Data Access

Global transactions enable you to 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 to use (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. Obviously the use of global transactions would limit 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 via 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 of course the use of EJB itself necessitates the use of JNDI. It removes most but not all of the need to write Java code to control transactions. The significant downside is that CMT is tied to JTA and an application server environment. Also, it is only available if one chooses to implement business logic in EJBs, or at least behind a transactional EJB facade. The negatives of EJB in general are so great that this is not an attractive proposition, especially in the face of compelling alternatives for declarative transaction management.

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

Spring resolves the disadvantages of global and local transactions. It enables application developers to 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 is recommended 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.

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 be focused purely on non-boilerplate persistence logic. Generally, you use the native ORM API or take a template approach for JDBC access by using the JdbcTemplate. These solutions are detailed in subsequent chapters of this reference documentation.

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 instead use Spring’s org.springframework.jdbc.datasource.DataSourceUtils class as follows:

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, any SQLException is wrapped in a Spring Framework CannotGetJdbcConnectionException, one of the Spring Framework’s hierarchy of unchecked DataAccessExceptions. This approach gives you more information than can be obtained easily from the SQLException, and ensures portability across databases, 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 are using Spring for transaction management.

Of course, once you have used Spring’s JDBC support, JPA support or Hibernate support, you will generally prefer not to use DataSourceUtils or the other helper classes, because you will be 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 won’t need to write any special code.

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

It should almost never be necessary or desirable 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 participating in Spring managed transactions. It is preferable to write your new code by using the higher level abstractions mentioned above.

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

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

Conceptually, calling a method on a transactional proxy looks like this…​

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; it allows you to see transactions created and then rolled back in response to the UnsupportedOperationException instance.

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

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

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

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

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

Now that we’ve analyzed the configuration, you may be asking yourself, "Okay…​ but what does all this configuration actually do?".

The above configuration will be used to create a transactional proxy around the object that is created from the fooService bean definition. The proxy will be 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 above configuration:

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

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

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

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

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

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

When the Spring Framework’s transaction infrastructure catches an exception and is consults 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.

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

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.

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 do this by defining distinct <aop:advisor/> elements with differing pointcut and advice-ref attribute values.

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

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

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

You can change these default settings; the various attributes of the <tx:method/> tags that are nested within <tx:advice/> and <tx:attributes/> tags are summarized below:

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.

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:

When the above POJO is defined as a bean in a Spring IoC container, the bean instance can be made transactional by adding merely one line of XML configuration:

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

Consider the use of AspectJ mode (see mode attribute in table below) if you expect self-invocations to be wrapped with transactions as well. In this case, there will not be a proxy in the first place; instead, the target class will be weaved (that is, its byte code will be modified) in order to turn @Transactional into runtime behavior on any kind of method.

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.

This section describes some semantics of transaction propagation in Spring. Please note that this section is not an introduction to transaction propagation proper; rather it details some of the semantics regarding transaction propagation in Spring.

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

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

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

Here is the code for a simple profiling aspect discussed above. The ordering of advice is controlled through the Ordered interface. For full details on advice ordering, see Advice ordering. .

The result of the above configuration is a fooService bean that has profiling and transactional aspects applied to it in the desired order. You configure any number of additional aspects in similar fashion.

The following example effects the same setup as above, but uses the purely XML declarative approach.

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

You configure additional aspects in similar fashion.

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

The @Transactional annotation on a class specifies the default transaction semantics for the execution of any 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). Any method may be annotated, regardless of visibility.

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

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 of transactional resources, and results in code that is intention driven, in that the code that is written focuses solely on what the developer wants to do.

Application code that must execute in a transactional context, and that will use the TransactionTemplate explicitly, looks like the following. You, as an application developer, write a TransactionCallback implementation (typically expressed as an anonymous inner class) that contains the code that you need to execute in the context of a transaction. You then pass an instance of your custom TransactionCallback to the execute(..) method exposed on the TransactionTemplate.

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

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

You can also use the org.springframework.transaction.PlatformTransactionManager directly to manage your transaction. Simply pass the implementation of the PlatformTransactionManager you are using to your bean through a bean reference. Then, using the TransactionDefinition and TransactionStatus objects you can initiate transactions, roll back, and commit.

On WebSphere 6.1.0.9 and above, the recommended Spring JTA transaction manager to use is WebSphereUowTransactionManager. This special adapter leverages 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/resume as initiated by PROPAGATION_REQUIRES_NEW) is officially supported by IBM.

On WebLogic Server 9.0 or above, you typically would 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.

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 are using global transactions, you must use the org.springframework.transaction.jta.JtaTransactionManager class (or an application server-specific subclass of it) for all your transactional operations. Otherwise the transaction infrastructure attempts to perform local transactions on resources such as container DataSource instances. Such local transactions do not make sense, and a good application server treats them as errors.

You can choose among several approaches to form the basis for your JDBC database access. In addition to three flavors of the 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.

The Spring Framework’s JDBC abstraction framework consists of four different packages, namely core, datasource, object, and support.

The org.springframework.jdbc.core package contains the JdbcTemplate class and its various callback interfaces, plus a variety of related classes. A subpackage named org.springframework.jdbc.core.simple contains the SimpleJdbcInsert and SimpleJdbcCall classes. Another subpackage named org.springframework.jdbc.core.namedparam contains the NamedParameterJdbcTemplate class and the related support classes. See Using the JDBC core classes to control basic JDBC processing and error handling, JDBC batch operations, and Simplifying JDBC operations with the SimpleJdbc classes.

The org.springframework.jdbc.datasource package contains a utility class for easy DataSource access, and various simple DataSource implementations that can be used for testing and running unmodified JDBC code outside of a Java EE container. A subpackage named org.springfamework.jdbc.datasource.embedded provides support for creating embedded databases using Java database engines such as HSQL, H2, and Derby. See Controlling database connections and Embedded database support.

The org.springframework.jdbc.object package contains classes that represent RDBMS queries, updates, and stored procedures as thread-safe, reusable objects. See Modeling JDBC operations as Java objects. This approach is modeled by JDO, although objects returned by queries are naturally disconnected from the database. This higher level of JDBC abstraction depends on the lower-level abstraction in the org.springframework.jdbc.core package.

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 allowing other exceptions to be propagated to the caller. See SQLExceptionTranslator.

The JdbcTemplate class 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 executes SQL queries, update statements and stored procedure calls, performs iteration over ResultSets and extraction of returned parameter values. It also catches JDBC exceptions and translates them to the generic, more informative, exception hierarchy defined in the org.springframework.dao package.

When you use the JdbcTemplate for your code, you only need to implement callback interfaces, giving them a clearly defined contract. The PreparedStatementCreator callback interface creates a prepared statement given a Connection provided by this class, 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.

The JdbcTemplate can be used within a DAO implementation through direct instantiation with a DataSource reference, or be configured in a Spring IoC container and given to DAOs as a bean reference.

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 are using a custom subclass of the JdbcTemplate class).

The NamedParameterJdbcTemplate class adds support for programming JDBC statements 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 using named parameters.

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.

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 snippet (the MapSqlParameterSource class). An SqlParameterSource is a source of named parameter values to a NamedParameterJdbcTemplate. The MapSqlParameterSource class is a very simple implementation that is simply an adapter around a java.util.Map, where the keys are the parameter names and the values are the parameter values.

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

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

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

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

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

The SQLErrorCodeSQLExceptionTranslator applies matching rules in the following sequence:

You can extend SQLErrorCodeSQLExceptionTranslator:

In this example, the specific error code -12345 is translated and other errors are left to be translated by the default translator implementation. To use this custom translator, it is necessary to pass it to the JdbcTemplate through the method setExceptionTranslator and to use this JdbcTemplate for all of the data access processing where this translator is needed. Here is an example of how this custom translator can be used:

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

Executing 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:

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, then an InvalidDataAccessApiUsageException is thrown. Here is an example that contains two query methods, one for an int and one that queries for a String.

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 entry is a Map with each entry in the map representing the column value for that row. If you add a method to the above example to retrieve a list of all the rows, it would look like this:

The list returned would look something like this:

The following example shows a column updated for a certain primary key. In this example, an SQL statement has placeholders for row parameters. The parameter values can be passed in as varargs or alternatively as an array of objects. Thus primitives should be wrapped in the primitive wrapper classes explicitly or using auto-boxing.

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 not a 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:

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

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

You obtain a connection with DriverManagerDataSource as you typically obtain a JDBC connection. Specify the fully qualified classname of the JDBC driver so that the DriverManager can load the driver class. Next, provide a URL that varies between JDBC drivers. (Consult the documentation for your driver for the correct value.) Then provide a username and a password to connect to the database. Here is an example of how to configure a DriverManagerDataSource in Java code:

Here is the corresponding XML configuration:

The following 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.

DBCP configuration:

C3P0 configuration:

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.

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

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

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

If any client code calls close in the assumption of a pooled connection, as when using persistence tools, set the suppressClose property to true. This setting returns a close-suppressing proxy wrapping the physical connection. Be aware that you will not be able to cast this to a native Oracle Connection or the like anymore.

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

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

This implementation is useful for test and stand-alone environments outside of a Java EE container, either as a DataSource bean in a Spring IoC container, or in conjunction with a simple JNDI environment. Pool-assuming Connection.close() calls will simply 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.

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

(See the TransactionAwareDataSourceProxy javadocs for more details.)

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

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

This implementation can be used 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, if you stick to the required connection lookup pattern. JTA does not support custom isolation levels!

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

If you are processing a stream of updates or reading from a file, then 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 allows you to interrupt a batch once the input source is exhausted. The isBatchExhausted method allows you to signal the end of the batch.

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 SqlParameterSource.createBatch method to create this array, passing in either an array of JavaBeans or an array of Maps containing the parameter values.

This example shows a batch update using named parameters:

For an SQL statement using 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 same example using classic JDBC "?" placeholders:

All of the above batch update methods 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 -2 value.

The last 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 of course do this with the methods mentioned above 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 containing 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.

This example shows a batch update using a batch size of 100:

The batch update methods for this call returns an array of int arrays containing an array entry for each batch with an array of the number of affected rows for each update. The top level array’s length indicates the number of batches executed and the second level array’s length indicates the number of updates in that batch. The number of updates in each batch should be the batch size provided for all batches except for 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 -2 value.

Let’s 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; simply create a new instance and set the table name using the withTableName method. Configuration methods for this class follow the "fluid" style that returns the instance of the SimpleJdbcInsert, which allows you to chain all configuration methods. This example uses only one configuration method; you will see examples of multiple ones later.

The execute method used here takes a plain java.utils.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 in order to construct the actual insert statement.

This example uses the same insert as the preceding, but instead of passing in the id it retrieves the auto-generated key and sets it on the new Actor object. When you create the SimpleJdbcInsert, in addition to specifying the table name, you specify the name of the generated key column with the usingGeneratedKeyColumns method.

The main difference when executing the insert by 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 our 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, then you can use a KeyHolder that is returned from the executeAndReturnKeyHolder method.

You can limit the columns for an insert by specifying a list of column names with the usingColumns method:

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

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

Another option is the MapSqlParameterSource that resembles a Map but provides a more convenient addValue method that can be chained.

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

The SimpleJdbcCall class leverages metadata in the database to look up names of in and out parameters, so that you do not have to declare them explicitly. 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 in_id parameter contains the id of the actor you are looking up. The out parameters return the data read from the table.

The SimpleJdbcCall is declared in a similar manner to the SimpleJdbcInsert. You should instantiate and configure the class in the initialization method of your data access layer. Compared to the StoredProcedure class, you don’t have to create a subclass and you don’t have to declare parameters that can be looked up in the database metadata. Following is an example of a SimpleJdbcCall configuration using the above stored procedure. The only configuration option, in addition to the DataSource, is the name of the stored procedure.

The code you write for the execution of the call involves creating an SqlParameterSource containing the IN parameter. It’s important to 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 containing 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 create your own JdbcTemplate and set the setResultsMapCaseInsensitive property to true. Then you pass this customized JdbcTemplate instance into the constructor of your SimpleJdbcCall. Here is an example of this configuration:

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

You have seen how the parameters are deduced based on metadata, but you can declare then explicitly if you wish. You do this by creating and configuring SimpleJdbcCall with the declareParameters method, which takes a variable number of SqlParameter objects as input. See the next section for details on how to define an SqlParameter.

You can opt to declare one, some, or all the parameters explicitly. The parameter metadata is still used where you do not declare parameters explicitly. To bypass all processing of metadata lookups for potential parameters and only use the declared parameters, you 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 the useInParameterNames to specify the list of IN parameter names to include for a given signature.

The following example shows a fully declared procedure call, using the information from the preceding example.

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

To define a parameter for the SimpleJdbc classes and also for the RDBMS operations classes, covered in Modeling JDBC operations as Java objects, you use an SqlParameter or one of its subclasses. You typically specify the parameter name and SQL type in the constructor. The SQL type is specified using the java.sql.Types constants. We have already seen declarations like:

The first line with the SqlParameter declares an IN parameter. IN parameters can be used for both stored procedure calls and for queries using the SqlQuery and its subclasses covered in the following section.

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.

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.

You 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 we want to make a call to a function, and the corresponding string for a function call is generated. A specialized execute call, executeFunction, is used to execute the function and it returns the function return value as an object of a specified type, which means you do not have to retrieve the return value from the results map. A similar convenience method named executeObject is also available for stored procedures that only have one out parameter. The following example is based on a stored function named get_actor_name that returns an actor’s full name. Here is the MySQL source for this function:

To call this function we again create a SimpleJdbcCall in the initialization method.

The execute method used returns a String containing the return value from the function call.

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 use the returningResultSet method and declare a RowMapper implementation to be used for a specific parameter. In the case where the result set is returned during the results processing, there are no names defined, so the returned results will have to 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 uses a stored procedure that takes no IN parameters and returns all rows from the t_actor table. Here is the MySQL source for this procedure:

To call this procedure you declare the RowMapper. Because the class you want to map to 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 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.

SqlQuery is a reusable, threadsafe 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.

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.

The class extends MappingSqlQuery parameterized with the Actor type. The constructor for this customer query takes the DataSource as the only parameter. In this constructor you call the constructor on the superclass with the DataSource and the SQL that should be executed to retrieve the rows for this query. This SQL will be used to create a PreparedStatement so it may contain place holders for any parameters to be passed in during execution.You must declare each parameter 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 call the compile() method so the statement can be prepared and later executed. 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 method in this example retrieves the customer with the id that is passed in as the only parameter. Since we only want one object returned we simply call the convenience method findObject with the id as parameter. If we had instead a query that returned a list of objects and took additional parameters then we would use one of the execute methods that takes an array of parameter values passed in as varargs.

The SqlUpdate class encapsulates an SQL update. Like a query, an update object is reusable, and like 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, as in the following snippet where it’s simply called execute. However, you don’t have to subclass the SqlUpdate class since it can easily be parameterized by setting SQL and declaring parameters.

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

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

To define a parameter for the StoredProcedure class, you use an SqlParameter or one of its subclasses. You must specify the parameter name and SQL type in the constructor like in the following code snippet. The SQL type is specified using the java.sql.Types constants.

The first line with the SqlParameter declares an IN parameter. IN parameters can be used for both stored procedure calls and for queries using the SqlQuery and its subclasses covered in the following section.

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

For i n 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 enables you to define customized handling of the return values.

Here is an example of a simple DAO that 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, but if you need to reuse the StoredProcedure you declare it as a top-level class. This example has no input parameters, but an output parameter is declared as a date type using the class SqlOutParameter. The execute() method executes 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, using the parameter name as the key.

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

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 code for the two RowMapper implementations is provided below.

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

The GenreMapper class maps a ResultSet to a Genre domain object for each row in the supplied ResultSet.

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 superclass' untyped execute(Map parameters) method (which has protected access); for example:

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:

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. The LobHandler provides access to a LobCreator class, through the getLobCreator method, used for creating new LOB objects to be inserted.

The LobCreator/LobHandler provides the following support for LOB input and output:

The next example shows how to create and insert a BLOB. Later you will see 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 you 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 already is set to an instance of a DefaultLobHandler. You typically set this value through dependency injection.

Now it’s 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 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. Pass in the values as a java.util.List of primitive objects. This list will be used to insert the required placeholders and pass in the values during the statement execution.

In addition to the primitive values in the value list, you can create a java.util.List of object arrays. This list would support multiple expressions 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.

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.

Here is an example of returning the value of an Oracle STRUCT object of the user declared type ITEM_TYPE. 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.

You use the SqlTypeValue to pass in the value of a Java object like TestItem into 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 StructDescriptors, as shown in the following example, or ArrayDescriptors.

This SqlTypeValue can now be added to the Map containing 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.

An embedded database is 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 SQL during development.

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

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

The EmbeddedDatabaseBuilder class provides a fluent API for constructing an embedded database programmatically. Use this when you need to create an embedded database in a standalone environment or in a standalone integration test like in the following example.

Consult the Javadoc for EmbeddedDatabaseBuilder for further details on all supported options.

The EmbeddedDatabaseBuilder can also be used to create an embedded database using Java Config like in the following example.

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

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 (i.e., within the same JVM process) –- for example, integration tests against embedded databases whose ApplicationContext configuration only differs 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 Config) will set 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 (i.e., often something like "dataSource"). Thus, subsequent attempts to create an embedded database will not result in a new database. Instead, the same JDBC connection URL will be reused, and attempts to create a new embedded database will 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.

Spring JDBC embedded database support can be extended in two ways:

You are encouraged to contribute back extensions to the Spring community at jira.spring.io.

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

The example above executes the two scripts specified 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 (e.g. classpath*:/com/foo/**/sql/*-data.sql). If a pattern is used, the scripts are executed in lexical order of their URL or filename.

The default behavior of the database initializer is to unconditionally execute the scripts provided. This will not always be what you want, for instance, if you are executing 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 (as shown above) of creating the tables first and then inserting the data — the first step will fail 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. This can be set according to the environment (e.g. to pull a boolean value from system properties or an environment bean), for example:

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

In this example we are saying we expect that sometimes the scripts will be executed against an empty database, and there are some DROP statements in the scripts which 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, for example:

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 override that default for the db-schema script.

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

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

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

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

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 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 and/or do not need any special exception treatment. However, Spring enables exception translation to be applied transparently through the @Repository annotation:

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.

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

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

Switching from a local Jakarta Commons DBCP BasicDataSource to a JNDI-located DataSource (usually managed by an application server) is just a matter of configuration:

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.

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:

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 above DAO follows the dependency injection pattern: it fits nicely into a Spring IoC container, just as it would if coded against Spring’s HibernateTemplate. Of course, such a DAO can also be set up in plain Java (for example, in unit tests). Simply instantiate it and call setSessionFactory(..) with the desired factory reference. As a Spring bean definition, the DAO would resemble the following:

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 of course appealing from a non-invasiveness perspective, and will no doubt feel more natural to Hibernate developers.

However, the DAO throws plain HibernateException (which is unchecked, so does not have to be declared or caught), which means that callers can only treat exceptions as 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 and/or do not need any special exception treatment.

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. Of course, the standard behavior of that method remains the return of the current Session associated with the ongoing JTA transaction, if any. This behavior applies regardless of whether you are using 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.

We recommend that you use Spring’s declarative transaction support, which enables you to replace explicit transaction demarcation API calls in your Java code with an AOP transaction interceptor. This transaction interceptor can be configured in a Spring container using either Java annotations or XML. This declarative transaction capability allows you to keep business services free of repetitive transaction demarcation code and to focus on adding business logic, which is the real value of your application.

You may annotate the service layer with @Transactional annotations and instruct the Spring container to find these annotations and provide transactional semantics for these annotated methods.

All you need to set up in the container is the PlatformTransactionManager implementation as a bean as well as a "<tx:annotation-driven/>" entry, opting into @Transactional processing at runtime.

You can demarcate transactions in a higher level of the application, on top of such lower-level data access services spanning any number of operations. Nor do restrictions exist on the implementation of the surrounding business service; it just needs a Spring PlatformTransactionManager. Again, the latter can come from anywhere, but preferably as a bean reference through a setTransactionManager(..) method, just as the productDAO should be set by a setProductDao(..) method. The following snippets show a transaction manager and a business service definition in a Spring application context, and an example for a business method implementation:

Spring’s TransactionInterceptor allows any checked application exception to 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 (via TransactionStatus). TransactionInterceptor behaves the same way by default but allows configurable rollback policies per method.

Both TransactionTemplate and TransactionInterceptor delegate the actual transaction handling to a PlatformTransactionManager instance, which can be a HibernateTransactionManager (for a single Hibernate SessionFactory, 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 just a matter of configuration. Simply replace the Hibernate transaction manager with Spring’s JTA transaction implementation. Both transaction demarcation and data access code will work without changes, because they just use the generic transaction management APIs.

For distributed transactions across multiple Hibernate session factories, simply 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 is using 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 are not using EJB to initiate transactions).

HibernateTransactionManager can export the Hibernate JDBC Connection to plain JDBC access code, for a specific DataSource. This capability allows for high-level transaction demarcation with mixed Hibernate and JDBC data access completely without JTA, if you are accessing 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.

You can switch between a container-managed JNDI SessionFactory and a locally defined one, without having to change a single line of application code. Whether to keep resource definitions in the container or locally within the application is mainly a matter of the transaction strategy that you use. Compared to a Spring-defined local SessionFactory, a manually registered JNDI SessionFactory does not provide any benefits. Deploying a SessionFactory through Hibernate’s JCA connector provides the added value of participating in the Java EE server’s management infrastructure, but does not add actual value beyond that.

Spring’s transaction support is not bound to a container. 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 JTA, even if you access only a single database, and only use stateless session beans to provide declarative transactions through container-managed transactions. Also, direct use of JTA programmatically requires a Java EE environment as well. JTA does not involve only container dependencies in terms of JTA itself and of JNDI DataSource instances. For non-Spring, JTA-driven Hibernate transactions, you have to use the Hibernate JCA connector, or extra Hibernate transaction code with the TransactionManagerLookup configured for proper JVM-level caching.

Spring-driven transactions can work as well with a locally defined Hibernate SessionFactory as they do with a local JDBC DataSource if they are accessing a single database. Thus you only have to use Spring’s JTA transaction strategy when you have distributed transaction requirements. A JCA connector requires container-specific deployment steps, and obviously JCA support in the first place. This configuration requires more work than deploying a simple web application with local resource definitions and Spring-driven transactions. Also, you often need the Enterprise Edition of your container if you are using, for example, WebLogic Express, which does not provide JCA. A Spring application with local resources and transactions spanning one single database works in any Java EE web container (without JTA, JCA, or EJB) such as Tomcat, Resin, or even plain Jetty. Additionally, you can easily reuse such a middle tier in desktop applications or test suites.

All things considered, if you do not use EJBs, stick with local SessionFactory setup and Spring’s HibernateTransactionManager or JtaTransactionManager. You get all of the benefits, including proper transactional JVM-level caching and distributed transactions, without the inconvenience of container deployment. JNDI registration of a Hibernate SessionFactory through the JCA connector only adds value when used in conjunction with EJBs.

In some JTA environments with very strict XADataSource implementations — currently only some WebLogic Server and WebSphere versions — when Hibernate is configured without regard to the JTA PlatformTransactionManager object for that environment, it is possible for spurious warning or exceptions to 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:

You resolve this warning by simply making Hibernate aware of the JTA PlatformTransactionManager instance, to which it will synchronize (along with Spring). You have two options for doing this:

The remainder of this section describes the sequence of events that occur with and without Hibernate’s awareness of the JTA PlatformTransactionManager.

When Hibernate is not configured with any awareness of the JTA PlatformTransactionManager, the following events occur when a JTA transaction commits:

When Hibernate is configured with awareness of the JTA PlatformTransactionManager, the following events occur when a JTA transaction commits:

The Spring JPA support offers three ways of setting up the JPA EntityManagerFactory that will be used by the application to obtain an entity manager.