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ephemeral segment If the ephemeral segment is exhausted while a concurrent GC is underway, the managed threads are suspended until the concurrent GC completes (turning the concurrent GC into a blocking GC) In essence, this means that as long as the ephemeral segment is not exhausted, lag times can be avoided On the other hand, the server GC doesn t have to worry about immediate response times as much as the workstation GC, because most server applications don t have the need for immediate response times (such as in the case of UI applications) Instead of allowing allocations to occur while the GC is working, the server mode GC keeps all managed threads suspended throughout the duration of a GC Although this may result in a nonvisible lag time while a GC is underway, the benefit of a server GC is higher throughput primarily due to not having to worry about other managed threads working at the same time Additionally, in a server GC, each processor has a dedicated GC thread which, in turn, means that we can have X GCs happen at the same time (where X is number of processors* number of cores) One of the primary drawbacks with the existing concurrent GC is that it works really well with applications that have relatively small-sized managed heaps (remember that as long as the ephemeral segment is not exhausted, managed threads can keep allocating memory) In today s world, it is not uncommon to have applications whose managed heaps are in the gigabytes In these cases, lag times can still be experienced since the concurrent GC becomes a blocking GC when the ephemeral segment limit has been reached To address this deficiency, CLR 40 replaces the concurrent GC with what is known as the background GC The biggest difference between a concurrent GC and a background GC is that the background GC allows for a full GC and allocations to happen at the same time as well as allowing a collection of generation 0 and 1 The background GC periodically checks to see if a concurrent allocation resulted in a GC in an ephemeral segment and if so, suspends itself and allows the ephemeral GC to take place (foreground GC) This means that although a full GC is taking place, we still have the capability to get rid of dead short-lived objects Because the background GC allows for collections in generation 0 and 1, what happens if the threshold of the ephemeral segment is reached In this case, the foreground GC grows the ephemeral segment as needed To summarize, server GCs always block throughout the duration of a GC To avoid lag times during this suspension, the workstation GC was introduced, which minimizes the time threads spend in the suspended state during a GC Although this approach works well with applications that have a relatively small managed heap foot print, lag times can still be observed if the ephemeral segment is exhausted This deficiency led to an evolution of the workstation GC called the background GC, which allows for true concurrent allocations and ephemeral collections (and segment expansion if needed).

finally the book provides introductions to object-oriented programming, applet construction, and addition, { if (out != null) { user interface design Other topics include exceptions, I/O, and threads To help beginners avoid many Systemoutprintln("Closing PrintWriter"); common mistakes, an entire chapter is devoted to programming problems and their solutions outclose(); Convenient summaries at the end of each section are new to this edition Also new for this edition are } else { Exercises" sections to help you practice what you learn "Questions and Systemoutprintln("PrintWriter not open"); } After working through the lessons in this proven tutorial, you will be well prepared to use the Java } programming language in your school or workplace

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In the writeList example, you could provide for cleanup without the intervention of a finally statement For example, you could put the code to close the PrintWriter at the end of the try block and again within the exception handler for ArrayIndexOutOfBoundsException, as shown here:

10

Here you are simply loading your custom WorkerPool module, setting the interval at which the run method will be executed, and starting up the server As you might imagine, implementing queues and worker pools to support scaling an application and taking slow writes out of the user s request lifecycle is a significant change and addition to the infrastructure that a team is supporting These worker pools should be managed and instrumented in much the same way as the actual application servers in order to ensure that they are running and healthy at all times The example here is relatively generic and would require that additional considerations be dealt with in a live application This is left for you as an exercise because the actual requirements are unique to the project at hand

try {

outclose(); // don't do this; it duplicates code } catch (ArrayIndexOutOfBoundsException e) { outclose(); // don't do this; it duplicates code Systemerrprintln("Caught ArrayIndexOutOfBoundsException: " + egetMessage()); } catch (IOException e) { Systemerrprintln("Caught IOException: " + egetMessage()); }

In 6, Synchronization, we took a look at the most commonly used synchronization primitives in NET 20 as well as the internals of synchronization in the CLR In NET 40, a lot of great additions have been made in the form of enhancing existing synchronization primitives as well as adding new ones In this part of the chapter, we will take a look at some of the additions and enhancements made in NET 40

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