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You can think of a single-threaded program as one lonely entity moving around through your problem space and doing one thing at a time. Because there’s only one entity, you never have to think about the problem of two entities trying to use the same resource at the same time, like two people trying to park in the same space, walk through a door at the same time, or even talk at the same time.
With multithreading, things aren’t lonely anymore, but you now have the possibility of two or more threads trying to use the same limited resource at once. Colliding over a resource must be prevented or else you’ll have two threads trying to access the same bank account at the same time, print to the same printer, or adjust the same valve, etc.
Consider a variation on the counters that have been used so far in this chapter. In the following example, each thread contains two counters that are incremented and displayed inside run( ). In addition, there’s another thread of class Watcher that is watching the counters to see if they’re always equivalent. This seems like a needless activity, since looking at the code it appears obvious that the counters will always be the same. But that’s where the surprise comes in. Here’s the first version of the program:
As before, each counter contains its own display components: two text fields and a label that initially indicates that the counts are equivalent. These components are added to the Container in the TwoCounter constructor. Because this thread is started via a button press by the user, it’s possible that start( ) could be called more than once. It’s illegal for Thread.start( ) to be called more than once for a thread (an exception is thrown). You can see that the machinery to prevent this in the started flag and the overridden start( ) method.
In run( ), count1 and count2 are incremented and displayed in a manner that would seem to keep them identical. Then sleep( ) is called; without this call the program balks because it becomes hard for the CPU to swap tasks.
The synchTest( ) method performs the apparently useless activity of checking to see if count1 is equivalent to count2; if they are not equivalent it sets the label to “Unsynched” to indicate this. But first, it calls a static member of the class Sharing1 that increments and displays an access counter to show how many times this check has occurred successfully. (The reason for this will become apparent in future variations of this example.)
The Watcher class is a thread whose job is to call synchTest( ) for all of the TwoCounter objects that are active. It does this by stepping through the array that’s kept in the Sharing1 object. You can think of the Watcher as constantly peeking over the shoulders of the TwoCounter objects.
Sharing1 contains an array of TwoCounter objects that it initializes in init( ) and starts as threads when you press the “start” button. Later, when you press the “Observe” button, one or more observers are created and freed upon the unsuspecting TwoCounter threads.
Note that to run this as an applet in a browser, your Web page will need to contain the lines:
You can change the width, height, and parameters to suit your experimental tastes. By changing the size and observers you’ll change the behavior of the program. You can also see that this program is set up to run as a stand-alone application by pulling the arguments from the command line (or providing defaults).
Here’s the surprising part. In TwoCounter.run( ), the infinite loop is just repeatedly passing over the adjacent lines:
(as well as sleeping, but that’s not important here). When you run the program, however, you’ll discover that count1 and count2 will be observed (by the Watcher) to be unequal at times! This is because of the nature of threads – they can be suspended at any time. So at times, the suspension occurs between the execution of the above two lines, and the Watcher thread happens to come along and perform the comparison at just this moment, thus finding the two counters to be different.
This example shows a fundamental problem with using threads. You never know when a thread might be run. Imagine sitting at a table with a fork, about to spear the last piece of food on your plate and as your fork reaches for it, the food suddenly vanishes (because your thread was suspended and another thread came in and stole the food). That’s the problem that you’re dealing with.
Sometimes you don’t care if a resource is being accessed at the same time you’re trying to use it (the food is on some other plate). But for multithreading to work, you need some way to prevent two threads from accessing the same resource, at least during critical periods.
Preventing this kind of collision is simply a matter of putting a lock on a resource when one thread is using it. The first thread that accesses a resource locks it, and then the other threads cannot access that resource until it is unlocked, at which time another thread locks and uses it, etc. If the front seat of the car is the limited resource, the child who shouts “Dibs!” asserts the lock.
Java has built-in support to prevent collisions over one kind of resource: the memory in an object. Since you typically make the data elements of a class private and access that memory only through methods, you can prevent collisions by making a particular method synchronized. Only one thread at a time can call a synchronized method for a particular object (although that thread can call more than one of the object’s synchronized methods). Here are simple synchronized methods:
Each object contains a single lock (also called a monitor) that is automatically part of the object (you don’t have to write any special code). When you call any synchronized method, that object is locked and no other synchronized method of that object can be called until the first one finishes and releases the lock. In the example above, if f( ) is called for an object, g( ) cannot be called for the same object until f( ) is completed and releases the lock. Thus, there’s a single lock that’s shared by all the synchronized methods of a particular object, and this lock prevents common memory from being written by more than one method at a time (i.e. more than one thread at a time).
There’s also a single lock per class (as part of the Class object for the class), so that synchronized static methods can lock each other out from static data on a class-wide basis.
Note that if you want to guard some other resource from simultaneous access by multiple threads, you can do so by forcing access to that resource through synchronized methods.
Armed with this new keyword it appears that the solution is at hand: we’ll simply use the synchronized keyword for the methods in TwoCounter. The following example is the same as the previous one, with the addition of the new keyword:
You’ll notice that both run( ) and synchTest( ) are synchronized. If you synchronize only one of the methods, then the other is free to ignore the object lock and can be called with impunity. This is an important point: Every method that accesses a critical shared resource must be synchronized or it won’t work right.
Now a new issue arises. The Watcher2 can never get a peek at what’s going on because the entire run( ) method has been synchronized, and since run( ) is always running for each object the lock is always tied up and synchTest( ) can never be called. You can see this because the accessCount never changes.
What we’d like for this example is a way to isolate only part of the code inside run( ). The section of code you want to isolate this way is called a critical section and you use the synchronized keyword in a different way to set up a critical section. Java supports critical sections with the synchronized block; this time synchronized is used to specify the object whose lock is being used to synchronize the enclosed code:
Before the synchronized block can be entered, the lock must be acquired on syncObject. If some other thread already has this lock, then the block cannot be entered until the lock is given up.
The Sharing2 example can be modified by removing the synchronized keyword from the entire run( ) method and instead putting a synchronized block around the two critical lines. But what object should be used as the lock? The one that is already respected by synchTest( ), which is the current object (this)! So the modified run( ) looks like this:
This is the only change that must be made to Sharing2.java, and you’ll see that while the two counters are never out of synch (according to when the Watcher is allowed to look at them), there is still adequate access provided to the Watcher during the execution of run( ).
Of course, all synchronization depends on programmer diligence: every piece of code that can access a shared resource must be wrapped in an appropriate synchronized block.
Since having two methods write to the same piece of data never sounds like a particularly good idea, it might seem to make sense for all methods to be automatically synchronized and eliminate the synchronized keyword altogether. (Of course, the example with a synchronized run( ) shows that this wouldn’t work either.) But it turns out that acquiring a lock is not a cheap operation – it multiplies the cost of a method call (that is, entering and exiting from the method, not executing the body of the method) by a minimum of four times, and could be more depending on your implementation. So if you know that a particular method will not cause contention problems it is expedient to leave off the synchronized keyword.
Now that you understand synchronization you can take another look at Java Beans. Whenever you create a Bean, you must assume that it will run in a multithreaded environment. This means that:
Whenever possible, all the public methods of a Bean should be synchronized. Of course, this incurs the synchronized runtime overhead. If that’s a problem, methods that will not cause problems in critical sections can be left un-synchronized, but keep in mind that this is not always obvious. Methods that qualify tend to be small (such as getCircleSize( ) in the following example) and/or “atomic,” that is, the method call executes in such a short amount of code that the object cannot be changed during execution. Making such methods un-synchronized might not have a significant effect on the execution speed of your program. You might as well make all public methods of a Bean synchronized and remove the synchronized keyword only when you know for sure that it’s necessary and that it makes a difference.
When firing a multicast event to a bunch of listeners interested in that event, you must assume that listeners might be added or removed while moving through the list.
The first point is fairly easy to deal with, but the second point requires a little more thought. Consider the BangBean.java example presented in the last chapter. That ducked out of the multithreading question by ignoring the synchronized keyword (which hadn’t been introduced yet) and making the event unicast. Here’s that example modified to work in a multithreaded environment and to use multicasting for events:
Adding synchronized to the methods is an easy change. However, notice in addActionListener( ) and removeActionListener( ) that the ActionListeners are now added to and removed from a Vector, so you can have as many as you want.
You can see that the method notifyListeners( ) is not synchronized. It can be called from more than one thread at a time. It’s also possible for addActionListener( ) or removeActionListener( ) to be called in the middle of a call to notifyListeners( ), which is a problem since it traverses the Vector actionListeners. To alleviate the problem, the Vector is cloned inside a synchronized clause and the clone is traversed. This way the original Vector can be manipulated without impact on notifyListeners( ).
The paint( ) method is also not synchronized. Deciding whether to synchronize overridden methods is not as clear as when you’re just adding your own methods. In this example it turns out that paint( ) seems to work OK whether it’s synchronized or not. But the issues you must consider are:
Does the method modify the state of “critical” variables within the object? To discover whether the variables are “critical” you must determine whether they will be read or set by other threads in the program. (In this case, the reading or setting is virtually always accomplished via synchronized methods, so you can just examine those.) In the case of paint( ), no modification takes place.
Does the method depend on the state of these “critical” variables? If a synchronized method modifies a variable that your method uses, then you might very well want to make your method synchronized as well. Based on this, you might observe that cSize is changed by synchronized methods and therefore paint( ) should be synchronized. Here, however, you can ask “What’s the worst thing that will happen if cSize is changed during a paint( )?” When you see that it’s nothing too bad, and a transient effect at that, it’s best to leave paint( ) un-synchronized to prevent the extra overhead from the synchronized method call.
A third clue is to notice whether the base-class version of paint( ) is synchronized, which it isn’t. This isn’t an airtight argument, just a clue. In this case, for example, a field that is changed via synchronized methods (that is cSize) has been mixed into the paint( ) formula and might have changed the situation. Notice, however, that synchronized doesn’t inherit – that is, if a method is synchronized in the base class then it is not automatically synchronized in the derived class overridden version.
The test code in TestBangBean2 has been modified from that in the previous chapter to demonstrate the multicast ability of BangBean2 by adding extra listeners.
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