Synchronization
Every thread has a life of its own. Normally, a thread goes about its business without any regard for what other threads in the application are doing. Threads may be time-sliced, which means they can run in arbitrary spurts and bursts as directed by the operating system. On a multiprocessor system, it is even possible for many different threads to be running simultaneously on different CPUs. This section is about coordinating the activities of two or more threads, so they can work together and not collide in their use of the same address space.
Java provides a few simple structures for synchronizing the activities of threads. They are all based on the concept of monitors, a widely used synchronization scheme developed by C.A.R. Hoare. You don't have to know the details about how monitors work to be able to use them, but it may help you to have a picture in mind.
A monitor is essentially a lock. The lock is attached to a resource that many threads may need to access, but that should be accessed by only one thread at a time. It's not unlike a public restroom at a gas station. If the resource is not being used, the thread can acquire the lock and access the resource. By the same token, if the restroom is unlocked, you can enter and lock the door. When the thread is done, it relinquishes the lock, just as you unlock the door and leave it open for the next person. However, if another thread already has the lock for the resource, all other threads have to wait until the current thread finishes and releases the lock, just as if the restroom is locked when you arrive, you have to wait until the current occupant is done and unlocks the door.
Fortunately, Java makes the process of synchronizing access to resources quite easy. The language handles setting up and acquiring locks; all you have to do is specify which resources require locks.
Serializing Methods
The most common need for synchronization among threads in Java is to serialize their access to some resource, namely an object. In other words, synchronization makes sure only one thread at a time can perform certain activities that manipulate an object. In Java, every object has a lock associated with it. To be more specific, every class and every instance of a class has its own lock. The synchronized keyword marks places where a thread must acquire the lock before proceeding.
For example, say we implemented a SpeechSynthesizer class that contains a say() method. We don't want multiple threads calling say() at the same time or we wouldn't be able to understand anything being said. So we mark the say() method as synchronized, which means that a thread has to acquire the lock on the SpeechSynthesizer object before it can speak:
class SpeechSynthesizer {
synchronized void say( String words ) {
// Speak
}
}
Because say() is an instance method, a thread has to acquire the lock on the particular SpeechSynthesizer instance it is using before it can invoke the say() method. When say() has completed, it gives up the lock, which allows the next waiting thread to acquire the lock and run the method. Note that it doesn't matter whether the thread is owned by the SpeechSynthesizer itself or some other object; every thread has to acquire the same lock, that of the SpeechSynthesizer instance. If say() were a class (static) method instead of an instance method, we could still mark it as synchronized. But in this case as there is no instance object involved, the lock would be on the class object itself.
Often, you want to synchronize multiple methods of the same class, so that only one of the methods modifies or examines parts of the class at a time. All static synchronized methods in a class use the same class object lock. By the same token, all instance methods in a class use the same instance object lock. In this way, Java can guarantee that only one of a set of synchronized methods is running at a time. For example, a SpreadSheet class might contain a number of instance variables that represent cell values, as well as some methods that manipulate the cells in a row:
class SpreadSheet {
int cellA1, cellA2, cellA3; synchronized int sumRow() {
return cellA1 + cellA2 + cellA3;
}
synchronized void setRow( int a1, int a2, int a3 ) {
cellA1 = a1; cellA2 = a2; cellA3 = a3;
}
...
}
In this example, both methods setRow() and sumRow() access the cell values. You can see that problems might arise if one thread were changing the values of the variables in setRow() at the same moment another thread was reading the values in sumRow(). To prevent this, we have marked both methods as synchronized. When threads are synchronized, only one will be run at a time. If a thread is in the middle of executing setRow() when another thread calls sumRow(), the second thread waits until the first one is done executing setRow() before it gets to run sumRow(). This synchronization allows us to preserve the consistency of the SpreadSheet. And the best part is that all of this locking and waiting is handled by Java; it's transparent to the developer.
In addition to synchronizing entire methods, the synchronized keyword can be used in a special construct to guard arbitrary blocks of code. In this form it also takes an explicit argument that specifies the object for which it is to acquire a lock:
synchronized ( myObject ) {
// Functionality that needs to be synced ...
}
The code block above can appear in any method. When it is reached, the thread has to acquire the lock on myObject before proceeding. In this way, we can have methods (or parts of methods) in different classes synchronized the same as methods in the same class.
A synchronized method is, therefore, equivalent to a method with its statements synchronized on the current object. Thus:
synchronized void myMethod () {
...
}
is equivalent to:
void myMethod () {
synchronized ( this ) {
...
}
}
wait( ) and notify( )
With the synchronized keyword, we can serialize the execution of complete methods and blocks of code. The wait() and notify() methods of the Object class extend this capability. Every object in Java is a subclass of Object, so every object inherits these methods. By using wait() and notify(), a thread can give up its hold on a lock at an arbitrary point, and then wait for another thread to give it back before continuing. All of the coordinated activity still happens inside of synchronized blocks, and still only one thread is executing at a given time.
wait() from a synchronized block, a thread gives up its hold on the lock and goes to sleep. A thread might do this if it needs to wait for something to happen in another part of the application, as you'll see shortly. Later, when the necessary event happens, the thread that is running it calls notify() from a block synchronized on the same object. Now the first thread wakes up and begins trying to acquire the lock again.
When the first thread manages to reacquire the lock, it continues from the point it left off. However, the thread that waited may not get the lock immediately (or perhaps ever). It depends on when the second thread eventually releases the lock, and which thread manages to snag it next. Note also, that the first thread won't wake up from the wait() unless another thread calls notify(). There is an overloaded version of wait(), however, that allows us to specify a timeout period. If another thread doesn't call notify() in the specified period, the waiting thread automatically wakes up.
Let's look at a simple scenario to see what's going on. In the following example, we'll assume there are three threads--one waiting to execute each of the three synchronized methods of the MyThing class. We'll call them the waiter, notifier, and related threads, respectively. Here's a code fragment to illustrate:
class MyThing {
synchronized void waiterMethod() {
// Do some stuff // Now we need to wait for notifier to do something wait(); // Continue where we left off
}
synchronized void notifierMethod() {
// Do some stuff // Notify waiter that we've done it notify(); // Do more things
}
synchronized void relatedMethod() {
// Do some related stuff
}
Let's assume waiter gets through the gate first and begins executing waiterMethod(). The two other threads are initially blocked, trying to acquire the lock for the MyThing object. When waiter executes the wait() method, it relinquishes its hold on the lock and goes to sleep. Now there are now two viable threads waiting for the lock. Which thread gets it depends on several factors, including chance and the priorities of the threads. (We'll discuss thread scheduling in the next section.)
Let's say that notifier is the next thread to acquire the lock, so it begins to run. waiter continues to sleep and related languishes, waiting for its turn. When notifier executes the call to notify(), Java prods the waiter thread, effectively telling it something has changed. waiter then wakes up and rejoins related in vying for the MyThing lock. Note that it doesn't actually receive the lock; it just changes from saying "leave me alone" to "I want the lock."
At this point, notifier still owns the lock and continues to hold it until it leaves its synchronized method (or perhaps executes a wait() itself ). When it finally completes, the other two methods get to fight over the lock. waiter would like to continue executing waiterMethod() from the point it left off, while unrelated, which has been patient, would like to get started. We'll let you choose your own ending for the story.
For each call to notify(), Java wakes up just one method that is asleep in a wait() call. If there are multiple threads waiting, Java picks the first thread on a first-in, first-out basis. The Object class also provides a notifyAll() call to wake up all waiting threads. In most cases, you'll probably want to use notifyAll() rather than notify(). Keep in mind that notify() really means "Hey, something related to this object has changed. The condition you are waiting for may have changed, so check it again." In general, there is no reason to assume only one thread at a time is interested in the change or able to act upon it. Different threads might look upon whatever has changed in different ways.
Often, our waiter thread is waiting for a particular condition to change and we will want to sit in a loop like the following:
... while ( condition != true ) wait(); ...
Other synchronized threads call notify() or notifyAll() when they have modified the environment so that waiter can check the condition again. This is the civilized alternative to polling and sleeping, as you'll see the following example.
The Message Passer
Now we'll illustrate a classic interaction between two threads: a Producer and a Consumer. A producer thread creates messages and places them into a queue, while a consumer reads them out and displays them. To be realistic, we'll give the queue a maximum depth. And to make things really interesting, we'll have our consumer thread be lazy and run much slower than the producer. This means that Producer occasionally has to stop and wait for Consumer to catch up. The example below shows the Producer and Consumer classes.
import java.util.Vector; class Producer extends Thread {
static final int MAXQUEUE = 5; private Vector messages = new Vector();
public void run() {
try {
while ( true ) {
putMessage(); sleep( 1000 );
}
} catch( InterruptedException e ) {
}
} private synchronized void putMessage() throws InterruptedException {
while ( messages.size() == MAXQUEUE ) wait(); messages.addElement( new java.util.Date().toString() ); notify();
}
// Called by Consumer public synchronized String getMessage() throws InterruptedException {
notify(); while ( messages.size() == 0 ) wait(); String message = (String)messages.firstElement(); messages.removeElement( message );
return message;
}
} class Consumer extends Thread {
Producer producer; Consumer(Producer p) {
producer = p;
}
public void run() {
try {
while ( true ) {
String message = producer.getMessage(); System.out.println("Got message: " + message); sleep( 2000 );
}
} catch( InterruptedException e ) {
}
}
public static void main(String args[]) {
Producer producer = new Producer(); producer.start(); new Consumer( producer ).start();
}
}
For convenience, we have included a main() method that runs the complete example in the Consumer class. It creates a Consumer that is tied to a Producer and starts the two classes. You can run the example as follows:
% java Consumer
The output is the time-stamp messages created by the Producer:
Got message: Sun Dec 19 03:35:55 CST 1996 Got message: Sun Dec 19 03:35:56 CST 1996 Got message: Sun Dec 19 03:35:57 CST 1996 ...
The time stamps initially show a spacing of one second, although they appear every two seconds. Our Producer runs faster than our Consumer. Producer would like to generate a new message every second, while Consumer gets around to reading and displaying a message only every two seconds. Can you see how long it will take the message queue to fill up? What will happen when it does?
Let's look at the code. We are using a few new tools here. Producer and Consumer are subclasses of Thread. It would have been a better design decision to have Producer and Consumer implement the Runnable interface, but we took the slightly easier path and subclassed Thread. You should find it fairly simple to use the other technique; you might try it as an exercise.
The Producer and Consumer classes pass messages through an instance of a java.util.Vector object. We haven't discussed the Vector class yet, but you can think of this one as a queue where we add and remove elements in first-in, first-out order. See Basic Utility Classes for more information about the Vector class.
The important activity is in the synchronized methods: putMessage() and getMessage(). Although one of the methods is used by the Producer thread and the other by the Consumer thread, they both live in the Producer class because they have to be synchronized on the same object to work together. Here they both implicitly use the Producer object's lock. If the queue is empty, the Consumer blocks in a call in the Producer, waiting for another message.
Another design option would implement the getMessage() method in the Consumer class and use a synchronized code block to explicitly synchronize on the Producer object. In either case, synchronizing on the Producer is important because it allows us to have multiple Consumer objects that feed on the same Producer.
putMessage()'s job is to add a new message to the queue. It can't do this if the queue is already full, so it first checks the number of elements in messages. If there is room, it stuffs in another time stamp. If the queue is at its limit however, putMessage() has to wait until there's space. In this situation, putMessage() executes a wait() and relies on the consumer to call notify() to wake it up after a message has been read. Here we have putMessage() testing the condition in a loop. In this simple example, the test probably isn't necessary; we could assume that when putMessage() wakes up, there is a free spot. However, this test is another example of good developing practice. Before it finishes, putMessage() calls notify() itself to prod any Consumer that might be waiting on an empty queue.
getMessage() retrieves a message for the Consumer. It enters a loop like the Producer's, waiting for the queue to have at least one element before proceeding. If the queue is empty, it executes a wait() and expects the producer to call notify() when more items are available. Notice that getMessage() makes its own unconditional call to notify(). This is a somewhat lazy way of keeping the Producer on its toes, so that the queue should generally be full. Alternatively, getMessage() might test to see if the queue had fallen below a low water mark before waking up the producer.
Now let's add another Consumer to the scenario, just to make things really interesting. Most of the necessary changes are in the Consumer class; the example below shows the code for the modified class.
class Consumer extends Thread {
Producer producer; String name; Consumer(String name, Producer producer) {
this.producer = producer; this.name = name;
}
public void run() {
try {
while ( true ) {
String message = producer.getMessage(); System.out.println(name + " got message: " + message); sleep( 2000 );
}
} catch( InterruptedException e ) {
}
}
public static void main(String args[]) {
Producer producer = new Producer(); producer.start(); // Start two this time new Consumer( "One", producer ).start(); new Consumer( "Two", producer ).start();
}
}
The Consumer constructor now takes a string name, to identify each consumer. The run() method uses this name in the call to println() to identify which consumer received the message.
The only modification to make in the Producer code is to change the call to notify() in putMessage() to a call to notifyAll(). Now, instead of the consumer and producer playing tag with the queue, we can have many players waiting on the condition of the queue to change. We might have a number of consumers waiting for a message, or we might have the producer waiting for a consumer to take a message. Whenever the condition of the queue changes, we prod all of the waiting methods to reevaluate the situation by calling notifyAll(). Note, however, that we don't need to change the call to notify() in getMessage(). If a Consumer thread is waiting for a message to appear in the queue, it's not possible for the Producer to be simultaneously waiting because the queue is full.
Here is some sample output when there are two consumers running, as in the main() method shown above:
One got message: Wed Mar 20 20:00:01 CST 1996 Two got message: Wed Mar 20 20:00:02 CST 1996 One got message: Wed Mar 20 20:00:03 CST 1996 Two got message: Wed Mar 20 20:00:04 CST 1996 One got message: Wed Mar 20 20:00:05 CST 1996 Two got message: Wed Mar 20 20:00:06 CST 1996 One got message: Wed Mar 20 20:00:07 CST 1996 Two got message: Wed Mar 20 20:00:08 CST 1996 ...
We see nice, orderly alternation between the two consumers, as a result of the calls to sleep() in the various methods. Interesting things would happen, however, if we were to remove all of the calls to sleep() and let things run at full speed. The threads would compete and their behavior would depend on whether or not the system is using time slicing. On a time-sliced system, there should be a fairly random distribution between the two consumers, while on a nontime-sliced system, a single consumer could monopolize the messages. And since you're probably wondering about time slicing, let's talk about thread priority and scheduling.