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Pessimistic locking implies obtaining a lock on one or more objects immediately, instead of optimistically waiting until the commit phase and hoping that the data has not changed in the database since it was last read in. A pessimistic lock is synchronous in that by the time the locking call returns, it is guaranteed that the locked object will not be modified by another transaction until after the current transaction completes and releases its lock. This does not leave the window open for transaction failure due to concurrent changes, a very real possibility when simple optimistic locking is used. It was probably obvious from the preceding section that handling optimistic lock exceptions is not always a simple matter. This is likely one of the reasons why many developers tend to use pessimistic locking because it is always easier to write your application logic when you know up front whether your update will succeed or not. In actuality, though, they are often limiting the scalability of their applications because needless locking serializes many operations that could easily occur in parallel. The reality is that very few applications actually need pessimistic locking, and those that do only need it for a limited subset of queries. The rule is that if you think you need pessimistic locking, think again. If you are in a situation where you have a very high degree of write concurrency on the same object(s) and the occurrence of optimistic failures is high, then you might need pessimistic locking because the cost of retries can become so prohibitively expensive that you are better off locking pessimistically. If you absolutely cannot retry your transactions and are willing to sacrifice some amount of scalability for it, this also might lead you to use pessimistic locking.

One issue that you can circumvent by defensive programming is the behavior of the InputStreamavailable() implementation on Symbian and Motorola devices On these devices the available() method returns 0 when you read a resource from your JAR file Please note that this behavior is perfectly allowed by the CLDC specification, which states that the default available() implementation always returns 0 but that subclasses should override this method It is just somewhat unexpected Listing 15-6 shows an implementation that reads a resource and returns its contents as a byte array Next to the available() call is another problem in that code: you probably just assume that the whole buffer will be read in one go when you call InputStreamread( byte[] ) This is not the case, as the JavaDoc of the CLDC mentions.

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Figure 4-5. All control positions in the map As you can see, the control doesn t display properly in all positions. The bottom-right corner doesn t work at all, and LEFT and RIGHT will display at the same position as TOP_LEFT and TOP_RIGHT. The control set to BOTTOM_LEFT displays it a bit right of the Google logo. That s because of the rule that controls added first to the map are displayed closer to the edge. So, let s say you want to position this control at the bottom of the map (Figure 4-6). Then you will need to write the code shown in Listing 4-5. Listing 4-5. The mapTypeControlOptions Position Property var options = { zoom: 3, center: new google.maps.LatLng(37.09, -95.71), mapTypeId: google.maps.MapTypeId.ROADMAP, mapTypeControl: true, mapTypeControlOptions: { position: google.maps.ControlPosition.BOTTOM } };

Assuming that your application does fall within the small percentage of applications that should acquire pessimistic locks, you can pessimistically lock entities using the same API methods as we described in the Advanced Optimistic Locking Modes section. Like the optimistic modes, the pessimistic locking modes also guarantee Repeatable Read isolation, they just do so pessimistically. Similarly, a transaction must be active in order to acquire a pessimistic lock. There are three supported pessimistic locking modes, but by far the most common is pessimistic write locking, so we will discuss that one first.

When a developer decides that he wants to use pessimistic locking, he is usually thinking about the kind of locking that is offered by the PESSIMISTIC_WRITE mode. This mode will be translated by most providers into a SQL "SELECT FOR UPDATE" statement in the database, obtaining a write lock on the entity so no other applications can modify it. Listing 11-28 shows an example of using the lock() method with PESSIMISTIC_WRITE mode. It shows a process that runs every day and accrues the vacation amount for each employee. Listing 11-28. Pessimistic Write Locking @Stateless public class VacationAccrualBean implements VacationAccrualService { @PersistenceContext(unitName="Employee") EntityManager em; public void accrueEmployeeVacation(int id) { Employee emp = em.find(Employee.class, id); // Find amt according to union rules and emp status

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