The synchronized keyword ensures that only a single thread can
execute a method or block at one time. Many programmers think of
synchronization solely as a means of mutual exclusion, to prevent an object
from being observed in an inconsistent state while it’s being modified by
another thread. In this view, an object is created in a consistent state (Item
15) and locked by the methods that access it. These methods observe the state
and optionally cause a state transition, transforming
the object from one consistent state to another. Proper use of synchronization
guarantees that no method will ever observe the object in an inconsistent
state.
This view is
correct, but it’s only half the story. Without synchronization, one thread’s
changes might not be visible to other threads. Not only does synchronization
revent a thread from observing an object in an inconsistent state, but it
ensures that each thread entering a synchronized method or block sees the
effects of all previous modifications that were guarded by the same lock.
The language
specification guarantees that reading or writing a variable is atomic unless the
variable is of type long or double
[JLS,
17.4.7]. In other words, reading a variable other than a long or double
is
guaranteed to return a value that was stored into that variable by some thread,
even if multiple threads modify the variable concurrently and without
synchronization.
You may hear
it said that to improve performance, you should avoid synchronization when
reading or writing atomic data. This advice is dangerously wrong.
Synchronization
is required for reliable communication between threads as well as for mutual
exclusion.
The libraries
provide the Thread.stop method, but
this method was deprecated long ago because it is inherently unsafe—its use can
result in data corruption. Do not use Thread.stop. A recommended
way to stop one thread from another is to have the first thread poll a boolean field that is initially false but can be set to true by the second thread to indicate that the
first thread is to stop itself. Because reading and writing a boolean field is atomic, some programmers dispense
with synchronization when accessing the field:
// Broken! - How long would you expect this program
to run?
public class StopThread {
private static boolean stopRequested;
public static void main(String[] args)
throws InterruptedException {
Thread backgroundThread = new Thread(new Runnable() {
public void run() {
int i = 0;
while (!stopRequested)
i++;
}
});
backgroundThread.start();
TimeUnit.SECONDS.sleep(1);
stopRequested = true;
}
}
You might
expect this program to run for about a second, after which the main thread sets
stopRequested to true, causing the background thread’s loop to
terminate. On my machine, however, the program never terminates:
the background thread loops forever!
The problem is
that in the absence of synchronization, there is no guarantee as to when, if
ever, the background thread will see the change in the value of stop- Requested that was made by the main thread. In the
absence of synchronization, it’s quite acceptable for the virtual machine to
transform this code:
while (!done)
i++;
into this
code:
if (!done)
while (true)
i++;
This
optimization is known as hoisting, and it is precisely what the
HotSpot server VM does. The result is a liveness failure: the program
fails to make progress. One way to fix the problem is to synchronize access to
the stopRequested field. This
program terminates in about one second, as expected:
// Properly synchronized cooperative thread
termination
public class StopThread {
private static boolean stopRequested;
private static synchronized void requestStop() {
stopRequested = true;
}
private static synchronized boolean stopRequested()
{
return stopRequested;
}
public static void main(String[] args)
throws InterruptedException {
Thread backgroundThread = new Thread(new Runnable() {
public void run() {
int i = 0;
while (!stopRequested())
i++;
}
});
backgroundThread.start();
TimeUnit.SECONDS.sleep(1);
requestStop();
}
}
synchronization
has no effect unless both read and write operations are synchronized.
The locking in
the second version of StopThread can be omitted
if stopRequested is declared
volatile. While the volatile modifier
performs no mutual exclusion, it guarantees that any thread that reads the
field will see the most recently written value:
// Cooperative thread termination with a volatile
field
public class StopThread {
private static volatile
boolean stopRequested;
public static void main(String[] args)
throws InterruptedException {
Thread backgroundThread = new Thread(new Runnable() {
public void run() {
int i = 0;
while (!stopRequested)
i++;
}
});
backgroundThread.start();
TimeUnit.SECONDS.sleep(1);
stopRequested = true;
}
}
You do have to
be careful when using volatile. Consider the
following method, which is supposed to generate serial numbers:
// Broken - requires synchronization!
private static volatile
int nextSerialNumber = 0;
public static int generateSerialNumber() {
return nextSerialNumber++;
}
The best way
to avoid the problems discussed in this item is not to share mutable data.
Either share immutable data (Item 15), or don’t share at all. In other words, confine mutable
data to a single thread. If you adopt this policy, it is important to
document it, so that it is maintained as your program evolves.
In summary, when multiple
threads share mutable data, each thread that reads or writes the data must
perform synchronization. Without synchronization, there is no
guarantee that one thread’s changes will be visible to another. The penalties
for failing to synchronize shared mutable data are liveness and safety ailures.
These failures are among the most difficult to debug. They can be intermittent
and timing-dependent, and program behavior can vary radically from one VM to
another. If you need only inter-thread communication, and not mutual exclusion,
the volatile modifier is an
acceptable form of synchronization, but it can be tricky to use correctly.
Reference: Effective Java 2nd Edition by Joshua Bloch
