler">
                <aop:pointcut id="serviceMethodWithReturnValue"
                        expression="execution(!void x.y..*Service.*(..))"/>
                <aop:around method="profile" pointcut-ref="serviceMethodWithReturnValue"/>
            </aop:aspect>
    </aop:config>

    <bean id="dataSource" class="org.apache.commons.dbcp.BasicDataSource" destroy-method="close">
        <property name="driverClassName" value="oracle.jdbc.driver.OracleDriver"/>
        <property name="url" value="jdbc:oracle:thin:@rj-t42:1521:elvis"/>
        <property name="username" value="scott"/>
        <property name="password" value="tiger"/>
    </bean>

    <bean id="txManager" class="org.springframework.jdbc.datasource.DataSourceTransactionManager">
        <property name="dataSource" ref="dataSource"/>
    </bean>

</beans>

You can configure any number of additional aspects in similar fashion.

The following example creates the same setup as the previous two examples but uses the purely XML declarative approach:

<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
    xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
    xmlns:aop="http://www.springframework.org/schema/aop"
    xmlns:tx="http://www.springframework.org/schema/tx"
    xsi:schemaLocation="
        http://www.springframework.org/schema/beans
        https://www.springframework.org/schema/beans/spring-beans.xsd
        http://www.springframework.org/schema/tx
        https://www.springframework.org/schema/tx/spring-tx.xsd
        http://www.springframework.org/schema/aop
        https://www.springframework.org/schema/aop/spring-aop.xsd">

    <bean id="fooService" class="x.y.service.DefaultFooService"/>

    <!-- the profiling advice -->
    <bean id="profiler" class="x.y.SimpleProfiler">
        <!-- execute before the transactional advice (hence the lower order number) -->
        <property name="order" value="1"/>
    </bean>

    <aop:config>
        <aop:pointcut id="entryPointMethod" expression="execution(* x.y..*Service.*(..))"/>
        <!-- will execute after the profiling advice (c.f. the order attribute) -->

        <aop:advisor advice-ref="txAdvice" pointcut-ref="entryPointMethod" order="2"/>
        <!-- order value is higher than the profiling aspect -->

        <aop:aspect id="profilingAspect" ref="profiler">
            <aop:pointcut id="serviceMethodWithReturnValue"
                    expression="execution(!void x.y..*Service.*(..))"/>
            <aop:around method="profile" pointcut-ref="serviceMethodWithReturnValue"/>
        </aop:aspect>

    </aop:config>

    <tx:advice id="txAdvice" transaction-manager="txManager">
        <tx:attributes>
            <tx:method name="get*" read-only="true"/>
            <tx:method name="*"/>
        </tx:attributes>
    </tx:advice>

    <!-- other <bean/> definitions such as a DataSource and a PlatformTransactionManager here -->

</beans>

The result of the preceding configuration is a fooService bean that has profiling and transactional aspects applied to it in that order. If you want the profiling advice to execute after the transactional advice on the way in and before the transactional advice on the way out, you can swap the value of the profiling aspect bean’s order property so that it is higher than the transactional advice’s order value.

You can configure additional aspects in similar fashion.

Using `@Transactional` with AspectJ

You can also use the Spring Framework’s @Transactional support outside of a Spring container by means of an AspectJ aspect. To do so, first annotate your classes (and optionally your classes' methods) with the @Transactional annotation, and then link (weave) your application with the org.springframework.transaction.aspectj.AnnotationTransactionAspect defined in the spring-aspects.jar file. You must also configure The aspect with a transaction manager. You can use the Spring Framework’s IoC container to take care of dependency-injecting the aspect. The simplest way to configure the transaction management aspect is to use the <tx:annotation-driven/> element and specify the mode attribute to aspectj as described in Using @Transactional. Because we focus here on applications that run outside of a Spring container, we show you how to do it programmatically.

Note	Prior to continuing, you may want to read Using `@Transactional` and AOP respectively.

The following example shows how to create a transaction manager and configure the AnnotationTransactionAspect to use it:

Java

// construct an appropriate transaction manager
DataSourceTransactionManager txManager = new DataSourceTransactionManager(getDataSource());

// configure the AnnotationTransactionAspect to use it; this must be done before executing any transactional methods
AnnotationTransactionAspect.aspectOf().setTransactionManager(txManager);

Kotlin

// construct an appropriate transaction manager
val txManager = DataSourceTransactionManager(getDataSource())

// configure the AnnotationTransactionAspect to use it; this must be done before executing any transactional methods
AnnotationTransactionAspect.aspectOf().transactionManager = txManager

Note	When you use this aspect, you must annotate the implementation class (or the methods within that class or both), not the interface (if any) that the class implements. AspectJ follows Java’s rule that annotations on interfaces are not inherited.

The @Transactional annotation on a class specifies the default transaction semantics for the execution of any public method in the class.

The @Transactional annotation on a method within the class overrides the default transaction semantics given by the class annotation (if present). You can annotate any method, regardless of visibility.

To weave your applications with the AnnotationTransactionAspect, you must either build your application with AspectJ (see the AspectJ Development Guide) or use load-time weaving. See Load-time weaving with AspectJ in the Spring Framework for a discussion of load-time weaving with AspectJ.

Programmatic Transaction Management

The Spring Framework provides two means of programmatic transaction management, by using:

The TransactionTemplate.
A PlatformTransactionManager implementation directly.

The Spring team generally recommends the TransactionTemplate for programmatic transaction management. The second approach is similar to using the JTA UserTransaction API, although exception handling is less cumbersome.

Using the `TransactionTemplate`

The TransactionTemplate adopts the same approach as other Spring templates, such as the JdbcTemplate. It uses a callback approach (to free application code from having to do the boilerplate acquisition and release transactional resources) and results in code that is intention driven, in that your code focuses solely on what you want to do.

Note	As the examples that follow show, using the `TransactionTemplate` absolutely couples you to Spring’s transaction infrastructure and APIs. Whether or not programmatic transaction management is suitable for your development needs is a decision that you have to make yourself.

Application code that must execute in a transactional context and that explicitly uses the TransactionTemplate resembles the next example. You, as an application developer, can write a TransactionCallback implementation (typically expressed as an anonymous inner class) that contains the code that you need to execute in the context of a transaction. You can then pass an instance of your custom TransactionCallback to the execute(..) method exposed on the TransactionTemplate. The following example shows how to do so:

Java

public class SimpleService implements Service {

    // single TransactionTemplate shared amongst all methods in this instance
    private final TransactionTemplate transactionTemplate;

    // use constructor-injection to supply the PlatformTransactionManager
    public SimpleService(PlatformTransactionManager transactionManager) {
        this.transactionTemplate = new TransactionTemplate(transactionManager);
    }

    public Object someServiceMethod() {
        return transactionTemplate.execute(new TransactionCallback() {
            // the code in this method executes in a transactional context
            public Object doInTransaction(TransactionStatus status) {
                updateOperation1();
                return resultOfUpdateOperation2();
            }
        });
    }
}

Kotlin

// use constructor-injection to supply the PlatformTransactionManager
class SimpleService(transactionManager: PlatformTransactionManager) : Service {

    // single TransactionTemplate shared amongst all methods in this instance
    private val transactionTemplate = TransactionTemplate(transactionManager)

    fun someServiceMethod() = transactionTemplate.execute<Any?> {
        updateOperation1()
        resultOfUpdateOperation2()
    }
}

If there is no return value, you can use the convenient TransactionCallbackWithoutResult class with an anonymous class, as follows:

Java

transactionTemplate.execute(new TransactionCallbackWithoutResult() {
    protected void doInTransactionWithoutResult(TransactionStatus status) {
        updateOperation1();
        updateOperation2();
    }
});

Kotlin

transactionTemplate.execute(object : TransactionCallbackWithoutResult() {
    override fun doInTransactionWithoutResult(status: TransactionStatus) {
        updateOperation1()
        updateOperation2()
    }
})

Code within the callback can roll the transaction back by calling the setRollbackOnly() method on the supplied TransactionStatus object, as follows:

Java

transactionTemplate.execute(new TransactionCallbackWithoutResult() {

    protected void doInTransactionWithoutResult(TransactionStatus status) {
        try {
            updateOperation1();
            updateOperation2();
        } catch (SomeBusinessException ex) {
            status.setRollbackOnly();
        }
    }
});

Kotlin

transactionTemplate.execute(object : TransactionCallbackWithoutResult() {

    override fun doInTransactionWithoutResult(status: TransactionStatus) {
        try {
            updateOperation1()
            updateOperation2()
        } catch (ex: SomeBusinessException) {
            status.setRollbackOnly()
        }
    }
})

Specifying Transaction Settings

You can specify transaction settings (such as the propagation mode, the isolation level, the timeout, and so forth) on the TransactionTemplate either programmatically or in configuration. By default, TransactionTemplate instances have the default transactional settings. The following example shows the programmatic customization of the transactional settings for a specific TransactionTemplate:

Java

public class SimpleService implements Service {

    private final TransactionTemplate transactionTemplate;

    public SimpleService(PlatformTransactionManager transactionManager) {
        this.transactionTemplate = new TransactionTemplate(transactionManager);

        // the transaction settings can be set here explicitly if so desired
        this.transactionTemplate.setIsolationLevel(TransactionDefinition.ISOLATION_READ_UNCOMMITTED);
        this.transactionTemplate.setTimeout(30); // 30 seconds
        // and so forth...
    }
}

Kotlin

class SimpleService(transactionManager: PlatformTransactionManager) : Service {

    private val transactionTemplate = TransactionTemplate(transactionManager).apply {
        // the transaction settings can be set here explicitly if so desired
        isolationLevel = TransactionDefinition.ISOLATION_READ_UNCOMMITTED
        timeout = 30 // 30 seconds
        // and so forth...
    }
}

The following example defines a TransactionTemplate with some custom transactional settings by using Spring XML configuration:

<bean id="sharedTransactionTemplate"
        class="org.springframework.transaction.support.TransactionTemplate">
    <property name="isolationLevelName" value="ISOLATION_READ_UNCOMMITTED"/>
    <property name="timeout" value="30"/>
</bean>

You can then inject the sharedTransactionTemplate into as many services as are required.

Finally, instances of the TransactionTemplate class are thread-safe, in that instances do not maintain any conversational state. TransactionTemplate instances do, however, maintain configuration state. So, while a number of classes may share a single instance of a TransactionTemplate, if a class needs to use a TransactionTemplate with different settings (for example, a different isolation level), you need to create two distinct TransactionTemplate instances.

Using the `PlatformTransactionManager`

You can also use the org.springframework.transaction.PlatformTransactionManager directly to manage your transaction. To do so, pass the implementation of the PlatformTransactionManager you use to your bean through a bean reference. Then, by using the TransactionDefinition and TransactionStatus objects, you can initiate transactions, roll back, and commit. The following example shows how to do so:

Java

DefaultTransactionDefinition def = new DefaultTransactionDefinition();
// explicitly setting the transaction name is something that can be done only programmatically
def.setName("SomeTxName");
def.setPropagationBehavior(TransactionDefinition.PROPAGATION_REQUIRED);

TransactionStatus status = txManager.getTransaction(def);
try {
    // execute your business logic here
}
catch (MyException ex) {
    txManager.rollback(status);
    throw ex;
}
txManager.commit(status);

Kotlin

val def = DefaultTransactionDefinition()
// explicitly setting the transaction name is something that can be done only programmatically
def.setName("SomeTxName")
def.propagationBehavior = TransactionDefinition.PROPAGATION_REQUIRED

val status = txManager.getTransaction(def)
try {
    // execute your business logic here
} catch (ex: MyException) {
    txManager.rollback(status)
    throw ex
}

txManager.commit(status)

Choosing Between Programmatic and Declarative Transaction Management

Programmatic transaction management is usually a good idea only if you have a small number of transactional operations. For example, if you have a web application that requires transactions only for certain update operations, you may not want to set up transactional proxies by using Spring or any other technology. In this case, using the TransactionTemplate may be a good approach. Being able to set the transaction name explicitly is also something that can be done only by using the programmatic approach to transaction management.

On the other hand, if your application has numerous transactional operations, declarative transaction management is usually worthwhile. It keeps transaction management out of business logic and is not difficult to configure. When using the Spring Framework, rather than EJB CMT, the configuration cost of declarative transaction management is greatly reduced.

Transaction-bound Events

As of Spring 4.2, the listener of an event can be bound to a phase of the transaction. The typical example is to handle the event when the transaction has completed successfully. Doing so lets events be used with more flexibility when the outcome of the current transaction actually matters to the listener.

You can register a regular event listener by using the @EventListener annotation. If you need to bind it to the transaction, use @TransactionalEventListener. When you do so, the listener is bound to the commit phase of the transaction by default.

The next example shows this concept. Assume that a component publishes an order-created event and that we want to define a listener that should only handle that event once the transaction in which it has been published has committed successfully. The following example sets up such an event listener:

Java

@Component
public class MyComponent {

    @TransactionalEventListener
    public void handleOrderCreatedEvent(CreationEvent<Order> creationEvent) {
        // ...
    }
}

Kotlin

@Component
class MyComponent {

    @TransactionalEventListener
    fun handleOrderCreatedEvent(creationEvent: CreationEvent<Order>) {
        // ...
    }
}

The @TransactionalEventListener annotation exposes a phase attribute that lets you customize the phase of the transaction to which the listener should be bound. The valid phases are BEFORE_COMMIT, AFTER_COMMIT (default), AFTER_ROLLBACK, and AFTER_COMPLETION that aggregates the transaction completion (be it a commit or a rollback).

If no transaction is running, the listener is not invoked at all, since we cannot honor the required semantics. You can, however, override that behavior by setting the fallbackExecution attribute of the annotation to true.

Application server-specific integration

Spring’s transaction abstraction is generally application server-agnostic. Additionally, Spring’s JtaTransactionManager class (which can optionally perform a JNDI lookup for the JTA UserTransaction and TransactionManager objects) autodetects the location for the latter object, which varies by application server. Having access to the JTA TransactionManager allows for enhanced transaction semantics — in particular, supporting transaction suspension. See the JtaTransactionManager javadoc for details.

Spring’s JtaTransactionManager is the standard choice to run on Java EE application servers and is known to work on all common servers. Advanced functionality, such as transaction suspension, works on many servers as well (including GlassFish, JBoss and Geronimo) without any special configuration required. However, for fully supported transaction suspension and further advanced integration, Spring includes special adapters for WebLogic Server and WebSphere. These adapters are discussed in the following sections.

For standard scenarios, including WebLogic Server and WebSphere, consider using the convenient <tx:jta-transaction-manager/> configuration element. When configured, this element automatically detects the underlying server and chooses the best transaction manager available for the platform. This means that you need not explicitly configure server-specific adapter classes (as discussed in the following sections). Rather, they are chosen automatically, with the standard JtaTransactionManager as the default fallback.

IBM WebSphere

On WebSphere 6.1.0.9 and above, the recommended Spring JTA transaction manager to use is WebSphereUowTransactionManager. This special adapter uses IBM’s UOWManager API, which is available in WebSphere Application Server 6.1.0.9 and later. With this adapter, Spring-driven transaction suspension (suspend and resume as initiated by PROPAGATION_REQUIRES_NEW) is officially supported by IBM.

Oracle WebLogic Server

On WebLogic Server 9.0 or above, you would typically use the WebLogicJtaTransactionManager instead of the stock JtaTransactionManager class. This special WebLogic-specific subclass of the normal JtaTransactionManager supports the full power of Spring’s transaction definitions in a WebLogic-managed transaction environment, beyond standard JTA semantics. Features include transaction names, per-transaction isolation levels, and proper resuming of transactions in all cases.

Solutions to Common Problems

This section describes solutions to some common problems.

Using the Wrong Transaction Manager for a Specific `DataSource`

Use the correct PlatformTransactionManager implementation based on your choice of transactional technologies and requirements. Used properly, the Spring Framework merely provides a straightforward and portable abstraction. If you use global transactions, you must use the org.springframework.transaction.jta.JtaTransactionManager class (or an application server-specific subclass of it) for all your transactional operations. Otherwise, the transaction infrastructure tries to perform local transactions on such resources as container DataSource instances. Such local transactions do not make sense, and a good application server treats them as errors.

Further Resources

For more information about the Spring Framework’s transaction support, see:

Distributed transactions in Spring, with and without XA is a JavaWorld presentation in which Spring’s David Syer guides you through seven patterns for distributed transactions in Spring applications, three of them with XA and four without.
Java Transaction Design Strategies is a book available from InfoQ that provides a well-paced introduction to transactions in Java. It also includes side-by-side examples of how to configure and use transactions with both the Spring Framework and EJB3.

DAO Support

The Data Access Object (DAO) support in Spring is aimed at making it easy to work with data access technologies (such as JDBC, Hibernate, or JPA) in a consistent way. This lets you switch between the aforementioned persistence technologies fairly easily, and it also lets you code without worrying about catching exceptions that are specific to each technology.

Consistent Exception Hierarchy

Spring provides a convenient translation from technology-specific exceptions, such as SQLException to its own exception class hierarchy, which has DataAccessException as the root exception. These exceptions wrap the original exception so that there is never any risk that you might lose any information about what might have gone wrong.

In addition to JDBC exceptions, Spring can also wrap JPA- and Hibernate-specific exceptions, converting them to a set of focused runtime exceptions. This lets you handle most non-recoverable persistence exceptions in only the appropriate layers, without having annoying boilerplate catch-and-throw blocks and exception declarations in your DAOs. (You can still trap and handle exceptions anywhere you need to though.) As mentioned above, JDBC exceptions (including database-specific dialects) are also converted to the same hierarchy, meaning that you can perform some operations with JDBC within a consistent programming model.

The preceding discussion holds true for the various template classes in Spring’s support for various ORM frameworks. If you use the interceptor-based classes, the application must care about handling HibernateExceptions and PersistenceExceptions itself, preferably by delegating to the convertHibernateAccessException(..) or convertJpaAccessException() methods, respectively, of SessionFactoryUtils. These methods convert the exceptions to exceptions that are compatible with the exceptions in the org.springframework.dao exception hierarchy. As PersistenceExceptions are unchecked, they can get thrown, too (sacrificing generic DAO abstraction in terms of exceptions, though).

The following image shows the exception hierarchy that Spring provides. (Note that the class hierarchy detailed in the image shows only a subset of the entire DataAccessException hierarchy.)

Annotations Used to Configure DAO or Repository Classes

The best way to guarantee that your Data Access Objects (DAOs) or repositories provide exception translation is to use the @Repository annotation. This annotation also lets the component scanning support find and configure your DAOs and repositories without having to provide XML configuration entries for them. The following example shows how to use the @Repository annotation:

Java

@Repository // (1)
public class SomeMovieFinder implements MovieFinder {
    // ...
}

The @Repository annotation.

Kotlin

@Repository // (1)
class SomeMovieFinder : MovieFinder {
    // ...
}

The @Repository annotation.

Any DAO or repository implementation needs access to a persistence resource, depending on the persistence technology used. For example, a JDBC-based repository needs access to a JDBC DataSource, and a JPA-based repository needs access to an EntityManager. The easiest way to accomplish this is to have this resource dependency injected by using one of the @Autowired, @Inject, @Resource or @PersistenceContext annotations. The following example works for a JPA repository:

Java

@Repository
public class JpaMovieFinder implements MovieFinder {

    @PersistenceContext
    private EntityManager entityManager;

    // ...
}

Kotlin

@Repository
class JpaMovieFinder : MovieFinder {

    @PersistenceContext
    private lateinit var entityManager: EntityManager

    // ...
}

If you use the classic Hibernate APIs, you can inject SessionFactory, as the following example shows:

Java

@Repository
public class HibernateMovieFinder implements MovieFinder {

    private SessionFactory sessionFactory;

    @Autowired
    public void setSessionFactory(SessionFactory sessionFactory) {
        this.sessionFactory = sessionFactory;
    }

    // ...
}

Kotlin

@Repository
class HibernateMovieFinder(private val sessionFactory: SessionFactory) : MovieFinder {
    // ...
}

The last example we show here is for typical JDBC support. You could have the DataSource injected into an initialization method or a constructor, where you would create a JdbcTemplate and other data access support classes (such as SimpleJdbcCall and others) by using this DataSource. The following example autowires a DataSource:

Java

@Repository
public class JdbcMovieFinder implements MovieFinder {

    private JdbcTemplate jdbcTemplate;

    @Autowired
    public void init(DataSource dataSource) {
        this.jdbcTemplate = new JdbcTemplate(dataSource);
    }

    // ...
}

Kotlin

@Repository
class JdbcMovieFinder(dataSource: DataSource) : MovieFinder {

    private val jdbcTemplate = JdbcTemplate(dataSource)

    // ...
}

Note	See the specific coverage of each persistence technology for details on how to configure the application context to take advantage of these annotations.

Data Access with JDBC

The value provided by the Spring Framework JDBC abstraction is perhaps best shown by the sequence of actions outlined in the following table below. The table shows which actions Spring takes care of and which actions are your responsibility.

Table 4. Spring JDBC - who does what?

Action	Spring	You
Define connection parameters.		X
Open the connection.	X
Specify the SQL statement.		X
Declare parameters and provide parameter values		X
Prepare and execute the statement.	X
Set up the loop to iterate through the results (if any).	X
Do the work for each iteration.		X
Process any exception.	X
Handle transactions.	X
Close the connection, the statement, and the resultset.	X

The Spring Framework takes care of all the low-level details that can make JDBC such a tedious API.

Choosing an Approach for JDBC Database Access

You can choose among several approaches to form the basis for your JDBC database access. In addition to three flavors of JdbcTemplate, a new SimpleJdbcInsert and SimpleJdbcCall approach optimizes database metadata, and the RDBMS Object style takes a more object-oriented approach similar to that of JDO Query design. Once you start using one of these approaches, you can still mix and match to include a feature from a different approach. All approaches require a JDBC 2.0-compliant driver, and some advanced features require a JDBC 3.0 driver.

JdbcTemplate is the classic and most popular Spring JDBC approach. This “lowest-level” approach and all others use a JdbcTemplate under the covers.
NamedParameterJdbcTemplate wraps a JdbcTemplate to provide named parameters instead of the traditional JDBC ? placeholders. This approach provides better documentation and ease of use when you have multiple parameters for an SQL statement.
SimpleJdbcInsert and SimpleJdbcCall optimize database metadata to limit the amount of necessary configuration. This approach simplifies coding so that you need to provide only the name of the table or procedure and provide a map of parameters matching the column names. This works only if the database provides adequate metadata. If the database does not provide this metadata, you have to provide explicit configuration of the parameters.
RDBMS objects, including MappingSqlQuery, SqlUpdate and StoredProcedure, require you to create reusable and thread-safe objects during initialization of your data-access layer. This approach is modeled after JDO Query, wherein you define your query string, declare parameters, and compile the query. Once you do that, execute methods can be called multiple times with various parameter values.

Package Hierarchy

The Spring Framework’s JDBC abstraction framework consists of four different packages:

core: The org.springframework.jdbc.core package contains the JdbcTemplate class and its various callback interfaces, plus a variety of related classes. A subpackage named org.springframework.jdbc.core.simple contains the SimpleJdbcInsert and SimpleJdbcCall classes. Another subpackage named org.springframework.jdbc.core.namedparam contains the NamedParameterJdbcTemplate class and the related support classes. See Using the JDBC Core Classes to Control Basic JDBC Processing and Error Handling, JDBC Batch Operations, and Simplifying JDBC Operations with the SimpleJdbc Classes.
datasource: The org.springframework.jdbc.datasource package contains a utility class for easy DataSource access and various simple DataSource implementations that you can use for testing and running unmodified JDBC code outside of a Java EE container. A subpackage named org.springfamework.jdbc.datasource.embedded provides support for creating embedded databases by using Java database engines, such as HSQL, H2, and Derby. See Controlling Database Connections and Embedded Database Support.
object: The org.springframework.jdbc.object package contains classes that represent RDBMS queries, updates, and stored procedures as thread-safe, reusable objects. See Modeling JDBC Operations as Java Objects. This approach is modeled by JDO, although objects returned by queries are naturally disconnected from the database. This higher-level of JDBC abstraction depends on the lower-level abstraction in the org.springframework.jdbc.core package.
support: The org.springframework.jdbc.support package provides SQLException translation functionality and some utility classes. Exceptions thrown during JDBC processing are translated to exceptions defined in the org.springframework.dao package. This means that code using the Spring JDBC abstraction layer does not need to implement JDBC or RDBMS-specific error handling. All translated exceptions are unchecked, which gives you the option of catching the exceptions from which you can recover while letting other exceptions be propagated to the caller. See Using SQLExceptionTranslator.

Using the JDBC Core Classes to Control Basic JDBC Processing and Error Handling

This section covers how to use the JDBC core classes to control basic JDBC processing, including error handling. It includes the following topics:

Using JdbcTemplate
Using NamedParameterJdbcTemplate
Using SQLExceptionTranslator
Running Statements
Running Queries
Updating the Database
Retrieving Auto-generated Keys

Using `JdbcTemplate`

JdbcTemplate is the central class in the JDBC core package. It handles the creation and release of resources, which helps you avoid common errors, such as forgetting to close the connection. It performs the basic tasks of the core JDBC workflow (such as statement creation and execution), leaving application code to provide SQL and extract results. The JdbcTemplate class:

Runs SQL queries
Updates statements and stored procedure calls
Performs iteration over ResultSet instances and extraction of returned parameter values.
Catches JDBC exceptions and translates them to the generic, more informative, exception hierarchy defined in the org.springframework.dao package. (See Consistent Exception Hierarchy.)

When you use the JdbcTemplate for your code, you need only to implement callback interfaces, giving them a clearly defined contract. Given a Connection provided by the JdbcTemplate class, the PreparedStatementCreator callback interface creates a prepared statement, providing SQL and any necessary parameters. The same is true for the CallableStatementCreator interface, which creates callable statements. The RowCallbackHandler interface extracts values from each row of a ResultSet.

You can use JdbcTemplate within a DAO implementation through direct instantiation with a DataSource reference, or you can configure it in a Spring IoC container and give it to DAOs as a bean reference.

Note	The `DataSource` should always be configured as a bean in the Spring IoC container. In the first case the bean is given to the service directly; in the second case it is given to the prepared template.

All SQL issued by this class is logged at the DEBUG level under the category corresponding to the fully qualified class name of the template instance (typically JdbcTemplate, but it may be different if you use a custom subclass of the JdbcTemplate class).

The following sections provide some examples of JdbcTemplate usage. These examples are not an exhaustive list of all of the functionality exposed by the JdbcTemplate. See the attendant javadoc for that.

Querying (`SELECT`)

The following query gets the number of rows in a relation:

Java

int rowCount = this.jdbcTemplate.queryForObject("select count(*) from t_actor", Integer.class);

Kotlin

val rowCount = jdbcTemplate.queryForObject<Int>("select count(*) from t_actor")!!

The following query uses a bind variable:

Java

int countOfActorsNamedJoe = this.jdbcTemplate.queryForObject(
        "select count(*) from t_actor where first_name = ?", Integer.class, "Joe");

Kotlin

val countOfActorsNamedJoe = jdbcTemplate.queryForObject<Int>(
        "select count(*) from t_actor where first_name = ?", arrayOf("Joe"))!!

The following query looks for a String:

Java

String lastName = this.jdbcTemplate.queryForObject(
        "select last_name from t_actor where id = ?",
        new Object[]{1212L}, String.class);

Kotlin

val lastName = this.jdbcTemplate.queryForObject<String>(
        "select last_name from t_actor where id = ?",
        arrayOf(1212L))!!

The following query finds and populates a single domain object:

Java

Actor actor = this.jdbcTemplate.queryForObject(
        "select first_name, last_name from t_actor where id = ?",
        new Object[]{1212L},
        new RowMapper<Actor>() {
            public Actor mapRow(ResultSet rs, int rowNum) throws SQLException {
                Actor actor = new Actor();
                actor.setFirstName(rs.getString("first_name"));
                actor.setLastName(rs.getString("last_name"));
                return actor;
            }
        });

Kotlin

val actor = jdbcTemplate.queryForObject(
            "select first_name, last_name from t_actor where id = ?",
            arrayOf(1212L)) { rs, _ ->
        Actor(rs.getString("first_name"), rs.getString("last_name"))
    }

The following query finds and populates a number of domain objects:

Java

List<Actor> actors = this.jdbcTemplate.query(
        "select first_name, last_name from t_actor",
        new RowMapper<Actor>() {
            public Actor mapRow(ResultSet rs, int rowNum) throws SQLException {
                Actor actor = new Actor();
                actor.setFirstName(rs.getString("first_name"));
                actor.setLastName(rs.getString("last_name"));
                return actor;
            }
        });

Kotlin

val actors = jdbcTemplate.query("select first_name, last_name from t_actor") { rs, _ ->
        Actor(rs.getString("first_name"), rs.getString("last_name"))

If the last two snippets of code actually existed in the same application, it would make sense to remove the duplication present in the two RowMapper anonymous inner classes and extract them out into a single class (typically a static nested class) that could then be referenced by DAO methods as needed. For example, it may be better to write the preceding code snippet as follows:

Java

public List<Actor> findAllActors() {
    return this.jdbcTemplate.query( "select first_name, last_name from t_actor", new ActorMapper());
}

private static final class ActorMapper implements RowMapper<Actor> {

    public Actor mapRow(ResultSet rs, int rowNum) throws SQLException {
        Actor actor = new Actor();
        actor.setFirstName(rs.getString("first_name"));
        actor.setLastName(rs.getString("last_name"));
        return actor;
    }
}

Kotlin

fun findAllActors(): List<Actor> {
    return jdbcTemplate.query("select first_name, last_name from t_actor", ActorMapper())
}

class ActorMapper : RowMapper<Actor> {

    override fun mapRow(rs: ResultSet, rowNum: Int) = Actor(
            rs.getString("first_name"),
            rs.getString("last_name"))
    }
}

Updating (`INSERT`, `UPDATE`, and `DELETE`) with `JdbcTemplate`

You can use the update(..) method to perform insert, update, and delete operations. Parameter values are usually provided as variable arguments or, alternatively, as an object array.

The following example inserts a new entry:

Java

this.jdbcTemplate.update(
        "insert into t_actor (first_name, last_name) values (?, ?)",
        "Leonor", "Watling");

Kotlin

jdbcTemplate.update(
        "insert into t_actor (first_name, last_name) values (?, ?)",
        "Leonor", "Watling")

The following example updates an existing entry:

Java

this.jdbcTemplate.update(
        "update t_actor set last_name = ? where id = ?",
        "Banjo", 5276L);

Kotlin

jdbcTemplate.update(
        "update t_actor set last_name = ? where id = ?",
        "Banjo", 5276L)

The following example deletes an entry:

Java

this.jdbcTemplate.update(
        "delete from actor where id = ?",
        Long.valueOf(actorId));

Kotlin

jdbcTemplate.update("delete from actor where id = ?", actorId.toLong())

Other `JdbcTemplate` Operations

You can use the execute(..) method to run any arbitrary SQL. Consequently, the method is often used for DDL statements. It is heavily overloaded with variants that take callback interfaces, binding variable arrays, and so on. The following example creates a table:

Java

this.jdbcTemplate.execute("create table mytable (id integer, name varchar(100))");

Kotlin

jdbcTemplate.execute("create table mytable (id integer, name varchar(100))")

The following example invokes a stored procedure:

Java

this.jdbcTemplate.update(
        "call SUPPORT.REFRESH_ACTORS_SUMMARY(?)",
        Long.valueOf(unionId));

Kotlin

jdbcTemplate.update(
        "call SUPPORT.REFRESH_ACTORS_SUMMARY(?)",
        unionId.toLong())

More sophisticated stored procedure support is covered later.

`JdbcTemplate` Best Practices

Instances of the JdbcTemplate class are thread-safe, once configured. This is important because it means that you can configure a single instance of a JdbcTemplate and then safely inject this shared reference into multiple DAOs (or repositories). The JdbcTemplate is stateful, in that it maintains a reference to a DataSource, but this state is not conversational state.

A common practice when using the JdbcTemplate class (and the associated NamedParameterJdbcTemplate class) is to configure a DataSource in your Spring configuration file and then dependency-inject that shared DataSource bean into your DAO classes. The JdbcTemplate is created in the setter for the DataSource. This leads to DAOs that resemble the following:

Java

public class JdbcCorporateEventDao implements CorporateEventDao {

    private JdbcTemplate jdbcTemplate;

    public void setDataSource(DataSource dataSource) {
        this.jdbcTemplate = new JdbcTemplate(dataSource);
    }

    // JDBC-backed implementations of the methods on the CorporateEventDao follow...
}

Kotlin

class JdbcCorporateEventDao(dataSource: DataSource) : CorporateEventDao {

    private val jdbcTemplate = JdbcTemplate(dataSource)

    // JDBC-backed implementations of the methods on the CorporateEventDao follow...
}

The following example shows the corresponding XML configuration:

<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
    xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
    xmlns:context="http://www.springframework.org/schema/context"
    xsi:schemaLocation="
        http://www.springframework.org/schema/beans
        https://www.springframework.org/schema/beans/spring-beans.xsd
        http://www.springframework.org/schema/context
        https://www.springframework.org/schema/context/spring-context.xsd">

    <bean id="corporateEventDao" class="com.example.JdbcCorporateEventDao">
        <property name="dataSource" ref="dataSource"/>
    </bean>

    <bean id="dataSource" class="org.apache.commons.dbcp.BasicDataSource" destroy-method="close">
        <property name="driverClassName" value="${jdbc.driverClassName}"/>
        <property name="url" value="${jdbc.url}"/>
        <property name="username" value="${jdbc.username}"/>
        <property name="password" value="${jdbc.password}"/>
    </bean>

    <context:property-placeholder location="jdbc.properties"/>

</beans>

An alternative to explicit configuration is to use component-scanning and annotation support for dependency injection. In this case, you can annotate the class with @Repository (which makes it a candidate for component-scanning) and annotate the DataSource setter method with @Autowired. The following example shows how to do so:

Java

@Repository // (1)
public class JdbcCorporateEventDao implements CorporateEventDao {

    private JdbcTemplate jdbcTemplate;

    @Autowired // (2)
    public void setDataSource(DataSource dataSource) {
        this.jdbcTemplate = new JdbcTemplate(dataSource); // (3)
    }

    // JDBC-backed implementations of the methods on the CorporateEventDao follow...
}

Annotate the class with @Repository.
Annotate the DataSource setter method with @Autowired.
Create a new JdbcTemplate with the DataSource.

Kotlin

@Repository // (1)
class JdbcCorporateEventDao(dataSource: DataSource) : CorporateEventDao { // (2)

    private val jdbcTemplate = JdbcTemplate(dataSource) // (3)

    // JDBC-backed implementations of the methods on the CorporateEventDao follow...
}

Annotate the class with @Repository.
Constructor injection of the DataSource.
Create a new JdbcTemplate with the DataSource.

The following example shows the corresponding XML configuration:

<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
    xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
    xmlns:context="http://www.springframework.org/schema/context"
    xsi:schemaLocation="
        http://www.springframework.org/schema/beans
        https://www.springframework.org/schema/beans/spring-beans.xsd
        http://www.springframework.org/schema/context
        https://www.springframework.org/schema/context/spring-context.xsd">

    <!-- Scans within the base package of the application for @Component classes to configure as beans -->
    <context:component-scan base-package="org.springframework.docs.test" />

    <bean id="dataSource" class="org.apache.commons.dbcp.BasicDataSource" destroy-method="close">
        <property name="driverClassName" value="${jdbc.driverClassName}"/>
        <property name="url" value="${jdbc.url}"/>
        <property name="username" value="${jdbc.username}"/>
        <property name="password" value="${jdbc.password}"/>
    </bean>

    <context:property-placeholder location="jdbc.properties"/>

</beans>

If you use Spring’s JdbcDaoSupport class and your various JDBC-backed DAO classes extend from it, your sub-class inherits a setDataSource(..) method from the JdbcDaoSupport class. You can choose whether to inherit from this class. The JdbcDaoSupport class is provided as a convenience only.

Regardless of which of the above template initialization styles you choose to use (or not), it is seldom necessary to create a new instance of a JdbcTemplate class each time you want to run SQL. Once configured, a JdbcTemplate instance is thread-safe. If your application accesses multiple databases, you may want multiple JdbcTemplate instances, which requires multiple DataSources and, subsequently, multiple differently configured JdbcTemplate instances.

Using `NamedParameterJdbcTemplate`

The NamedParameterJdbcTemplate class adds support for programming JDBC statements by using named parameters, as opposed to programming JDBC statements using only classic placeholder ( '?') arguments. The NamedParameterJdbcTemplate class wraps a JdbcTemplate and delegates to the wrapped JdbcTemplate to do much of its work. This section describes only those areas of the NamedParameterJdbcTemplate class that differ from the JdbcTemplate itself — namely, programming JDBC statements by using named parameters. The following example shows how to use NamedParameterJdbcTemplate:

Java

// some JDBC-backed DAO class...
private NamedParameterJdbcTemplate namedParameterJdbcTemplate;

public void setDataSource(DataSource dataSource) {
    this.namedParameterJdbcTemplate = new NamedParameterJdbcTemplate(dataSource);
}

public int countOfActorsByFirstName(String firstName) {

    String sql = "select count(*) from T_ACTOR where first_name = :first_name";

    SqlParameterSource namedParameters = new MapSqlParameterSource("first_name", firstName);

    return this.namedParameterJdbcTemplate.queryForObject(sql, namedParameters, Integer.class);
}

Kotlin

private val namedParameterJdbcTemplate = NamedParameterJdbcTemplate(dataSource)

fun countOfActorsByFirstName(firstName: String): Int {
    val sql = "select count(*) from T_ACTOR where first_name = :first_name"
    val namedParameters = MapSqlParameterSource("first_name", firstName)
    return namedParameterJdbcTemplate.queryForObject(sql, namedParameters, Int::class.java)!!
}

Notice the use of the named parameter notation in the value assigned to the sql variable and the corresponding value that is plugged into the namedParameters variable (of type MapSqlParameterSource).

Alternatively, you can pass along named parameters and their corresponding values to a NamedParameterJdbcTemplate instance by using the Map-based style.The remaining methods exposed by the NamedParameterJdbcOperations and implemented by the NamedParameterJdbcTemplate class follow a similar pattern and are not covered here.

The following example shows the use of the Map-based style:

Java

// some JDBC-backed DAO class...
private NamedParameterJdbcTemplate namedParameterJdbcTemplate;

public void setDataSource(DataSource dataSource) {
    this.namedParameterJdbcTemplate = new NamedParameterJdbcTemplate(dataSource);
}

public int countOfActorsByFirstName(String firstName) {

    String sql = "select count(*) from T_ACTOR where first_name = :first_name";

    Map<String, String> namedParameters = Collections.singletonMap("first_name", firstName);

    return this.namedParameterJdbcTemplate.queryForObject(sql, namedParameters,  Integer.class);
}

Kotlin

// some JDBC-backed DAO class...
private val namedParameterJdbcTemplate = NamedParameterJdbcTemplate(dataSource)

fun countOfActorsByFirstName(firstName: String): Int {
    val sql = "select count(*) from T_ACTOR where first_name = :first_name"
    val namedParameters = mapOf("first_name" to firstName)
    return namedParameterJdbcTemplate.queryForObject(sql, namedParameters, Int::class.java)!!
}

One nice feature related to the NamedParameterJdbcTemplate (and existing in the same Java package) is the SqlParameterSource interface. You have already seen an example of an implementation of this interface in one of the previous code snippets (the MapSqlParameterSource class). An SqlParameterSource is a source of named parameter values to a NamedParameterJdbcTemplate. The MapSqlParameterSource class is a simple implementation that is an adapter around a java.util.Map, where the keys are the parameter names and the values are the parameter values.

Another SqlParameterSource implementation is the BeanPropertySqlParameterSource class. This class wraps an arbitrary JavaBean (that is, an instance of a class that adheres to the JavaBean conventions) and uses the properties of the wrapped JavaBean as the source of named parameter values.

The following example shows a typical JavaBean:

Java

public class Actor {

    private Long id;
    private String firstName;
    private String lastName;

    public String getFirstName() {
        return this.firstName;
    }

    public String getLastName() {
        return this.lastName;
    }

    public Long getId() {
        return this.id;
    }

    // setters omitted...

}

Kotlin

data class Actor(val id: Long, val firstName: String, val lastName: String)

The following example uses a NamedParameterJdbcTemplate to return the count of the members of the class shown in the preceding example:

Java

// some JDBC-backed DAO class...
private NamedParameterJdbcTemplate namedParameterJdbcTemplate;

public void setDataSource(DataSource dataSource) {
    this.namedParameterJdbcTemplate = new NamedParameterJdbcTemplate(dataSource);
}

public int countOfActors(Actor exampleActor) {

    // notice how the named parameters match the properties of the above 'Actor' class
    String sql = "select count(*) from T_ACTOR where first_name = :firstName and last_name = :lastName";

    SqlParameterSource namedParameters = new BeanPropertySqlParameterSource(exampleActor);

    return this.namedParameterJdbcTemplate.queryForObject(sql, namedParameters, Integer.class);
}

Kotlin

// some JDBC-backed DAO class...
private val namedParameterJdbcTemplate = NamedParameterJdbcTemplate(dataSource)

private val namedParameterJdbcTemplate = NamedParameterJdbcTemplate(dataSource)

fun countOfActors(exampleActor: Actor): Int {
    // notice how the named parameters match the properties of the above 'Actor' class
    val sql = "select count(*) from T_ACTOR where first_name = :firstName and last_name = :lastName"
    val namedParameters = BeanPropertySqlParameterSource(exampleActor)
    return namedParameterJdbcTemplate.queryForObject(sql, namedParameters, Int::class.java)!!
}

Remember that the NamedParameterJdbcTemplate class wraps a classic JdbcTemplate template. If you need access to the wrapped JdbcTemplate instance to access functionality that is present only in the JdbcTemplate class, you can use the getJdbcOperations() method to access the wrapped JdbcTemplate through the JdbcOperations interface.

See also JdbcTemplate Best Practices for guidelines on using the NamedParameterJdbcTemplate class in the context of an application.

Using `SQLExceptionTranslator`

SQLExceptionTranslator is an interface to be implemented by classes that can translate between SQLExceptions and Spring’s own org.springframework.dao.DataAccessException, which is agnostic in regard to data access strategy. Implementations can be generic (for example, using SQLState codes for JDBC) or proprietary (for example, using Oracle error codes) for greater precision.

SQLErrorCodeSQLExceptionTranslator is the implementation of SQLExceptionTranslator that is used by default. This implementation uses specific vendor codes. It is more precise than the SQLState implementation. The error code translations are based on codes held in a JavaBean type class called SQLErrorCodes. This class is created and populated by an SQLErrorCodesFactory, which (as the name suggests) is a factory for creating SQLErrorCodes based on the contents of a configuration file named sql-error-codes.xml. This file is populated with vendor codes and based on the DatabaseProductName taken from DatabaseMetaData. The codes for the actual database you are using are used.

The SQLErrorCodeSQLExceptionTranslator applies matching rules in the following sequence:

Any custom translation implemented by a subclass. Normally, the provided concrete SQLErrorCodeSQLExceptionTranslator is used, so this rule does not apply. It applies only if you have actually provided a subclass implementation.
Any custom implementation of the SQLExceptionTranslator interface that is provided as the customSqlExceptionTranslator property of the SQLErrorCodes class.
The list of instances of the CustomSQLErrorCodesTranslation class (provided for the customTranslations property of the SQLErrorCodes class) are searched for a match.
Error code matching is applied.
Use the fallback translator. SQLExceptionSubclassTranslator is the default fallback translator. If this translation is not available, the next fallback translator is the SQLStateSQLExceptionTranslator.

Note

The SQLErrorCodesFactory is used by default to define Error codes and custom exception translations. They are looked up in a file named sql-error-codes.xml from the classpath, and the matching SQLErrorCodes instance is located based on the database name from the database metadata of the database in use.

You can extend SQLErrorCodeSQLExceptionTranslator, as the following example shows:

Java

public class CustomSQLErrorCodesTranslator extends SQLErrorCodeSQLExceptionTranslator {

    protected DataAccessException customTranslate(String task, String sql, SQLException sqlEx) {
        if (sqlEx.getErrorCode() == -12345) {
            return new DeadlockLoserDataAccessException(task, sqlEx);
        }
        return null;
    }
}

Kotlin

class CustomSQLErrorCodesTranslator : SQLErrorCodeSQLExceptionTranslator() {

    override fun customTranslate(task: String, sql: String?, sqlEx: SQLException): DataAccessException? {
        if (sqlEx.errorCode == -12345) {
                return DeadlockLoserDataAccessException(task, sqlEx)
            }
            return null;
    }
}

In the preceding example, the specific error code (-12345) is translated, while other errors are left to be translated by the default translator implementation. To use this custom translator, you must pass it to the JdbcTemplate through the method setExceptionTranslator, and you must use this JdbcTemplate for all of the data access processing where this translator is needed. The following example shows how you can use this custom translator:

Java

private JdbcTemplate jdbcTemplate;

public void setDataSource(DataSource dataSource) {

    // create a JdbcTemplate and set data source
    this.jdbcTemplate = new JdbcTemplate();
    this.jdbcTemplate.setDataSource(dataSource);

    // create a custom translator and set the DataSource for the default translation lookup
    CustomSQLErrorCodesTranslator tr = new CustomSQLErrorCodesTranslator();
    tr.setDataSource(dataSource);
    this.jdbcTemplate.setExceptionTranslator(tr);

}

public void updateShippingCharge(long orderId, long pct) {
    // use the prepared JdbcTemplate for this update
    this.jdbcTemplate.update("update orders" +
        " set shipping_charge = shipping_charge * ? / 100" +
        " where id = ?", pct, orderId);
}

Kotlin

// create a JdbcTemplate and set data source
private val jdbcTemplate = JdbcTemplate(dataSource).apply {
    // create a custom translator and set the DataSource for the default translation lookup
    exceptionTranslator = CustomSQLErrorCodesTranslator().apply {
        this.dataSource = dataSource
    }
}

fun updateShippingCharge(orderId: Long, pct: Long) {
    // use the prepared JdbcTemplate for this update
    this.jdbcTemplate!!.update("update orders" +
            " set shipping_charge = shipping_charge * ? / 100" +
            " where id = ?", pct, orderId)
}

The custom translator is passed a data source in order to look up the error codes in sql-error-codes.xml.

Running Statements

Running an SQL statement requires very little code. You need a DataSource and a JdbcTemplate, including the convenience methods that are provided with the JdbcTemplate. The following example shows what you need to include for a minimal but fully functional class that creates a new table:

Java

import javax.sql.DataSource;
import org.springframework.jdbc.core.JdbcTemplate;

public class ExecuteAStatement {

    private JdbcTemplate jdbcTemplate;

    public void setDataSource(DataSource dataSource) {
        this.jdbcTemplate = new JdbcTemplate(dataSource);
    }

    public void doExecute() {
        this.jdbcTemplate.execute("create table mytable (id integer, name varchar(100))");
    }
}

Kotlin

import javax.sql.DataSource
import org.springframework.jdbc.core.JdbcTemplate

class ExecuteAStatement(dataSource: DataSource) {

    private val jdbcTemplate = JdbcTemplate(dataSource)

    fun doExecute() {
        jdbcTemplate.execute("create table mytable (id integer, name varchar(100))")
    }
}

Running Queries

Some query methods return a single value. To retrieve a count or a specific value from one row, use queryForObject(..). The latter converts the returned JDBC Type to the Java class that is passed in as an argument. If the type conversion is invalid, an InvalidDataAccessApiUsageException is thrown. The following example contains two query methods, one for an int and one that queries for a String:

Java

import javax.sql.DataSource;
import org.springframework.jdbc.core.JdbcTemplate;

public class RunAQuery {

    private JdbcTemplate jdbcTemplate;

    public void setDataSource(DataSource dataSource) {
        this.jdbcTemplate = new JdbcTemplate(dataSource);
    }

    public int getCount() {
        return this.jdbcTemplate.queryForObject("select count(*) from mytable", Integer.class);
    }

    public String getName() {
        return this.jdbcTemplate.queryForObject("select name from mytable", String.class);
    }
}

Kotlin

import javax.sql.DataSource
import org.springframework.jdbc.core.JdbcTemplate

class RunAQuery(dataSource: DataSource) {

    private val jdbcTemplate = JdbcTemplate(dataSource)

    val count: Int
        get() = jdbcTemplate.queryForObject("select count(*) from mytable")!!

    val name: String?
        get() = jdbcTemplate.queryForObject("select name from mytable")
}

In addition to the single result query methods, several methods return a list with an entry for each row that the query returned. The most generic method is queryForList(..), which returns a List where each element is a Map containing one entry for each column, using the column name as the key. If you add a method to the preceding example to retrieve a list of all the rows, it might be as follows:

Java

private JdbcTemplate jdbcTemplate;

public void setDataSource(DataSource dataSource) {
    this.jdbcTemplate = new JdbcTemplate(dataSource);
}

public List<Map<String, Object>> getList() {
    return this.jdbcTemplate.queryForList("select * from mytable");
}

Kotlin

private val jdbcTemplate = JdbcTemplate(dataSource)

fun getList(): List<Map<String, Any>> {
    return jdbcTemplate.queryForList("select * from mytable")
}

The returned list would resemble the following:

[{name=Bob, id=1}, {name=Mary, id=2}]

Updating the Database

The following example updates a column for a certain primary key:

Java

import javax.sql.DataSource;
import org.springframework.jdbc.core.JdbcTemplate;

public class ExecuteAnUpdate {

    private JdbcTemplate jdbcTemplate;

    public void setDataSource(DataSource dataSource) {
        this.jdbcTemplate = new JdbcTemplate(dataSource);
    }

    public void setName(int id, String name) {
        this.jdbcTemplate.update("update mytable set name = ? where id = ?", name, id);
    }
}

Kotlin

import javax.sql.DataSource
import org.springframework.jdbc.core.JdbcTemplate

class ExecuteAnUpdate(dataSource: DataSource) {

    private val jdbcTemplate = JdbcTemplate(dataSource)

    fun setName(id: Int, name: String) {
        jdbcTemplate.update("update mytable set name = ? where id = ?", name, id)
    }
}

In the preceding example, an SQL statement has placeholders for row parameters. You can pass the parameter values in as varargs or ,alternatively, as an array of objects. Thus, you should explicitly wrap primitives in the primitive wrapper classes, or you should use auto-boxing.

Retrieving Auto-generated Keys

An update() convenience method supports the retrieval of primary keys generated by the database. This support is part of the JDBC 3.0 standard. See Chapter 13.6 of the specification for details. The method takes a PreparedStatementCreator as its first argument, and this is the way the required insert statement is specified. The other argument is a KeyHolder, which contains the generated key on successful return from the update. There is no standard single way to create an appropriate PreparedStatement (which explains why the method signature is the way it is). The following example works on Oracle but may not work on other platforms:

Java

final String INSERT_SQL = "insert into my_test (name) values(?)";
final String name = "Rob";

KeyHolder keyHolder = new GeneratedKeyHolder();
jdbcTemplate.update(
    new PreparedStatementCreator() {
        public PreparedStatement createPreparedStatement(Connection connection) throws SQLException {
            PreparedStatement ps = connection.prepareStatement(INSERT_SQL, new String[] {"id"});
            ps.setString(1, name);
            return ps;
        }
    },
    keyHolder);

// keyHolder.getKey() now contains the generated key

Kotlin

val INSERT_SQL = "insert into my_test (name) values(?)"
val name = "Rob"

val keyHolder = GeneratedKeyHolder()
jdbcTemplate.update({
    it.prepareStatement (INSERT_SQL, arrayOf("id")).apply { setString(1, name) }
}, keyHolder)

// keyHolder.getKey() now contains the generated key

Controlling Database Connections

This section covers:

Using DataSource
Using DataSourceUtils
Implementing SmartDataSource
Extending AbstractDataSource
Using SingleConnectionDataSource
Using DriverManagerDataSource
Using TransactionAwareDataSourceProxy
Using DataSourceTransactionManager

Using `DataSource`

Spring obtains a connection to the database through a DataSource. A DataSource is part of the JDBC specification and is a generalized connection factory. It lets a container or a framework hide connection pooling and transaction management issues from the application code. As a developer, you need not know details about how to connect to the database. That is the responsibility of the administrator who sets up the datasource. You most likely fill both roles as you develop and test code, but you do not necessarily have to know how the production data source is configured.

When you use Spring’s JDBC layer, you can obtain a data source from JNDI, or you can configure your own with a connection pool implementation provided by a third party. Popular implementations are Apache Jakarta Commons DBCP and C3P0. Implementations in the Spring distribution are meant only for testing purposes and do not provide pooling.

This section uses Spring’s DriverManagerDataSource implementation, and several additional implementations are covered later.

Note	You should use the `DriverManagerDataSource` class only for testing purposes, since it does not provide pooling and performs poorly when multiple requests for a connection are made.

To configure a DriverManagerDataSource:

Obtain a connection with DriverManagerDataSource as you typically obtain a JDBC connection.
Specify the fully qualified classname of the JDBC driver so that the DriverManager can load the driver class.
Provide a URL that varies between JDBC drivers. (See the documentation for your driver for the correct value.)
Provide a username and a password to connect to the database.

The following example shows how to configure a DriverManagerDataSource in Java:

Java

DriverManagerDataSource dataSource = new DriverManagerDataSource();
dataSource.setDriverClassName("org.hsqldb.jdbcDriver");
dataSource.setUrl("jdbc:hsqldb:hsql://localhost:");
dataSource.setUsername("sa");
dataSource.setPassword("");

Kotlin

val dataSource = DriverManagerDataSource().apply {
    setDriverClassName("org.hsqldb.jdbcDriver")
    url = "jdbc:hsqldb:hsql://localhost:"
    username = "sa"
    password = ""
}

The following example shows the corresponding XML configuration:

<bean id="dataSource" class="org.springframework.jdbc.datasource.DriverManagerDataSource">
    <property name="driverClassName" value="${jdbc.driverClassName}"/>
    <property name="url" value="${jdbc.url}"/>
    <property name="username" value="${jdbc.username}"/>
    <property name="password" value="${jdbc.password}"/>
</bean>

<context:property-placeholder location="jdbc.properties"/>

The next two examples show the basic connectivity and configuration for DBCP and C3P0. To learn about more options that help control the pooling features, see the product documentation for the respective connection pooling implementations.

The following example shows DBCP configuration:

<bean id="dataSource" class="org.apache.commons.dbcp.BasicDataSource" destroy-method="close">
    <property name="driverClassName" value="${jdbc.driverClassName}"/>
    <property name="url" value="${jdbc.url}"/>
    <property name="username" value="${jdbc.username}"/>
    <property name="password" value="${jdbc.password}"/>
</bean>

<context:property-placeholder location="jdbc.properties"/>

The following example shows C3P0 configuration:

<bean id="dataSource" class="com.mchange.v2.c3p0.ComboPooledDataSource" destroy-method="close">
    <property name="driverClass" value="${jdbc.driverClassName}"/>
    <property name="jdbcUrl" value="${jdbc.url}"/>
    <property name="user" value="${jdbc.username}"/>
    <property name="password" value="${jdbc.password}"/>
</bean>

<context:property-placeholder location="jdbc.properties"/>

Using `DataSourceUtils`

The DataSourceUtils class is a convenient and powerful helper class that provides static methods to obtain connections from JNDI and close connections if necessary. It supports thread-bound connections with, for example, DataSourceTransactionManager.

Implementing `SmartDataSource`

The SmartDataSource interface should be implemented by classes that can provide a connection to a relational database. It extends the DataSource interface to let classes that use it query whether the connection should be closed after a given operation. This usage is efficient when you know that you need to reuse a connection.

Extending `AbstractDataSource`

AbstractDataSource is an abstract base class for Spring’s DataSource implementations. It implements code that is common to all DataSource implementations. You should extend the AbstractDataSource class if you write your own DataSource implementation.

Using `SingleConnectionDataSource`

The SingleConnectionDataSource class is an implementation of the SmartDataSource interface that wraps a single Connection that is not closed after each use. This is not multi-threading capable.

If any client code calls close on the assumption of a pooled connection (as when using persistence tools), you should set the suppressClose property to true. This setting returns a close-suppressing proxy that wraps the physical connection. Note that you can no longer cast this to a native Oracle Connection or a similar object.

SingleConnectionDataSource is primarily a test class. For example, it enables easy testing of code outside an application server, in conjunction with a simple JNDI environment. In contrast to DriverManagerDataSource, it reuses the same connection all the time, avoiding excessive creation of physical connections.

Using `DriverManagerDataSource`

The DriverManagerDataSource class is an implementation of the standard DataSource interface that configures a plain JDBC driver through bean properties and returns a new Connection every time.

This implementation is useful for test and stand-alone environments outside of a Java EE container, either as a DataSource bean in a Spring IoC container or in conjunction with a simple JNDI environment. Pool-assuming Connection.close() calls close the connection, so any DataSource-aware persistence code should work. However, using JavaBean-style connection pools (such as commons-dbcp) is so easy, even in a test environment, that it is almost always preferable to use such a connection pool over DriverManagerDataSource.

Using `TransactionAwareDataSourceProxy`

TransactionAwareDataSourceProxy is a proxy for a target DataSource. The proxy wraps that target DataSource to add awareness of Spring-managed transactions. In this respect, it is similar to a transactional JNDI DataSource, as provided by a Java EE server.

Note

It is rarely desirable to use this class, except when already existing code must be called and passed a standard JDBC DataSource interface implementation. In this case, you can still have this code be usable and, at the same time, have this code participating in Spring managed transactions. It is generally preferable to write your own new code by using the higher level abstractions for resource management, such as JdbcTemplate or DataSourceUtils.

See the TransactionAwareDataSourceProxy javadoc for more details.

Using `DataSourceTransactionManager`

The DataSourceTransactionManager class is a PlatformTransactionManager implementation for single JDBC datasources. It binds a JDBC connection from the specified data source to the currently executing thread, potentially allowing for one thread connection per data source.

Application code is required to retrieve the JDBC connection through DataSourceUtils.getConnection(DataSource) instead of Java EE’s standard DataSource.getConnection. It throws unchecked org.springframework.dao exceptions instead of checked SQLExceptions. All framework classes (such as JdbcTemplate) use this strategy implicitly. If not used with this transaction manager, the lookup strategy behaves exactly like the common one. Thus, it can be used in any case.

The DataSourceTransactionManager class supports custom isolation levels and timeouts that get applied as appropriate JDBC statement query timeouts. To support the latter, application code must either use JdbcTemplate or call the DataSourceUtils.applyTransactionTimeout(..) method for each created statement.

You can use this implementation instead of JtaTransactionManager in the single-resource case, as it does not require the container to support JTA. Switching between both is just a matter of configuration, provided you stick to the required connection lookup pattern. JTA does not support custom isolation levels.

JDBC Batch Operations

Most JDBC drivers provide improved performance if you batch multiple calls to the same prepared statement. By grouping updates into batches, you limit the number of round trips to the database.

Basic Batch Operations with `JdbcTemplate`

You accomplish JdbcTemplate batch processing by implementing two methods of a special interface, BatchPreparedStatementSetter, and passing that implementation in as the second parameter in your batchUpdate method call. You can use the getBatchSize method to provide the size of the current batch. You can use the setValues method to set the values for the parameters of the prepared statement. This method is called the number of times that you specified in the getBatchSize call. The following example updates the actor table based on entries in a list, and the entire list is used as the batch:

Java

public class JdbcActorDao implements ActorDao {

    private JdbcTemplate jdbcTemplate;

    public void setDataSource(DataSource dataSource) {
        this.jdbcTemplate = new JdbcTemplate(dataSource);
    }

    public int[] batchUpdate(final List<Actor> actors) {
        return this.jdbcTemplate.batchUpdate(
                "update t_actor set first_name = ?, last_name = ? where id = ?",
                new BatchPreparedStatementSetter() {
                    public void setValues(PreparedStatement ps, int i) throws SQLException {
                        ps.setString(1, actors.get(i).getFirstName());
                        ps.setString(2, actors.get(i).getLastName());
                        ps.setLong(3, actors.get(i).getId().longValue());
                    }
                    public int getBatchSize() {
                        return actors.size();
                    }
                });
    }

    // ... additional methods
}

Kotlin

class JdbcActorDao(dataSource: DataSource) : ActorDao {

    private val jdbcTemplate = JdbcTemplate(dataSource)

    fun batchUpdate(actors: List<Actor>): IntArray {
        return jdbcTemplate.batchUpdate(
                "update t_actor set first_name = ?, last_name = ? where id = ?",
                object: BatchPreparedStatementSetter {
                    override fun setValues(ps: PreparedStatement, i: Int) {
                        ps.setString(1, actors[i].firstName)
                        ps.setString(2, actors[i].lastName)
                        ps.setLong(3, actors[i].id)
                    }

                    override fun getBatchSize() = actors.size
                })
    }

    // ... additional methods
}

If you process a stream of updates or reading from a file, you might have a preferred batch size, but the last batch might not have that number of entries. In this case, you can use the InterruptibleBatchPreparedStatementSetter interface, which lets you interrupt a batch once the input source is exhausted. The isBatchExhausted method lets you signal the end of the batch.

Batch Operations with a List of Objects

Both the JdbcTemplate and the NamedParameterJdbcTemplate provides an alternate way of providing the batch update. Instead of implementing a special batch interface, you provide all parameter values in the call as a list. The framework loops over these values and uses an internal prepared statement setter. The API varies, depending on whether you use named parameters. For the named parameters, you provide an array of SqlParameterSource, one entry for each member of the batch. You can use the SqlParameterSourceUtils.createBatch convenience methods to create this array, passing in an array of bean-style objects (with getter methods corresponding to parameters), String-keyed Map instances (containing the corresponding parameters as values), or a mix of both.

The following example shows a batch update using named parameters:

Java

public class JdbcActorDao implements ActorDao {

    private NamedParameterTemplate namedParameterJdbcTemplate;

    public void setDataSource(DataSource dataSource) {
        this.namedParameterJdbcTemplate = new NamedParameterJdbcTemplate(dataSource);
    }

    public int[] batchUpdate(List<Actor> actors) {
        return this.namedParameterJdbcTemplate.batchUpdate(
                "update t_actor set first_name = :firstName, last_name = :lastName where id = :id",
                SqlParameterSourceUtils.createBatch(actors));
    }

    // ... additional methods
}

Kotlin

class JdbcActorDao(dataSource: DataSource) : ActorDao {

    private val namedParameterJdbcTemplate = NamedParameterJdbcTemplate(dataSource)

    fun batchUpdate(actors: List<Actor>): IntArray {
        return this.namedParameterJdbcTemplate.batchUpdate(
                "update t_actor set first_name = :firstName, last_name = :lastName where id = :id",
                SqlParameterSourceUtils.createBatch(actors));
    }

        // ... additional methods
}

For an SQL statement that uses the classic ? placeholders, you pass in a list containing an object array with the update values. This object array must have one entry for each placeholder in the SQL statement, and they must be in the same order as they are defined in the SQL statement.

The following example is the same as the preceding example, except that it uses classic JDBC ? placeholders:

Java

public class JdbcActorDao implements ActorDao {

    private JdbcTemplate jdbcTemplate;

    public void setDataSource(DataSource dataSource) {
        this.jdbcTemplate = new JdbcTemplate(dataSource);
    }

    public int[] batchUpdate(final List<Actor> actors) {
        List<Object[]> batch = new ArrayList<Object[]>();
        for (Actor actor : actors) {
            Object[] values = new Object[] {
                    actor.getFirstName(), actor.getLastName(), actor.getId()};
            batch.add(values);
        }
        return this.jdbcTemplate.batchUpdate(
                "update t_actor set first_name = ?, last_name = ? where id = ?",
                batch);
    }

    // ... additional methods
}

Kotlin

class JdbcActorDao(dataSource: DataSource) : ActorDao {

    private val jdbcTemplate = JdbcTemplate(dataSource)

    fun batchUpdate(actors: List<Actor>): IntArray {
        val batch = mutableListOf<Array<Any>>()
        for (actor in actors) {
            batch.add(arrayOf(actor.firstName, actor.lastName, actor.id))
        }
        return jdbcTemplate.batchUpdate(
                "update t_actor set first_name = ?, last_name = ? where id = ?", batch)
    }

    // ... additional methods
}

All of the batch update methods that we described earlier return an int array containing the number of affected rows for each batch entry. This count is reported by the JDBC driver. If the count is not available, the JDBC driver returns a value of -2.

Note

In such a scenario, with automatic setting of values on an underlying PreparedStatement, the corresponding JDBC type for each value needs to be derived from the given Java type. While this usually works well, there is a potential for issues (for example, with Map-contained null values). Spring, by default, calls ParameterMetaData.getParameterType in such a case, which can be expensive with your JDBC driver. You should use a recent driver version and consider setting the spring.jdbc.getParameterType.ignore property to true (as a JVM system property or in a spring.properties file in the root of your classpath) if you encounter a performance issue — for example, as reported on Oracle 12c (SPR-16139).

Alternatively, you might consider specifying the corresponding JDBC types explicitly, either through a 'BatchPreparedStatementSetter' (as shown earlier), through an explicit type array given to a 'List<Object[]>' based call, through 'registerSqlType' calls on a custom 'MapSqlParameterSource' instance, or through a 'BeanPropertySqlParameterSource' that derives the SQL type from the Java-declared property type even for a null value.

Batch Operations with Multiple Batches

The preceding example of a batch update deals with batches that are so large that you want to break them up into several smaller batches. You can do this with the methods mentioned earlier by making multiple calls to the batchUpdate method, but there is now a more convenient method. This method takes, in addition to the SQL statement, a Collection of objects that contain the parameters, the number of updates to make for each batch, and a ParameterizedPreparedStatementSetter to set the values for the parameters of the prepared statement. The framework loops over the provided values and breaks the update calls into batches of the size specified.

The following example shows a batch update that uses a batch size of 100:

Java

public class JdbcActorDao implements ActorDao {

    private JdbcTemplate jdbcTemplate;

    public void setDataSource(DataSource dataSource) {
        this.jdbcTemplate = new JdbcTemplate(dataSource);
    }

    public int[][] batchUpdate(final Collection<Actor> actors) {
        int[][] updateCounts = jdbcTemplate.batchUpdate(
                "update t_actor set first_name = ?, last_name = ? where id = ?",
                actors,
                100,
                new ParameterizedPreparedStatementSetter<Actor>() {
                    public void setValues(PreparedStatement ps, Actor argument) throws SQLException {
                        ps.setString(1, argument.getFirstName());
                        ps.setString(2, argument.getLastName());
                        ps.setLong(3, argument.getId().longValue());
                    }
                });
        return updateCounts;
    }

    // ... additional methods
}

Kotlin

class JdbcActorDao(dataSource: DataSource) : ActorDao {

    private val jdbcTemplate = JdbcTemplate(dataSource)

    fun batchUpdate(actors: List<Actor>): Array<IntArray> {
        return jdbcTemplate.batchUpdate(
                    "update t_actor set first_name = ?, last_name = ? where id = ?",
                    actors, 100) { ps, argument ->
            ps.setString(1, argument.firstName)
            ps.setString(2, argument.lastName)
            ps.setLong(3, argument.id)
        }
    }

    // ... additional methods
}

The batch update methods for this call returns an array of int arrays that contain an array entry for each batch with an array of the number of affected rows for each update. The top level array’s length indicates the number of batches executed and the second level array’s length indicates the number of updates in that batch. The number of updates in each batch should be the batch size provided for all batches (except that the last one that might be less), depending on the total number of update objects provided. The update count for each update statement is the one reported by the JDBC driver. If the count is not available, the JDBC driver returns a value of -2.

Simplifying JDBC Operations with the `SimpleJdbc` Classes

The SimpleJdbcInsert and SimpleJdbcCall classes provide a simplified configuration by taking advantage of database metadata that can be retrieved through the JDBC driver. This means that you have less to configure up front, although you can override or turn off the metadata processing if you prefer to provide all the details in your code.

Inserting Data by Using `SimpleJdbcInsert`

We start by looking at the SimpleJdbcInsert class with the minimal amount of configuration options. You should instantiate the SimpleJdbcInsert in the data access layer’s initialization method. For this example, the initializing method is the setDataSource method. You do not need to subclass the SimpleJdbcInsert class. Instead, you can create a new instance and set the table name by using the withTableName method. Configuration methods for this class follow the fluid style that returns the instance of the SimpleJdbcInsert, which lets you chain all configuration methods. The following example uses only one configuration method (we show examples of multiple methods later):

Java

public class JdbcActorDao implements ActorDao {

    private JdbcTemplate jdbcTemplate;
    private SimpleJdbcInsert insertActor;

    public void setDataSource(DataSource dataSource) {
        this.jdbcTemplate = new JdbcTemplate(dataSource);
        this.insertActor = new SimpleJdbcInsert(dataSource).withTableName("t_actor");
    }

    public void add(Actor actor) {
        Map<String, Object> parameters = new HashMap<String, Object>(3);
        parameters.put("id", actor.getId());
        parameters.put("first_name", actor.getFirstName());
        parameters.put("last_name", actor.getLastName());
        insertActor.execute(parameters);
    }

    // ... additional methods
}

Kotlin

class JdbcActorDao(dataSource: DataSource) : ActorDao {

    private val jdbcTemplate = JdbcTemplate(dataSource)
    private val insertActor = SimpleJdbcInsert(dataSource).withTableName("t_actor")

    fun add(actor: Actor) {
        val parameters = mutableMapOf<String, Any>()
        parameters["id"] = actor.id
        parameters["first_name"] = actor.firstName
        parameters["last_name"] = actor.lastName
        insertActor.execute(parameters)
    }

    // ... additional methods
}

The execute method used here takes a plain java.util.Map as its only parameter. The important thing to note here is that the keys used for the Map must match the column names of the table, as defined in the database. This is because we read the metadata to construct the actual insert statement.

Retrieving Auto-generated Keys by Using `SimpleJdbcInsert`

The next example uses the same insert as the preceding example, but, instead of passing in the id, it retrieves the auto-generated key and sets it on the new Actor object. When it creates the SimpleJdbcInsert, in addition to specifying the table name, it specifies the name of the generated key column with the usingGeneratedKeyColumns method. The following listing shows how it works:

Java

public class JdbcActorDao implements ActorDao {

    private JdbcTemplate jdbcTemplate;
    private SimpleJdbcInsert insertActor;

    public void setDataSource(DataSource dataSource) {
        this.jdbcTemplate = new JdbcTemplate(dataSource);
        this.insertActor = new SimpleJdbcInsert(dataSource)
                .withTableName("t_actor")
                .usingGeneratedKeyColumns("id");
    }

    public void add(Actor actor) {
        Map<String, Object> parameters = new HashMap<String, Object>(2);
        parameters.put("first_name", actor.getFirstName());
        parameters.put("last_name", actor.getLastName());
        Number newId = insertActor.executeAndReturnKey(parameters);
        actor.setId(newId.longValue());
    }

    // ... additional methods
}

Kotlin

class JdbcActorDao(dataSource: DataSource) : ActorDao {

    private val jdbcTemplate = JdbcTemplate(dataSource)
    private val insertActor = SimpleJdbcInsert(dataSource)
            .withTableName("t_actor").usingGeneratedKeyColumns("id")

    fun add(actor: Actor): Actor {
        val parameters = mapOf(
                "first_name" to actor.firstName,
                "last_name" to actor.lastName)
        val newId = insertActor.executeAndReturnKey(parameters);
        return actor.copy(id = newId.toLong())
    }

    // ... additional methods
}

The main difference when you run the insert by using this second approach is that you do not add the id to the Map, and you call the executeAndReturnKey method. This returns a java.lang.Number object with which you can create an instance of the numerical type that is used in your domain class. You cannot rely on all databases to return a specific Java class here. java.lang.Number is the base class that you can rely on. If you have multiple auto-generated columns or the generated values are non-numeric, you can use a KeyHolder that is returned from the executeAndReturnKeyHolder method.

Specifying Columns for a `SimpleJdbcInsert`

You can limit the columns for an insert by specifying a list of column names with the usingColumns method, as the following example shows:

Java

public class JdbcActorDao implements ActorDao {

    private JdbcTemplate jdbcTemplate;
    private SimpleJdbcInsert insertActor;

    public void setDataSource(DataSource dataSource) {
        this.jdbcTemplate = new JdbcTemplate(dataSource);
        this.insertActor = new SimpleJdbcInsert(dataSource)
                .withTableName("t_actor")
                .usingColumns("first_name", "last_name")
                .usingGeneratedKeyColumns("id");
    }

    public void add(Actor actor) {
        Map<String, Object> parameters = new HashMap<String, Object>(2);
        parameters.put("first_name", actor.getFirstName());
        parameters.put("last_name", actor.getLastName());
        Number newId = insertActor.executeAndReturnKey(parameters);
        actor.setId(newId.longValue());
    }

    // ... additional methods
}

Kotlin

class JdbcActorDao(dataSource: DataSource) : ActorDao {

    private val jdbcTemplate = JdbcTemplate(dataSource)
    private val insertActor = SimpleJdbcInsert(dataSource)
            .withTableName("t_actor")
            .usingColumns("first_name", "last_name")
            .usingGeneratedKeyColumns("id")

    fun add(actor: Actor): Actor {
        val parameters = mapOf(
                "first_name" to actor.firstName,
                "last_name" to actor.lastName)
        val newId = insertActor.executeAndReturnKey(parameters);
        return actor.copy(id = newId.toLong())
    }

    // ... additional methods
}

The execution of the insert is the same as if you had relied on the metadata to determine which columns to use.

Using `SqlParameterSource` to Provide Parameter Values

Using a Map to provide parameter values works fine, but it is not the most convenient class to use. Spring provides a couple of implementations of the SqlParameterSource interface that you can use instead. The first one is BeanPropertySqlParameterSource, which is a very convenient class if you have a JavaBean-compliant class that contains your values. It uses the corresponding getter method to extract the parameter values. The following example shows how to use BeanPropertySqlParameterSource:

Java

public class JdbcActorDao implements ActorDao {

    private JdbcTemplate jdbcTemplate;
    private SimpleJdbcInsert insertActor;

    public void setDataSource(DataSource dataSource) {
        this.jdbcTemplate = new JdbcTemplate(dataSource);
        this.insertActor = new SimpleJdbcInsert(dataSource)
                .withTableName("t_actor")
                .usingGeneratedKeyColumns("id");
    }

    public void add(Actor actor) {
        SqlParameterSource parameters = new BeanPropertySqlParameterSource(actor);
        Number newId = insertActor.executeAndReturnKey(parameters);
        actor.setId(newId.longValue());
    }

    // ... additional methods
}

Kotlin

class JdbcActorDao(dataSource: DataSource) : ActorDao {

    private val jdbcTemplate = JdbcTemplate(dataSource)
    private val insertActor = SimpleJdbcInsert(dataSource)
            .withTableName("t_actor")
            .usingGeneratedKeyColumns("id")

    fun add(actor: Actor): Actor {
        val parameters = BeanPropertySqlParameterSource(actor)
        val newId = insertActor.executeAndReturnKey(parameters)
        return actor.copy(id = newId.toLong())
    }

    // ... additional methods
}

Another option is the MapSqlParameterSource that resembles a Map but provides a more convenient addValue method that can be chained. The following example shows how to use it:

Java

public class JdbcActorDao implements ActorDao {

    private JdbcTemplate jdbcTemplate;
    private SimpleJdbcInsert insertActor;

    public void setDataSource(DataSource dataSource) {
        this.jdbcTemplate = new JdbcTemplate(dataSource);
        this.insertActor = new SimpleJdbcInsert(dataSource)
                .withTableName("t_actor")
                .usingGeneratedKeyColumns("id");
    }

    public void add(Actor actor) {
        SqlParameterSource parameters = new MapSqlParameterSource()
                .addValue("first_name", actor.getFirstName())
                .addValue("last_name", actor.getLastName());
        Number newId = insertActor.executeAndReturnKey(parameters);
        actor.setId(newId.longValue());
    }

    // ... additional methods
}

Kotlin

class JdbcActorDao(dataSource: DataSource) : ActorDao {

    private val jdbcTemplate = JdbcTemplate(dataSource)
    private val insertActor = SimpleJdbcInsert(dataSource)
            .withTableName("t_actor")
            .usingGeneratedKeyColumns("id")

    fun add(actor: Actor): Actor {
        val parameters = MapSqlParameterSource()
                    .addValue("first_name", actor.firstName)
                    .addValue("last_name", actor.lastName)
        val newId = insertActor.executeAndReturnKey(parameters)
        return actor.copy(id = newId.toLong())
    }

    // ... additional methods
}

As you can see, the configuration is the same. Only the executing code has to change to use these alternative input classes.

Calling a Stored Procedure with `SimpleJdbcCall`

The SimpleJdbcCall class uses metadata in the database to look up names of in and out parameters so that you do not have to explicitly declare them. You can declare parameters if you prefer to do that or if you have parameters (such as ARRAY or STRUCT) that do not have an automatic mapping to a Java class. The first example shows a simple procedure that returns only scalar values in VARCHAR and DATE format from a MySQL database. The example procedure reads a specified actor entry and returns first_name, last_name, and birth_date columns in the form of out parameters. The following listing shows the first example:

CREATE PROCEDURE read_actor (
    IN in_id INTEGER,
    OUT out_first_name VARCHAR(100),
    OUT out_last_name VARCHAR(100),
    OUT out_birth_date DATE)
BEGIN
    SELECT first_name, last_name, birth_date
    INTO out_first_name, out_last_name, out_birth_date
    FROM t_actor where id = in_id;
END;

The in_id parameter contains the id of the actor that you are looking up. The out parameters return the data read from the table.

You can declare SimpleJdbcCall in a manner similar to declaring SimpleJdbcInsert. You should instantiate and configure the class in the initialization method of your data-access layer. Compared to the StoredProcedure class, you need not create a subclass and you need not to declare parameters that can be looked up in the database metadata. The following example of a SimpleJdbcCall configuration uses the preceding stored procedure (the only configuration option, in addition to the DataSource, is the name of the stored procedure):

Java

public class JdbcActorDao implements ActorDao {

    private JdbcTemplate jdbcTemplate;
    private SimpleJdbcCall procReadActor;

    public void setDataSource(DataSource dataSource) {
        this.jdbcTemplate = new JdbcTemplate(dataSource);
        this.procReadActor = new SimpleJdbcCall(dataSource)
                .withProcedureName("read_actor");
    }

    public Actor readActor(Long id) {
        SqlParameterSource in = new MapSqlParameterSource()
                .addValue("in_id", id);
        Map out = procReadActor.execute(in);
        Actor actor = new Actor();
        actor.setId(id);
        actor.setFirstName((String) out.get("out_first_name"));
        actor.setLastName((String) out.get("out_last_name"));
        actor.setBirthDate((Date) out.get("out_birth_date"));
        return actor;
    }

    // ... additional methods
}

Kotlin

class JdbcActorDao(dataSource: DataSource) : ActorDao {

    private val jdbcTemplate = JdbcTemplate(dataSource)
    private val procReadActor = SimpleJdbcCall(dataSource)
            .withProcedureName("read_actor")


    fun readActor(id: Long): Actor {
        val source = MapSqlParameterSource().addValue("in_id", id)
        val output = procReadActor.execute(source)
        return Actor(
                id,
                output["out_first_name"] as String,
                output["out_last_name"] as String,
                output["out_birth_date"] as Date)
    }

        // ... additional methods
}

The code you write for the execution of the call involves creating an SqlParameterSource containing the IN parameter. You must match the name provided for the input value with that of the parameter name declared in the stored procedure. The case does not have to match because you use metadata to determine how database objects should be referred to in a stored procedure. What is specified in the source for the stored procedure is not necessarily the way it is stored in the database. Some databases transform names to all upper case, while others use lower case or use the case as specified.

The execute method takes the IN parameters and returns a Map that contains any out parameters keyed by the name, as specified in the stored procedure. In this case, they are out_first_name, out_last_name, and out_birth_date.

The last part of the execute method creates an Actor instance to use to return the data retrieved. Again, it is important to use the names of the out parameters as they are declared in the stored procedure. Also, the case in the names of the out parameters stored in the results map matches that of the out parameter names in the database, which could vary between databases. To make your code more portable, you should do a case-insensitive lookup or instruct Spring to use a LinkedCaseInsensitiveMap. To do the latter, you can create your own JdbcTemplate and set the setResultsMapCaseInsensitive property to true. Then you can pass this customized JdbcTemplate instance into the constructor of your SimpleJdbcCall. The following example shows this configuration:

Java

public class JdbcActorDao implements ActorDao {

    private SimpleJdbcCall procReadActor;

    public void setDataSource(DataSource dataSource) {
        JdbcTemplate jdbcTemplate = new JdbcTemplate(dataSource);
        jdbcTemplate.setResultsMapCaseInsensitive(true);
        this.procReadActor = new SimpleJdbcCall(jdbcTemplate)
                .withProcedureName("read_actor");
    }

    // ... additional methods
}

Kotlin

class JdbcActorDao(dataSource: DataSource) : ActorDao {

    private var procReadActor = SimpleJdbcCall(JdbcTemplate(dataSource).apply {
        isResultsMapCaseInsensitive = true
    }).withProcedureName("read_actor")

    // ... additional methods
}

By taking this action, you avoid conflicts in the case used for the names of your returned out parameters.

Explicitly Declaring Parameters to Use for a `SimpleJdbcCall`

Earlier in this chapter, we described how parameters are deduced from metadata, but you can declare them explicitly if you wish. You can do so by creating and configuring SimpleJdbcCall with the declareParameters method, which takes a variable number of SqlParameter objects as input. See the next section for details on how to define an SqlParameter.

Note

Explicit declarations are necessary if the database you use is not a Spring-supported database. Currently, Spring supports metadata lookup of stored procedure calls for the following databases: Apache Derby, DB2, MySQL, Microsoft SQL Server, Oracle, and Sybase. We also support metadata lookup of stored functions for MySQL, Microsoft SQL Server, and Oracle.

You can opt to explicitly declare one, some, or all of the parameters. The parameter metadata is still used where you do not explicitly declare parameters. To bypass all processing of metadata lookups for potential parameters and use only the declared parameters, you can call the method withoutProcedureColumnMetaDataAccess as part of the declaration. Suppose that you have two or more different call signatures declared for a database function. In this case, you call useInParameterNames to specify the list of IN parameter names to include for a given signature.

The following example shows a fully declared procedure call and uses the information from the preceding example:

Java

public class JdbcActorDao implements ActorDao {

    private SimpleJdbcCall procReadActor;

    public void setDataSource(DataSource dataSource) {
        JdbcTemplate jdbcTemplate = new JdbcTemplate(dataSource);
        jdbcTemplate.setResultsMapCaseInsensitive(true);
        this.procReadActor = new SimpleJdbcCall(jdbcTemplate)
                .withProcedureName("read_actor")
                .withoutProcedureColumnMetaDataAccess()
                .useInParameterNames("in_id")
                .declareParameters(
                        new SqlParameter("in_id", Types.NUMERIC),
                        new SqlOutParameter("out_first_name", Types.VARCHAR),
                        new SqlOutParameter("out_last_name", Types.VARCHAR),
                        new SqlOutParameter("out_birth_date", Types.DATE)
                );
    }

    // ... additional methods
}

Kotlin

class JdbcActorDao(dataSource: DataSource) : ActorDao {

        private val procReadActor = SimpleJdbcCall(JdbcTemplate(dataSource).apply {
            isResultsMapCaseInsensitive = true
        }).withProcedureName("read_actor")
                .withoutProcedureColumnMetaDataAccess()
                .useInParameterNames("in_id")
                .declareParameters(
                        SqlParameter("in_id", Types.NUMERIC),
                        SqlOutParameter("out_first_name", Types.VARCHAR),
                        SqlOutParameter("out_last_name", Types.VARCHAR),
                        SqlOutParameter("out_birth_date", Types.DATE)
    )

        // ... additional methods
}

The execution and end results of the two examples are the same. The second example specifies all details explicitly rather than relying on metadata.

How to Define `SqlParameters`

To define a parameter for the SimpleJdbc classes and also for the RDBMS operations classes (covered in Modeling JDBC Operations as Java Objects) you can use SqlParameter or one of its subclasses. To do so, you typically specify the parameter name and SQL type in the constructor. The SQL type is specified by using the java.sql.Types constants. Earlier in this chapter, we saw declarations similar to the following:

Java

new SqlParameter("in_id", Types.NUMERIC),
new SqlOutParameter("out_first_name", Types.VARCHAR),

Kotlin

SqlParameter("in_id", Types.NUMERIC),
SqlOutParameter("out_first_name", Types.VARCHAR),

The first line with the SqlParameter declares an IN parameter. You can use IN parameters for both stored procedure calls and for queries by using the SqlQuery and its subclasses (covered in Understanding SqlQuery).

The second line (with the SqlOutParameter) declares an out parameter to be used in a stored procedure call. There is also an SqlInOutParameter for InOut parameters (parameters that provide an IN value to the procedure and that also return a value).

Note	Only parameters declared as `SqlParameter` and `SqlInOutParameter` are used to provide input values. This is different from the `StoredProcedure` class, which (for backwards compatibility reasons) lets input values be provided for parameters declared as `SqlOutParameter`.

For IN parameters, in addition to the name and the SQL type, you can specify a scale for numeric data or a type name for custom database types. For out parameters, you can provide a RowMapper to handle mapping of rows returned from a REF cursor. Another option is to specify an SqlReturnType that provides an opportunity to define customized handling of the return values.

Calling a Stored Function by Using `SimpleJdbcCall`

You can call a stored function in almost the same way as you call a stored procedure, except that you provide a function name rather than a procedure name. You use the withFunctionName method as part of the configuration to indicate that you want to make a call to a function, and the corresponding string for a function call is generated. A specialized execute call (executeFunction) is used to execute the function, and it returns the function return value as an object of a specified type, which means you do not have to retrieve the return value from the results map. A similar convenience method (named executeObject) is also available for stored procedures that have only one out parameter. The following example (for MySQL) is based on a stored function named get_actor_name that returns an actor’s full name:

CREATE FUNCTION get_actor_name (in_id INTEGER)
RETURNS VARCHAR(200) READS SQL DATA
BEGIN
    DECLARE out_name VARCHAR(200);
    SELECT concat(first_name, ' ', last_name)
        INTO out_name
        FROM t_actor where id = in_id;
    RETURN out_name;
END;

To call this function, we again create a SimpleJdbcCall in the initialization method, as the following example shows:

Java

public class JdbcActorDao implements ActorDao {

    private JdbcTemplate jdbcTemplate;
    private SimpleJdbcCall funcGetActorName;

    public void setDataSource(DataSource dataSource) {
        this.jdbcTemplate = new JdbcTemplate(dataSource);
        JdbcTemplate jdbcTemplate = new JdbcTemplate(dataSource);
        jdbcTemplate.setResultsMapCaseInsensitive(true);
        this.funcGetActorName = new SimpleJdbcCall(jdbcTemplate)
                .withFunctionName("get_actor_name");
    }

    public String getActorName(Long id) {
        SqlParameterSource in = new MapSqlParameterSource()
                .addValue("in_id", id);
        String name = funcGetActorName.executeFunction(String.class, in);
        return name;
    }

    // ... additional methods
}

Kotlin

class JdbcActorDao(dataSource: DataSource) : ActorDao {

    private val jdbcTemplate = JdbcTemplate(dataSource).apply {
        isResultsMapCaseInsensitive = true
    }
    private val funcGetActorName = SimpleJdbcCall(jdbcTemplate)
            .withFunctionName("get_actor_name")

    fun getActorName(id: Long): String {
        val source = MapSqlParameterSource().addValue("in_id", id)
        return funcGetActorName.executeFunction(String::class.java, source)
    }

    // ... additional methods
}

The executeFunction method used returns a String that contains the return value from the function call.

Returning a `ResultSet` or REF Cursor from a `SimpleJdbcCall`

Calling a stored procedure or function that returns a result set is a bit tricky. Some databases return result sets during the JDBC results processing, while others require an explicitly registered out parameter of a specific type. Both approaches need additional processing to loop over the result set and process the returned rows. With the SimpleJdbcCall, you can use the returningResultSet method and declare a RowMapper implementation to be used for a specific parameter. If the result set is returned during the results processing, there are no names defined, so the returned results must match the order in which you declare the RowMapper implementations. The name specified is still used to store the processed list of results in the results map that is returned from the execute statement.

The next example (for MySQL) uses a stored procedure that takes no IN parameters and returns all rows from the t_actor table:

CREATE PROCEDURE read_all_actors()
BEGIN
 SELECT a.id, a.first_name, a.last_name, a.birth_date FROM t_actor a;
END;

To call this procedure, you can declare the RowMapper. Because the class to which you want to map follows the JavaBean rules, you can use a BeanPropertyRowMapper that is created by passing in the required class to map to in the newInstance method. The following example shows how to do so:

Java

public class JdbcActorDao implements ActorDao {

    private SimpleJdbcCall procReadAllActors;

    public void setDataSource(DataSource dataSource) {
        JdbcTemplate jdbcTemplate = new JdbcTemplate(dataSource);
        jdbcTemplate.setResultsMapCaseInsensitive(true);
        this.procReadAllActors = new SimpleJdbcCall(jdbcTemplate)
                .withProcedureName("read_all_actors")
                .returningResultSet("actors",
                BeanPropertyRowMapper.newInstance(Actor.class));
    }

    public List getActorsList() {
        Map m = procReadAllActors.execute(new HashMap<String, Object>(0));
        return (List) m.get("actors");
    }

    // ... additional methods
}

Kotlin

class JdbcActorDao(dataSource: DataSource) : ActorDao {

        private val procReadAllActors = SimpleJdbcCall(JdbcTemplate(dataSource).apply {
            isResultsMapCaseInsensitive = true
        }).withProcedureName("read_all_actors")
                .returningResultSet("actors",
                        BeanPropertyRowMapper.newInstance(Actor::class.java))

    fun getActorsList(): List<Actor> {
        val m = procReadAllActors.execute(mapOf<String, Any>())
        return m["actors"] as List<Actor>
    }

    // ... additional methods
}

The execute call passes in an empty Map, because this call does not take any parameters. The list of actors is then retrieved from the results map and returned to the caller.

Modeling JDBC Operations as Java Objects

The org.springframework.jdbc.object package contains classes that let you access the database in a more object-oriented manner. As an example, you can execute queries and get the results back as a list that contains business objects with the relational column data mapped to the properties of the business object. You can also run stored procedures and run update, delete, and insert statements.

Note

Many Spring developers believe that the various RDBMS operation classes described below (with the exception of the StoredProcedure class) can often be replaced with straight JdbcTemplate calls. Often, it is simpler to write a DAO method that calls a method on a JdbcTemplate directly (as opposed to encapsulating a query as a full-blown class).

However, if you are getting measurable value from using the RDBMS operation classes, you should continue to use these classes.

Understanding `SqlQuery`

SqlQuery is a reusable, thread-safe class that encapsulates an SQL query. Subclasses must implement the newRowMapper(..) method to provide a RowMapper instance that can create one object per row obtained from iterating over the ResultSet that is created during the execution of the query. The SqlQuery class is rarely used directly, because the MappingSqlQuery subclass provides a much more convenient implementation for mapping rows to Java classes. Other implementations that extend SqlQuery are MappingSqlQueryWithParameters and UpdatableSqlQuery.

Using `MappingSqlQuery`

MappingSqlQuery is a reusable query in which concrete subclasses must implement the abstract mapRow(..) method to convert each row of the supplied ResultSet into an object of the type specified. The following example shows a custom query that maps the data from the t_actor relation to an instance of the Actor class:

Java

public class ActorMappingQuery extends MappingSqlQuery<Actor> {

    public ActorMappingQuery(DataSource ds) {
        super(ds, "select id, first_name, last_name from t_actor where id = ?");
        declareParameter(new SqlParameter("id", Types.INTEGER));
        compile();
    }

    @Override
    protected Actor mapRow(ResultSet rs, int rowNumber) throws SQLException {
        Actor actor = new Actor();
        actor.setId(rs.getLong("id"));
        actor.setFirstName(rs.getString("first_name"));
        actor.setLastName(rs.getString("last_name"));
        return actor;
    }
}

Kotlin

class ActorMappingQuery(ds: DataSource) : MappingSqlQuery<Actor>(ds, "select id, first_name, last_name from t_actor where id = ?") {

    init {
        declareParameter(SqlParameter("id", Types.INTEGER))
        compile()
    }

    override fun mapRow(rs: ResultSet, rowNumber: Int) = Actor(
            rs.getLong("id"),
            rs.getString("first_name"),
            rs.getString("last_name")
    )
}

The class extends MappingSqlQuery parameterized with the Actor type. The constructor for this customer query takes a DataSource as the only parameter. In this constructor, you can call the constructor on the superclass with the DataSource and the SQL that should be executed to retrieve the rows for this query. This SQL is used to create a PreparedStatement, so it may contain placeholders for any parameters to be passed in during execution. You must declare each parameter by using the declareParameter method passing in an SqlParameter. The SqlParameter takes a name, and the JDBC type as defined in java.sql.Types. After you define all parameters, you can call the compile() method so that the statement can be prepared and later run. This class is thread-safe after it is compiled, so, as long as these instances are created when the DAO is initialized, they can be kept as instance variables and be reused. The following example shows how to define such a class:

Java

private ActorMappingQuery actorMappingQuery;

@Autowired
public void setDataSource(DataSource dataSource) {
    this.actorMappingQuery = new ActorMappingQuery(dataSource);
}

public Customer getCustomer(Long id) {
    return actorMappingQuery.findObject(id);
}

Kotlin

private val actorMappingQuery = ActorMappingQuery(dataSource)

fun getCustomer(id: Long) = actorMappingQuery.findObject(id)

The method in the preceding example retrieves the customer with the id that is passed in as the only parameter. Since we want only one object to be returned, we call the findObject convenience method with the id as the parameter. If we had instead a query that returned a list of objects and took additional parameters, we would use one of the execute methods that takes an array of parameter values passed in as varargs. The following example shows such a method:

Java

public List<Actor> searchForActors(int age, String namePattern) {
    List<Actor> actors = actorSearchMappingQuery.execute(age, namePattern);
    return actors;
}

Kotlin

fun searchForActors(age: Int, namePattern: String) =
            actorSearchMappingQuery.execute(age, namePattern)

Using `SqlUpdate`

The SqlUpdate class encapsulates an SQL update. As with a query, an update object is reusable, and, as with all RdbmsOperation classes, an update can have parameters and is defined in SQL. This class provides a number of update(..) methods analogous to the execute(..) methods of query objects. The SQLUpdate class is concrete. It can be subclassed — for example, to add a custom update method. However, you do not have to subclass the SqlUpdate class, since it can easily be parameterized by setting SQL and declaring parameters. The following example creates a custom update method named execute:

Java

import java.sql.Types;
import javax.sql.DataSource;
import org.springframework.jdbc.core.SqlParameter;
import org.springframework.jdbc.object.SqlUpdate;

public class UpdateCreditRating extends SqlUpdate {

    public UpdateCreditRating(DataSource ds) {
        setDataSource(ds);
        setSql("update customer set credit_rating = ? where id = ?");
        declareParameter(new SqlParameter("creditRating", Types.NUMERIC));
        declareParameter(new SqlParameter("id", Types.NUMERIC));
        compile();
    }

    /**
     * @param id for the Customer to be updated
     * @param rating the new value for credit rating
     * @return number of rows updated
     */
    public int execute(int id, int rating) {
        return update(rating, id);
    }
}

Kotlin

import java.sql.Types
import javax.sql.DataSource
import org.springframework.jdbc.core.SqlParameter
import org.springframework.jdbc.object.SqlUpdate

class UpdateCreditRating(ds: DataSource) : SqlUpdate() {

    init {
        setDataSource(ds)
        sql = "update customer set credit_rating = ? where id = ?"
        declareParameter(SqlParameter("creditRating", Types.NUMERIC))
        declareParameter(SqlParameter("id", Types.NUMERIC))
        compile()
    }

    /**
    * @param id for the Customer to be updated
    * @param rating the new value for credit rating
    * @return number of rows updated
    */
    fun execute(id: Int, rating: Int): Int {
        return update(rating, id)
    }
}

Using `StoredProcedure`

The StoredProcedure class is a superclass for object abstractions of RDBMS stored procedures. This class is abstract, and its various execute(..) methods have protected access, preventing use other than through a subclass that offers tighter typing.

The inherited sql property is the name of the stored procedure in the RDBMS.

To define a parameter for the StoredProcedure class, you can use an SqlParameter or one of its subclasses. You must specify the parameter name and SQL type in the constructor, as the following code snippet shows:

Java

new SqlParameter("in_id", Types.NUMERIC),
new SqlOutParameter("out_first_name", Types.VARCHAR),

Kotlin

SqlParameter("in_id", Types.NUMERIC),
SqlOutParameter("out_first_name", Types.VARCHAR),

The SQL type is specified using the java.sql.Types constants.

The first line (with the SqlParameter) declares an IN parameter. You can use IN parameters both for stored procedure calls and for queries using the SqlQuery and its subclasses (covered in Understanding SqlQuery).

The second line (with the SqlOutParameter) declares an out parameter to be used in the stored procedure call. There is also an SqlInOutParameter for InOut parameters (parameters that provide an in value to the procedure and that also return a value).

For in parameters, in addition to the name and the SQL type, you can specify a scale for numeric data or a type name for custom database types. For out parameters, you can provide a RowMapper to handle mapping of rows returned from a REF cursor. Another option is to specify an SqlReturnType that lets you define customized handling of the return values.

The next example of a simple DAO uses a StoredProcedure to call a function (sysdate()), which comes with any Oracle database. To use the stored procedure functionality, you have to create a class that extends StoredProcedure. In this example, the StoredProcedure class is an inner class. However, if you need to reuse the StoredProcedure, you can declare it as a top-level class. This example has no input parameters, but an output parameter is declared as a date type by using the SqlOutParameter class. The execute() method runs the procedure and extracts the returned date from the results Map. The results Map has an entry for each declared output parameter (in this case, only one) by using the parameter name as the key. The following listing shows our custom StoredProcedure class:

Java

import java.sql.Types;
import java.util.Date;
import java.util.HashMap;
import java.util.Map;
import javax.sql.DataSource;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.jdbc.core.SqlOutParameter;
import org.springframework.jdbc.object.StoredProcedure;

public class StoredProcedureDao {

    private GetSysdateProcedure getSysdate;

    @Autowired
    public void init(DataSource dataSource) {
        this.getSysdate = new GetSysdateProcedure(dataSource);
    }

    public Date getSysdate() {
        return getSysdate.execute();
    }

    private class GetSysdateProcedure extends StoredProcedure {

        private static final String SQL = "sysdate";

        public GetSysdateProcedure(DataSource dataSource) {
            setDataSource(dataSource);
            setFunction(true);
            setSql(SQL);
            declareParameter(new SqlOutParameter("date", Types.DATE));
            compile();
        }

        public Date execute() {
            // the 'sysdate' sproc has no input parameters, so an empty Map is supplied...
            Map<String, Object> results = execute(new HashMap<String, Object>());
            Date sysdate = (Date) results.get("date");
            return sysdate;
        }
    }

}

Kotlin

import java.sql.Types
import java.util.Date
import java.util.Map
import javax.sql.DataSource
import org.springframework.jdbc.core.SqlOutParameter
import org.springframework.jdbc.object.StoredProcedure

class StoredProcedureDao(dataSource: DataSource) {

    private val SQL = "sysdate"

    private val getSysdate = GetSysdateProcedure(dataSource)

    val sysdate: Date
        get() = getSysdate.execute()

    private inner class GetSysdateProcedure(dataSource: DataSource) : StoredProcedure() {

        init {
            setDataSource(dataSource)
            isFunction = true
            sql = SQL
            declareParameter(SqlOutParameter("date", Types.DATE))
            compile()
        }

        fun execute(): Date {
            // the 'sysdate' sproc has no input parameters, so an empty Map is supplied...
            val results = execute(mutableMapOf<String, Any>())
            return results["date"] as Date
        }
    }
}

The following example of a StoredProcedure has two output parameters (in this case, Oracle REF cursors):

Java

import java.util.HashMap;
import java.util.Map;
import javax.sql.DataSource;
import oracle.jdbc.OracleTypes;
import org.springframework.jdbc.core.SqlOutParameter;
import org.springframework.jdbc.object.StoredProcedure;

public class TitlesAndGenresStoredProcedure extends StoredProcedure {

    private static final String SPROC_NAME = "AllTitlesAndGenres";

    public TitlesAndGenresStoredProcedure(DataSource dataSource) {
        super(dataSource, SPROC_NAME);
        declareParameter(new SqlOutParameter("titles", OracleTypes.CURSOR, new TitleMapper()));
        declareParameter(new SqlOutParameter("genres", OracleTypes.CURSOR, new GenreMapper()));
        compile();
    }

    public Map<String, Object> execute() {
        // again, this sproc has no input parameters, so an empty Map is supplied
        return super.execute(new HashMap<String, Object>());
    }
}

Kotlin

import java.util.HashMap
import javax.sql.DataSource
import oracle.jdbc.OracleTypes
import org.springframework.jdbc.core.SqlOutParameter
import org.springframework.jdbc.object.StoredProcedure

class TitlesAndGenresStoredProcedure(dataSource: DataSource) : StoredProcedure(dataSource, SPROC_NAME) {

    companion object {
        private const val SPROC_NAME = "AllTitlesAndGenres"
    }

    init {
        declareParameter(SqlOutParameter("titles", OracleTypes.CURSOR, TitleMapper()))
        declareParameter(SqlOutParameter("genres", OracleTypes.CURSOR, GenreMapper()))
        compile()
    }

    fun execute(): Map<String, Any> {
        // again, this sproc has no input parameters, so an empty Map is supplied
        return super.execute(HashMap<String, Any>())
    }
}

Notice how the overloaded variants of the declareParameter(..) method that have been used in the TitlesAndGenresStoredProcedure constructor are passed RowMapper implementation instances. This is a very convenient and powerful way to reuse existing functionality. The next two examples provide code for the two RowMapper implementations.

The TitleMapper class maps a ResultSet to a Title domain object for each row in the supplied ResultSet, as follows:

Java

import java.sql.ResultSet;
import java.sql.SQLException;
import com.foo.domain.Title;
import org.springframework.jdbc.core.RowMapper;

public final class TitleMapper implements RowMapper<Title> {

    public Title mapRow(ResultSet rs, int rowNum) throws SQLException {
        Title title = new Title();
        title.setId(rs.getLong("id"));
        title.setName(rs.getString("name"));
        return title;
    }
}

Kotlin

import java.sql.ResultSet
import com.foo.domain.Title
import org.springframework.jdbc.core.RowMapper

class TitleMapper : RowMapper<Title> {

    override fun mapRow(rs: ResultSet, rowNum: Int) =
            Title(rs.getLong("id"), rs.getString("name"))
}

The GenreMapper class maps a ResultSet to a Genre domain object for each row in the supplied ResultSet, as follows:

Java

import java.sql.ResultSet;
import java.sql.SQLException;
import com.foo.domain.Genre;
import org.springframework.jdbc.core.RowMapper;

public final class GenreMapper implements RowMapper<Genre> {

    public Genre mapRow(ResultSet rs, int rowNum) throws SQLException {
        return new Genre(rs.getString("name"));
    }
}

Kotlin

import java.sql.ResultSet
import com.foo.domain.Genre
import org.springframework.jdbc.core.RowMapper

class GenreMapper : RowMapper<Genre> {

    override fun mapRow(rs: ResultSet, rowNum: Int): Genre {
        return Genre(rs.getString("name"))
    }
}

To pass parameters to a stored procedure that has one or more input parameters in its definition in the RDBMS, you can code a strongly typed execute(..) method that would delegate to the untyped execute(Map) method in the superclass, as the following example shows:

Java

import java.sql.Types;
import java.util.Date;
import java.util.HashMap;
import java.util.Map;
import javax.sql.DataSource;
import oracle.jdbc.OracleTypes;
import org.springframework.jdbc.core.SqlOutParameter;
import org.springframework.jdbc.core.SqlParameter;
import org.springframework.jdbc.object.StoredProcedure;

public class TitlesAfterDateStoredProcedure extends StoredProcedure {

    private static final String SPROC_NAME = "TitlesAfterDate";
    private static final String CUTOFF_DATE_PARAM = "cutoffDate";

    public TitlesAfterDateStoredProcedure(DataSource dataSource) {
        super(dataSource, SPROC_NAME);
        declareParameter(new SqlParameter(CUTOFF_DATE_PARAM, Types.DATE);
        declareParameter(new SqlOutParameter("titles", OracleTypes.CURSOR, new TitleMapper()));
        compile();
    }

    public Map<String, Object> execute(Date cutoffDate) {
        Map<String, Object> inputs = new HashMap<String, Object>();
        inputs.put(CUTOFF_DATE_PARAM, cutoffDate);
        return super.execute(inputs);
    }
}

Kotlin

import java.sql.Types
import java.util.Date
import javax.sql.DataSource
import oracle.jdbc.OracleTypes
import org.springframework.jdbc.core.SqlOutParameter
import org.springframework.jdbc.core.SqlParameter
import org.springframework.jdbc.object.StoredProcedure

class TitlesAfterDateStoredProcedure(dataSource: DataSource) : StoredProcedure(dataSource, SPROC_NAME) {

    companion object {
        private const val SPROC_NAME = "TitlesAfterDate"
        private const val CUTOFF_DATE_PARAM = "cutoffDate"
    }

    init {
        declareParameter(SqlParameter(CUTOFF_DATE_PARAM, Types.DATE))
        declareParameter(SqlOutParameter("titles", OracleTypes.CURSOR, TitleMapper()))
        compile()
    }

    fun execute(cutoffDate: Date) = super.execute(
            mapOf<String, Any>(CUTOFF_DATE_PARAM to cutoffDate))
}

Common Problems with Parameter and Data Value Handling

Common problems with parameters and data values exist in the different approaches provided by Spring Framework’s JDBC support. This section covers how to address them.

Providing SQL Type Information for Parameters

Usually, Spring determines the SQL type of the parameters based on the type of parameter passed in. It is possible to explicitly provide the SQL type to be used when setting parameter values. This is sometimes necessary to correctly set NULL values.

You can provide SQL type information in several ways:

Many update and query methods of the JdbcTemplate take an additional parameter in the form of an int array. This array is used to indicate the SQL type of the corresponding parameter by using constant values from the java.sql.Types class. Provide one entry for each parameter.
You can use the SqlParameterValue class to wrap the parameter value that needs this additional information. To do so, create a new instance for each value and pass in the SQL type and the parameter value in the constructor. You can also provide an optional scale parameter for numeric values.
For methods that work with named parameters, you can use the SqlParameterSource classes, BeanPropertySqlParameterSource or MapSqlParameterSource. They both have methods for registering the SQL type for any of the named parameter values.

Handling BLOB and CLOB objects

You can store images, other binary data, and large chunks of text in the database. These large objects are called BLOBs (Binary Large OBject) for binary data and CLOBs (Character Large OBject) for character data. In Spring, you can handle these large objects by using the JdbcTemplate directly and also when using the higher abstractions provided by RDBMS Objects and the SimpleJdbc classes. All of these approaches use an implementation of the LobHandler interface for the actual management of the LOB (Large OBject) data. LobHandler provides access to a LobCreator class, through the getLobCreator method, that is used for creating new LOB objects to be inserted.

LobCreator and LobHandler provide the following support for LOB input and output:

BLOB
- byte[]: getBlobAsBytes and setBlobAsBytes
- InputStream: getBlobAsBinaryStream and setBlobAsBinaryStream
CLOB
- String: getClobAsString and setClobAsString
- InputStream: getClobAsAsciiStream and setClobAsAsciiStream
- Reader: getClobAsCharacterStream and setClobAsCharacterStream

The next example shows how to create and insert a BLOB. Later we show how to read it back from the database.

This example uses a JdbcTemplate and an implementation of the AbstractLobCreatingPreparedStatementCallback. It implements one method, setValues. This method provides a LobCreator that we use to set the values for the LOB columns in your SQL insert statement.

For this example, we assume that there is a variable, lobHandler, that is already set to an instance of a DefaultLobHandler. You typically set this value through dependency injection.

The following example shows how to create and insert a BLOB:

Java

final File blobIn = new File("spring2004.jpg");
final InputStream blobIs = new FileInputStream(blobIn);
final File clobIn = new File("large.txt");
final InputStream clobIs = new FileInputStream(clobIn);
final InputStreamReader clobReader = new InputStreamReader(clobIs);

jdbcTemplate.execute(
    "INSERT INTO lob_table (id, a_clob, a_blob) VALUES (?, ?, ?)",
    new AbstractLobCreatingPreparedStatementCallback(lobHandler) {  // (1)
        protected void setValues(PreparedStatement ps, LobCreator lobCreator) throws SQLException {
            ps.setLong(1, 1L);
            lobCreator.setClobAsCharacterStream(ps, 2, clobReader, (int)clobIn.length());  // (2)
            lobCreator.setBlobAsBinaryStream(ps, 3, blobIs, (int)blobIn.length());  // (3)
        }
    }
);

blobIs.close();
clobReader.close();

Pass in the lobHandler that (in this example) is a plain DefaultLobHandler.
Using the method setClobAsCharacterStream to pass in the contents of the CLOB.
Using the method setBlobAsBinaryStream to pass in the contents of the BLOB.

Kotlin

val blobIn = File("spring2004.jpg")
val blobIs = FileInputStream(blobIn)
val clobIn = File("large.txt")
val clobIs = FileInputStream(clobIn)
val clobReader = InputStreamReader(clobIs)

jdbcTemplate.execute(
        "INSERT INTO lob_table (id, a_clob, a_blob) VALUES (?, ?, ?)",
        object: AbstractLobCreatingPreparedStatementCallback(lobHandler) {  // (1)
            override fun setValues(ps: PreparedStatement, lobCreator: LobCreator) {
                ps.setLong(1, 1L)
                lobCreator.setClobAsCharacterStream(ps, 2, clobReader, clobIn.length().toInt())  // (2)
                lobCreator.setBlobAsBinaryStream(ps, 3, blobIs, blobIn.length().toInt())  // (3)
            }
        }
)
blobIs.close()
clobReader.close()

Pass in the lobHandler that (in this example) is a plain DefaultLobHandler.
Using the method setClobAsCharacterStream to pass in the contents of the CLOB.
Using the method setBlobAsBinaryStream to pass in the contents of the BLOB.

Note

If you invoke the setBlobAsBinaryStream, setClobAsAsciiStream, or setClobAsCharacterStream method on the LobCreator returned from DefaultLobHandler.getLobCreator(), you can optionally specify a negative value for the contentLength argument. If the specified content length is negative, the DefaultLobHandler uses the JDBC 4.0 variants of the set-stream methods without a length parameter. Otherwise, it passes the specified length on to the driver.

See the documentation for the JDBC driver you use to verify that it supports streaming a LOB without providing the content length.

Now it is time to read the LOB data from the database. Again, you use a JdbcTemplate with the same instance variable lobHandler and a reference to a DefaultLobHandler. The following example shows how to do so:

Java

List<Map<String, Object>> l = jdbcTemplate.query("select id, a_clob, a_blob from lob_table",
    new RowMapper<Map<String, Object>>() {
        public Map<String, Object> mapRow(ResultSet rs, int i) throws SQLException {
            Map<String, Object> results = new HashMap<String, Object>();
            String clobText = lobHandler.getClobAsString(rs, "a_clob");  // (1)
            results.put("CLOB", clobText);
            byte[] blobBytes = lobHandler.getBlobAsBytes(rs, "a_blob");  // (2)
            results.put("BLOB", blobBytes);
            return results;
        }
    });

Using the method getClobAsString to retrieve the contents of the CLOB.
Using the method getBlobAsBytes to retrieve the contents of the BLOB.

Kotlin

val l = jdbcTemplate.query("select id, a_clob, a_blob from lob_table") { rs, _ ->
    val clobText = lobHandler.getClobAsString(rs, "a_clob")  // (1)
    val blobBytes = lobHandler.getBlobAsBytes(rs, "a_blob")  // (2)
    mapOf("CLOB" to clobText, "BLOB" to blobBytes)
}

Using the method getClobAsString to retrieve the contents of the CLOB.
Using the method getBlobAsBytes to retrieve the contents of the BLOB.

Passing in Lists of Values for IN Clause

The SQL standard allows for selecting rows based on an expression that includes a variable list of values. A typical example would be select * from T_ACTOR where id in (1, 2, 3). This variable list is not directly supported for prepared statements by the JDBC standard. You cannot declare a variable number of placeholders. You need a number of variations with the desired number of placeholders prepared, or you need to generate the SQL string dynamically once you know how many placeholders are required. The named parameter support provided in the NamedParameterJdbcTemplate and JdbcTemplate takes the latter approach. You can pass in the values as a java.util.List of primitive objects. This list is used to insert the required placeholders and pass in the values during statement execution.

Note	Be careful when passing in many values. The JDBC standard does not guarantee that you can use more than 100 values for an `in` expression list. Various databases exceed this number, but they usually have a hard limit for how many values are allowed. For example, Oracle’s limit is 1000.

In addition to the primitive values in the value list, you can create a java.util.List of object arrays. This list can support multiple expressions being defined for the in clause, such as select * from T_ACTOR where (id, last_name) in ((1, 'Johnson'), (2, 'Harrop'\)). This, of course, requires that your database supports this syntax.

Handling Complex Types for Stored Procedure Calls

When you call stored procedures, you can sometimes use complex types specific to the database. To accommodate these types, Spring provides a SqlReturnType for handling them when they are returned from the stored procedure call and SqlTypeValue when they are passed in as a parameter to the stored procedure.

The SqlReturnType interface has a single method (named getTypeValue) that must be implemented. This interface is used as part of the declaration of an SqlOutParameter. The following example shows returning the value of an Oracle STRUCT object of the user declared type ITEM_TYPE:

Java

public class TestItemStoredProcedure extends StoredProcedure {

    public TestItemStoredProcedure(DataSource dataSource) {
        // ...
        declareParameter(new SqlOutParameter("item", OracleTypes.STRUCT, "ITEM_TYPE",
            new SqlReturnType() {
                public Object getTypeValue(CallableStatement cs, int colIndx, int sqlType, String   ) throws SQLException {
                    STRUCT struct = (STRUCT) cs.getObject(colIndx);
                    Object[] attr = struct.getAttributes();
                    TestItem item = new TestItem();
                    item.setId(((Number) attr[0]).longValue());
                    item.setDescription((String) attr[1]);
                    item.setExpirationDate((java.util.Date) attr[2]);
                    return item;
                }
            }));
        // ...
    }

Kotlin

class TestItemStoredProcedure(dataSource: DataSource) : StoredProcedure() {

    init {
        // ...
        declareParameter(SqlOutParameter("item", OracleTypes.STRUCT, "ITEM_TYPE") { cs, colIndx, sqlType, typeName ->
            val struct = cs.getObject(colIndx) as STRUCT
            val attr = struct.getAttributes()
            TestItem((attr[0] as Long, attr[1] as String, attr[2] as Date)
        })
        // ...
    }
}

You can use SqlTypeValue to pass the value of a Java object (such as TestItem) to a stored procedure. The SqlTypeValue interface has a single method (named createTypeValue) that you must implement. The active connection is passed in, and you can use it to create database-specific objects, such as StructDescriptor instances or ArrayDescriptor instances. The following example creates a StructDescriptor instance:

Java

final TestItem testItem = new TestItem(123L, "A test item",
        new SimpleDateFormat("yyyy-M-d").parse("2010-12-31"));

SqlTypeValue value = new AbstractSqlTypeValue() {
    protected Object createTypeValue(Connection conn, int sqlType, String typeName) throws SQLException {
        StructDescriptor itemDescriptor = new StructDescriptor(typeName, conn);
        Struct item = new STRUCT(itemDescriptor, conn,
        new Object[] {
            testItem.getId(),
            testItem.getDescription(),
            new java.sql.Date(testItem.getExpirationDate().getTime())
        });
        return item;
    }
};

Kotlin

val (id, description, expirationDate) = TestItem(123L, "A test item",
        SimpleDateFormat("yyyy-M-d").parse("2010-12-31"))

val value = object : AbstractSqlTypeValue() {
    override fun createTypeValue(conn: Connection, sqlType: Int, typeName: String?): Any {
        val itemDescriptor = StructDescriptor(typeName, conn)
        return STRUCT(itemDescriptor, conn,
                arrayOf(id, description, java.sql.Date(expirationDate.time)))
    }
}

You can now add this SqlTypeValue to the Map that contains the input parameters for the execute call of the stored procedure.

Another use for the SqlTypeValue is passing in an array of values to an Oracle stored procedure. Oracle has its own internal ARRAY class that must be used in this case, and you can use the SqlTypeValue to create an instance of the Oracle ARRAY and populate it with values from the Java ARRAY, as the following example shows:

Java

final Long[] ids = new Long[] {1L, 2L};

SqlTypeValue value = new AbstractSqlTypeValue() {
    protected Object createTypeValue(Connection conn, int sqlType, String typeName) throws SQLException {
        ArrayDescriptor arrayDescriptor = new ArrayDescriptor(typeName, conn);
        ARRAY idArray = new ARRAY(arrayDescriptor, conn, ids);
        return idArray;
    }
};

Kotlin

class TestItemStoredProcedure(dataSource: DataSource) : StoredProcedure() {

    init {
        val ids = arrayOf(1L, 2L)
        val value = object : AbstractSqlTypeValue() {
            override fun createTypeValue(conn: Connection, sqlType: Int, typeName: String?): Any {
                val arrayDescriptor = ArrayDescriptor(typeName, conn)
                return ARRAY(arrayDescriptor, conn, ids)
            }
        }
    }
}

Embedded Database Support

The org.springframework.jdbc.datasource.embedded package provides support for embedded Java database engines. Support for HSQL, H2, and Derby is provided natively. You can also use an extensible API to plug in new embedded database types and DataSource implementations.

Why Use an Embedded Database?

An embedded database can be useful during the development phase of a project because of its lightweight nature. Benefits include ease of configuration, quick startup time, testability, and the ability to rapidly evolve your SQL during development.

Creating an Embedded Database by Using Spring XML

If you want to expose an embedded database instance as a bean in a Spring ApplicationContext, you can use the embedded-database tag in the spring-jdbc namespace:

<jdbc:embedded-database id="dataSource" generate-name="true">
    <jdbc:script location="classpath:schema.sql"/>
    <jdbc:script location="classpath:test-data.sql"/>
</jdbc:embedded-database>

The preceding configuration creates an embedded HSQL database that is populated with SQL from the schema.sql and test-data.sql resources in the root of the classpath. In addition, as a best practice, the embedded database is assigned a uniquely generated name. The embedded database is made available to the Spring container as a bean of type javax.sql.DataSource that can then be injected into data access objects as needed.

Creating an Embedded Database Programmatically

The EmbeddedDatabaseBuilder class provides a fluent API for constructing an embedded database programmatically. You can use this when you need to create an embedded database in a stand-alone environment or in a stand-alone integration test, as in the following example:

Java

EmbeddedDatabase db = new EmbeddedDatabaseBuilder()
        .generateUniqueName(true)
        .setType(H2)
        .setScriptEncoding("UTF-8")
        .ignoreFailedDrops(true)
        .addScript("schema.sql")
        .addScripts("user_data.sql", "country_data.sql")
        .build();

// perform actions against the db (EmbeddedDatabase extends javax.sql.DataSource)

db.shutdown()

Kotlin

val db = EmbeddedDatabaseBuilder()
        .generateUniqueName(true)
        .setType(H2)
        .setScriptEncoding("UTF-8")
        .ignoreFailedDrops(true)
        .addScript("schema.sql")
        .addScripts("user_data.sql", "country_data.sql")
        .build()

// perform actions against the db (EmbeddedDatabase extends javax.sql.DataSource)

db.shutdown()

See the javadoc for EmbeddedDatabaseBuilder for further details on all supported options.

You can also use the EmbeddedDatabaseBuilder to create an embedded database by using Java configuration, as the following example shows:

Java

@Configuration
public class DataSourceConfig {

    @Bean
    public DataSource dataSource() {
        return new EmbeddedDatabaseBuilder()
                .generateUniqueName(true)
                .setType(H2)
                .setScriptEncoding("UTF-8")
                .ignoreFailedDrops(true)
                .addScript("schema.sql")
                .addScripts("user_data.sql", "country_data.sql")
                .build();
    }
}

Kotlin

@Configuration
class DataSourceConfig {

    @Bean
    fun dataSource(): DataSource {
        return EmbeddedDatabaseBuilder()
                .generateUniqueName(true)
                .setType(H2)
                .setScriptEncoding("UTF-8")
                .ignoreFailedDrops(true)
                .addScript("schema.sql")
                .addScripts("user_data.sql", "country_data.sql")
                .build()
    }
}

Selecting the Embedded Database Type

This section covers how to select one of the three embedded databases that Spring supports. It includes the following topics:

Using HSQL
Using H2
Using Derby

Using HSQL

Spring supports HSQL 1.8.0 and above. HSQL is the default embedded database if no type is explicitly specified. To specify HSQL explicitly, set the type attribute of the embedded-database tag to HSQL. If you use the builder API, call the setType(EmbeddedDatabaseType) method with EmbeddedDatabaseType.HSQL.

Using H2

Spring supports the H2 database. To enable H2, set the type attribute of the embedded-database tag to H2. If you use the builder API, call the setType(EmbeddedDatabaseType) method with EmbeddedDatabaseType.H2.

Using Derby

Spring supports Apache Derby 10.5 and above. To enable Derby, set the type attribute of the embedded-database tag to DERBY. If you use the builder API, call the setType(EmbeddedDatabaseType) method with EmbeddedDatabaseType.DERBY.

Testing Data Access Logic with an Embedded Database

Embedded databases provide a lightweight way to test data access code. The next example is a data access integration test template that uses an embedded database. Using such a template can be useful for one-offs when the embedded database does not need to be reused across test classes. However, if you wish to create an embedded database that is shared within a test suite, consider using the Spring TestContext Framework and configuring the embedded database as a bean in the Spring ApplicationContext as described in Creating an Embedded Database by Using Spring XML and Creating an Embedded Database Programmatically. The following listing shows the test template:

Java

public class DataAccessIntegrationTestTemplate {

    private EmbeddedDatabase db;

    @BeforeEach
    public void setUp() {
        // creates an HSQL in-memory database populated from default scripts
        // classpath:schema.sql and classpath:data.sql
        db = new EmbeddedDatabaseBuilder()
                .generateUniqueName(true)
                .addDefaultScripts()
                .build();
    }

    @Test
    public void testDataAccess() {
        JdbcTemplate template = new JdbcTemplate(db);
        template.query( /* ... */ );
    }

    @AfterEach
    public void tearDown() {
        db.shutdown();
    }

}

Kotlin

class DataAccessIntegrationTestTemplate {

    private lateinit var db: EmbeddedDatabase

    @BeforeEach
    fun setUp() {
        // creates an HSQL in-memory database populated from default scripts
        // classpath:schema.sql and classpath:data.sql
        db = EmbeddedDatabaseBuilder()
                .generateUniqueName(true)
                .addDefaultScripts()
                .build()
    }

    @Test
    fun testDataAccess() {
        val template = JdbcTemplate(db)
        template.query( /* ... */)
    }

    @AfterEach
    fun tearDown() {
        db.shutdown()
    }
}

Generating Unique Names for Embedded Databases

Development teams often encounter errors with embedded databases if their test suite inadvertently attempts to recreate additional instances of the same database. This can happen quite easily if an XML configuration file or @Configuration class is responsible for creating an embedded database and the corresponding configuration is then reused across multiple testing scenarios within the same test suite (that is, within the same JVM process) — for example, integration tests against embedded databases whose ApplicationContext configuration differs only with regard to which bean definition profiles are active.

The root cause of such errors is the fact that Spring’s EmbeddedDatabaseFactory (used internally by both the <jdbc:embedded-database> XML namespace element and the EmbeddedDatabaseBuilder for Java configuration) sets the name of the embedded database to testdb if not otherwise specified. For the case of <jdbc:embedded-database>, the embedded database is typically assigned a name equal to the bean’s id (often, something like dataSource). Thus, subsequent attempts to create an embedded database do not result in a new database. Instead, the same JDBC connection URL is reused, and attempts to create a new embedded database actually point to an existing embedded database created from the same configuration.

To address this common issue, Spring Framework 4.2 provides support for generating unique names for embedded databases. To enable the use of generated names, use one of the following options.

EmbeddedDatabaseFactory.setGenerateUniqueDatabaseName()
EmbeddedDatabaseBuilder.generateUniqueName()
<jdbc:embedded-database generate-name="true" … >

Extending the Embedded Database Support

You can extend Spring JDBC embedded database support in two ways:

Implement EmbeddedDatabaseConfigurer to support a new embedded database type.
Implement DataSourceFactory to support a new DataSource implementation, such as a connection pool to manage embedded database connections.

We encourage you to contribute extensions to the Spring community at GitHub Issues.

Initializing a `DataSource`

The org.springframework.jdbc.datasource.init package provides support for initializing an existing DataSource. The embedded database support provides one option for creating and initializing a DataSource for an application. However, you may sometimes need to initialize an instance that runs on a server somewhere.

Initializing a Database by Using Spring XML

If you want to initialize a database and you can provide a reference to a DataSource bean, you can use the initialize-database tag in the spring-jdbc namespace:

<jdbc:initialize-database data-source="dataSource">
    <jdbc:script location="classpath:com/foo/sql/db-schema.sql"/>
    <jdbc:script location="classpath:com/foo/sql/db-test-data.sql"/>
</jdbc:initialize-database>

The preceding example runs the two specified scripts against the database. The first script creates a schema, and the second populates tables with a test data set. The script locations can also be patterns with wildcards in the usual Ant style used for resources in Spring (for example, classpath*:/com/foo/**/sql/*-data.sql). If you use a pattern, the scripts are run in the lexical order of their URL or filename.

The default behavior of the database initializer is to unconditionally run the provided scripts. This may not always be what you want — for instance, if you run the scripts against a database that already has test data in it. The likelihood of accidentally deleting data is reduced by following the common pattern (shown earlier) of creating the tables first and then inserting the data. The first step fails if the tables already exist.

However, to gain more control over the creation and deletion of existing data, the XML namespace provides a few additional options. The first is a flag to switch the initialization on and off. You can set this according to the environment (such as pulling a boolean value from system properties or from an environment bean). The following example gets a value from a system property:

<jdbc:initialize-database data-source="dataSource"
    enabled="#{systemProperties.INITIALIZE_DATABASE}"> (1)
    <jdbc:script location="..."/>
</jdbc:initialize-database>

Get the value for enabled from a system property called INITIALIZE_DATABASE.

The second option to control what happens with existing data is to be more tolerant of failures. To this end, you can control the ability of the initializer to ignore certain errors in the SQL it executes from the scripts, as the following example shows:

<jdbc:initialize-database data-source="dataSource" ignore-failures="DROPS">
    <jdbc:script location="..."/>
</jdbc:initialize-database>

In the preceding example, we are saying that we expect that, sometimes, the scripts are run against an empty database, and there are some DROP statements in the scripts that would, therefore, fail. So failed SQL DROP statements will be ignored, but other failures will cause an exception. This is useful if your SQL dialect doesn’t support DROP … IF EXISTS (or similar) but you want to unconditionally remove all test data before re-creating it. In that case the first script is usually a set of DROP statements, followed by a set of CREATE statements.

The ignore-failures option can be set to NONE (the default), DROPS (ignore failed drops), or ALL (ignore all failures).

Each statement should be separated by ; or a new line if the ; character is not present at all in the script. You can control that globally or script by script, as the following example shows:

<jdbc:initialize-database data-source="dataSource" separator="@@"> (1)
    <jdbc:script location="classpath:com/myapp/sql/db-schema.sql" separator=";"/> (2)
    <jdbc:script location="classpath:com/myapp/sql/db-test-data-1.sql"/>
    <jdbc:script location="classpath:com/myapp/sql/db-test-data-2.sql"/>
</jdbc:initialize-database>

Set the separator scripts to @@.
Set the separator for db-schema.sql to ;.

In this example, the two test-data scripts use @@ as statement separator and only the db-schema.sql uses ;. This configuration specifies that the default separator is @@ and overrides that default for the db-schema script.

If you need more control than you get from the XML namespace, you can use the DataSourceInitializer directly and define it as a component in your application.

Initialization of Other Components that Depend on the Database

A large class of applications (those that do not use the database until after the Spring context has started) can use the database initializer with no further complications. If your application is not one of those, you might need to read the rest of this section.

The database initializer depends on a DataSource instance and runs the scripts provided in its initialization callback (analogous to an init-method in an XML bean definition, a @PostConstruct method in a component, or the afterPropertiesSet() method in a component that implements InitializingBean). If other beans depend on the same data source and use the data source in an initialization callback, there might be a problem because the data has not yet been initialized. A common example of this is a cache that initializes eagerly and loads data from the database on application startup.

To get around this issue, you have two options: change your cache initialization strategy to a later phase or ensure that the database initializer is initialized first.

Changing your cache initialization strategy might be easy if the application is in your control and not otherwise. Some suggestions for how to implement this include:

Make the cache initialize lazily on first usage, which improves application startup time.
Have your cache or a separate component that initializes the cache implement Lifecycle or SmartLifecycle. When the application context starts, you can automatically start a SmartLifecycle by setting its autoStartup flag, and you can manually start a Lifecycle by calling ConfigurableApplicationContext.start() on the enclosing context.
Use a Spring ApplicationEvent or similar custom observer mechanism to trigger the cache initialization. ContextRefreshedEvent is always published by the context when it is ready for use (after all beans have been initialized), so that is often a useful hook (this is how the SmartLifecycle works by default).

Ensuring that the database initializer is initialized first can also be easy. Some suggestions on how to implement this include:

Rely on the default behavior of the Spring BeanFactory, which is that beans are initialized in registration order. You can easily arrange that by adopting the common practice of a set of <import/> elements in XML configuration that order your application modules and ensuring that the database and database initialization are listed first.
Separate the DataSource and the business components that use it and control their startup order by putting them in separate ApplicationContext instances (for example, the parent context contains the DataSource, and the child context contains the business components). This structure is common in Spring web applications but can be more generally applied.

Object Relational Mapping (ORM) Data Access

This section covers data access when you use Object Relational Mapping (ORM).

Introduction to ORM with Spring

The Spring Framework supports integration with the Java Persistence API (JPA) and supports native Hibernate for resource management, data access object (DAO) implementations, and transaction strategies. For example, for Hibernate, there is first-class support with several convenient IoC features that address many typical Hibernate integration issues. You can configure all of the supported features for OR (object relational) mapping tools through Dependency Injection. They can participate in Spring’s resource and transaction management, and they comply with Spring’s generic transaction and DAO exception hierarchies. The recommended integration style is to code DAOs against plain Hibernate or JPA APIs.

Spring adds significant enhancements to the ORM layer of your choice when you create data access applications. You can leverage as much of the integration support as you wish, and you should compare this integration effort with the cost and risk of building a similar infrastructure in-house. You can use much of the ORM support as you would a library, regardless of technology, because everything is designed as a set of reusable JavaBeans. ORM in a Spring IoC container facilitates configuration and deployment. Thus, most examples in this section show configuration inside a Spring container.

The benefits of using the Spring Framework to create your ORM DAOs include:

Easier testing. Spring’s IoC approach makes it easy to swap the implementations and configuration locations of Hibernate SessionFactory instances, JDBC DataSource instances, transaction managers, and mapped object implementations (if needed). This in turn makes it much easier to test each piece of persistence-related code in isolation.
Common data access exceptions. Spring can wrap exceptions from your ORM tool, converting them from proprietary (potentially checked) exceptions to a common runtime DataAccessException hierarchy. This feature lets you handle most persistence exceptions, which are non-recoverable, only in the appropriate layers, without annoying boilerplate catches, throws, and exception declarations. You can still trap and handle exceptions as necessary. Remember that JDBC exceptions (including DB-specific dialects) are also converted to the same hierarchy, meaning that you can perform some operations with JDBC within a consistent programming model.
General resource management. Spring application contexts can handle the location and configuration of Hibernate SessionFactory instances, JPA EntityManagerFactory instances, JDBC DataSource instances, and other related resources. This makes these values easy to manage and change. Spring offers efficient, easy, and safe handling of persistence resources. For example, related code that uses Hibernate generally needs to use the same Hibernate Session to ensure efficiency and proper transaction handling. Spring makes it easy to create and bind a Session to the current thread transparently, by exposing a current Session through the Hibernate SessionFactory. Thus, Spring solves many chronic problems of typical Hibernate usage, for any local or JTA transaction environment.
Integrated transaction management. You can wrap your ORM code with a declarative, aspect-oriented programming (AOP) style method interceptor either through the @Transactional annotation or by explicitly configuring the transaction AOP advice in an XML configuration file. In both cases, transaction semantics and exception handling (rollback and so on) are handled for you. As discussed in Resource and Transaction Management, you can also swap various transaction managers, without affecting your ORM-related code. For example, you can swap between local transactions and JTA, with the same full services (such as declarative transactions) available in both scenarios. Additionally, JDBC-related code can fully integrate transactionally with the code you use to do ORM. This is useful for data access that is not suitable for ORM (such as batch processing and BLOB streaming) but that still needs to share common transactions with ORM operations.

Tip	For more comprehensive ORM support, including support for alternative database technologies such as MongoDB, you might want to check out the Spring Data suite of projects. If you are a JPA user, the Getting Started Accessing Data with JPA guide from https://spring.io provides a great introduction.

General ORM Integration Considerations

This section highlights considerations that apply to all ORM technologies. The Hibernate section provides more details and also show these features and configurations in a concrete context.

The major goal of Spring’s ORM integration is clear application layering (with any data access and transaction technology) and for loose coupling of application objects — no more business service dependencies on the data access or transaction strategy, no more hard-coded resource lookups, no more hard-to-replace singletons, no more custom service registries. The goal is to have one simple and consistent approach to wiring up application objects, keeping them as reusable and free from container dependencies as possible. All the individual data access features are usable on their own but integrate nicely with Spring’s application context concept, providing XML-based configuration and cross-referencing of plain JavaBean instances that need not be Spring-aware. In a typical Spring application, many important objects are JavaBeans: data access templates, data access objects, transaction managers, business services that use the data access objects and transaction managers, web view resolvers, web controllers that use the business services, and so on.

Resource and Transaction Management

Typical business applications are cluttered with repetitive resource management code. Many projects try to invent their own solutions, sometimes sacrificing proper handling of failures for programming convenience. Spring advocates simple solutions for proper resource handling, namely IoC through templating in the case of JDBC and applying AOP interceptors for the ORM technologies.

The infrastructure provides proper resource handling and appropriate conversion of specific API exceptions to an unchecked infrastructure exception hierarchy. Spring introduces a DAO exception hierarchy, applicable to any data access strategy. For direct JDBC, the JdbcTemplate class mentioned in a previous section provides connection handling and proper conversion of SQLException to the DataAccessException hierarchy, including translation of database-specific SQL error codes to meaningful exception classes. For ORM technologies, see the next section for how to get the same exception translation benefits.

When it comes to transaction management, the JdbcTemplate class hooks in to the Spring transaction support and supports both JTA and JDBC transactions, through respective Spring transaction managers. For the supported ORM technologies, Spring offers Hibernate and JPA support through the Hibernate and JPA transaction managers as well as JTA support. For details on transaction support, see the Transaction Management chapter.

Exception Translation

When you use Hibernate or JPA in a DAO, you must decide how to handle the persistence technology’s native exception classes. The DAO throws a subclass of a HibernateException or PersistenceException, depending on the technology. These exceptions are all runtime exceptions and do not have to be declared or caught. You may also have to deal with IllegalArgumentException and IllegalStateException. This means that callers can only treat exceptions as being generally fatal, unless they want to depend on the persistence technology’s own exception structure. Catching specific causes (such as an optimistic locking failure) is not possible without tying the caller to the implementation strategy. This trade-off might be acceptable to applications that are strongly ORM-based or do not need any special exception treatment (or both). However, Spring lets exception translation be applied transparently through the @Repository annotation. The following examples (one for Java configuration and one for XML configuration) show how to do so:

Java

@Repository
public class ProductDaoImpl implements ProductDao {

    // class body here...

}

Kotlin

@Repository
class ProductDaoImpl : ProductDao {
    // class body here...
}

<beans>

    <!-- Exception translation bean post processor -->
    <bean class="org.springframework.dao.annotation.PersistenceExceptionTranslationPostProcessor"/>

    <bean id="myProductDao" class="product.ProductDaoImpl"/>

</beans>

The postprocessor automatically looks for all exception translators (implementations of the PersistenceExceptionTranslator interface) and advises all beans marked with the @Repository annotation so that the discovered translators can intercept and apply the appropriate translation on the thrown exceptions.

In summary, you can implement DAOs based on the plain persistence technology’s API and annotations while still benefiting from Spring-managed transactions, dependency injection, and transparent exception conversion (if desired) to Spring’s custom exception hierarchies.

Hibernate

We start with a coverage of Hibernate 5 in a Spring environment, using it to demonstrate the approach that Spring takes towards integrating OR mappers. This section covers many issues in detail and shows different variations of DAO implementations and transaction demarcation. Most of these patterns can be directly translated to all other supported ORM tools. The later sections in this chapter then cover the other ORM technologies and show brief examples.

Note

As of Spring Framework 5.0, Spring requires Hibernate ORM 4.3 or later for JPA support and even Hibernate ORM 5.0+ for programming against the native Hibernate Session API. Note that the Hibernate team does not maintain any versions prior to 5.1 anymore and is likely to focus on 5.3+ exclusively soon.

`SessionFactory` Setup in a Spring Container

To avoid tying application objects to hard-coded resource lookups, you can define resources (such as a JDBC DataSource or a Hibernate SessionFactory) as beans in the Spring container. Application objects that need to access resources receive references to such predefined instances through bean references, as illustrated in the DAO definition in the next section.

The following excerpt from an XML application context definition shows how to set up a JDBC DataSource and a Hibernate SessionFactory on top of it:

<beans>

    <bean id="myDataSource" class="org.apache.commons.dbcp.BasicDataSource" destroy-method="close">
        <property name="driverClassName" value="org.hsqldb.jdbcDriver"/>
        <property name="url" value="jdbc:hsqldb:hsql://localhost:9001"/>
        <property name="username" value="sa"/>
        <property name="password" value=""/>
    </bean>

    <bean id="mySessionFactory" class="org.springframework.orm.hibernate5.LocalSessionFactoryBean">
        <property name="dataSource" ref="myDataSource"/>
        <property name="mappingResources">
            <list>
                <value>product.hbm.xml</value>
            </list>
        </property>
        <property name="hibernateProperties">
            <value>
                hibernate.dialect=org.hibernate.dialect.HSQLDialect
            </value>
        </property>
    </bean>

</beans>

Switching from a local Jakarta Commons DBCP BasicDataSource to a JNDI-located DataSource (usually managed by an application server) is only a matter of configuration, as the following example shows:

<beans>
    <jee:jndi-lookup id="myDataSource" jndi-name="java:comp/env/jdbc/myds"/>
</beans>

You can also access a JNDI-located SessionFactory, using Spring’s JndiObjectFactoryBean / <jee:jndi-lookup> to retrieve and expose it. However, that is typically not common outside of an EJB context.

Note

Spring also provides a LocalSessionFactoryBuilder variant, seamlessly integrating with @Bean style configuration and programmatic setup (no FactoryBean involved).

Both LocalSessionFactoryBean and LocalSessionFactoryBuilder support background bootstrapping, with Hibernate initialization running in parallel to the application bootstrap thread on a given bootstrap executor (such as a SimpleAsyncTaskExecutor). On LocalSessionFactoryBean, this is available through the bootstrapExecutor property. On the programmatic LocalSessionFactoryBuilder, there is an overloaded buildSessionFactory method that takes a bootstrap executor argument.

As of Spring Framework 5.1, such a native Hibernate setup can also expose a JPA EntityManagerFactory for standard JPA interaction next to native Hibernate access. See Native Hibernate Setup for JPA for details.

Implementing DAOs Based on the Plain Hibernate API

Hibernate has a feature called contextual sessions, wherein Hibernate itself manages one current Session per transaction. This is roughly equivalent to Spring’s synchronization of one Hibernate Session per transaction. A corresponding DAO implementation resembles the following example, based on the plain Hibernate API:

Java

public class ProductDaoImpl implements ProductDao {

    private SessionFactory sessionFactory;

    public void setSessionFactory(SessionFactory sessionFactory) {
        this.sessionFactory = sessionFactory;
    }

    public Collection loadProductsByCategory(String category) {
        return this.sessionFactory.getCurrentSession()
                .createQuery("from test.Product product where product.category=?")
                .setParameter(0, category)
                .list();
    }
}

Kotlin

class ProductDaoImpl(private val sessionFactory: SessionFactory) : ProductDao {

    fun loadProductsByCategory(category: String): Collection<*> {
        return sessionFactory.currentSession
                .createQuery("from test.Product product where product.category=?")
                .setParameter(0, category)
                .list()
    }
}

This style is similar to that of the Hibernate reference documentation and examples, except for holding the SessionFactory in an instance variable. We strongly recommend such an instance-based setup over the old-school static HibernateUtil class from Hibernate’s CaveatEmptor sample application. (In general, do not keep any resources in static variables unless absolutely necessary.)

The preceding DAO example follows the dependency injection pattern. It fits nicely into a Spring IoC container, as it would if coded against Spring’s HibernateTemplate. You can also set up such a DAO in plain Java (for example, in unit tests). To do so, instantiate it and call setSessionFactory(..) with the desired factory reference. As a Spring bean definition, the DAO would resemble the following:

<beans>

    <bean id="myProductDao" class="product.ProductDaoImpl">
        <property name="sessionFactory" ref="mySessionFactory"/>
    </bean>

</beans>

The main advantage of this DAO style is that it depends on Hibernate API only. No import of any Spring class is required. This is appealing from a non-invasiveness perspective and may feel more natural to Hibernate developers.

However, the DAO throws plain HibernateException (which is unchecked, so it does not have to be declared or caught), which means that callers can treat exceptions only as being generally fatal — unless they want to depend on Hibernate’s own exception hierarchy. Catching specific causes (such as an optimistic locking failure) is not possible without tying the caller to the implementation strategy. This trade off might be acceptable to applications that are strongly Hibernate-based, do not need any special exception treatment, or both.

Fortunately, Spring’s LocalSessionFactoryBean supports Hibernate’s SessionFactory.getCurrentSession() method for any Spring transaction strategy, returning the current Spring-managed transactional Session, even with HibernateTransactionManager. The standard behavior of that method remains to return the current Session associated with the ongoing JTA transaction, if any. This behavior applies regardless of whether you use Spring’s JtaTransactionManager, EJB container managed transactions (CMTs), or JTA.

In summary, you can implement DAOs based on the plain Hibernate API, while still being able to participate in Spring-managed transactions.

Declarative Transaction Demarcation

We recommend that you use Spring’s declarative transaction support, which lets you replace explicit transaction demarcation API calls in your Java code with an AOP transaction interceptor. You can configure this transaction interceptor in a Spring container by using either Java annotations or XML. This declarative transaction capability lets you keep business services free of repetitive transaction demarcation code and focus on adding business logic, which is the real value of your application.

Note	Before you continue, we are strongly encourage you to read Declarative transaction management if you have not already done so.

You can annotate the service layer with @Transactional annotations and instruct the Spring container to find these annotations and provide transactional semantics for these annotated methods. The following example shows how to do so:

Java

public class ProductServiceImpl implements ProductService {

    private ProductDao productDao;

    public void setProductDao(ProductDao productDao) {
        this.productDao = productDao;
    }

    @Transactional
    public void increasePriceOfAllProductsInCategory(final String category) {
        List productsToChange = this.productDao.loadProductsByCategory(category);
        // ...
    }

    @Transactional(readOnly = true)
    public List<Product> findAllProducts() {
        return this.productDao.findAllProducts();
    }
}

Kotlin

class ProductServiceImpl(private val productDao: ProductDao) : ProductService {

    @Transactional
    fun increasePriceOfAllProductsInCategory(category: String) {
        val productsToChange = productDao.loadProductsByCategory(category)
        // ...
    }

    @Transactional(readOnly = true)
    fun findAllProducts() = productDao.findAllProducts()
}

In the container, you need to set up the PlatformTransactionManager implementation (as a bean) and a <tx:annotation-driven/> entry, opting into @Transactional processing at runtime. The following example shows how to do so:

<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
    xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
    xmlns:aop="http://www.springframework.org/schema/aop"
    xmlns:tx="http://www.springframework.org/schema/tx"
    xsi:schemaLocation="
        http://www.springframework.org/schema/beans
        https://www.springframework.org/schema/beans/spring-beans.xsd
        http://www.springframework.org/schema/tx
        https://www.springframework.org/schema/tx/spring-tx.xsd
        http://www.springframework.org/schema/aop
        https://www.springframework.org/schema/aop/spring-aop.xsd">

    <!-- SessionFactory, DataSource, etc. omitted -->

    <bean id="transactionManager"
            class="org.springframework.orm.hibernate5.HibernateTransactionManager">
        <property name="sessionFactory" ref="sessionFactory"/>
    </bean>

    <tx:annotation-driven/>

    <bean id="myProductService" class="product.SimpleProductService">
        <property name="productDao" ref="myProductDao"/>
    </bean>

</beans>

Programmatic Transaction Demarcation

You can demarcate transactions in a higher level of the application, on top of lower-level data access services that span any number of operations. Nor do restrictions exist on the implementation of the surrounding business service. It needs only a Spring PlatformTransactionManager. Again, the latter can come from anywhere, but preferably as a bean reference through a setTransactionManager(..) method. Also, the productDAO should be set by a setProductDao(..) method. The following pair of snippets show a transaction manager and a business service definition in a Spring application context and an example for a business method implementation:

<beans>

    <bean id="myTxManager" class="org.springframework.orm.hibernate5.HibernateTransactionManager">
        <property name="sessionFactory" ref="mySessionFactory"/>
    </bean>

    <bean id="myProductService" class="product.ProductServiceImpl">
        <property name="transactionManager" ref="myTxManager"/>
        <property name="productDao" ref="myProductDao"/>
    </bean>

</beans>

Java

public class ProductServiceImpl implements ProductService {

    private TransactionTemplate transactionTemplate;
    private ProductDao productDao;

    public void setTransactionManager(PlatformTransactionManager transactionManager) {
        this.transactionTemplate = new TransactionTemplate(transactionManager);
    }

    public void setProductDao(ProductDao productDao) {
        this.productDao = productDao;
    }

    public void increasePriceOfAllProductsInCategory(final String category) {
        this.transactionTemplate.execute(new TransactionCallbackWithoutResult() {
            public void doInTransactionWithoutResult(TransactionStatus status) {
                List productsToChange = this.productDao.loadProductsByCategory(category);
                // do the price increase...
            }
        });
    }
}

Kotlin

class ProductServiceImpl(transactionManager: PlatformTransactionManager,
                        private val productDao: ProductDao) : ProductService {

    private val transactionTemplate = TransactionTemplate(transactionManager)

    fun increasePriceOfAllProductsInCategory(category: String) {
        transactionTemplate.execute {
            val productsToChange = productDao.loadProductsByCategory(category)
            // do the price increase...
        }
    }
}

Spring’s TransactionInterceptor lets any checked application exception be thrown with the callback code, while TransactionTemplate is restricted to unchecked exceptions within the callback. TransactionTemplate triggers a rollback in case of an unchecked application exception or if the transaction is marked rollback-only by the application (by setting TransactionStatus). By default, TransactionInterceptor behaves the same way but allows configurable rollback policies per method.

Transaction Management Strategies

Both TransactionTemplate and TransactionInterceptor delegate the actual transaction handling to a PlatformTransactionManager instance (which can be a HibernateTransactionManager (for a single Hibernate SessionFactory) by using a ThreadLocal Session under the hood) or a JtaTransactionManager (delegating to the JTA subsystem of the container) for Hibernate applications. You can even use a custom PlatformTransactionManager implementation. Switching from native Hibernate transaction management to JTA (such as when facing distributed transaction requirements for certain deployments of your application) is only a matter of configuration. You can replace the Hibernate transaction manager with Spring’s JTA transaction implementation. Both transaction demarcation and data access code work without changes, because they use the generic transaction management APIs.

For distributed transactions across multiple Hibernate session factories, you can combine JtaTransactionManager as a transaction strategy with multiple LocalSessionFactoryBean definitions. Each DAO then gets one specific SessionFactory reference passed into its corresponding bean property. If all underlying JDBC data sources are transactional container ones, a business service can demarcate transactions across any number of DAOs and any number of session factories without special regard, as long as it uses JtaTransactionManager as the strategy.

Both HibernateTransactionManager and JtaTransactionManager allow for proper JVM-level cache handling with Hibernate, without container-specific transaction manager lookup or a JCA connector (if you do not use EJB to initiate transactions).

HibernateTransactionManager can export the Hibernate JDBC Connection to plain JDBC access code for a specific DataSource. This ability allows for high-level transaction demarcation with mixed Hibernate and JDBC data access completely without JTA, provided you access only one database. HibernateTransactionManager automatically exposes the Hibernate transaction as a JDBC transaction if you have set up the passed-in SessionFactory with a DataSource through the dataSource property of the LocalSessionFactoryBean class. Alternatively, you can specify explicitly the DataSource for which the transactions are supposed to be exposed through the dataSource property of the HibernateTransactionManager class.

Comparing Container-managed and Locally Defined Resources

You can switch between a container-managed JNDI SessionFactory and a locally defined one without having to change a single line of application code. Whether to keep resource definitions in the container or locally within the application is mainly a matter of the transaction strategy that you use. Compared to a Spring-defined local SessionFactory, a manually registered JNDI SessionFactory does not provide any benefits. Deploying a SessionFactory through Hibernate’s JCA connector provides the added value of participating in the Java EE server’s management infrastructure, but does not add actual value beyond that.

Spring’s transaction support is not bound to a container. When configured with any strategy other than JTA, transaction support also works in a stand-alone or test environment. Especially in the typical case of single-database transactions, Spring’s single-resource local transaction support is a lightweight and powerful alternative to JTA. When you use local EJB stateless session beans to drive transactions, you depend both on an EJB container and on JTA, even if you access only a single database and use only stateless session beans to provide declarative transactions through container-managed transactions. Direct use of JTA programmatically also requires a Java EE environment. JTA does not involve only container dependencies in terms of JTA itself and of JNDI DataSource instances. For non-Spring, JTA-driven Hibernate transactions, you have to use the Hibernate JCA connector or extra Hibernate transaction code with the TransactionManagerLookup configured for proper JVM-level caching.

Spring-driven transactions can work as well with a locally defined Hibernate SessionFactory as they do with a local JDBC DataSource, provided they access a single database. Thus, you need only use Spring’s JTA transaction strategy when you have distributed transaction requirements. A JCA connector requires container-specific deployment steps, and (obviously) JCA support in the first place. This configuration requires more work than deploying a simple web application with local resource definitions and Spring-driven transactions. Also, you often need the Enterprise Edition of your container if you use, for example, WebLogic Express, which does not provide JCA. A Spring application with local resources and transactions that span one single database works in any Java EE web container (without JTA, JCA, or EJB), such as Tomcat, Resin, or even plain Jetty. Additionally, you can easily reuse such a middle tier in desktop applications or test suites.

All things considered, if you do not use EJBs, stick with local SessionFactory setup and Spring’s HibernateTransactionManager or JtaTransactionManager. You get all of the benefits, including proper transactional JVM-level caching and distributed transactions, without the inconvenience of container deployment. JNDI registration of a Hibernate SessionFactory through the JCA connector adds value only when used in conjunction with EJBs.

Spurious Application Server Warnings with Hibernate

In some JTA environments with very strict XADataSource implementations (currently only some WebLogic Server and WebSphere versions), when Hibernate is configured without regard to the JTA PlatformTransactionManager object for that environment, spurious warning or exceptions can show up in the application server log. These warnings or exceptions indicate that the connection being accessed is no longer valid or JDBC access is no longer valid, possibly because the transaction is no longer active. As an example, here is an actual exception from WebLogic:

java.sql.SQLException: The transaction is no longer active - status: 'Committed'. No
further JDBC access is allowed within this transaction.

You can resolve this warning by making Hibernate aware of the JTA PlatformTransactionManager instance, to which it synchronizes (along with Spring). You have two options for doing this:

If, in your application context, you already directly obtain the JTA PlatformTransactionManager object (presumably from JNDI through JndiObjectFactoryBean or <jee:jndi-lookup>) and feed it, for example, to Spring’s JtaTransactionManager, the easiest way is to specify a reference to the bean that defines this JTA PlatformTransactionManager instance as the value of the jtaTransactionManager property for LocalSessionFactoryBean. Spring then makes the object available to Hibernate.
More likely, you do not already have the JTA PlatformTransactionManager instance, because Spring’s JtaTransactionManager can find it itself. Thus, you need to configure Hibernate to look up JTA PlatformTransactionManager directly. You do this by configuring an application server-specific TransactionManagerLookup class in the Hibernate configuration, as described in the Hibernate manual.

The remainder of this section describes the sequence of events that occur with and without Hibernate’s awareness of the JTA PlatformTransactionManager.

When Hibernate is not configured with any awareness of the JTA PlatformTransactionManager, the following events occur when a JTA transaction commits:

The JTA transaction commits.
Spring’s JtaTransactionManager is synchronized to the JTA transaction, so it is called back through an afterCompletion callback by the JTA transaction manager.
Among other activities, this synchronization can trigger a callback by Spring to Hibernate, through Hibernate’s afterTransactionCompletion callback (used to clear the Hibernate cache), followed by an explicit close() call on the Hibernate session, which causes Hibernate to attempt to close() the JDBC Connection.
In some environments, this Connection.close() call then triggers the warning or error, as the application server no longer considers the Connection to be usable, because the transaction has already been committed.

When Hibernate is configured with awareness of the JTA PlatformTransactionManager, the following events occur when a JTA transaction commits:

The JTA transaction is ready to commit.
Spring’s JtaTransactionManager is synchronized to the JTA transaction, so the transaction is called back through a beforeCompletion callback by the JTA transaction manager.
Spring is aware that Hibernate itself is synchronized to the JTA transaction and behaves differently than in the previous scenario. Assuming the Hibernate Session needs to be closed at all, Spring closes it now.
The JTA transaction commits.
Hibernate is synchronized to the JTA transaction, so the transaction is called back through an afterCompletion callback by the JTA transaction manager and can properly clear its cache.

JPA

The Spring JPA, available under the org.springframework.orm.jpa package, offers comprehensive support for the Java Persistence API in a manner similar to the integration with Hibernate while being aware of the underlying implementation in order to provide additional features.

Three Options for JPA Setup in a Spring Environment

The Spring JPA support offers three ways of setting up the JPA EntityManagerFactory that is used by the application to obtain an entity manager.

Using LocalEntityManagerFactoryBean
Obtaining an EntityManagerFactory from JNDI
Using LocalContainerEntityManagerFactoryBean

Using `LocalEntityManagerFactoryBean`

You can use this option only in simple deployment environments such as stand-alone applications and integration tests.

The LocalEntityManagerFactoryBean creates an EntityManagerFactory suitable for simple deployment environments where the application uses only JPA for data access. The factory bean uses the JPA PersistenceProvider auto-detection mechanism (according to JPA’s Java SE bootstrapping) and, in most cases, requires you to specify only the persistence unit name. The following XML example configures such a bean:

<beans>
    <bean id="myEmf" class="org.springframework.orm.jpa.LocalEntityManagerFactoryBean">
        <property name="persistenceUnitName" value="myPersistenceUnit"/>
    </bean>
</beans>

This form of JPA deployment is the simplest and the most limited. You cannot refer to an existing JDBC DataSource bean definition, and no support for global transactions exists. Furthermore, weaving (byte-code transformation) of persistent classes is provider-specific, often requiring a specific JVM agent to specified on startup. This option is sufficient only for stand-alone applications and test environments, for which the JPA specification is designed.

Obtaining an EntityManagerFactory from JNDI

You can use this option when deploying to a Java EE server. Check your server’s documentation on how to deploy a custom JPA provider into your server, allowing for a different provider than the server’s default.

Obtaining an EntityManagerFactory from JNDI (for example in a Java EE environment), is a matter of changing the XML configuration, as the following example shows:

<beans>
    <jee:jndi-lookup id="myEmf" jndi-name="persistence/myPersistenceUnit"/>
</beans>

This action assumes standard Java EE bootstrapping. The Java EE server auto-detects persistence units (in effect, META-INF/persistence.xml files in application jars) and persistence-unit-ref entries in the Java EE deployment descriptor (for example, web.xml) and defines environment naming context locations for those persistence units.

In such a scenario, the entire persistence unit deployment, including the weaving (byte-code transformation) of persistent classes, is up to the Java EE server. The JDBC DataSource is defined through a JNDI location in the META-INF/persistence.xml file. EntityManager transactions are integrated with the server’s JTA subsystem. Spring merely uses the obtained EntityManagerFactory, passing it on to application objects through dependency injection and managing transactions for the persistence unit (typically through JtaTransactionManager).

If you use multiple persistence units in the same application, the bean names of such JNDI-retrieved persistence units should match the persistence unit names that the application uses to refer to them (for example, in @PersistenceUnit and @PersistenceContext annotations).

Using `LocalContainerEntityManagerFactoryBean`

You can use this option for full JPA capabilities in a Spring-based application environment. This includes web containers such as Tomcat, stand-alone applications, and integration tests with sophisticated persistence requirements.

Note

If you want to specifically configure a Hibernate setup, an immediate alternative is to go with Hibernate 5.2 or 5.3 and set up a native Hibernate LocalSessionFactoryBean instead of a plain JPA LocalContainerEntityManagerFactoryBean, letting it interact with JPA access code as well as native Hibernate access code. See Native Hibernate setup for JPA interaction for details.

The LocalContainerEntityManagerFactoryBean gives full control over EntityManagerFactory configuration and is appropriate for environments where fine-grained customization is required. The LocalContainerEntityManagerFactoryBean creates a PersistenceUnitInfo instance based on the persistence.xml file, the supplied dataSourceLookup strategy, and the specified loadTimeWeaver. It is, thus, possible to work with custom data sources outside of JNDI and to control the weaving process. The following example shows a typical bean definition for a LocalContainerEntityManagerFactoryBean:

<beans>
    <bean id="myEmf" class="org.springframework.orm.jpa.LocalContainerEntityManagerFactoryBean">
        <property name="dataSource" ref="someDataSource"/>
        <property name="loadTimeWeaver">
            <bean class="org.springframework.instrument.classloading.InstrumentationLoadTimeWeaver"/>
        </property>
    </bean>
</beans>

The following example shows a typical persistence.xml file:

<persistence xmlns="http://java.sun.com/xml/ns/persistence" version="1.0">
    <persistence-unit name="myUnit" transaction-type="RESOURCE_LOCAL">
        <mapping-file>META-INF/orm.xml</mapping-file>
        <exclude-unlisted-classes/>
    </persistence-unit>
</persistence>

Note

The <exclude-unlisted-classes/> shortcut indicates that no scanning for annotated entity classes is supposed to occur. An explicit 'true' value (<exclude-unlisted-classes>true</exclude-unlisted-classes/>) also means no scan. <exclude-unlisted-classes>false</exclude-unlisted-classes/> does trigger a scan. However, we recommend omitting the exclude-unlisted-classes element if you want entity class scanning to occur.

Using the LocalContainerEntityManagerFactoryBean is the most powerful JPA setup option, allowing for flexible local configuration within the application. It supports links to an existing JDBC DataSource, supports both local and global transactions, and so on. However, it also imposes requirements on the runtime environment, such as the availability of a weaving-capable class loader if the persistence provider demands byte-code transformation.

This option may conflict with the built-in JPA capabilities of a Java EE server. In a full Java EE environment, consider obtaining your EntityManagerFactory from JNDI. Alternatively, specify a custom persistenceXmlLocation on your LocalContainerEntityManagerFactoryBean definition (for example, META-INF/my-persistence.xml) and include only a descriptor with that name in your application jar files. Because the Java EE server looks only for default META-INF/persistence.xml files, it ignores such custom persistence units and, hence, avoids conflicts with a Spring-driven JPA setup upfront. (This applies to Resin 3.1, for example.)

When is load-time weaving required?

Not all JPA providers require a JVM agent. Hibernate is an example of one that does not. If your provider does not require an agent or you have other alternatives, such as applying enhancements at build time through a custom compiler or an Ant task, you should not use the load-time weaver.

The LoadTimeWeaver interface is a Spring-provided class that lets JPA ClassTransformer instances be plugged in a specific manner, depending on whether the environment is a web container or application server. Hooking ClassTransformers through an agent is typically not efficient. The agents work against the entire virtual machine and inspect every class that is loaded, which is usually undesirable in a production server environment.

Spring provides a number of LoadTimeWeaver implementations for various environments, letting ClassTransformer instances be applied only for each class loader and not for each VM.

See the Spring configuration in the AOP chapter for more insight regarding the LoadTimeWeaver implementations and their setup, either generic or customized to various platforms (such as Tomcat, JBoss and WebSphere).

As described in Spring configuration, you can configure a context-wide LoadTimeWeaver by using the @EnableLoadTimeWeaving annotation of the context:load-time-weaver XML element. Such a global weaver is automatically picked up by all JPA LocalContainerEntityManagerFactoryBean instances. The following example shows the preferred way of setting up a load-time weaver, delivering auto-detection of the platform (e.g. Tomcat’s weaving-capable class loader or Spring’s JVM agent) and automatic propagation of the weaver to all weaver-aware beans:

<context:load-time-weaver/>
<bean id="emf" class="org.springframework.orm.jpa.LocalContainerEntityManagerFactoryBean">
    ...
</bean>

However, you can, if needed, manually specify a dedicated weaver through the loadTimeWeaver property, as the following example shows:

<bean id="emf" class="org.springframework.orm.jpa.LocalContainerEntityManagerFactoryBean">
    <property name="loadTimeWeaver">
        <bean class="org.springframework.instrument.classloading.ReflectiveLoadTimeWeaver"/>
    </property>
</bean>

No matter how the LTW is configured, by using this technique, JPA applications relying on instrumentation can run in the target platform (for example, Tomcat) without needing an agent. This is especially important when the hosting applications rely on different JPA implementations, because the JPA transformers are applied only at the class-loader level and are, thus, isolated from each other.

Dealing with Multiple Persistence Units

For applications that rely on multiple persistence units locations (stored in various JARS in the classpath, for example), Spring offers the PersistenceUnitManager to act as a central repository and to avoid the persistence units discovery process, which can be expensive. The default implementation lets multiple locations be specified. These locations are parsed and later retrieved through the persistence unit name. (By default, the classpath is searched for META-INF/persistence.xml files.) The following example configures multiple locations:

<bean id="pum" class="org.springframework.orm.jpa.persistenceunit.DefaultPersistenceUnitManager">
    <property name="persistenceXmlLocations">
        <list>
            <value>org/springframework/orm/jpa/domain/persistence-multi.xml</value>
            <value>classpath:/my/package/**/custom-persistence.xml</value>
            <value>classpath*:META-INF/persistence.xml</value>
        </list>
    </property>
    <property name="dataSources">
        <map>
            <entry key="localDataSource" value-ref="local-db"/>
            <entry key="remoteDataSource" value-ref="remote-db"/>
        </map>
    </property>
    <!-- if no datasource is specified, use this one -->
    <property name="defaultDataSource" ref="remoteDataSource"/>
</bean>

<bean id="emf" class="org.springframework.orm.jpa.LocalContainerEntityManagerFactoryBean">
    <property name="persistenceUnitManager" ref="pum"/>
    <property name="persistenceUnitName" value="myCustomUnit"/>
</bean>

The default implementation allows customization of the PersistenceUnitInfo instances (before they are fed to the JPA provider) either declaratively (through its properties, which affect all hosted units) or programmatically (through the PersistenceUnitPostProcessor, which allows persistence unit selection). If no PersistenceUnitManager is specified, one is created and used internally by LocalContainerEntityManagerFactoryBean.

Background Bootstrapping

LocalContainerEntityManagerFactoryBean supports background bootstrapping through the bootstrapExecutor property, as the following example shows:

<bean id="emf" class="org.springframework.orm.jpa.LocalContainerEntityManagerFactoryBean">
    <property name="bootstrapExecutor">
        <bean class="org.springframework.core.task.SimpleAsyncTaskExecutor"/>
    </property>
</bean>

The actual JPA provider bootstrapping is handed off to the specified executor and then, running in parallel, to the application bootstrap thread. The exposed EntityManagerFactory proxy can be injected into other application components and is even able to respond to EntityManagerFactoryInfo configuration inspection. However, once the actual JPA provider is being accessed by other components (for example, calling createEntityManager), those calls block until the background bootstrapping has completed. In particular, when you use Spring Data JPA, make sure to set up deferred bootstrapping for its repositories as well.

Implementing DAOs Based on JPA: `EntityManagerFactory` and `EntityManager`

Note

Although EntityManagerFactory instances are thread-safe, EntityManager instances are not. The injected JPA EntityManager behaves like an EntityManager fetched from an application server’s JNDI environment, as defined by the JPA specification. It delegates all calls to the current transactional EntityManager, if any. Otherwise, it falls back to a newly created EntityManager per operation, in effect making its usage thread-safe.

It is possible to write code against the plain JPA without any Spring dependencies, by using an injected EntityManagerFactory or EntityManager. Spring can understand the @PersistenceUnit and @PersistenceContext annotations both at the field and the method level if a PersistenceAnnotationBeanPostProcessor is enabled. The following example shows a plain JPA DAO implementation that uses the @PersistenceUnit annotation:

Java

public class ProductDaoImpl implements ProductDao {

    private EntityManagerFactory emf;

    @PersistenceUnit
    public void setEntityManagerFactory(EntityManagerFactory emf) {
        this.emf = emf;
    }

    public Collection loadProductsByCategory(String category) {
        try (EntityManager em = this.emf.createEntityManager()) {
            Query query = em.createQuery("from Product as p where p.category = ?1");
            query.setParameter(1, category);
            return query.getResultList();
        }
    }
}

Kotlin

class ProductDaoImpl : ProductDao {

    private lateinit var emf: EntityManagerFactory

    @PersistenceUnit
    fun setEntityManagerFactory(emf: EntityManagerFactory) {
        this.emf = emf
    }

    fun loadProductsByCategory(category: String): Collection<*> {
        val em = this.emf.createEntityManager()
        val query = em.createQuery("from Product as p where p.category = ?1");
        query.setParameter(1, category);
        return query.resultList;
    }
}

The preceding DAO has no dependency on Spring and still fits nicely into a Spring application context. Moreover, the DAO takes advantage of annotations to require the injection of the default EntityManagerFactory, as the following example bean definition shows:

<beans>

    <!-- bean post-processor for JPA annotations -->
    <bean class="org.springframework.orm.jpa.support.PersistenceAnnotationBeanPostProcessor"/>

    <bean id="myProductDao" class="product.ProductDaoImpl"/>

</beans>

As an alternative to explicitly defining a PersistenceAnnotationBeanPostProcessor, consider using the Spring context:annotation-config XML element in your application context configuration. Doing so automatically registers all Spring standard post-processors for annotation-based configuration, including CommonAnnotationBeanPostProcessor and so on.

Consider the following example:

<beans>

    <!-- post-processors for all standard config annotations -->
    <context:annotation-config/>

    <bean id="myProductDao" class="product.ProductDaoImpl"/>

</beans>

The main problem with such a DAO is that it always creates a new EntityManager through the factory. You can avoid this by requesting a transactional EntityManager (also called a “shared EntityManager” because it is a shared, thread-safe proxy for the actual transactional EntityManager) to be injected instead of the factory. The following example shows how to do so:

Java

public class ProductDaoImpl implements ProductDao {

    @PersistenceContext
    private EntityManager em;

    public Collection loadProductsByCategory(String category) {
        Query query = em.createQuery("from Product as p where p.category = :category");
        query.setParameter("category", category);
        return query.getResultList();
    }
}

Kotlin

class ProductDaoImpl : ProductDao {

    @PersistenceContext
    private lateinit var em: EntityManager

    fun loadProductsByCategory(category: String): Collection<*> {
        val query = em.createQuery("from Product as p where p.category = :category")
        query.setParameter("category", category)
        return query.resultList
    }
}

The @PersistenceContext annotation has an optional attribute called type, which defaults to PersistenceContextType.TRANSACTION. You can use this default to receive a shared EntityManager proxy. The alternative, PersistenceContextType.EXTENDED, is a completely different affair. This results in a so-called extended EntityManager, which is not thread-safe and, hence, must not be used in a concurrently accessed component, such as a Spring-managed singleton bean. Extended EntityManager instances are only supposed to be used in stateful components that, for example, reside in a session, with the lifecycle of the EntityManager not tied to a current transaction but rather being completely up to the application.

Method- and field-level Injection

You can apply annotations that indicate dependency injections (such as @PersistenceUnit and @PersistenceContext) on field or methods inside a class — hence the expressions “method-level injection” and “field-level injection”. Field-level annotations are concise and easier to use while method-level annotations allow for further processing of the injected dependency. In both cases, the member visibility (public, protected, or private) does not matter.

What about class-level annotations?

On the Java EE platform, they are used for dependency declaration and not for resource injection.

The injected EntityManager is Spring-managed (aware of the ongoing transaction). Even though the new DAO implementation uses method-level injection of an EntityManager instead of an EntityManagerFactory, no change is required in the application context XML, due to annotation usage.

The main advantage of this DAO style is that it depends only on the Java Persistence API. No import of any Spring class is required. Moreover, as the JPA annotations are understood, the injections are applied automatically by the Spring container. This is appealing from a non-invasiveness perspective and can feel more natural to JPA developers.

Spring-driven JPA transactions

Note	We strongly encourage you to read Declarative transaction management, if you have not already done so, to get more detailed coverage of Spring’s declarative transaction support.

The recommended strategy for JPA is local transactions through JPA’s native transaction support. Spring’s JpaTransactionManager provides many capabilities known from local JDBC transactions (such as transaction-specific isolation levels and resource-level read-only optimizations) against any regular JDBC connection pool (no XA requirement).

Spring JPA also lets a configured JpaTransactionManager expose a JPA transaction to JDBC access code that accesses the same DataSource, provided that the registered JpaDialect supports retrieval of the underlying JDBC Connection. Spring provides dialects for the EclipseLink and Hibernate JPA implementations. See the next section for details on the JpaDialect mechanism.

Note

As an immediate alternative, Spring’s native HibernateTransactionManager is capable of interacting with JPA access code as of Spring Framework 5.1 and Hibernate 5.2/5.3, adapting to several Hibernate specifics and providing JDBC interaction. This makes particular sense in combination with LocalSessionFactoryBean setup. See Native Hibernate Setup for JPA Interaction for details.

Understanding `JpaDialect` and `JpaVendorAdapter`

As an advanced feature, JpaTransactionManager and subclasses of AbstractEntityManagerFactoryBean allow a custom JpaDialect to be passed into the jpaDialect bean property. A JpaDialect implementation can enable the following advanced features supported by Spring, usually in a vendor-specific manner:

Applying specific transaction semantics (such as custom isolation level or transaction timeout)
Retrieving the transactional JDBC Connection (for exposure to JDBC-based DAOs)
Advanced translation of PersistenceExceptions to Spring DataAccessExceptions

This is particularly valuable for special transaction semantics and for advanced translation of exception. The default implementation (DefaultJpaDialect) does not provide any special abilities and, if the features listed earlier are required, you have to specify the appropriate dialect.

Tip

As an even broader provider adaptation facility primarily for Spring’s full-featured LocalContainerEntityManagerFactoryBean setup, JpaVendorAdapter combines the capabilities of JpaDialect with other provider-specific defaults. Specifying a HibernateJpaVendorAdapter or EclipseLinkJpaVendorAdapter is the most convenient way of auto-configuring an EntityManagerFactory setup for Hibernate or EclipseLink, respectively. Note that those provider adapters are primarily designed for use with Spring-driven transaction management (that is, for use with JpaTransactionManager).

See the JpaDialect and JpaVendorAdapter javadoc for more details of its operations and how they are used within Spring’s JPA support.

Setting up JPA with JTA Transaction Management

As an alternative to JpaTransactionManager, Spring also allows for multi-resource transaction coordination through JTA, either in a Java EE environment or with a stand-alone transaction coordinator, such as Atomikos. Aside from choosing Spring’s JtaTransactionManager instead of JpaTransactionManager, you need to take few further steps:

The underlying JDBC connection pools need to be XA-capable and be integrated with your transaction coordinator. This is usually straightforward in a Java EE environment, exposing a different kind of DataSource through JNDI. See your application server documentation for details. Analogously, a standalone transaction coordinator usually comes with special XA-integrated DataSource implementations. Again, check its documentation.
The JPA EntityManagerFactory setup needs to be configured for JTA. This is provider-specific, typically through special properties to be specified as jpaProperties on LocalContainerEntityManagerFactoryBean. In the case of Hibernate, these properties are even version-specific. See your Hibernate documentation for details.
Spring’s HibernateJpaVendorAdapter enforces certain Spring-oriented defaults, such as the connection release mode, on-close, which matches Hibernate’s own default in Hibernate 5.0 but not any more in 5.1/5.2. For a JTA setup, either do not declare HibernateJpaVendorAdapter to begin with or turn off its prepareConnection flag. Alternatively, set Hibernate 5.2’s hibernate.connection.handling_mode property to DELAYED_ACQUISITION_AND_RELEASE_AFTER_STATEMENT to restore Hibernate’s own default. See Spurious Application Server Warnings with Hibernate for a related note about WebLogic.
Alternatively, consider obtaining the EntityManagerFactory from your application server itself (that is, through a JNDI lookup instead of a locally declared LocalContainerEntityManagerFactoryBean). A server-provided EntityManagerFactory might require special definitions in your server configuration (making the deployment less portable) but is set up for the server’s JTA environment.

Native Hibernate Setup and Native Hibernate Transactions for JPA Interaction

As of Spring Framework 5.1 and Hibernate 5.2/5.3, a native LocalSessionFactoryBean setup in combination with HibernateTransactionManager allows for interaction with @PersistenceContext and other JPA access code. A Hibernate SessionFactory natively implements JPA’s EntityManagerFactory interface now and a Hibernate Session handle natively is a JPA EntityManager. Spring’s JPA support facilities automatically detect native Hibernate sessions.

Such native Hibernate setup can, therefore, serve as a replacement for a standard JPA LocalContainerEntityManagerFactoryBean and JpaTransactionManager combination in many scenarios, allowing for interaction with SessionFactory.getCurrentSession() (and also HibernateTemplate) next to @PersistenceContext EntityManager within the same local transaction. Such a setup also provides stronger Hibernate integration and more configuration flexibility, because it is not constrained by JPA bootstrap contracts.

You do not need HibernateJpaVendorAdapter configuration in such a scenario, since Spring’s native Hibernate setup provides even more features (for example, custom Hibernate Integrator setup, Hibernate 5.3 bean container integration, and stronger optimizations for read-only transactions). Last but not least, you can also express native Hibernate setup through LocalSessionFactoryBuilder, seamlessly integrating with @Bean style configuration (no FactoryBean involved).

Note

LocalSessionFactoryBean and LocalSessionFactoryBuilder support background bootstrapping, just as the JPA LocalContainerEntityManagerFactoryBean does. See Background Bootstrapping for an introduction.

On LocalSessionFactoryBean, this is available through the bootstrapExecutor property. On the programmatic LocalSessionFactoryBuilder, an overloaded buildSessionFactory method takes a bootstrap executor argument.

Marshalling XML by Using Object-XML Mappers

Introduction

This chapter, describes Spring’s Object-XML Mapping support. Object-XML Mapping (O-X mapping for short) is the act of converting an XML document to and from an object. This conversion process is also known as XML Marshalling, or XML Serialization. This chapter uses these terms interchangeably.

Within the field of O-X mapping, a marshaller is responsible for serializing an object (graph) to XML. In similar fashion, an unmarshaller deserializes the XML to an object graph. This XML can take the form of a DOM document, an input or output stream, or a SAX handler.

Some of the benefits of using Spring for your O/X mapping needs are:

Ease of configuration
Consistent Interfaces
Consistent Exception Hierarchy

Ease of configuration

Spring’s bean factory makes it easy to configure marshallers, without needing to construct JAXB context, JiBX binding factories, and so on. You can configure the marshallers as you would any other bean in your application context. Additionally, XML namespace-based configuration is available for a number of marshallers, making the configuration even simpler.

Consistent Interfaces

Spring’s O-X mapping operates through two global interfaces: Marshaller and Unmarshaller. These abstractions let you switch O-X mapping frameworks with relative ease, with little or no change required on the classes that do the marshalling. This approach has the additional benefit of making it possible to do XML marshalling with a mix-and-match approach (for example, some marshalling performed using JAXB and some by XStream) in a non-intrusive fashion, letting you use the strength of each technology.

Consistent Exception Hierarchy

Spring provides a conversion from exceptions from the underlying O-X mapping tool to its own exception hierarchy with the XmlMappingException as the root exception. These runtime exceptions wrap the original exception so that no information is lost.

`Marshaller` and `Unmarshaller`

As stated in the introduction, a marshaller serializes an object to XML, and an unmarshaller deserializes XML stream to an object. This section describes the two Spring interfaces used for this purpose.

Understanding `Marshaller`

Spring abstracts all marshalling operations behind the org.springframework.oxm.Marshaller interface, the main method of which follows:

Java

public interface Marshaller {

    /**
     * Marshal the object graph with the given root into the provided Result.
     */
    void marshal(Object graph, Result result) throws XmlMappingException, IOException;
}

Kotlin

interface Marshaller {

    /**
    * Marshal the object graph with the given root into the provided Result.
    */
    @Throws(XmlMappingException::class, IOException::class)
    fun marshal(
            graph: Any,
            result: Result
    )
}

The Marshaller interface has one main method, which marshals the given object to a given javax.xml.transform.Result. The result is a tagging interface that basically represents an XML output abstraction. Concrete implementations wrap various XML representations, as the following table indicates:

Result implementation	Wraps XML representation
`DOMResult`	`org.w3c.dom.Node`
`SAXResult`	`org.xml.sax.ContentHandler`
`StreamResult`	`java.io.File`, `java.io.OutputStream`, or `java.io.Writer`

Note

Although the marshal() method accepts a plain object as its first parameter, most Marshaller implementations cannot handle arbitrary objects. Instead, an object class must be mapped in a mapping file, be marked with an annotation, be registered with the marshaller, or have a common base class. Refer to the later sections in this chapter to determine how your O-X technology manages this.

Understanding `Unmarshaller`

Similar to the Marshaller, we have the org.springframework.oxm.Unmarshaller interface, which the following listing shows:

Java

public interface Unmarshaller {

    /**
     * Unmarshal the given provided Source into an object graph.
     */
    Object unmarshal(Source source) throws XmlMappingException, IOException;
}

Kotlin

interface Unmarshaller {

    /**
    * Unmarshal the given provided Source into an object graph.
    */
    @Throws(XmlMappingException::class, IOException::class)
    fun unmarshal(source: Source): Any
}

This interface also has one method, which reads from the given javax.xml.transform.Source (an XML input abstraction) and returns the object read. As with Result, Source is a tagging interface that has three concrete implementations. Each wraps a different XML representation, as the following table indicates:

Source implementation	Wraps XML representation
`DOMSource`	`org.w3c.dom.Node`
`SAXSource`	`org.xml.sax.InputSource`, and `org.xml.sax.XMLReader`
`StreamSource`	`java.io.File`, `java.io.InputStream`, or `java.io.Reader`

Even though there are two separate marshalling interfaces (Marshaller and Unmarshaller), all implementations in Spring-WS implement both in one class. This means that you can wire up one marshaller class and refer to it both as a marshaller and as an unmarshaller in your applicationContext.xml.

Understanding `XmlMappingException`

Spring converts exceptions from the underlying O-X mapping tool to its own exception hierarchy with the XmlMappingException as the root exception. These runtime exceptions wrap the original exception so that no information will be lost.

Additionally, the MarshallingFailureException and UnmarshallingFailureException provide a distinction between marshalling and unmarshalling operations, even though the underlying O-X mapping tool does not do so.

The O-X Mapping exception hierarchy is shown in the following figure:

Using `Marshaller` and `Unmarshaller`

You can use Spring’s OXM for a wide variety of situations. In the following example, we use it to marshal the settings of a Spring-managed application as an XML file. In the following example, we use a simple JavaBean to represent the settings:

Java

public class Settings {

    private boolean fooEnabled;

    public boolean isFooEnabled() {
        return fooEnabled;
    }

    public void setFooEnabled(boolean fooEnabled) {
        this.fooEnabled = fooEnabled;
    }
}

Kotlin

class Settings {
    var isFooEnabled: Boolean = false
}

The application class uses this bean to store its settings. Besides a main method, the class has two methods: saveSettings() saves the settings bean to a file named settings.xml, and loadSettings() loads these settings again. The following main() method constructs a Spring application context and calls these two methods:

Java

import java.io.FileInputStream;
import java.io.FileOutputStream;
import java.io.IOException;
import javax.xml.transform.stream.StreamResult;
import javax.xml.transform.stream.StreamSource;
import org.springframework.context.ApplicationContext;
import org.springframework.context.support.ClassPathXmlApplicationContext;
import org.springframework.oxm.Marshaller;
import org.springframework.oxm.Unmarshaller;

public class Application {

    private static final String FILE_NAME = "settings.xml";
    private Settings settings = new Settings();
    private Marshaller marshaller;
    private Unmarshaller unmarshaller;

    public void setMarshaller(Marshaller marshaller) {
        this.marshaller = marshaller;
    }

    public void setUnmarshaller(Unmarshaller unmarshaller) {
        this.unmarshaller = unmarshaller;
    }

    public void saveSettings() throws IOException {
        try (FileOutputStream os = new FileOutputStream(FILE_NAME)) {
            this.marshaller.marshal(settings, new StreamResult(os));
        }
    }

    public void loadSettings() throws IOException {
        try (FileInputStream is = new FileInputStream(FILE_NAME)) {
            this.settings = (Settings) this.unmarshaller.unmarshal(new StreamSource(is));
        }
    }

    public static void main(String[] args) throws IOException {
        ApplicationContext appContext =
                new ClassPathXmlApplicationContext("applicationContext.xml");
        Application application = (Application) appContext.getBean("application");
        application.saveSettings();
        application.loadSettings();
    }
}

Kotlin

class Application {

    lateinit var marshaller: Marshaller

    lateinit var unmarshaller: Unmarshaller

    fun saveSettings() {
        FileOutputStream(FILE_NAME).use { outputStream -> marshaller.marshal(settings, StreamResult(outputStream)) }
    }

    fun loadSettings() {
        FileInputStream(FILE_NAME).use { inputStream -> settings = unmarshaller.unmarshal(StreamSource(inputStream)) as Settings }
    }
}

private const val FILE_NAME = "settings.xml"

fun main(args: Array<String>) {
    val appContext = ClassPathXmlApplicationContext("applicationContext.xml")
    val application = appContext.getBean("application") as Application
    application.saveSettings()
    application.loadSettings()
}

The Application requires both a marshaller and an unmarshaller property to be set. We can do so by using the following applicationContext.xml:

<beans>
    <bean id="application" class="Application">
        <property name="marshaller" ref="xstreamMarshaller" />
        <property name="unmarshaller" ref="xstreamMarshaller" />
    </bean>
    <bean id="xstreamMarshaller" class="org.springframework.oxm.xstream.XStreamMarshaller"/>
</beans>

This application context uses XStream, but we could have used any of the other marshaller instances described later in this chapter. Note that, by default, XStream does not require any further configuration, so the bean definition is rather simple. Also note that the XStreamMarshaller implements both Marshaller and Unmarshaller, so we can refer to the xstreamMarshaller bean in both the marshaller and unmarshaller property of the application.

This sample application produces the following settings.xml file:

<?xml version="1.0" encoding="UTF-8"?>
<settings foo-enabled="false"/>

XML Configuration Namespace

You can configure marshallers more concisely by using tags from the OXM namespace. To make these tags available, you must first reference the appropriate schema in the preamble of the XML configuration file. The following example shows how to do so:

<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
    xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
    xmlns:oxm="http://www.springframework.org/schema/oxm" (1)
xsi:schemaLocation="http://www.springframework.org/schema/beans
  https://www.springframework.org/schema/beans/spring-beans.xsd
  http://www.springframework.org/schema/oxm https://www.springframework.org/schema/oxm/spring-oxm.xsd"> (2)

Reference the oxm schema.
Specify the oxm schema location.

The schema makes the following elements available:

jaxb2-marshaller
jibx-marshaller

Each tag is explained in its respective marshaller’s section. As an example, though, the configuration of a JAXB2 marshaller might resemble the following:

<oxm:jaxb2-marshaller id="marshaller" contextPath="org.springframework.ws.samples.airline.schema"/>

JAXB

The JAXB binding compiler translates a W3C XML Schema into one or more Java classes, a jaxb.properties file, and possibly some resource files. JAXB also offers a way to generate a schema from annotated Java classes.

Spring supports the JAXB 2.0 API as XML marshalling strategies, following the Marshaller and Unmarshaller interfaces described in Marshaller and Unmarshaller. The corresponding integration classes reside in the org.springframework.oxm.jaxb package.

Using `Jaxb2Marshaller`

The Jaxb2Marshaller class implements both of Spring’s Marshaller and Unmarshaller interfaces. It requires a context path to operate. You can set the context path by setting the contextPath property. The context path is a list of colon-separated Java package names that contain schema derived classes. It also offers a classesToBeBound property, which allows you to set an array of classes to be supported by the marshaller. Schema validation is performed by specifying one or more schema resources to the bean, as the following example shows:

<beans>
    <bean id="jaxb2Marshaller" class="org.springframework.oxm.jaxb.Jaxb2Marshaller">
        <property name="classesToBeBound">
            <list>
                <value>org.springframework.oxm.jaxb.Flight</value>
                <value>org.springframework.oxm.jaxb.Flights</value>
            </list>
        </property>
        <property name="schema" value="classpath:org/springframework/oxm/schema.xsd"/>
    </bean>

    ...

</beans>

XML Configuration Namespace

The jaxb2-marshaller element configures a org.springframework.oxm.jaxb.Jaxb2Marshaller, as the following example shows:

<oxm:jaxb2-marshaller id="marshaller" contextPath="org.springframework.ws.samples.airline.schema"/>

Alternatively, you can provide the list of classes to bind to the marshaller by using the class-to-be-bound child element:

<oxm:jaxb2-marshaller id="marshaller">
    <oxm:class-to-be-bound name="org.springframework.ws.samples.airline.schema.Airport"/>
    <oxm:class-to-be-bound name="org.springframework.ws.samples.airline.schema.Flight"/>
    ...
</oxm:jaxb2-marshaller>

The following table describes the available attributes:

Attribute	Description	Required
`id`	The ID of the marshaller	No
`contextPath`	The JAXB Context path	No

JiBX

The JiBX framework offers a solution similar to that which Hibernate provides for ORM: A binding definition defines the rules for how your Java objects are converted to or from XML. After preparing the binding and compiling the classes, a JiBX binding compiler enhances the class files and adds code to handle converting instances of the classes from or to XML.

For more information on JiBX, see the JiBX web site. The Spring integration classes reside in the org.springframework.oxm.jibx package.

Using `JibxMarshaller`

The JibxMarshaller class implements both the Marshaller and Unmarshaller interface. To operate, it requires the name of the class to marshal in, which you can set using the targetClass property. Optionally, you can set the binding name by setting the bindingName property. In the following example, we bind the Flights class:

<beans>
    <bean id="jibxFlightsMarshaller" class="org.springframework.oxm.jibx.JibxMarshaller">
        <property name="targetClass">org.springframework.oxm.jibx.Flights</property>
    </bean>
    ...
</beans>

A JibxMarshaller is configured for a single class. If you want to marshal multiple classes, you have to configure multiple JibxMarshaller instances with different targetClass property values.

XML Configuration Namespace

The jibx-marshaller tag configures a org.springframework.oxm.jibx.JibxMarshaller, as the following example shows:

<oxm:jibx-marshaller id="marshaller" target-class="org.springframework.ws.samples.airline.schema.Flight"/>

The following table describes the available attributes:

Attribute	Description	Required
`id`	The ID of the marshaller	No
`target-class`	The target class for this marshaller	Yes
`bindingName`	The binding name used by this marshaller	No

XStream

XStream is a simple library to serialize objects to XML and back again. It does not require any mapping and generates clean XML.

For more information on XStream, see the XStream web site. The Spring integration classes reside in the org.springframework.oxm.xstream package.

Using `XStreamMarshaller`

The XStreamMarshaller does not require any configuration and can be configured in an application context directly. To further customize the XML, you can set an alias map, which consists of string aliases mapped to classes, as the following example shows:

<beans>
    <bean id="xstreamMarshaller" class="org.springframework.oxm.xstream.XStreamMarshaller">
        <property name="aliases">
            <props>
                <prop key="Flight">org.springframework.oxm.xstream.Flight</prop>
            </props>
        </property>
    </bean>
    ...
</beans>

Warning

By default, XStream lets arbitrary classes be unmarshalled, which can lead to unsafe Java serialization effects. As such, we do not recommend using the XStreamMarshaller to unmarshal XML from external sources (that is, the Web), as this can result in security vulnerabilities.

If you choose to use the XStreamMarshaller to unmarshal XML from an external source, set the supportedClasses property on the XStreamMarshaller, as the following example shows:

<bean id="xstreamMarshaller" class="org.springframework.oxm.xstream.XStreamMarshaller">
    <property name="supportedClasses" value="org.springframework.oxm.xstream.Flight"/>
    ...
</bean>

Doing so ensures that only the registered classes are eligible for unmarshalling.

Additionally, you can register custom converters to make sure that only your supported classes can be unmarshalled. You might want to add a CatchAllConverter as the last converter in the list, in addition to converters that explicitly support the domain classes that should be supported. As a result, default XStream converters with lower priorities and possible security vulnerabilities do not get invoked.

Note	Note that XStream is an XML serialization library, not a data binding library. Therefore, it has limited namespace support. As a result, it is rather unsuitable for usage within Web services.

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Data Access

Transaction Management

Advantages of the Spring Framework’s Transaction Support Model

Global Transactions

Local Transactions

Spring Framework’s Consistent Programming Model

Understanding the Spring Framework Transaction Abstraction

Synchronizing Resources with Transactions

High-level Synchronization Approach

Low-level Synchronization Approach

TransactionAwareDataSourceProxy

Declarative transaction management

Understanding the Spring Framework’s Declarative Transaction Implementation

Example of Declarative Transaction Implementation

Rolling Back a Declarative Transaction

Configuring Different Transactional Semantics for Different Beans

<tx:advice/> Settings

Using @Transactional

@Transactional Settings

Multiple Transaction Managers with @Transactional

Custom Shortcut Annotations

Transaction Propagation

Understanding PROPAGATION_REQUIRED

Understanding PROPAGATION_REQUIRES_NEW

Understanding PROPAGATION_NESTED

Advising Transactional Operations

Using @Transactional with AspectJ

Programmatic Transaction Management

Using the TransactionTemplate

Specifying Transaction Settings

Using the PlatformTransactionManager

Choosing Between Programmatic and Declarative Transaction Management

Transaction-bound Events

Application server-specific integration

IBM WebSphere

Oracle WebLogic Server

Solutions to Common Problems

Using the Wrong Transaction Manager for a Specific DataSource

Further Resources

DAO Support

Consistent Exception Hierarchy

Annotations Used to Configure DAO or Repository Classes

Data Access with JDBC

Choosing an Approach for JDBC Database Access

Package Hierarchy

Using the JDBC Core Classes to Control Basic JDBC Processing and Error Handling

Using JdbcTemplate

Querying (SELECT)

Updating (INSERT, UPDATE, and DELETE) with JdbcTemplate

Other JdbcTemplate Operations

JdbcTemplate Best Practices

Using NamedParameterJdbcTemplate

Using SQLExceptionTranslator

Running Statements

Running Queries

Updating the Database

Retrieving Auto-generated Keys

Controlling Database Connections

Using DataSource

Using DataSourceUtils

Implementing SmartDataSource

Extending AbstractDataSource

Using SingleConnectionDataSource

Using DriverManagerDataSource

Using TransactionAwareDataSourceProxy

Using DataSourceTransactionManager

JDBC Batch Operations

Basic Batch Operations with JdbcTemplate

Batch Operations with a List of Objects

Batch Operations with Multiple Batches

Simplifying JDBC Operations with the SimpleJdbc Classes

Inserting Data by Using SimpleJdbcInsert

Retrieving Auto-generated Keys by Using SimpleJdbcInsert

Specifying Columns for a SimpleJdbcInsert

`TransactionAwareDataSourceProxy`

Using `@Transactional`

`@Transactional` Settings

Multiple Transaction Managers with `@Transactional`

Understanding `PROPAGATION_REQUIRED`

Understanding `PROPAGATION_REQUIRES_NEW`

Understanding `PROPAGATION_NESTED`

Using `@Transactional` with AspectJ

Using the `TransactionTemplate`

Using the `PlatformTransactionManager`

Using the Wrong Transaction Manager for a Specific `DataSource`

Using `JdbcTemplate`

Querying (`SELECT`)

Updating (`INSERT`, `UPDATE`, and `DELETE`) with `JdbcTemplate`

Other `JdbcTemplate` Operations

`JdbcTemplate` Best Practices

Using `NamedParameterJdbcTemplate`

Using `SQLExceptionTranslator`

Using `DataSource`

Using `DataSourceUtils`

Implementing `SmartDataSource`

Extending `AbstractDataSource`

Using `SingleConnectionDataSource`

Using `DriverManagerDataSource`

Using `TransactionAwareDataSourceProxy`

Using `DataSourceTransactionManager`

Basic Batch Operations with `JdbcTemplate`

Simplifying JDBC Operations with the `SimpleJdbc` Classes

Inserting Data by Using `SimpleJdbcInsert`

Retrieving Auto-generated Keys by Using `SimpleJdbcInsert`

Specifying Columns for a `SimpleJdbcInsert`

Using `SqlParameterSource` to Provide Parameter Values

Calling a Stored Procedure with `SimpleJdbcCall`

Explicitly Declaring Parameters to Use for a `SimpleJdbcCall`

How to Define `SqlParameters`

Calling a Stored Function by Using `SimpleJdbcCall`

Returning a `ResultSet` or REF Cursor from a `SimpleJdbcCall`

Understanding `SqlQuery`

Using `MappingSqlQuery`

Using `SqlUpdate`

Using `StoredProcedure`

Initializing a `DataSource`

`SessionFactory` Setup in a Spring Container

Using `LocalEntityManagerFactoryBean`

Using `LocalContainerEntityManagerFactoryBean`

Implementing DAOs Based on JPA: `EntityManagerFactory` and `EntityManager`

Understanding `JpaDialect` and `JpaVendorAdapter`

`Marshaller` and `Unmarshaller`

Understanding `Marshaller`

Understanding `Unmarshaller`