[[spring-data-tier]] = Data Access include::attributes.adoc[] include::page-layout.adoc[] 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]] == 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 <>. * A simpler API for <> 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: * <> 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. * <> outlines the core classes and describes how to configure and obtain `DataSource` instances from a variety of sources. * <> describes how the application code ensures that resources are created, reused, and cleaned up properly. * <> describes support for declarative transaction management. * <> covers support for programmatic (that is, explicitly coded) transaction management. * <> describes how you could use application events within a transaction. The chapter also includes discussions of best practices, <>, and <>. [[transaction-motivation]] === Advantages of the Spring Framework's Transaction Support Model Traditionally, EE application 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. [[transaction-global]] ==== 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. [[transaction-local]] ==== 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. [[transaction-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 https://www.atomikos.com/[Atomikos Transactions]) are other options. Of course, you may need other application server capabilities, such as Java Message Service (JMS) and Jakarta 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). **** [[transaction-strategies]] === 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 a `TransactionManager`, specifically the `org.springframework.transaction.PlatformTransactionManager` interface for imperative transaction management and the `org.springframework.transaction.ReactiveTransactionManager` interface for reactive transaction management. The following listing shows the definition of the `PlatformTransactionManager` API: [source,java,indent=0,subs="verbatim,quotes"] ---- public interface PlatformTransactionManager extends TransactionManager { TransactionStatus getTransaction(TransactionDefinition definition) throws TransactionException; void commit(TransactionStatus status) throws TransactionException; void rollback(TransactionStatus status) throws TransactionException; } ---- This is primarily a service provider interface (SPI), although you can use it <> 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 Jakarta EE transaction contexts, a `TransactionStatus` is associated with a thread of execution. As of Spring Framework 5.2, Spring also provides a transaction management abstraction for reactive applications that make use of reactive types or Kotlin Coroutines. The following listing shows the transaction strategy defined by `org.springframework.transaction.ReactiveTransactionManager`: [source,java,indent=0,subs="verbatim,quotes"] ---- public interface ReactiveTransactionManager extends TransactionManager { Mono getReactiveTransaction(TransactionDefinition definition) throws TransactionException; Mono commit(ReactiveTransaction status) throws TransactionException; Mono rollback(ReactiveTransaction status) throws TransactionException; } ---- The reactive transaction manager is primarily a service provider interface (SPI), although you can use it <> from your application code. Because `ReactiveTransactionManager` is an interface, it can be easily mocked or stubbed as necessary. The `TransactionDefinition` interface specifies: * Propagation: Typically, all code within a transaction scope runs in that transaction. However, you can specify the behavior if a transactional method is run 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 <>. * 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: [source,java,indent=0,subs="verbatim,quotes"] ---- public interface TransactionStatus extends TransactionExecution, SavepointManager, Flushable { @Override boolean isNewTransaction(); boolean hasSavepoint(); @Override void setRollbackOnly(); @Override boolean isRollbackOnly(); void flush(); @Override boolean isCompleted(); } ---- Regardless of whether you opt for declarative or programmatic transaction management in Spring, defining the correct `TransactionManager` implementation is absolutely essential. You typically define this implementation through dependency injection. `TransactionManager` 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: [source,xml,indent=0,subs="verbatim,quotes"] ---- ---- The related `PlatformTransactionManager` bean definition then has a reference to the `DataSource` definition. It should resemble the following example: [source,xml,indent=0,subs="verbatim,quotes"] ---- ---- If you use JTA in a Jakarta 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: [source,xml,indent=0,subs="verbatim,quotes"] ---- ---- 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 `` tag from the `jee` namespace. For more information see <>. 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 Spring transaction setups, 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. [[transaction-strategies-hibernate]] ==== Hibernate Transaction Setup You can also easily use 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 Jakarta EE container, it should be non-transactional, because the Spring Framework (rather than the Jakarta 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: [source,xml,indent=0,subs="verbatim,quotes"] ---- org/springframework/samples/petclinic/hibernate/petclinic.hbm.xml hibernate.dialect=${hibernate.dialect} ---- If you use Hibernate and Jakarta EE container-managed JTA transactions, you should use the same `JtaTransactionManager` as in the previous JTA example for JDBC, as the following example shows. Also, it is recommended to make Hibernate aware of JTA through its transaction coordinator and possibly also its connection release mode configuration: [source,xml,indent=0,subs="verbatim,quotes"] ---- org/springframework/samples/petclinic/hibernate/petclinic.hbm.xml hibernate.dialect=${hibernate.dialect} hibernate.transaction.coordinator_class=jta hibernate.connection.handling_mode=DELAYED_ACQUISITION_AND_RELEASE_AFTER_STATEMENT ---- Or alternatively, you may pass the `JtaTransactionManager` into your `LocalSessionFactoryBean` for enforcing the same defaults: [source,xml,indent=0,subs="verbatim,quotes"] ---- org/springframework/samples/petclinic/hibernate/petclinic.hbm.xml hibernate.dialect=${hibernate.dialect} ---- [[tx-resource-synchronization]] === 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 `TransactionManager`. [[tx-resource-synchronization-high]] ==== 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 sections of this reference documentation. [[tx-resource-synchronization-low]] ==== 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: [source,java,indent=0,subs="verbatim,quotes"] ---- 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. [[tx-resource-synchronization-tadsp]] ==== `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 Jakarta 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. [[transaction-declarative]] === 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 <>, 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. [[tx-decl-explained]] ==== 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 context 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 <> 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 `TransactionManager` implementation to drive transactions around method invocations. NOTE: Spring AOP is covered in <>. Spring Framework's `TransactionInterceptor` provides transaction management for imperative and reactive programming models. The interceptor detects the desired flavor of transaction management by inspecting the method return type. Methods returning a reactive type such as `Publisher` or Kotlin `Flow` (or a subtype of those) qualify for reactive transaction management. All other return types including `void` use the code path for imperative transaction management. Transaction management flavors impact which transaction manager is required. Imperative transactions require a `PlatformTransactionManager`, while reactive transactions use `ReactiveTransactionManager` implementations. [NOTE] ==== `@Transactional` commonly works with thread-bound transactions managed by `PlatformTransactionManager`, exposing a transaction to all data access operations within the current execution thread. Note: This does _not_ propagate to newly started threads within the method. A reactive transaction managed by `ReactiveTransactionManager` uses the Reactor context instead of thread-local attributes. As a consequence, all participating data access operations need to execute within the same Reactor context in the same reactive pipeline. ==== The following image shows a conceptual view of calling a method on a transactional proxy: image::images/tx.png[] [[transaction-declarative-first-example]] ==== 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 being created and then rolled back in response to the `UnsupportedOperationException` instance. The following listing shows the `FooService` interface: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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); } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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) { // ... } } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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 run in the context of a transaction with read-only semantics and that the other methods, `insertFoo(Foo)` and `updateFoo(Foo)`, must run in the context of a transaction with read-write semantics. The following configuration is explained in detail in the next few paragraphs: [source,xml,indent=0,subs="verbatim"] ---- ---- 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 `` definition. The `` definition reads as "all methods starting with `get` are to run in the context of a read-only transaction, and all other methods are to run with the default transaction semantics". The `transaction-manager` attribute of the `` tag is set to the name of the `TransactionManager` 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 (``) if the bean name of the `TransactionManager` that you want to wire in has the name `transactionManager`. If the `TransactionManager` 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 `` definition ensures that the transactional advice defined by the `txAdvice` bean runs 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 `` element is an AspectJ pointcut expression. See <> 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: [source,xml,indent=0,subs="verbatim"] ---- ---- NOTE: In the preceding example, it is assumed that all your service interfaces are defined in the `x.y.service` package. See <> 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- public final class Boot { public static void main(final String[] args) throws Exception { ApplicationContext ctx = new ClassPathXmlApplicationContext("context.xml"); FooService fooService = ctx.getBean(FooService.class); fooService.insertFoo(new Foo()); } } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- import org.springframework.beans.factory.getBean fun main() { val ctx = ClassPathXmlApplicationContext("context.xml") val fooService = ctx.getBean("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): [source,xml,indent=0,subs="verbatim,quotes"] ---- [AspectJInvocationContextExposingAdvisorAutoProxyCreator] - Creating implicit proxy for bean 'fooService' with 0 common interceptors and 1 specific interceptors [JdkDynamicAopProxy] - Creating JDK dynamic proxy for [x.y.service.DefaultFooService] [TransactionInterceptor] - Getting transaction for x.y.service.FooService.insertFoo [DataSourceTransactionManager] - Creating new transaction with name [x.y.service.FooService.insertFoo] [DataSourceTransactionManager] - Acquired Connection [org.apache.commons.dbcp.PoolableConnection@a53de4] for JDBC transaction [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] [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) at $Proxy0.insertFoo(Unknown Source) at Boot.main(Boot.java:11) ---- To use reactive transaction management the code has to use reactive types. NOTE: Spring Framework uses the `ReactiveAdapterRegistry` to determine whether a method return type is reactive. The following listing shows a modified version of the previously used `FooService`, but this time the code uses reactive types: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- // the reactive service interface that we want to make transactional package x.y.service; public interface FooService { Flux getFoo(String fooName); Publisher getFoo(String fooName, String barName); Mono insertFoo(Foo foo); Mono updateFoo(Foo foo); } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- // the reactive service interface that we want to make transactional package x.y.service interface FooService { fun getFoo(fooName: String): Flow fun getFoo(fooName: String, barName: String): Publisher fun insertFoo(foo: Foo) : Mono fun updateFoo(foo: Foo) : Mono } ---- The following example shows an implementation of the preceding interface: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- package x.y.service; public class DefaultFooService implements FooService { @Override public Flux getFoo(String fooName) { // ... } @Override public Publisher getFoo(String fooName, String barName) { // ... } @Override public Mono insertFoo(Foo foo) { // ... } @Override public Mono updateFoo(Foo foo) { // ... } } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- package x.y.service class DefaultFooService : FooService { override fun getFoo(fooName: String): Flow { // ... } override fun getFoo(fooName: String, barName: String): Publisher { // ... } override fun insertFoo(foo: Foo): Mono { // ... } override fun updateFoo(foo: Foo): Mono { // ... } } ---- Imperative and reactive transaction management share the same semantics for transaction boundary and transaction attribute definitions. The main difference between imperative and reactive transactions is the deferred nature of the latter. `TransactionInterceptor` decorates the returned reactive type with a transactional operator to begin and clean up the transaction. Therefore, calling a transactional reactive method defers the actual transaction management to a subscription type that activates processing of the reactive type. Another aspect of reactive transaction management relates to data escaping which is a natural consequence of the programming model. Method return values of imperative transactions are returned from transactional methods upon successful termination of a method so that partially computed results do not escape the method closure. Reactive transaction methods return a reactive wrapper type which represents a computation sequence along with a promise to begin and complete the computation. A `Publisher` can emit data while a transaction is ongoing but not necessarily completed. Therefore, methods that depend upon successful completion of an entire transaction need to ensure completion and buffer results in the calling code. [[transaction-declarative-rolling-back]] ==== 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 in XML configuration. For details on controlling rollback semantics declaratively with the `@Transactional` annotation, see <>. 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 by specifying _rollback rules_. .Rollback rules [[transaction-declarative-rollback-rules]] [NOTE] ==== Rollback rules determine if a transaction should be rolled back when a given exception is thrown, and the rules are based on exception types or exception patterns. Rollback rules may be configured in XML via the `rollback-for` and `no-rollback-for` attributes, which allow rules to be defined as patterns. When using <>, rollback rules may be configured via the `rollbackFor`/`noRollbackFor` and `rollbackForClassName`/`noRollbackForClassName` attributes, which allow rules to be defined based on exception types or patterns, respectively. When a rollback rule is defined with an exception type, that type will be used to match against the type of a thrown exception and its super types, providing type safety and avoiding any unintentional matches that may occur when using a pattern. For example, a value of `jakarta.servlet.ServletException.class` will only match thrown exceptions of type `jakarta.servlet.ServletException` and its subclasses. When a rollback rule is defined with an exception pattern, the pattern can be a fully qualified class name or a substring of a fully qualified class name for an exception type (which must be a subclass of `Throwable`), with no wildcard support at present. For example, a value of `"jakarta.servlet.ServletException"` or `"ServletException"` will match `jakarta.servlet.ServletException` and its subclasses. [WARNING] ===== You must carefully consider how specific a pattern is and whether to include package information (which isn't mandatory). For example, `"Exception"` will match nearly anything and will probably hide other rules. `"java.lang.Exception"` would be correct if `"Exception"` were meant to define a rule for all checked exceptions. With more unique exception names such as `"BaseBusinessException"` there is likely no need to use the fully qualified class name for the exception pattern. Furthermore, pattern-based rollback rules may result in unintentional matches for similarly named exceptions and nested classes. This is due to the fact that a thrown exception is considered to be a match for a given pattern-based rollback rule if the name of the thrown exception contains the exception pattern configured for the rollback rule. For example, given a rule configured to match on `"com.example.CustomException"`, that rule will match against an exception named `com.example.CustomExceptionV2` (an exception in the same package as `CustomException` but with an additional suffix) or an exception named `com.example.CustomException$AnotherException` (an exception declared as a nested class in `CustomException`). ===== ==== The following XML snippet demonstrates how to configure rollback for a checked, application-specific `Exception` type by supplying an _exception pattern_ via the `rollback-for` attribute: [source,xml,indent=0,subs="verbatim,quotes"] ---- ---- 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`: [source,xml,indent=0,subs="verbatim,quotes"] ---- ---- When the Spring Framework's transaction infrastructure catches an exception and 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: [source,xml,indent=0,subs="verbatim,quotes"] ---- ---- 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- public void resolvePosition() { try { // some business logic... } catch (NoProductInStockException ex) { // trigger rollback programmatically TransactionAspectSupport.currentTransactionStatus().setRollbackOnly(); } } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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. [[transaction-declarative-diff-tx]] ==== 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 `` 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: [source,xml,indent=0,subs="verbatim"] ---- ---- The following example shows how to configure two distinct beans with totally different transactional settings: [source,xml,indent=0,subs="verbatim"] ---- ---- [[transaction-declarative-txadvice-settings]] ==== Settings This section summarizes the various transactional settings that you can specify by using the `` tag. The default `` settings are: * The <> 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 `` tags that are nested within `` and `` tags: [[tx-method-settings]] . settings |=== | Attribute| Required?| Default| Description | `name` | Yes | | Method names with which the transaction attributes are to be associated. The wildcard ({asterisk}) character can be used to associate the same transaction attribute settings with a number of methods (for example, `get*`, `handle*`, `on*Event`, 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`. |=== [[transaction-declarative-annotations]] ==== 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 `jakarta.transaction.Transactional` annotation is also supported as a drop-in replacement to Spring's own annotation. Please refer to the JTA 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- // the service class that we want to make transactional @Transactional 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) { // ... } } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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 be annotated individually. See <> for further details on which methods Spring considers transactional. Note that a class-level annotation does not apply to ancestor classes up the class hierarchy; in such a scenario, inherited 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 {api-spring-framework}/transaction/annotation/EnableTransactionManagement.html[javadoc] for full details. In XML configuration, the `` tag provides similar convenience: [source,xml,indent=0,subs="verbatim,quotes"] ---- <1> ---- <1> The line that makes the bean instance transactional. TIP: You can omit the `transaction-manager` attribute in the `` tag if the bean name of the `TransactionManager` that you want to wire in has the name `transactionManager`. If the `TransactionManager` bean that you want to dependency-inject has any other name, you have to use the `transaction-manager` attribute, as in the preceding example. Reactive transactional methods use reactive return types in contrast to imperative programming arrangements as the following listing shows: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- // the reactive service class that we want to make transactional @Transactional public class DefaultFooService implements FooService { @Override public Publisher getFoo(String fooName) { // ... } @Override public Mono getFoo(String fooName, String barName) { // ... } @Override public Mono insertFoo(Foo foo) { // ... } @Override public Mono updateFoo(Foo foo) { // ... } } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- // the reactive service class that we want to make transactional @Transactional class DefaultFooService : FooService { override fun getFoo(fooName: String): Flow { // ... } override fun getFoo(fooName: String, barName: String): Mono { // ... } override fun insertFoo(foo: Foo): Mono { // ... } override fun updateFoo(foo: Foo): Mono { // ... } } ---- Note that there are special considerations for the returned `Publisher` with regards to Reactive Streams cancellation signals. See the <> section under "Using the TransactionalOperator" for more details. [[transaction-declarative-annotations-method-visibility]] .Method visibility and `@Transactional` [NOTE] ==== When you use transactional proxies with Spring's standard configuration, 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 the tip in the following paragraph for class-based proxies or consider using AspectJ compile-time or load-time weaving (described later). When using `@EnableTransactionManagement` in a `@Configuration` class, `protected` or package-visible methods can also be made transactional for class-based proxies by registering a custom `transactionAttributeSource` bean like in the following example. Note, however, that transactional methods in interface-based proxies must always be `public` and defined in the proxied interface. [source,java,indent=0,subs="verbatim,quotes"] ---- /** * Register a custom AnnotationTransactionAttributeSource with the * publicMethodsOnly flag set to false to enable support for * protected and package-private @Transactional methods in * class-based proxies. * * @see ProxyTransactionManagementConfiguration#transactionAttributeSource() */ @Bean TransactionAttributeSource transactionAttributeSource() { return new AnnotationTransactionAttributeSource(false); } ---- The _Spring TestContext Framework_ supports non-private `@Transactional` test methods by default. See <> in the testing chapter for examples. ==== You can apply the `@Transactional` annotation to an interface definition, a method on an interface, a class definition, or a 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 `` 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 -- for example, in a `@PostConstruct` method. Consider using 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 is no proxy in the first place. Instead, the target class is woven (that is, its byte code is modified) to support `@Transactional` runtime behavior on any kind of method. [[tx-annotation-driven-settings]] .Annotation driven transaction settings |=== | XML Attribute| Annotation Attribute| Default| Description | `transaction-manager` | N/A (see {api-spring-framework}/transaction/annotation/TransactionManagementConfigurer.html[`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 <> 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 <> 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 <>.) 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 <> for a discussion of the different proxy types.) NOTE: `@EnableTransactionManagement` and `` look 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 in your services. See <> 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. [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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) { // ... } } ---- [source,kotlin,indent=0,subs="verbatim",role="secondary"] .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) { // ... } } ---- [[transaction-declarative-attransactional-settings]] ===== `@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` or `Error` 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: [[tx-attransactional-properties]] .@Transactional Settings |=== | Property| Type| Description | <> | `String` | Optional qualifier that specifies the transaction manager to be used. | `transactionManager` | `String` | Alias for `value`. | `label` | Array of `String` labels to add an expressive description to the transaction. | Labels may be evaluated by transaction managers to associate implementation-specific behavior with the actual transaction. | <> | `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`. | `timeoutString` | `String` (in seconds of granularity) | Alternative for specifying the `timeout` in seconds as a `String` value -- for example, as a placeholder. | `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 types that must cause rollback. | `rollbackForClassName` | Array of exception name patterns. | Optional array of exception name patterns that must cause rollback. | `noRollbackFor` | Array of `Class` objects, which must be derived from `Throwable.` | Optional array of exception types that must not cause rollback. | `noRollbackForClassName` | Array of exception name patterns. | Optional array of exception name patterns that must not cause rollback. |=== TIP: See <> for further details on rollback rule semantics, patterns, and warnings regarding possible unintentional matches for pattern-based rollback rules. 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`. [[tx-multiple-tx-mgrs-with-attransactional]] ===== 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` or `transactionManager` attribute of the `@Transactional` annotation to optionally specify the identity of the `TransactionManager` 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- public class TransactionalService { @Transactional("order") public void setSomething(String name) { ... } @Transactional("account") public void doSomething() { ... } @Transactional("reactive-account") public Mono doSomethingReactive() { ... } } ---- [source,kotlin,indent=0,subs="verbatim",role="secondary"] .Kotlin ---- class TransactionalService { @Transactional("order") fun setSomething(name: String) { // ... } @Transactional("account") fun doSomething() { // ... } @Transactional("reactive-account") fun doSomethingReactive(): Mono { // ... } } ---- The following listing shows the bean declarations: [source,xml,indent=0,subs="verbatim,quotes"] ---- ... ... ... ---- In this case, the individual methods on `TransactionalService` run under separate transaction managers, differentiated by the `order`, `account`, and `reactive-account` qualifiers. The default `` target bean name, `transactionManager`, is still used if no specifically qualified `TransactionManager` bean is found. [[tx-custom-attributes]] ===== Custom Composed Annotations If you find you repeatedly use the same attributes with `@Transactional` on many different methods, <> lets you define custom composed annotations for your specific use cases. For example, consider the following annotation definitions: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- @Target({ElementType.METHOD, ElementType.TYPE}) @Retention(RetentionPolicy.RUNTIME) @Transactional(transactionManager = "order", label = "causal-consistency") public @interface OrderTx { } @Target({ElementType.METHOD, ElementType.TYPE}) @Retention(RetentionPolicy.RUNTIME) @Transactional(transactionManager = "account", label = "retryable") public @interface AccountTx { } ---- [source,kotlin,indent=0,subs="verbatim",role="secondary"] .Kotlin ---- @Target(AnnotationTarget.FUNCTION, AnnotationTarget.TYPE) @Retention(AnnotationRetention.RUNTIME) @Transactional(transactionManager = "order", label = ["causal-consistency"]) annotation class OrderTx @Target(AnnotationTarget.FUNCTION, AnnotationTarget.TYPE) @Retention(AnnotationRetention.RUNTIME) @Transactional(transactionManager = "account", label = ["retryable"]) annotation class AccountTx ---- The preceding annotations let us write the example from the previous section as follows: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- public class TransactionalService { @OrderTx public void setSomething(String name) { // ... } @AccountTx public void doSomething() { // ... } } ---- [source,kotlin,indent=0,subs="verbatim",role="secondary"] .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 and transactional labels, but we could also have included propagation behavior, rollback rules, timeouts, and other features. [[tx-propagation]] ==== Transaction Propagation This section describes some semantics of transaction propagation in Spring. Note that this section is not a proper introduction to transaction propagation. 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. [[tx-propagation-required]] ===== Understanding `PROPAGATION_REQUIRED` image::images/tx_prop_required.png[] `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. [[tx-propagation-requires_new]] ===== Understanding `PROPAGATION_REQUIRES_NEW` image::images/tx_prop_requires_new.png[] `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. [[tx-propagation-nested]] ===== 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 {api-spring-framework}/jdbc/datasource/DataSourceTransactionManager.html[`DataSourceTransactionManager`]. [[transaction-declarative-applying-more-than-just-tx-advice]] ==== Advising Transactional Operations Suppose you want to run both transactional operations and some basic profiling advice. How do you effect this in the context of ``? When you invoke the `updateFoo(Foo)` method, you want to see the following actions: * The configured profiling aspect starts. * The transactional advice runs. * The method on the advised object runs. * 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 <> for detailed coverage of the AOP configuration and AOP in general. The following code shows the simple profiling aspect discussed earlier: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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; } } ---- [source,kotlin,indent=0,subs="verbatim",role="secondary"] .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 <>. The following configuration creates a `fooService` bean that has profiling and transactional aspects applied to it in the desired order: [source,xml,indent=0,subs="verbatim"] ---- ---- 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: [source,xml,indent=0,subs="verbatim"] ---- ---- 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 run 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. [[transaction-declarative-aspectj]] ==== 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 `` element and specify the `mode` attribute to `aspectj` as described in <>. 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 <> and <> respectively. The following example shows how to create a transaction manager and configure the `AnnotationTransactionAspect` to use it: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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); ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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 https://www.eclipse.org/aspectj/doc/released/devguide/index.html[AspectJ Development Guide]) or use load-time weaving. See <> for a discussion of load-time weaving with AspectJ. [[transaction-programmatic]] === Programmatic Transaction Management The Spring Framework provides two means of programmatic transaction management, by using: * The `TransactionTemplate` or `TransactionalOperator`. * A `TransactionManager` implementation directly. The Spring team generally recommends the `TransactionTemplate` for programmatic transaction management in imperative flows and `TransactionalOperator` for reactive code. The second approach is similar to using the JTA `UserTransaction` API, although exception handling is less cumbersome. [[tx-prog-template]] ==== 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 run 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 run 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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 runs in a transactional context public Object doInTransaction(TransactionStatus status) { updateOperation1(); return resultOfUpdateOperation2(); } }); } } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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 { updateOperation1() resultOfUpdateOperation2() } } ---- If there is no return value, you can use the convenient `TransactionCallbackWithoutResult` class with an anonymous class, as follows: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- transactionTemplate.execute(new TransactionCallbackWithoutResult() { protected void doInTransactionWithoutResult(TransactionStatus status) { updateOperation1(); updateOperation2(); } }); ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- transactionTemplate.execute(new TransactionCallbackWithoutResult() { protected void doInTransactionWithoutResult(TransactionStatus status) { try { updateOperation1(); updateOperation2(); } catch (SomeBusinessException ex) { status.setRollbackOnly(); } } }); ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- transactionTemplate.execute(object : TransactionCallbackWithoutResult() { override fun doInTransactionWithoutResult(status: TransactionStatus) { try { updateOperation1() updateOperation2() } catch (ex: SomeBusinessException) { status.setRollbackOnly() } } }) ---- [[tx-prog-template-settings]] ===== 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 <>. The following example shows the programmatic customization of the transactional settings for a specific `TransactionTemplate:` [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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... } } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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: [source,xml,indent=0,subs="verbatim,quotes"] ---- ---- 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. [[tx-prog-operator]] ==== Using the `TransactionalOperator` The `TransactionalOperator` follows an operator design that is similar to other reactive operators. 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 `TransactionalOperator` 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 run in a transactional context and that explicitly uses the `TransactionalOperator` resembles the next example: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- public class SimpleService implements Service { // single TransactionalOperator shared amongst all methods in this instance private final TransactionalOperator transactionalOperator; // use constructor-injection to supply the ReactiveTransactionManager public SimpleService(ReactiveTransactionManager transactionManager) { this.transactionalOperator = TransactionalOperator.create(transactionManager); } public Mono someServiceMethod() { // the code in this method runs in a transactional context Mono update = updateOperation1(); return update.then(resultOfUpdateOperation2).as(transactionalOperator::transactional); } } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- // use constructor-injection to supply the ReactiveTransactionManager class SimpleService(transactionManager: ReactiveTransactionManager) : Service { // single TransactionalOperator shared amongst all methods in this instance private val transactionalOperator = TransactionalOperator.create(transactionManager) suspend fun someServiceMethod() = transactionalOperator.executeAndAwait { updateOperation1() resultOfUpdateOperation2() } } ---- `TransactionalOperator` can be used in two ways: * Operator-style using Project Reactor types (`mono.as(transactionalOperator::transactional)`) * Callback-style for every other case (`transactionalOperator.execute(TransactionCallback)`) Code within the callback can roll the transaction back by calling the `setRollbackOnly()` method on the supplied `ReactiveTransaction` object, as follows: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- transactionalOperator.execute(new TransactionCallback<>() { public Mono doInTransaction(ReactiveTransaction status) { return updateOperation1().then(updateOperation2) .doOnError(SomeBusinessException.class, e -> status.setRollbackOnly()); } } }); ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- transactionalOperator.execute(object : TransactionCallback() { override fun doInTransactionWithoutResult(status: ReactiveTransaction) { updateOperation1().then(updateOperation2) .doOnError(SomeBusinessException.class, e -> status.setRollbackOnly()) } }) ---- [[tx-prog-operator-cancel]] ===== Cancel Signals In Reactive Streams, a `Subscriber` can cancel its `Subscription` and stop its `Publisher`. Operators in Project Reactor, as well as in other libraries, such as `next()`, `take(long)`, `timeout(Duration)`, and others can issue cancellations. There is no way to know the reason for the cancellation, whether it is due to an error or a simply lack of interest to consume further. Since version 5.3 cancel signals lead to a roll back. As a result it is important to consider the operators used downstream from a transaction `Publisher`. In particular in the case of a `Flux` or other multi-value `Publisher`, the full output must be consumed to allow the transaction to complete. [[tx-prog-operator-settings]] ===== Specifying Transaction Settings You can specify transaction settings (such as the propagation mode, the isolation level, the timeout, and so forth) for the `TransactionalOperator`. By default, `TransactionalOperator` instances have <>. The following example shows customization of the transactional settings for a specific `TransactionalOperator:` [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- public class SimpleService implements Service { private final TransactionalOperator transactionalOperator; public SimpleService(ReactiveTransactionManager transactionManager) { DefaultTransactionDefinition definition = new DefaultTransactionDefinition(); // the transaction settings can be set here explicitly if so desired definition.setIsolationLevel(TransactionDefinition.ISOLATION_READ_UNCOMMITTED); definition.setTimeout(30); // 30 seconds // and so forth... this.transactionalOperator = TransactionalOperator.create(transactionManager, definition); } } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- class SimpleService(transactionManager: ReactiveTransactionManager) : Service { private val definition = DefaultTransactionDefinition().apply { // the transaction settings can be set here explicitly if so desired isolationLevel = TransactionDefinition.ISOLATION_READ_UNCOMMITTED timeout = 30 // 30 seconds // and so forth... } private val transactionalOperator = TransactionalOperator(transactionManager, definition) } ---- [[transaction-programmatic-tm]] ==== Using the `TransactionManager` The following sections explain programmatic usage of imperative and reactive transaction managers. [[transaction-programmatic-ptm]] ===== Using the `PlatformTransactionManager` For imperative transactions, you can use a `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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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 { // put your business logic here } catch (MyException ex) { txManager.rollback(status); throw ex; } txManager.commit(status); ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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 { // put your business logic here } catch (ex: MyException) { txManager.rollback(status) throw ex } txManager.commit(status) ---- [[transaction-programmatic-rtm]] ===== Using the `ReactiveTransactionManager` When working with reactive transactions, you can use a `org.springframework.transaction.ReactiveTransactionManager` directly to manage your transaction. To do so, pass the implementation of the `ReactiveTransactionManager` you use to your bean through a bean reference. Then, by using the `TransactionDefinition` and `ReactiveTransaction` objects, you can initiate transactions, roll back, and commit. The following example shows how to do so: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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); Mono reactiveTx = txManager.getReactiveTransaction(def); reactiveTx.flatMap(status -> { Mono tx = ...; // put your business logic here return tx.then(txManager.commit(status)) .onErrorResume(ex -> txManager.rollback(status).then(Mono.error(ex))); }); ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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 reactiveTx = txManager.getReactiveTransaction(def) reactiveTx.flatMap { status -> val tx = ... // put your business logic here tx.then(txManager.commit(status)) .onErrorResume { ex -> txManager.rollback(status).then(Mono.error(ex)) } } ---- [[tx-decl-vs-prog]] === 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-event]] === 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- @Component public class MyComponent { @TransactionalEventListener public void handleOrderCreatedEvent(CreationEvent creationEvent) { // ... } } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- @Component class MyComponent { @TransactionalEventListener fun handleOrderCreatedEvent(creationEvent: CreationEvent) { // ... } } ---- 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`, as well as `AFTER_COMPLETION` which 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`. [NOTE] ==== `@TransactionalEventListener` only works with thread-bound transactions managed by `PlatformTransactionManager`. A reactive transaction managed by `ReactiveTransactionManager` uses the Reactor context instead of thread-local attributes, so from the perspective of an event listener, there is no compatible active transaction that it can participate in. ==== [[transaction-application-server-integration]] === 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 {api-spring-framework}/transaction/jta/JtaTransactionManager.html[`JtaTransactionManager`] javadoc for details. Spring's `JtaTransactionManager` is the standard choice to run on Jakarta 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 `` 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. [[transaction-application-server-integration-websphere]] ==== 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. [[transaction-application-server-integration-weblogic]] ==== 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. [[transaction-solutions-to-common-problems]] === Solutions to Common Problems This section describes solutions to some common problems. [[transaction-solutions-to-common-problems-wrong-ptm]] ==== 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 <> 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. [[transaction-resources]] === Further Resources For more information about the Spring Framework's transaction support, see: * https://www.infoworld.com/article/2077963/distributed-transactions-in-spring--with-and-without-xa.html[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. * https://www.infoq.com/minibooks/JTDS[_Java Transaction Design Strategies_] is a book available from https://www.infoq.com/[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]] == 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. [[dao-exceptions]] === 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.) image::images/DataAccessException.png[] [[dao-annotations]] === 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- @Repository // <1> public class SomeMovieFinder implements MovieFinder { // ... } ---- <1> The `@Repository` annotation. [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- @Repository // <1> class SomeMovieFinder : MovieFinder { // ... } ---- <1> 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- @Repository public class JpaMovieFinder implements MovieFinder { @PersistenceContext private EntityManager entityManager; // ... } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- @Repository public class HibernateMovieFinder implements MovieFinder { private SessionFactory sessionFactory; @Autowired public void setSessionFactory(SessionFactory sessionFactory) { this.sessionFactory = sessionFactory; } // ... } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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`: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- @Repository public class JdbcMovieFinder implements MovieFinder { private JdbcTemplate jdbcTemplate; @Autowired public void init(DataSource dataSource) { this.jdbcTemplate = new JdbcTemplate(dataSource); } // ... } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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. [[jdbc]] == 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. [[jdbc-who-does-what]] .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 run 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. [[jdbc-choose-style]] === 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(...)`, `update(...)`, and `findObject(...)` methods can be called multiple times with various parameter values. [[jdbc-packages]] === 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 <>, <>, and <>. * `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 Jakarta 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 <> and <>. * `object`: The `org.springframework.jdbc.object` package contains classes that represent RDBMS queries, updates, and stored procedures as thread-safe, reusable objects. See <>. 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 <>. [[jdbc-core]] === 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: * <> * <> * <> * <> * <> * <> * <> [[jdbc-JdbcTemplate]] ==== 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 <>.) 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 {api-spring-framework}/jdbc/core/JdbcTemplate.html[javadoc] for that. [[jdbc-JdbcTemplate-examples-query]] ===== Querying (`SELECT`) The following query gets the number of rows in a relation: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- int rowCount = this.jdbcTemplate.queryForObject("select count(*) from t_actor", Integer.class); ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- val rowCount = jdbcTemplate.queryForObject("select count(*) from t_actor")!! ---- The following query uses a bind variable: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- int countOfActorsNamedJoe = this.jdbcTemplate.queryForObject( "select count(*) from t_actor where first_name = ?", Integer.class, "Joe"); ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- val countOfActorsNamedJoe = jdbcTemplate.queryForObject( "select count(*) from t_actor where first_name = ?", arrayOf("Joe"))!! ---- The following query looks for a `String`: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- String lastName = this.jdbcTemplate.queryForObject( "select last_name from t_actor where id = ?", String.class, 1212L); ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- val lastName = this.jdbcTemplate.queryForObject( "select last_name from t_actor where id = ?", arrayOf(1212L))!! ---- The following query finds and populates a single domain object: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- Actor actor = jdbcTemplate.queryForObject( "select first_name, last_name from t_actor where id = ?", (resultSet, rowNum) -> { Actor newActor = new Actor(); newActor.setFirstName(resultSet.getString("first_name")); newActor.setLastName(resultSet.getString("last_name")); return newActor; }, 1212L); ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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 list of domain objects: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- List actors = this.jdbcTemplate.query( "select first_name, last_name from t_actor", (resultSet, rowNum) -> { Actor actor = new Actor(); actor.setFirstName(resultSet.getString("first_name")); actor.setLastName(resultSet.getString("last_name")); return actor; }); ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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` lambda expressions and extract them out into a single field that could then be referenced by DAO methods as needed. For example, it may be better to write the preceding code snippet as follows: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- private final RowMapper actorRowMapper = (resultSet, rowNum) -> { Actor actor = new Actor(); actor.setFirstName(resultSet.getString("first_name")); actor.setLastName(resultSet.getString("last_name")); return actor; }; public List findAllActors() { return this.jdbcTemplate.query("select first_name, last_name from t_actor", actorRowMapper); } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- val actorMapper = RowMapper { rs: ResultSet, rowNum: Int -> Actor(rs.getString("first_name"), rs.getString("last_name")) } fun findAllActors(): List { return jdbcTemplate.query("select first_name, last_name from t_actor", actorMapper) } ---- [[jdbc-JdbcTemplate-examples-update]] ===== 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- this.jdbcTemplate.update( "insert into t_actor (first_name, last_name) values (?, ?)", "Leonor", "Watling"); ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- jdbcTemplate.update( "insert into t_actor (first_name, last_name) values (?, ?)", "Leonor", "Watling") ---- The following example updates an existing entry: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- this.jdbcTemplate.update( "update t_actor set last_name = ? where id = ?", "Banjo", 5276L); ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- jdbcTemplate.update( "update t_actor set last_name = ? where id = ?", "Banjo", 5276L) ---- The following example deletes an entry: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- this.jdbcTemplate.update( "delete from t_actor where id = ?", Long.valueOf(actorId)); ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- jdbcTemplate.update("delete from t_actor where id = ?", actorId.toLong()) ---- [[jdbc-JdbcTemplate-examples-other]] ===== 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- this.jdbcTemplate.execute("create table mytable (id integer, name varchar(100))"); ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- jdbcTemplate.execute("create table mytable (id integer, name varchar(100))") ---- The following example invokes a stored procedure: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- this.jdbcTemplate.update( "call SUPPORT.REFRESH_ACTORS_SUMMARY(?)", Long.valueOf(unionId)); ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- jdbcTemplate.update( "call SUPPORT.REFRESH_ACTORS_SUMMARY(?)", unionId.toLong()) ---- More sophisticated stored procedure support is <>. [[jdbc-JdbcTemplate-idioms]] ===== `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 <> 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: -- [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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... } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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: [source,xml,indent=0,subs="verbatim,quotes"] ---- ---- 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: -- [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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... } ---- <1> Annotate the class with `@Repository`. <2> Annotate the `DataSource` setter method with `@Autowired`. <3> Create a new `JdbcTemplate` with the `DataSource`. [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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... } ---- <1> Annotate the class with `@Repository`. <2> Constructor injection of the `DataSource`. <3> Create a new `JdbcTemplate` with the `DataSource`. -- The following example shows the corresponding XML configuration: [source,xml,indent=0,subs="verbatim,quotes"] ---- ---- 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. [[jdbc-NamedParameterJdbcTemplate]] ==== 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`: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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); } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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 namedParameters = Collections.singletonMap("first_name", firstName); return this.namedParameterJdbcTemplate.queryForObject(sql, namedParameters, Integer.class); } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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 https://www.oracle.com/technetwork/java/javase/documentation/spec-136004.html[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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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... } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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); } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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 <> for guidelines on using the `NamedParameterJdbcTemplate` class in the context of an application. [[jdbc-SQLExceptionTranslator]] ==== Using `SQLExceptionTranslator` `SQLExceptionTranslator` is an interface to be implemented by classes that can translate between ``SQLException``s 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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; } } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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); } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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`. [[jdbc-statements-executing]] ==== 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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))"); } } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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))") } } ---- [[jdbc-statements-querying]] ==== 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`: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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); } } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- private JdbcTemplate jdbcTemplate; public void setDataSource(DataSource dataSource) { this.jdbcTemplate = new JdbcTemplate(dataSource); } public List> getList() { return this.jdbcTemplate.queryForList("select * from mytable"); } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- private val jdbcTemplate = JdbcTemplate(dataSource) fun getList(): List> { return jdbcTemplate.queryForList("select * from mytable") } ---- The returned list would resemble the following: [literal,subs="verbatim,quotes"] ---- [{name=Bob, id=1}, {name=Mary, id=2}] ---- [[jdbc-updates]] ==== Updating the Database The following example updates a column for a certain primary key: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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); } } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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. [[jdbc-auto-generated-keys]] ==== 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- final String INSERT_SQL = "insert into my_test (name) values(?)"; final String name = "Rob"; KeyHolder keyHolder = new GeneratedKeyHolder(); jdbcTemplate.update(connection -> { PreparedStatement ps = connection.prepareStatement(INSERT_SQL, new String[] { "id" }); ps.setString(1, name); return ps; }, keyHolder); // keyHolder.getKey() now contains the generated key ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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 ---- [[jdbc-connections]] === Controlling Database Connections This section covers: * <> * <> * <> * <> * <> * <> * <> * <> [[jdbc-datasource]] ==== 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. Traditional choices are Apache Commons DBCP and C3P0 with bean-style `DataSource` classes; for a modern JDBC connection pool, consider HikariCP with its builder-style API instead. NOTE: You should use the `DriverManagerDataSource` and `SimpleDriverDataSource` classes (as included in the Spring distribution) only for testing purposes! Those variants do not provide pooling and perform poorly when multiple requests for a connection are made. The following section uses Spring's `DriverManagerDataSource` implementation. Several other `DataSource` variants are covered later. To configure a `DriverManagerDataSource`: . Obtain a connection with `DriverManagerDataSource` as you typically obtain a JDBC connection. . Specify the fully qualified class name 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- DriverManagerDataSource dataSource = new DriverManagerDataSource(); dataSource.setDriverClassName("org.hsqldb.jdbcDriver"); dataSource.setUrl("jdbc:hsqldb:hsql://localhost:"); dataSource.setUsername("sa"); dataSource.setPassword(""); ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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: [source,xml,indent=0,subs="verbatim,quotes"] ---- ---- 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: [source,xml,indent=0,subs="verbatim,quotes"] ---- ---- The following example shows C3P0 configuration: [source,xml,indent=0,subs="verbatim,quotes"] ---- ---- [[jdbc-DataSourceUtils]] ==== 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`. [[jdbc-SmartDataSource]] ==== 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. [[jdbc-AbstractDataSource]] ==== 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. [[jdbc-SingleConnectionDataSource]] ==== 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. It typically 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. [[jdbc-DriverManagerDataSource]] ==== 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 Jakarta 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`. [[jdbc-TransactionAwareDataSourceProxy]] ==== 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 Jakarta 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 {api-spring-framework}/jdbc/datasource/TransactionAwareDataSourceProxy.html[`TransactionAwareDataSourceProxy`] javadoc for more details. [[jdbc-DataSourceTransactionManager]] ==== Using `DataSourceTransactionManager` The `DataSourceTransactionManager` class is a `PlatformTransactionManager` implementation for single JDBC data sources. 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 Jakarta 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-advanced-jdbc]] === 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. [[jdbc-batch-classic]] ==== 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 `t_actor` table based on entries in a list, and the entire list is used as the batch: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- public class JdbcActorDao implements ActorDao { private JdbcTemplate jdbcTemplate; public void setDataSource(DataSource dataSource) { this.jdbcTemplate = new JdbcTemplate(dataSource); } public int[] batchUpdate(final List 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 { Actor actor = actors.get(i); ps.setString(1, actor.getFirstName()); ps.setString(2, actor.getLastName()); ps.setLong(3, actor.getId().longValue()); } public int getBatchSize() { return actors.size(); } }); } // ... additional methods } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- class JdbcActorDao(dataSource: DataSource) : ActorDao { private val jdbcTemplate = JdbcTemplate(dataSource) fun batchUpdate(actors: List): 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. [[jdbc-batch-list]] ==== 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- public class JdbcActorDao implements ActorDao { private NamedParameterTemplate namedParameterJdbcTemplate; public void setDataSource(DataSource dataSource) { this.namedParameterJdbcTemplate = new NamedParameterJdbcTemplate(dataSource); } public int[] batchUpdate(List actors) { return this.namedParameterJdbcTemplate.batchUpdate( "update t_actor set first_name = :firstName, last_name = :lastName where id = :id", SqlParameterSourceUtils.createBatch(actors)); } // ... additional methods } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- class JdbcActorDao(dataSource: DataSource) : ActorDao { private val namedParameterJdbcTemplate = NamedParameterJdbcTemplate(dataSource) fun batchUpdate(actors: List): 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- public class JdbcActorDao implements ActorDao { private JdbcTemplate jdbcTemplate; public void setDataSource(DataSource dataSource) { this.jdbcTemplate = new JdbcTemplate(dataSource); } public int[] batchUpdate(final List actors) { List batch = new ArrayList(); 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 } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- class JdbcActorDao(dataSource: DataSource) : ActorDao { private val jdbcTemplate = JdbcTemplate(dataSource) fun batchUpdate(actors: List): IntArray { val batch = mutableListOf>() 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 via the <> mechanism) if you encounter a performance issue (as reported on Oracle 12c, JBoss, and PostgreSQL). 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` 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. ==== [[jdbc-batch-multi]] ==== 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- public class JdbcActorDao implements ActorDao { private JdbcTemplate jdbcTemplate; public void setDataSource(DataSource dataSource) { this.jdbcTemplate = new JdbcTemplate(dataSource); } public int[][] batchUpdate(final Collection actors) { int[][] updateCounts = jdbcTemplate.batchUpdate( "update t_actor set first_name = ?, last_name = ? where id = ?", actors, 100, (PreparedStatement ps, Actor actor) -> { ps.setString(1, actor.getFirstName()); ps.setString(2, actor.getLastName()); ps.setLong(3, actor.getId().longValue()); }); return updateCounts; } // ... additional methods } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- class JdbcActorDao(dataSource: DataSource) : ActorDao { private val jdbcTemplate = JdbcTemplate(dataSource) fun batchUpdate(actors: List): Array { 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 method for this call returns an array of `int` arrays that contains 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 run, 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`. [[jdbc-simple-jdbc]] === 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. [[jdbc-simple-jdbc-insert-1]] ==== 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): [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- public class JdbcActorDao implements ActorDao { private SimpleJdbcInsert insertActor; public void setDataSource(DataSource dataSource) { this.insertActor = new SimpleJdbcInsert(dataSource).withTableName("t_actor"); } public void add(Actor actor) { Map parameters = new HashMap(3); parameters.put("id", actor.getId()); parameters.put("first_name", actor.getFirstName()); parameters.put("last_name", actor.getLastName()); insertActor.execute(parameters); } // ... additional methods } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- class JdbcActorDao(dataSource: DataSource) : ActorDao { private val insertActor = SimpleJdbcInsert(dataSource).withTableName("t_actor") fun add(actor: Actor) { val parameters = mutableMapOf() 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. [[jdbc-simple-jdbc-insert-2]] ==== 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- public class JdbcActorDao implements ActorDao { private SimpleJdbcInsert insertActor; public void setDataSource(DataSource dataSource) { this.insertActor = new SimpleJdbcInsert(dataSource) .withTableName("t_actor") .usingGeneratedKeyColumns("id"); } public void add(Actor actor) { Map parameters = new HashMap(2); parameters.put("first_name", actor.getFirstName()); parameters.put("last_name", actor.getLastName()); Number newId = insertActor.executeAndReturnKey(parameters); actor.setId(newId.longValue()); } // ... additional methods } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- class JdbcActorDao(dataSource: DataSource) : ActorDao { 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. [[jdbc-simple-jdbc-insert-3]] ==== 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- public class JdbcActorDao implements ActorDao { private SimpleJdbcInsert insertActor; public void setDataSource(DataSource dataSource) { this.insertActor = new SimpleJdbcInsert(dataSource) .withTableName("t_actor") .usingColumns("first_name", "last_name") .usingGeneratedKeyColumns("id"); } public void add(Actor actor) { Map parameters = new HashMap(2); parameters.put("first_name", actor.getFirstName()); parameters.put("last_name", actor.getLastName()); Number newId = insertActor.executeAndReturnKey(parameters); actor.setId(newId.longValue()); } // ... additional methods } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- class JdbcActorDao(dataSource: DataSource) : ActorDao { 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. [[jdbc-simple-jdbc-parameters]] ==== 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`: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- public class JdbcActorDao implements ActorDao { private SimpleJdbcInsert insertActor; public void setDataSource(DataSource 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 } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- class JdbcActorDao(dataSource: DataSource) : ActorDao { 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- public class JdbcActorDao implements ActorDao { private SimpleJdbcInsert insertActor; public void setDataSource(DataSource 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 } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- class JdbcActorDao(dataSource: DataSource) : ActorDao { 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. [[jdbc-simple-jdbc-call-1]] ==== 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: [source,sql,indent=0,subs="verbatim,quotes"] ---- 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): [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- public class JdbcActorDao implements ActorDao { private SimpleJdbcCall procReadActor; public void setDataSource(DataSource 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 } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- class JdbcActorDao(dataSource: DataSource) : ActorDao { 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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 } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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. [[jdbc-simple-jdbc-call-2]] ==== 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 <> 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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 } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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. [[jdbc-params]] ==== How to Define `SqlParameters` To define a parameter for the `SimpleJdbc` classes and also for the RDBMS operations classes (covered in <>) 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- new SqlParameter("in_id", Types.NUMERIC), new SqlOutParameter("out_first_name", Types.VARCHAR), ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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 <>). 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. [[jdbc-simple-jdbc-call-3]] ==== 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 call (`executeFunction`) is used to run 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: [source,sql,indent=0,subs="verbatim,quotes"] ---- 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- public class JdbcActorDao implements ActorDao { private SimpleJdbcCall funcGetActorName; public void setDataSource(DataSource 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 } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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. [[jdbc-simple-jdbc-call-4]] ==== 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: [source,sql,indent=0,subs="verbatim,quotes"] ---- 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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(0)); return (List) m.get("actors"); } // ... additional methods } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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 { val m = procReadAllActors.execute(mapOf()) return m["actors"] as List } // ... 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. [[jdbc-object]] === 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 run 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 <> 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. ==== [[jdbc-SqlQuery]] ==== 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`. [[jdbc-MappingSqlQuery]] ==== 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- public class ActorMappingQuery extends MappingSqlQuery { 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; } } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- class ActorMappingQuery(ds: DataSource) : MappingSqlQuery(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 run 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- private ActorMappingQuery actorMappingQuery; @Autowired public void setDataSource(DataSource dataSource) { this.actorMappingQuery = new ActorMappingQuery(dataSource); } public Customer getCustomer(Long id) { return actorMappingQuery.findObject(id); } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- public List searchForActors(int age, String namePattern) { return actorSearchMappingQuery.execute(age, namePattern); } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- fun searchForActors(age: Int, namePattern: String) = actorSearchMappingQuery.execute(age, namePattern) ---- [[jdbc-SqlUpdate]] ==== 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`: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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); } } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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) } } ---- [[jdbc-StoredProcedure]] ==== Using `StoredProcedure` The `StoredProcedure` class is an `abstract` superclass for object abstractions of RDBMS stored procedures. 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- new SqlParameter("in_id", Types.NUMERIC), new SqlOutParameter("out_first_name", Types.VARCHAR), ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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 <>). 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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 results = execute(new HashMap()); Date sysdate = (Date) results.get("date"); return sysdate; } } } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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()) return results["date"] as Date } } } ---- The following example of a `StoredProcedure` has two output parameters (in this case, Oracle REF cursors): [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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 execute() { // again, this sproc has no input parameters, so an empty Map is supplied return super.execute(new HashMap()); } } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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 { // again, this sproc has no input parameters, so an empty Map is supplied return super.execute(HashMap()) } } ---- 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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 { 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; } } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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")); } } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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); } } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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)) } ---- [[jdbc-parameter-handling]] === 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. [[jdbc-type-information]] ==== 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. [[jdbc-lob]] ==== 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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(); ---- <1> Pass in the `lobHandler` that (in this example) is a plain `DefaultLobHandler`. <2> Using the method `setClobAsCharacterStream` to pass in the contents of the CLOB. <3> Using the method `setBlobAsBinaryStream` to pass in the contents of the BLOB. [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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() ---- <1> Pass in the `lobHandler` that (in this example) is a plain `DefaultLobHandler`. <2> Using the method `setClobAsCharacterStream` to pass in the contents of the CLOB. <3> 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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; } }); ---- <1> Using the method `getClobAsString` to retrieve the contents of the CLOB. <2> Using the method `getBlobAsBytes` to retrieve the contents of the BLOB. [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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) } ---- <1> Using the method `getClobAsString` to retrieve the contents of the CLOB. <2> Using the method `getBlobAsBytes` to retrieve the contents of the BLOB. [[jdbc-in-clause]] ==== 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. [[jdbc-complex-types]] ==== 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`: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- public class TestItemStoredProcedure extends StoredProcedure { public TestItemStoredProcedure(DataSource dataSource) { // ... declareParameter(new SqlOutParameter("item", OracleTypes.STRUCT, "ITEM_TYPE", (CallableStatement cs, int colIndx, int sqlType, String typeName) -> { 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; })); // ... } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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; } }; ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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; } }; ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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) } } } } ---- [[jdbc-embedded-database-support]] === Embedded Database Support The `org.springframework.jdbc.datasource.embedded` package provides support for embedded Java database engines. Support for https://www.hsqldb.org[HSQL], https://www.h2database.com[H2], and https://db.apache.org/derby[Derby] is provided natively. You can also use an extensible API to plug in new embedded database types and `DataSource` implementations. [[jdbc-why-embedded-database]] ==== 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. [[jdbc-embedded-database-xml]] ==== 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: [source,xml,indent=0,subs="verbatim,quotes"] ---- <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. [[jdbc-embedded-database-java]] ==== 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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() ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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 {api-spring-framework}/jdbc/datasource/embedded/EmbeddedDatabaseBuilder.html[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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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(); } } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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() } } ---- [[jdbc-embedded-database-types]] ==== 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: * <<jdbc-embedded-database-using-HSQL>> * <<jdbc-embedded-database-using-H2>> * <<jdbc-embedded-database-using-Derby>> [[jdbc-embedded-database-using-HSQL]] ===== 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`. [[jdbc-embedded-database-using-H2]] ===== 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`. [[jdbc-embedded-database-using-Derby]] ===== 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`. [[jdbc-embedded-database-dao-testing]] ==== 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 <<testing.adoc#testcontext-framework, Spring TestContext Framework>> and configuring the embedded database as a bean in the Spring `ApplicationContext` as described in <<jdbc-embedded-database-xml>> and <<jdbc-embedded-database-java>>. The following listing shows the test template: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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(); } } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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() } } ---- [[jdbc-embedded-database-unique-names]] ==== 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" ... >` [[jdbc-embedded-database-extension]] ==== 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 https://github.com/spring-projects/spring-framework/issues[GitHub Issues]. [[jdbc-initializing-datasource]] === 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. [[jdbc-initializing-datasource-xml]] ==== 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: [source,xml,indent=0,subs="verbatim,quotes"] ---- <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{asterisk}:/com/foo/{asterisk}{asterisk}/sql/{asterisk}-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: [source,xml,indent=0,subs="verbatim,quotes"] ---- <jdbc:initialize-database data-source="dataSource" enabled="#{systemProperties.INITIALIZE_DATABASE}"> <1> <jdbc:script location="..."/> </jdbc:initialize-database> ---- <1> 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 runs from the scripts, as the following example shows: [source,xml,indent=0,subs="verbatim,quotes"] ---- <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: [source,xml,indent=0,subs="verbatim,quotes"] ---- <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> ---- <1> Set the separator scripts to `@@`. <2> 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. [[jdbc-client-component-initialization]] ===== 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. [[r2dbc]] == Data Access with R2DBC https://r2dbc.io[R2DBC] ("Reactive Relational Database Connectivity") is a community-driven specification effort to standardize access to SQL databases using reactive patterns. [[r2dbc-packages]] === Package Hierarchy The Spring Framework's R2DBC abstraction framework consists of two different packages: * `core`: The `org.springframework.r2dbc.core` package contains the `DatabaseClient` class plus a variety of related classes. See <<r2dbc-core>>. * `connection`: The `org.springframework.r2dbc.connection` package contains a utility class for easy `ConnectionFactory` access and various simple `ConnectionFactory` implementations that you can use for testing and running unmodified R2DBC. See <<r2dbc-connections>>. [[r2dbc-core]] === Using the R2DBC Core Classes to Control Basic R2DBC Processing and Error Handling This section covers how to use the R2DBC core classes to control basic R2DBC processing, including error handling. It includes the following topics: * <<r2dbc-DatabaseClient>> * <<r2dbc-DatabaseClient-examples-statement>> * <<r2dbc-DatabaseClient-examples-query>> * <<r2dbc-DatabaseClient-examples-update>> * <<r2dbc-DatabaseClient-filter>> * <<r2dbc-auto-generated-keys>> [[r2dbc-DatabaseClient]] ==== Using `DatabaseClient` `DatabaseClient` is the central class in the R2DBC core package. It handles the creation and release of resources, which helps to avoid common errors, such as forgetting to close the connection. It performs the basic tasks of the core R2DBC workflow (such as statement creation and execution), leaving application code to provide SQL and extract results. The `DatabaseClient` class: * Runs SQL queries * Update statements and stored procedure calls * Performs iteration over `Result` instances * Catches R2DBC exceptions and translates them to the generic, more informative, exception hierarchy defined in the `org.springframework.dao` package. (See <<dao-exceptions>>.) The client has a functional, fluent API using reactive types for declarative composition. When you use the `DatabaseClient` for your code, you need only to implement `java.util.function` interfaces, giving them a clearly defined contract. Given a `Connection` provided by the `DatabaseClient` class, a `Function` callback creates a `Publisher`. The same is true for mapping functions that extract a `Row` result. You can use `DatabaseClient` within a DAO implementation through direct instantiation with a `ConnectionFactory` reference, or you can configure it in a Spring IoC container and give it to DAOs as a bean reference. The simplest way to create a `DatabaseClient` object is through a static factory method, as follows: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- DatabaseClient client = DatabaseClient.create(connectionFactory); ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- val client = DatabaseClient.create(connectionFactory) ---- NOTE: The `ConnectionFactory` should always be configured as a bean in the Spring IoC container. The preceding method creates a `DatabaseClient` with default settings. You can also obtain a `Builder` instance from `DatabaseClient.builder()`. You can customize the client by calling the following methods: * `….bindMarkers(…)`: Supply a specific `BindMarkersFactory` to configure named parameter to database bind marker translation. * `….executeFunction(…)`: Set the `ExecuteFunction` how `Statement` objects get run. * `….namedParameters(false)`: Disable named parameter expansion. Enabled by default. TIP: Dialects are resolved by {api-spring-framework}/r2dbc/core/binding/BindMarkersFactoryResolver.html[`BindMarkersFactoryResolver`] from a `ConnectionFactory`, typically by inspecting `ConnectionFactoryMetadata`. + You can let Spring auto-discover your `BindMarkersFactory` by registering a class that implements `org.springframework.r2dbc.core.binding.BindMarkersFactoryResolver$BindMarkerFactoryProvider` through `META-INF/spring.factories`. `BindMarkersFactoryResolver` discovers bind marker provider implementations from the class path using Spring's `SpringFactoriesLoader`. + Currently supported databases are: * H2 * MariaDB * Microsoft SQL Server * MySQL * Postgres All SQL issued by this class is logged at the `DEBUG` level under the category corresponding to the fully qualified class name of the client instance (typically `DefaultDatabaseClient`). Additionally, each execution registers a checkpoint in the reactive sequence to aid debugging. The following sections provide some examples of `DatabaseClient` usage. These examples are not an exhaustive list of all of the functionality exposed by the `DatabaseClient`. See the attendant {api-spring-framework}/r2dbc/core/DatabaseClient.html[javadoc] for that. [[r2dbc-DatabaseClient-examples-statement]] ===== Executing Statements `DatabaseClient` provides the basic functionality of running a statement. The following example shows what you need to include for minimal but fully functional code that creates a new table: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- Mono<Void> completion = client.sql("CREATE TABLE person (id VARCHAR(255) PRIMARY KEY, name VARCHAR(255), age INTEGER);") .then(); ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- client.sql("CREATE TABLE person (id VARCHAR(255) PRIMARY KEY, name VARCHAR(255), age INTEGER);") .await() ---- `DatabaseClient` is designed for convenient, fluent usage. It exposes intermediate, continuation, and terminal methods at each stage of the execution specification. The preceding example above uses `then()` to return a completion `Publisher` that completes as soon as the query (or queries, if the SQL query contains multiple statements) completes. NOTE: `execute(…)` accepts either the SQL query string or a query `Supplier<String>` to defer the actual query creation until execution. [[r2dbc-DatabaseClient-examples-query]] ===== Querying (`SELECT`) SQL queries can return values through `Row` objects or the number of affected rows. `DatabaseClient` can return the number of updated rows or the rows themselves, depending on the issued query. The following query gets the `id` and `name` columns from a table: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- Mono<Map<String, Object>> first = client.sql("SELECT id, name FROM person") .fetch().first(); ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- val first = client.sql("SELECT id, name FROM person") .fetch().awaitSingle() ---- The following query uses a bind variable: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- Mono<Map<String, Object>> first = client.sql("SELECT id, name FROM person WHERE first_name = :fn") .bind("fn", "Joe") .fetch().first(); ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- val first = client.sql("SELECT id, name FROM person WHERE first_name = :fn") .bind("fn", "Joe") .fetch().awaitSingle() ---- You might have noticed the use of `fetch()` in the example above. `fetch()` is a continuation operator that lets you specify how much data you want to consume. Calling `first()` returns the first row from the result and discards remaining rows. You can consume data with the following operators: * `first()` return the first row of the entire result. Its Kotlin Coroutine variant is named `awaitSingle()` for non-nullable return values and `awaitSingleOrNull()` if the value is optional. * `one()` returns exactly one result and fails if the result contains more rows. Using Kotlin Coroutines, `awaitOne()` for exactly one value or `awaitOneOrNull()` if the value may be `null`. * `all()` returns all rows of the result. When using Kotlin Coroutines, use `flow()`. * `rowsUpdated()` returns the number of affected rows (`INSERT`/`UPDATE`/`DELETE` count). Its Kotlin Coroutine variant is named `awaitRowsUpdated()`. Without specifying further mapping details, queries return tabular results as `Map` whose keys are case-insensitive column names that map to their column value. You can take control over result mapping by supplying a `Function<Row, T>` that gets called for each `Row` so it can return arbitrary values (singular values, collections and maps, and objects). The following example extracts the `name` column and emits its value: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- Flux<String> names = client.sql("SELECT name FROM person") .map(row -> row.get("name", String.class)) .all(); ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- val names = client.sql("SELECT name FROM person") .map{ row: Row -> row.get("name", String.class) } .flow() ---- [[r2dbc-DatabaseClient-mapping-null]] .What about `null`? **** Relational database results can contain `null` values. The Reactive Streams specification forbids the emission of `null` values. That requirement mandates proper `null` handling in the extractor function. While you can obtain `null` values from a `Row`, you must not emit a `null` value. You must wrap any `null` values in an object (for example, `Optional` for singular values) to make sure a `null` value is never returned directly by your extractor function. **** [[r2dbc-DatabaseClient-examples-update]] ===== Updating (`INSERT`, `UPDATE`, and `DELETE`) with `DatabaseClient` The only difference of modifying statements is that these statements typically do not return tabular data so you use `rowsUpdated()` to consume results. The following example shows an `UPDATE` statement that returns the number of updated rows: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- Mono<Integer> affectedRows = client.sql("UPDATE person SET first_name = :fn") .bind("fn", "Joe") .fetch().rowsUpdated(); ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- val affectedRows = client.sql("UPDATE person SET first_name = :fn") .bind("fn", "Joe") .fetch().awaitRowsUpdated() ---- [[r2dbc-DatabaseClient-named-parameters]] ===== Binding Values to Queries A typical application requires parameterized SQL statements to select or update rows according to some input. These are typically `SELECT` statements constrained by a `WHERE` clause or `INSERT` and `UPDATE` statements that accept input parameters. Parameterized statements bear the risk of SQL injection if parameters are not escaped properly. `DatabaseClient` leverages R2DBC's `bind` API to eliminate the risk of SQL injection for query parameters. You can provide a parameterized SQL statement with the `execute(…)` operator and bind parameters to the actual `Statement`. Your R2DBC driver then runs the statement by using prepared statements and parameter substitution. Parameter binding supports two binding strategies: * By Index, using zero-based parameter indexes. * By Name, using the placeholder name. The following example shows parameter binding for a query: ==== [source,java] ---- db.sql("INSERT INTO person (id, name, age) VALUES(:id, :name, :age)") .bind("id", "joe") .bind("name", "Joe") .bind("age", 34); ---- ==== .R2DBC Native Bind Markers **** R2DBC uses database-native bind markers that depend on the actual database vendor. As an example, Postgres uses indexed markers, such as `$1`, `$2`, `$n`. Another example is SQL Server, which uses named bind markers prefixed with `@`. This is different from JDBC, which requires `?` as bind markers. In JDBC, the actual drivers translate `?` bind markers to database-native markers as part of their statement execution. Spring Framework's R2DBC support lets you use native bind markers or named bind markers with the `:name` syntax. Named parameter support leverages a `BindMarkersFactory` instance to expand named parameters to native bind markers at the time of query execution, which gives you a certain degree of query portability across various database vendors. **** The query-preprocessor unrolls named `Collection` parameters into a series of bind markers to remove the need of dynamic query creation based on the number of arguments. Nested object arrays are expanded to allow usage of (for example) select lists. Consider the following query: [source,sql] ---- SELECT id, name, state FROM table WHERE (name, age) IN (('John', 35), ('Ann', 50)) ---- The preceding query can be parameterized and run as follows: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- List<Object[]> tuples = new ArrayList<>(); tuples.add(new Object[] {"John", 35}); tuples.add(new Object[] {"Ann", 50}); client.sql("SELECT id, name, state FROM table WHERE (name, age) IN (:tuples)") .bind("tuples", tuples); ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- val tuples: MutableList<Array<Any>> = ArrayList() tuples.add(arrayOf("John", 35)) tuples.add(arrayOf("Ann", 50)) client.sql("SELECT id, name, state FROM table WHERE (name, age) IN (:tuples)") .bind("tuples", tuples) ---- NOTE: Usage of select lists is vendor-dependent. The following example shows a simpler variant using `IN` predicates: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- client.sql("SELECT id, name, state FROM table WHERE age IN (:ages)") .bind("ages", Arrays.asList(35, 50)); ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- val tuples: MutableList<Array<Any>> = ArrayList() tuples.add(arrayOf("John", 35)) tuples.add(arrayOf("Ann", 50)) client.sql("SELECT id, name, state FROM table WHERE age IN (:ages)") .bind("tuples", arrayOf(35, 50)) ---- NOTE: R2DBC itself does not support Collection-like values. Nevertheless, expanding a given `List` in the example above works for named parameters in Spring's R2DBC support, e.g. for use in `IN` clauses as shown above. However, inserting or updating array-typed columns (e.g. in Postgres) requires an array type that is supported by the underlying R2DBC driver: typically a Java array, e.g. `String[]` to update a `text[]` column. Do not pass `Collection<String>` or the like as an array parameter. [[r2dbc-DatabaseClient-filter]] ===== Statement Filters Sometimes it you need to fine-tune options on the actual `Statement` before it gets run. Register a `Statement` filter (`StatementFilterFunction`) through `DatabaseClient` to intercept and modify statements in their execution, as the following example shows: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- client.sql("INSERT INTO table (name, state) VALUES(:name, :state)") .filter((s, next) -> next.execute(s.returnGeneratedValues("id"))) .bind("name", …) .bind("state", …); ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- client.sql("INSERT INTO table (name, state) VALUES(:name, :state)") .filter { s: Statement, next: ExecuteFunction -> next.execute(s.returnGeneratedValues("id")) } .bind("name", …) .bind("state", …) ---- `DatabaseClient` exposes also simplified `filter(…)` overload accepting `Function<Statement, Statement>`: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- client.sql("INSERT INTO table (name, state) VALUES(:name, :state)") .filter(statement -> s.returnGeneratedValues("id")); client.sql("SELECT id, name, state FROM table") .filter(statement -> s.fetchSize(25)); ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- client.sql("INSERT INTO table (name, state) VALUES(:name, :state)") .filter { statement -> s.returnGeneratedValues("id") } client.sql("SELECT id, name, state FROM table") .filter { statement -> s.fetchSize(25) } ---- `StatementFilterFunction` implementations allow filtering of the `Statement` and filtering of `Result` objects. [[r2dbc-DatabaseClient-idioms]] ===== `DatabaseClient` Best Practices Instances of the `DatabaseClient` class are thread-safe, once configured. This is important because it means that you can configure a single instance of a `DatabaseClient` and then safely inject this shared reference into multiple DAOs (or repositories). The `DatabaseClient` is stateful, in that it maintains a reference to a `ConnectionFactory`, but this state is not conversational state. A common practice when using the `DatabaseClient` class is to configure a `ConnectionFactory` in your Spring configuration file and then dependency-inject that shared `ConnectionFactory` bean into your DAO classes. The `DatabaseClient` is created in the setter for the `ConnectionFactory`. This leads to DAOs that resemble the following: -- [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- public class R2dbcCorporateEventDao implements CorporateEventDao { private DatabaseClient databaseClient; public void setConnectionFactory(ConnectionFactory connectionFactory) { this.databaseClient = DatabaseClient.create(connectionFactory); } // R2DBC-backed implementations of the methods on the CorporateEventDao follow... } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- class R2dbcCorporateEventDao(connectionFactory: ConnectionFactory) : CorporateEventDao { private val databaseClient = DatabaseClient.create(connectionFactory) // R2DBC-backed implementations of the methods on the CorporateEventDao follow... } ---- -- 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 `@Component` (which makes it a candidate for component-scanning) and annotate the `ConnectionFactory` setter method with `@Autowired`. The following example shows how to do so: -- [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- @Component // <1> public class R2dbcCorporateEventDao implements CorporateEventDao { private DatabaseClient databaseClient; @Autowired // <2> public void setConnectionFactory(ConnectionFactory connectionFactory) { this.databaseClient = DatabaseClient.create(connectionFactory); // <3> } // R2DBC-backed implementations of the methods on the CorporateEventDao follow... } ---- <1> Annotate the class with `@Component`. <2> Annotate the `ConnectionFactory` setter method with `@Autowired`. <3> Create a new `DatabaseClient` with the `ConnectionFactory`. [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- @Component // <1> class R2dbcCorporateEventDao(connectionFactory: ConnectionFactory) : CorporateEventDao { // <2> private val databaseClient = DatabaseClient(connectionFactory) // <3> // R2DBC-backed implementations of the methods on the CorporateEventDao follow... } ---- <1> Annotate the class with `@Component`. <2> Constructor injection of the `ConnectionFactory`. <3> Create a new `DatabaseClient` with the `ConnectionFactory`. -- 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 `DatabaseClient` class each time you want to run SQL. Once configured, a `DatabaseClient` instance is thread-safe. If your application accesses multiple databases, you may want multiple `DatabaseClient` instances, which requires multiple `ConnectionFactory` and, subsequently, multiple differently configured `DatabaseClient` instances. [[r2dbc-auto-generated-keys]] === Retrieving Auto-generated Keys `INSERT` statements may generate keys when inserting rows into a table that defines an auto-increment or identity column. To get full control over the column name to generate, simply register a `StatementFilterFunction` that requests the generated key for the desired column. [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- Mono<Integer> generatedId = client.sql("INSERT INTO table (name, state) VALUES(:name, :state)") .filter(statement -> s.returnGeneratedValues("id")) .map(row -> row.get("id", Integer.class)) .first(); // generatedId emits the generated key once the INSERT statement has finished ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- val generatedId = client.sql("INSERT INTO table (name, state) VALUES(:name, :state)") .filter { statement -> s.returnGeneratedValues("id") } .map { row -> row.get("id", Integer.class) } .awaitOne() // generatedId emits the generated key once the INSERT statement has finished ---- [[r2dbc-connections]] === Controlling Database Connections This section covers: * <<r2dbc-ConnectionFactory>> * <<r2dbc-ConnectionFactoryUtils>> * <<r2dbc-SingleConnectionFactory>> * <<r2dbc-TransactionAwareConnectionFactoryProxy>> * <<r2dbc-R2dbcTransactionManager>> [[r2dbc-ConnectionFactory]] ==== Using `ConnectionFactory` Spring obtains an R2DBC connection to the database through a `ConnectionFactory`. A `ConnectionFactory` is part of the R2DBC specification and is a common entry-point for drivers. 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 `ConnectionFactory`. 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 R2DBC layer, you can configure your own with a connection pool implementation provided by a third party. A popular implementation is R2DBC Pool (`r2dbc-pool`). Implementations in the Spring distribution are meant only for testing purposes and do not provide pooling. To configure a `ConnectionFactory`: . Obtain a connection with `ConnectionFactory` as you typically obtain an R2DBC `ConnectionFactory`. . Provide an R2DBC URL (See the documentation for your driver for the correct value). The following example shows how to configure a `ConnectionFactory`: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- ConnectionFactory factory = ConnectionFactories.get("r2dbc:h2:mem:///test?options=DB_CLOSE_DELAY=-1;DB_CLOSE_ON_EXIT=FALSE"); ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- val factory = ConnectionFactories.get("r2dbc:h2:mem:///test?options=DB_CLOSE_DELAY=-1;DB_CLOSE_ON_EXIT=FALSE"); ---- [[r2dbc-ConnectionFactoryUtils]] ==== Using `ConnectionFactoryUtils` The `ConnectionFactoryUtils` class is a convenient and powerful helper class that provides `static` methods to obtain connections from `ConnectionFactory` and close connections (if necessary). It supports subscriber ``Context``-bound connections with, for example `R2dbcTransactionManager`. [[r2dbc-SingleConnectionFactory]] ==== Using `SingleConnectionFactory` The `SingleConnectionFactory` class is an implementation of `DelegatingConnectionFactory` interface that wraps a single `Connection` that is not closed after each use. 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 `Connection` or a similar object. `SingleConnectionFactory` is primarily a test class and may be used for specific requirements such as pipelining if your R2DBC driver permits for such use. In contrast to a pooled `ConnectionFactory`, it reuses the same connection all the time, avoiding excessive creation of physical connections. [[r2dbc-TransactionAwareConnectionFactoryProxy]] ==== Using `TransactionAwareConnectionFactoryProxy` `TransactionAwareConnectionFactoryProxy` is a proxy for a target `ConnectionFactory`. The proxy wraps that target `ConnectionFactory` to add awareness of Spring-managed transactions. NOTE: Using this class is required if you use a R2DBC client that is not integrated otherwise with Spring's R2DBC support. In this case, you can still use this client and, at the same time, have this client participating in Spring managed transactions. It is generally preferable to integrate a R2DBC client with proper access to `ConnectionFactoryUtils` for resource management. See the {api-spring-framework}/r2dbc/connection/TransactionAwareConnectionFactoryProxy.html[`TransactionAwareConnectionFactoryProxy`] javadoc for more details. [[r2dbc-R2dbcTransactionManager]] ==== Using `R2dbcTransactionManager` The `R2dbcTransactionManager` class is a `ReactiveTransactionManager` implementation for single R2DBC data sources. It binds an R2DBC connection from the specified connection factory to the subscriber `Context`, potentially allowing for one subscriber connection for each connection factory. Application code is required to retrieve the R2DBC connection through `ConnectionFactoryUtils.getConnection(ConnectionFactory)`, instead of R2DBC's standard `ConnectionFactory.create()`. All framework classes (such as `DatabaseClient`) 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 `R2dbcTransactionManager` class supports custom isolation levels that get applied to the connection. [[orm]] == Object Relational Mapping (ORM) Data Access This section covers data access when you use Object Relational Mapping (ORM). [[orm-introduction]] === 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 <<orm-resource-mngmnt>>, 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 https://projects.spring.io/spring-data/[Spring Data] suite of projects. If you are a JPA user, the https://spring.io/guides/gs/accessing-data-jpa/[Getting Started Accessing Data with JPA] guide from https://spring.io provides a great introduction. [[orm-general]] === General ORM Integration Considerations This section highlights considerations that apply to all ORM technologies. The <<orm-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. [[orm-resource-mngmnt]] ==== 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 <<jdbc-JdbcTemplate, 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 <<orm-exception-translation, 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>> chapter. [[orm-exception-translation]] ==== 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- @Repository public class ProductDaoImpl implements ProductDao { // class body here... } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .Kotlin ---- @Repository class ProductDaoImpl : ProductDao { // class body here... } ---- [source,xml,indent=0,subs="verbatim,quotes"] ---- <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. [[orm-hibernate]] === Hibernate We start with a coverage of https://hibernate.org/[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 5.3, Spring requires Hibernate ORM 5.2+ for Spring's `HibernateJpaVendorAdapter` as well as for a native Hibernate `SessionFactory` setup. It is strongly recommended to go with Hibernate ORM 5.4 for a newly started application. For use with `HibernateJpaVendorAdapter`, Hibernate Search needs to be upgraded to 5.11.6. [[orm-session-factory-setup]] ==== `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 <<orm-hibernate-straight, 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: [source,xml,indent=0,subs="verbatim,quotes"] ---- <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: [source,xml,indent=0,subs="verbatim,quotes"] ---- <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 <<orm-jpa-hibernate, Native Hibernate Setup for JPA>> for details. ==== [[orm-hibernate-straight]] ==== 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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(); } } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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: [source,xml,indent=0,subs="verbatim,quotes"] ---- <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. [[orm-hibernate-tx-declarative]] ==== 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 <<transaction-declarative>> 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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(); } } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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: [source,xml,indent=0,subs="verbatim,quotes"] ---- <?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> ---- [[orm-hibernate-tx-programmatic]] ==== 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: [source,xml,indent=0,subs="verbatim,quotes"] ---- <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> ---- [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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... } }); } } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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. [[orm-hibernate-tx-strategies]] ==== 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. [[orm-hibernate-resources]] ==== 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 Jakarta 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 Jakarta EE environment. 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. 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. [[orm-hibernate-invalid-jdbc-access-error]] ==== Spurious Application Server Warnings with Hibernate In some JTA environments with very strict `XADataSource` implementations (currently some WebLogic Server and WebSphere versions), when Hibernate is configured without regard to the JTA transaction manager for that environment, spurious warnings 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: [literal] [subs="verbatim,quotes"] ---- java.sql.SQLException: The transaction is no longer active - status: 'Committed'. No further JDBC access is allowed within this transaction. ---- Another common problem is a connection leak after JTA transactions, with Hibernate sessions (and potentially underlying JDBC connections) not getting closed properly. You can resolve such issues by making Hibernate aware of the JTA transaction manager, to which it synchronizes (along with Spring). You have two options for doing this: * Pass your Spring `JtaTransactionManager` bean to your Hibernate setup. The easiest way is a bean reference into the `jtaTransactionManager` property for your `LocalSessionFactoryBean` bean (see <<transaction-strategies-hibernate>>). Spring then makes the corresponding JTA strategies available to Hibernate. * You may also configure Hibernate's JTA-related properties explicitly, in particular "hibernate.transaction.coordinator_class", "hibernate.connection.handling_mode" and potentially "hibernate.transaction.jta.platform" in your "hibernateProperties" on `LocalSessionFactoryBean` (see Hibernate's manual for details on those properties). 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 transaction manager, 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 transaction manager, 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. In particular, it aligns with Hibernate's transactional resource management. * 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. [[orm-jpa]] === JPA The Spring JPA, available under the `org.springframework.orm.jpa` package, offers comprehensive support for the https://www.oracle.com/technetwork/articles/javaee/jpa-137156.html[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. [[orm-jpa-setup]] ==== 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. * <<orm-jpa-setup-lemfb>> * <<orm-jpa-setup-jndi>> * <<orm-jpa-setup-lcemfb>> [[orm-jpa-setup-lemfb]] ===== 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: [source,xml,indent=0,subs="verbatim,quotes"] ---- <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 be specified on startup. This option is sufficient only for stand-alone applications and test environments, for which the JPA specification is designed. [[orm-jpa-setup-jndi]] ===== Obtaining an EntityManagerFactory from JNDI You can use this option when deploying to a Jakarta 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 Jakarta EE environment), is a matter of changing the XML configuration, as the following example shows: [source,xml,indent=0,subs="verbatim,quotes"] ---- <beans> <jee:jndi-lookup id="myEmf" jndi-name="persistence/myPersistenceUnit"/> </beans> ---- This action assumes standard Jakarta EE bootstrapping. The Jakarta EE server auto-detects persistence units (in effect, `META-INF/persistence.xml` files in application jars) and `persistence-unit-ref` entries in the Jakarta 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 Jakarta 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). [[orm-jpa-setup-lcemfb]] ===== 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 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 <<orm-jpa-hibernate, 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`: [source,xml,indent=0,subs="verbatim,quotes"] ---- <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: [source,xml,indent=0,subs="verbatim,quotes"] ---- <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 Jakarta EE server. In a full Jakarta 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 Jakarta 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 https://docs.oracle.com/javase/6/docs/api/java/lang/instrument/package-summary.html[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 <<core.adoc#aop-aj-ltw-spring, 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 <<core.adoc#aop-aj-ltw-spring, Spring configuration>>, you can configure a context-wide `LoadTimeWeaver` by using the `@EnableLoadTimeWeaving` annotation or 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: [source,xml,indent=0,subs="verbatim,quotes"] ---- <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: [source,xml,indent=0,subs="verbatim,quotes"] ---- <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. [[orm-jpa-setup-multiple]] ===== 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: [source,xml,indent=0,subs="verbatim"] ---- <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`. [[orm-jpa-setup-background]] ===== Background Bootstrapping `LocalContainerEntityManagerFactoryBean` supports background bootstrapping through the `bootstrapExecutor` property, as the following example shows: [source,xml,indent=0,subs="verbatim,quotes"] ---- <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. [[orm-jpa-dao]] ==== 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- public class ProductDaoImpl implements ProductDao { private EntityManagerFactory emf; @PersistenceUnit public void setEntityManagerFactory(EntityManagerFactory emf) { this.emf = emf; } public Collection loadProductsByCategory(String category) { EntityManager em = this.emf.createEntityManager(); try { Query query = em.createQuery("from Product as p where p.category = ?1"); query.setParameter(1, category); return query.getResultList(); } finally { if (em != null) { em.close(); } } } } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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: [source,xml,indent=0,subs="verbatim,quotes"] ---- <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: [source,xml,indent=0,subs="verbatim,quotes"] ---- <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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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(); } } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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 Jakarta 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. [[orm-jpa-tx]] ==== Spring-driven JPA transactions NOTE: We strongly encourage you to read <<transaction-declarative>>, 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 <<orm-jpa-dialect, 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, adapting to several Hibernate specifics and providing JDBC interaction. This makes particular sense in combination with `LocalSessionFactoryBean` setup. See <<orm-jpa-hibernate, Native Hibernate Setup for JPA Interaction>> for details. [[orm-jpa-dialect]] ==== 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 {api-spring-framework}/orm/jpa/JpaDialect.html[`JpaDialect`] and {api-spring-framework}/orm/jpa/JpaVendorAdapter.html[`JpaVendorAdapter`] javadoc for more details of its operations and how they are used within Spring's JPA support. [[orm-jpa-jta]] ==== 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 Jakarta 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 Jakarta 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` variants. 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 Hibernate 5.1+. For a JTA setup, make sure to declare your persistence unit transaction type as "JTA". 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 <<orm-hibernate-invalid-jdbc-access-error>> for related notes. * 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. [[orm-jpa-hibernate]] ==== Native Hibernate Setup and Native Hibernate Transactions for JPA Interaction 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 <<orm-jpa-setup-background, 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. ==== [[oxm]] == Marshalling XML by Using Object-XML Mappers [[oxm-introduction]] === 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: * <<oxm-ease-of-configuration>> * <<oxm-consistent-interfaces>> * <<oxm-consistent-exception-hierarchy>> [[oxm-ease-of-configuration]] ==== 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. [[oxm-consistent-interfaces]] ==== Consistent Interfaces Spring's O-X mapping operates through two global interfaces: {api-spring-framework}/oxm/Marshaller.html[`Marshaller`] and {api-spring-framework}/oxm/Unmarshaller.html[`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. [[oxm-consistent-exception-hierarchy]] ==== 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. [[oxm-marshaller-unmarshaller]] === `Marshaller` and `Unmarshaller` As stated in the <<oxm-introduction, 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. [[oxm-marshaller]] ==== Understanding `Marshaller` Spring abstracts all marshalling operations behind the `org.springframework.oxm.Marshaller` interface, the main method of which follows: [source,java,indent=0,subs="verbatim,quotes"] ---- public interface Marshaller { /** * Marshal the object graph with the given root into the provided Result. */ void marshal(Object graph, Result result) throws XmlMappingException, IOException; } ---- 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: [[oxm-marshaller-tbl]] |=== | 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. [[oxm-unmarshaller]] ==== Understanding `Unmarshaller` Similar to the `Marshaller`, we have the `org.springframework.oxm.Unmarshaller` interface, which the following listing shows: [source,java,indent=0,subs="verbatim,quotes"] ---- public interface Unmarshaller { /** * Unmarshal the given provided Source into an object graph. */ Object unmarshal(Source source) throws XmlMappingException, IOException; } ---- 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: [[oxm-unmarshaller-tbl]] |=== | 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`. [[oxm-xmlmappingexception]] ==== 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: image::images/oxm-exceptions.png[] [[oxm-usage]] === 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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .Java ---- public class Settings { private boolean fooEnabled; public boolean isFooEnabled() { return fooEnabled; } public void setFooEnabled(boolean fooEnabled) { this.fooEnabled = fooEnabled; } } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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: [source,java,indent=0,subs="verbatim,quotes",role="primary"] .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(); } } ---- [source,kotlin,indent=0,subs="verbatim,quotes",role="secondary"] .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`: [source,xml,indent=0,subs="verbatim,quotes"] ---- <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: [source,xml,indent=0,subs="verbatim,quotes"] ---- <?xml version="1.0" encoding="UTF-8"?> <settings foo-enabled="false"/> ---- [[oxm-schema-based-config]] === 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: [source,xml,indent=0,subs="verbatim,quotes"] ---- <?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> ---- <1> Reference the `oxm` schema. <2> Specify the `oxm` schema location. The schema makes the following elements available: * <<oxm-jaxb2-xsd, `jaxb2-marshaller`>> * <<oxm-jibx-xsd, `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: [source,xml,indent=0,subs="verbatim,quotes"] ---- <oxm:jaxb2-marshaller id="marshaller" contextPath="org.springframework.ws.samples.airline.schema"/> ---- [[oxm-jaxb]] === 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 <<oxm-marshaller-unmarshaller>>. The corresponding integration classes reside in the `org.springframework.oxm.jaxb` package. [[oxm-jaxb2]] ==== 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: [source,xml,indent=0,subs="verbatim,quotes"] ---- <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> ---- [[oxm-jaxb2-xsd]] ===== XML Configuration Namespace The `jaxb2-marshaller` element configures a `org.springframework.oxm.jaxb.Jaxb2Marshaller`, as the following example shows: [source,xml,indent=0,subs="verbatim,quotes"] ---- <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: [source,xml,indent=0,subs="verbatim,quotes"] ---- <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 |=== [[oxm-jibx]] === 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 http://jibx.sourceforge.net/[JiBX web site]. The Spring integration classes reside in the `org.springframework.oxm.jibx` package. [[oxm-jibx-marshaller]] ==== 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: [source,xml,indent=0,subs="verbatim,quotes"] ---- <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. [[oxm-jibx-xsd]] ===== XML Configuration Namespace The `jibx-marshaller` tag configures a `org.springframework.oxm.jibx.JibxMarshaller`, as the following example shows: [source,xml,indent=0,subs="verbatim,quotes"] ---- <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 |=== [[oxm-xstream]] === 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 https://x-stream.github.io/[XStream web site]. The Spring integration classes reside in the `org.springframework.oxm.xstream` package. [[oxm-xstream-marshaller]] ==== 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: [source,xml,indent=0,subs="verbatim,quotes"] ---- <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: [source,xml,indent=0,subs="verbatim,quotes"] ---- <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 {api-spring-framework}/oxm/xstream/XStreamMarshaller.html#setConverters(com.thoughtworks.xstream.converters.ConverterMatcher...)[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. include::data-access/data-access-appendix.adoc[leveloffset=+1]