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expensive to open and should be shared across calls whenever possible. It can hold a number of native resources, so it is important to close the JDBC connection when it is no longer needed. We accomplish both these goals using callbacks as well as resource injection. In listing 3.1, the JDBC data source from which the connection is created is injected using the @Resource annotation. We explore injecting resources using the @Resource annotation in chapter 5; for now, this is all that you need to know. Let s take a closer look at how we used the callbacks in listing 3.1. PostConstruct callback The setDataSource method saves the injected data source in an instance variable. After injecting all resources, the container checks whether there are any designated PostConstruct methods that need to be invoked before the bean instance is put into the pool. In our case, we mark the initialize method in listing 3.1 with the @PostConstruct annotation:

07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34

@PostConstruct public void initialize() { ... connection = dataSource.getConnection(); ... }

Before the end of a transaction, you want to roll back the current transaction regardless of the outcome of the method. Your code has detected an error or a

In the initialize method, we create a java.sql.Connection from the injected data source and save it into the connection instance variable used in addBid each time the client invokes the method. PreDestroy callback At some point the container decides that our bean should be removed from the pool and destroyed (perhaps at server shutdown). The PreDestroy callback gives us a chance to cleanly tear down bean resources before this is done. In the cleanup method marked with the @PreDestroy annotation in listing 3.1, we tear down the open database connection resource before the container retires our bean:

@PreDestroy public void cleanup() { ... connection.close(); connection = null; ... }

try { details = bank.getAccountDetails(returned); boolean readonly = true; frame.setDescription(details.getDescription()); ArrayList alist = new ArrayList(); alist = details.getCustomerIds(); frame.createActFields( readonly, details.getType(), details.getBalance(), details.getCreditLine(), details.getBeginBalance(), alist, details.getBeginBalanceTimeStamp()); } catch (AccountNotFoundException ex) { frame.resetPanelTwo(); frame.messlab3.setText( messages.getString("AccountException") + " " + returned + " " + messages.getString("NotFoundException")); } catch (RemoteException ex) { frame.messlab.setText( messages.getString("Remote Exception")); } catch (InvalidParameterException ex) { frame.messlab.setText( messages.getString("InvalidParameterException")); } [...]

Since bean instances from the pool are assigned randomly for each method invocation, trying to store client-specific state across method invocations is useless

condition that will cause the code to fail, and you want to roll back the previously executed code within the transaction.

since the same bean instance may not be used for subsequent calls by the same client. On the other hand, stateful session beans, which we ll discuss next, are ideally suited for this situation.

Stateful session beans are guaranteed to maintain conversational state. They are not programmatically very different from their stateless cousins: as a matter of fact, the only real difference between stateless and stateful beans is how the container manages their lifecycle. Unlike with stateless beans, the container makes sure that subsequent method invocations by the same client are handled by the same stateful bean instance. Figure 3.6 shows the one-to-one mapping between a bean instance and a client enforced behind the scenes by the container. As far as you are concerned, this one-to-one relation management happens automagically. The one-to-one mapping between a client and a bean instance makes saving bean conversational state in a useful manner possible. However, this one-to-one correlation comes at a price. Bean instances cannot be readily returned to the pool and reused while a client session is still active. Instead, a bean instance must be squirreled away in memory to wait for the next request from the client owning the session. As a result, stateful session bean instances held by a large number of concurrent clients can have a significant memory footprint. An optimization technique called passivation, which we ll discuss soon, is used to alleviate this problem. Stateful session beans are ideal for multistep, workflow-oriented business processes. In this section, we explore stateful beans by using the ActionBazaar bidder account creation workflow as an example.