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Why is a semaphore used when using synchronization?

I was reading about semaphore's and in the code example it confused me why a semaphore was used when the code uses sychronization around the method that is ultimately called. Isn't that doing the same thing, i.e. restricting 1 thread at a time to perform the mutation?
class Pool {
private static final int MAX_AVAILABLE = 100;
private final Semaphore available = new Semaphore(MAX_AVAILABLE, true);
public Object getItem() throws InterruptedException {
available.acquire();
return getNextAvailableItem();
}
public void putItem(Object x) {
if (markAsUnused(x))
available.release();
}
// Not a particularly efficient data structure; just for demo
protected Object[] items = ... whatever kinds of items being managed
protected boolean[] used = new boolean[MAX_AVAILABLE];
protected synchronized Object getNextAvailableItem() {
for (int i = 0; i < MAX_AVAILABLE; ++i) {
if (!used[i]) {
used[i] = true;
return items[i];
}
}
return null; // not reached
}
protected synchronized boolean markAsUnused(Object item) {
for (int i = 0; i < MAX_AVAILABLE; ++i) {
if (item == items[i]) {
if (used[i]) {
used[i] = false;
return true;
} else
return false;
}
}
return false;
}
}
I'm referring to the call to getItem() which calls acquire(), and then calls getNextAvailableItem, but that is synchronized anyhow.
What am I missing?
Reference: http://docs.oracle.com/javase/8/docs/api/java/util/concurrent/Semaphore.html

The semaphore and the synchronized block are doing two different jobs.
The synchronized keyword is protecting getNextAvailableItem() when it is accessing and mutating the array of items. An operation that would corrupt if it was not restricted to one thread at a time.
The semaphore will allow up to 100 threads through, significantly more than 1. Its purpose in this code sample is to block requests for an object from the pool when the pool is empty, and to then unblock one thread when an object is returned to the pool. Without the semaphore, things would look like they were working until the pool was empty. At that time requesting threads would not block and wait for an object to be returned, but would instead receive null.

A Semaphore gives you a thread-safe counter that blocks when the acquire has been called beyond the initial limit. release can be used to undo an acquire.
It will guarantee that if a call to acquire succeeds there is sufficient capacity to hold the new item.
In the sample there are loops that look for a free item. Using a Semaphore ensures that none of those loops are begun until there is a free item.
synchronized only guarantees that ony one thread can execute this section of code at a time.

Will the assignment of value in a Java Boolean object cause re-allocation in memory

I have the following piece of code
Boolean flag = new Boolean(false);
flag = true;
Will the second line (assignment) cause a recreation of the initial object (basically a call to new()) in the JVM? I am asking because I am using a Boolean object to synchronize multiple threads, and I am afraid that if a re-initialization takes places, the waiting threads will not see the change in value.
In my application, there are multiple threads that are given a reference to the previous Boolean object. Only one thread changes the objects value to true, and the rest wait until the object's value becomes true. So, if T1 is the thread that changes the value, its code is like:
synchronized(flag) {
flag = true;
flag.notifyAll();
}
and the rest of the threads (T2) will have code like:
synchronized(flag) {
while(flag == false)
wait();
if(flag == true) {
//do something
}
}
Therefore, the question is that after the assignment of true to flag, will the other threads (T2) still have access to the original object?
Thanks,
Nick

The assignment flag = false is a boxing conversion. It will get compiled as flag=Boolean.valueOf(false) which will end up returning the constant Boolean.FALSE.
So the answer is, it will not create a new object but it will change the variable flag as it assigns an instance distinct from your previous result of new Boolean(false).
It’s not quite clear what you are actually doing but in general, synchronizing on a mutable variable is broken design.
The problem is that you are mixing the value that makes up your condition and the object to synchronize on. The simplest implementation of your updated intention is to use a simple boolean flag and synchronize on the instance that contains the flag:
class WithFlag {
private boolean flag;
public synchronized void setToTrue() {
if(!flag) {
flag=true;
notifyAll();
}
}
public synchronized void waitForTrue() throws InterruptedException {
while(!flag) wait();
}
}
Note that declaring an instance method synchronized is similar to wrap its code with synchronized(this) { … }

If you want to use a boolean to synchronize threads, you should consider using AtomicBoolean, which is specifically designed for this purpose.

The other answers have already explained that when you say flag=false, it is a boxing conversion which will return the constant Boolean.FALSE. One important point that the other answers have covered but not emphasized on is that when you obtain a lock on two Boolean objects that were assigned the same value through a boxing conversion, it is as good as obtaining a lock on one Boolean object.
My answer attempts to give an example to explain this. Consider the following code that creates two threads that obtain a lock on a Boolean.
public class BooleanTest {
public static void main(String[] args) {
BooleanTest test = new BooleanTest();
test.booleanTest();
}
private void booleanTest() {
BooleanLockTester booleanLock1 = new BooleanLockTester();
booleanLock1.setBooleanLock(true);
BooleanLockTester booleanLock2 = new BooleanLockTester();
booleanLock2.setBooleanLock(true);
BooleanLocker booleanLocker1 = new BooleanLocker(booleanLock1);
BooleanLocker booleanLocker2 = new BooleanLocker(booleanLock2);
Thread threadOne = new Thread(booleanLocker1);
Thread threadTwo = new Thread(booleanLocker2);
threadOne.start();
threadTwo.start();
}
private class BooleanLocker implements Runnable {
private BooleanLockTester booleanLockObj;
public BooleanLocker(BooleanLockTester booleanLockObj) {
this.booleanLockObj = booleanLockObj;
}
#Override
public void run() {
booleanLockObj.testLockOnBoolean();
}
}
private class BooleanLockTester {
private Boolean booleanLock = false;
public synchronized void testLockOnBoolean() {
synchronized (booleanLock) {
for (int i = 0; i<1000000000; ++i) {
System.out.println(Thread.currentThread().getName());
}
}
}
public void setBooleanLock(Boolean booleanLock) {
this.booleanLock = booleanLock;
}
}
}
In the above example, the two threads will never be able to enter the for loop together. When you run the program, you will see that the thread that starts first will start printing on the console and only when it is finished, the next thread will start printing to the console.
Let's make a small change in the above code :
Change the following line in the code :
booleanLock2.setBooleanLock(true);
To this :
booleanLock2.setBooleanLock(false);
You will now see that the threads stop behaving and print to the console in a random order. This is because the threads now obtain a lock on two different objects.

Multi-threading program to print numbers from 1 to 50?

im trying to write a program in which two threads are created and the output should be like 1st thread prints 1 and the next thread prints 2 ,1st thread again prints 3 and so on. im a beginner so pls help me clearly. i thought thread share the same memory so they will share the i variable and print accordingly. but in output i get like thread1: 1, thread2 : 1, thread1: 2, thread2 : 2 nd so on. pls help. here is my code
class me extends Thread
{
public int name,i;
public void run()
{
for(i=1;i<=50;i++)
{
System.out.println("Thread" + name + " : " + i);
try
{
sleep(1000);
}
catch(Exception e)
{
System.out.println("some problem");
}
}
}
}
public class he
{
public static void main(String[] args)
{
me a=new me();
me b=new me();
a.name=1;
b.name=2;
a.start();
b.start();
}
}

First off you should read this http://www.oracle.com/technetwork/java/codeconventions-135099.html.
Secondly the class member variables are not shared memory. You need to explicitly pass an object (such as the counter) to both objects, such that it becomes shared. However, this will still not be enough. The shared memory can be cached by the threads so you will have race-conditions. To solve this you will need to use a Lock or use an AtomicInteger

It seems what you want to do is:
Write all numbers from 1 to 50 to System.out
without any number being printed multiple times
with the numbers being printed in order
Have this execution be done by two concurrent threads
First, let's look at what is happening in your code: Each number is printed twice. The reason for this is that i is an instance variable of me, your Thread. So each Thread has its own i, i.e., they do not share the value.
To make the two threads share the same value, we need to pass the same value when constructing me. Now, doing so with the primitive int won't help us much, because by passing an int we are not passing a reference, hence the two threads will still work on independent memory locations.
Let us define a new class, Value which holds the integer for us: (Edit: The same could also be achieved by passing an array int[], which also holds the reference to the memory location of its content)
class Value{
int i = 1;
}
Now, main can instantiate one object of type Value and pass the reference to it to both threads. This way, they can access the same memory location.
class Me extends Thread {
final Value v;
public Me(Value v){
this.v = v;
}
public void run(){
for(; v.i < 50; v.i++){
// ...
}
public static void main(){
Value valueInstance = new Value();
Me a = new Me(valueInstance);
Me b = new Me(valueInstance);
}
}
Now i isn't printed twice each time. However, you'll notice that the behavior is still not as desired. This is because the operations are interleaved: a may read i, let's say, the value is 5. Next, b increments the value of i, and stores the new value. i is now 6. However, a did still read the old value, 5, and will print 5 again, even though b just printed 5.
To solve this, we must lock the instance v, i.e., the object of type Value. Java provides the keyword synchronized, which will hold a lock during the execution of all code inside the synchronized block. However, if you simply put synchronize in your method, you still won't get what you desire. Assuming you write:
public void run(){ synchronized(v) {
for(; v.i < 50; v.i++) {
// ...
}}
Your first thread will acquire the lock, but never release it until the entire loop has been executed (which is when i has the value 50). Hence, you must release the lock somehow when it is safe to do so. Well... the only code in your run method that does not depend on i (and hence does not need to be locking) is sleep, which luckily also is where the thread spends the most time in.
Since everything is in the loop body, a simple synchronized block won't do. We can use Semaphore to acquire a lock. So, we create a Semaphore instance in the main method, and, similar to v, pass it to both threads. We can then acquire and release the lock on the Semaphore to let both threads have the chance to get the resource, while guaranteeing safety.
Here's the code that will do the trick:
public class Me extends Thread {
public int name;
final Value v;
final Semaphore lock;
public Me(Value v, Semaphore lock) {
this.v = v;
this.lock = lock;
}
public void run() {
try {
lock.acquire();
while (v.i <= 50) {
System.out.println("Thread" + name + " : " + v.i);
v.i++;
lock.release();
sleep(100);
lock.acquire();
}
lock.release();
} catch (Exception e) {
System.out.println("some problem");
}
}
public static void main(String[] args) {
Value v = new Value();
Semaphore lock = new Semaphore(1);
Me a = new Me(v, lock);
Me b = new Me(v, lock);
a.name = 1;
b.name = 2;
a.start();
b.start();
}
static class Value {
int i = 1;
}
}
Note: Since we are acquiring the lock at the end of the loop, we must also release it after the loop, or the resource will never be freed. Also, I changed the for-loop to a while loop, because we need to update i before releasing the lock for the first time, or the other thread can again read the same value.

Check the below link for the solution. Using multiple threads we can print the numbers in ascending order
http://cooltekhie.blogspot.in/2017/06/#987628206008590221

AtomicReference to a mutable object and visibility

Say I have an AtomicReferenceto a list of objects:
AtomicReference<List<?>> batch = new AtomicReference<List<Object>>(new ArrayList<Object>());
Thread A adds elements to this list: batch.get().add(o);
Later, thread B takes the list and, for example, stores it in a DB: insertBatch(batch.get());
Do I have to do additional synchronization when writing (Thread A) and reading (Thread B) to ensure thread B sees the list the way A left it, or is this taken care of by the AtomicReference?
In other words: if I have an AtomicReference to a mutable object, and one thread changes that object, do other threads see this change immediately?
Edit:
Maybe some example code is in order:
public void process(Reader in) throws IOException {
List<Future<AtomicReference<List<Object>>>> tasks = new ArrayList<Future<AtomicReference<List<Object>>>>();
ExecutorService exec = Executors.newFixedThreadPool(4);
for (int i = 0; i < 4; ++i) {
tasks.add(exec.submit(new Callable<AtomicReference<List<Object>>>() {
#Override public AtomicReference<List<Object>> call() throws IOException {
final AtomicReference<List<Object>> batch = new AtomicReference<List<Object>>(new ArrayList<Object>(batchSize));
Processor.this.parser.parse(in, new Parser.Handler() {
#Override public void onNewObject(Object event) {
batch.get().add(event);
if (batch.get().size() >= batchSize) {
dao.insertBatch(batch.getAndSet(new ArrayList<Object>(batchSize)));
}
}
});
return batch;
}
}));
}
List<Object> remainingBatches = new ArrayList<Object>();
for (Future<AtomicReference<List<Object>>> task : tasks) {
try {
AtomicReference<List<Object>> remainingBatch = task.get();
remainingBatches.addAll(remainingBatch.get());
} catch (ExecutionException e) {
Throwable cause = e.getCause();
if (cause instanceof IOException) {
throw (IOException)cause;
}
throw (RuntimeException)cause;
}
}
// these haven't been flushed yet by the worker threads
if (!remainingBatches.isEmpty()) {
dao.insertBatch(remainingBatches);
}
}
What happens here is that I create four worker threads to parse some text (this is the Reader in parameter to the process() method). Each worker saves the lines it has parsed in a batch, and flushes the batch when it is full (dao.insertBatch(batch.getAndSet(new ArrayList<Object>(batchSize)));).
Since the number of lines in the text isn't a multiple of the batch size, the last objects end up in a batch that isn't flushed, since it's not full. These remaining batches are therefore inserted by the main thread.
I use AtomicReference.getAndSet() to replace the full batch with an empty one. It this program correct with regards to threading?

Um... it doesn't really work like this. AtomicReference guarantees that the reference itself is visible across threads i.e. if you assign it a different reference than the original one the update will be visible. It makes no guarantees about the actual contents of the object that reference is pointing to.
Therefore, read/write operations on the list contents require separate synchronization.
Edit: So, judging from your updated code and the comment you posted, setting the local reference to volatile is sufficient to ensure visibility.

I think that, forgetting all the code here, you exact question is this:
Do I have to do additional synchronization when writing (Thread A) and
reading (Thread B) to ensure thread B sees the list the way A left it,
or is this taken care of by the AtomicReference?
So, the exact response to that is: YES, atomic take care of visibility. And it is not my opinion but the JDK documentation one:
The memory effects for accesses and updates of atomics generally follow the rules for volatiles, as stated in The Java Language Specification, Third Edition (17.4 Memory Model).
I hope this helps.

Adding to Tudor's answer: You will have to make the ArrayList itself threadsafe or - depending on your requirements - even larger code blocks.
If you can get away with a threadsafe ArrayList you can "decorate" it like this:
batch = java.util.Collections.synchronizedList(new ArrayList<Object>());
But keep in mind: Even "simple" constructs like this are not threadsafe with this:
Object o = batch.get(batch.size()-1);

The AtomicReference will only help you with the reference to the list, it will not do anything to the list itself. More particularly, in your scenario, you will almost certainly run into problems when the system is under load where the consumer has taken the list while the producer is adding an item to it.
This sound to me like you should be using a BlockingQueue. You can then Limit the memory footprint if you producer is faster than your consumer and let the queue handle all contention.
Something like:
ArrayBlockingQueue<Object> queue = new ArrayBlockingQueue<Object> (50);
// ... Producer
queue.put(o);
// ... Consumer
List<Object> queueContents = new ArrayList<Object> ();
// Grab everything waiting in the queue in one chunk. Should never be more than 50 items.
queue.drainTo(queueContents);
Added
Thanks to #Tudor for pointing out the architecture you are using. ... I have to admit it is rather strange. You don't really need AtomicReference at all as far as I can see. Each thread owns its own ArrayList until it is passed on to dao at which point it is replaced so there is no contention at all anywhere.
I am a little concerned about you creating four parser on a single Reader. I hope you have some way of ensuring each parser does not affect the others.
I personally would use some form of producer-consumer pattern as I have described in the code above. Something like this perhaps.
static final int PROCESSES = 4;
static final int batchSize = 10;
public void process(Reader in) throws IOException, InterruptedException {
final List<Future<Void>> tasks = new ArrayList<Future<Void>>();
ExecutorService exec = Executors.newFixedThreadPool(PROCESSES);
// Queue of objects.
final ArrayBlockingQueue<Object> queue = new ArrayBlockingQueue<Object> (batchSize * 2);
// The final object to post.
final Object FINISHED = new Object();
// Start the producers.
for (int i = 0; i < PROCESSES; i++) {
tasks.add(exec.submit(new Callable<Void>() {
#Override
public Void call() throws IOException {
Processor.this.parser.parse(in, new Parser.Handler() {
#Override
public void onNewObject(Object event) {
queue.add(event);
}
});
// Post a finished down the queue.
queue.add(FINISHED);
return null;
}
}));
}
// Start the consumer.
tasks.add(exec.submit(new Callable<Void>() {
#Override
public Void call() throws IOException {
List<Object> batch = new ArrayList<Object>(batchSize);
int finishedCount = 0;
// Until all threads finished.
while ( finishedCount < PROCESSES ) {
Object o = queue.take();
if ( o != FINISHED ) {
// Batch them up.
batch.add(o);
if ( batch.size() >= batchSize ) {
dao.insertBatch(batch);
// If insertBatch takes a copy we could merely clear it.
batch = new ArrayList<Object>(batchSize);
}
} else {
// Count the finishes.
finishedCount += 1;
}
}
// Finished! Post any incopmplete batch.
if ( batch.size() > 0 ) {
dao.insertBatch(batch);
}
return null;
}
}));
// Wait for everything to finish.
exec.shutdown();
// Wait until all is done.
boolean finished = false;
do {
try {
// Wait up to 1 second for termination.
finished = exec.awaitTermination(1, TimeUnit.SECONDS);
} catch (InterruptedException ex) {
}
} while (!finished);
}

Synchronizing on String objects in Java

I have a webapp that I am in the middle of doing some load/performance testing on, particularily on a feature where we expect a few hundred users to be accessing the same page and hitting refresh about every 10 seconds on this page. One area of improvement that we found we could make with this function was to cache the responses from the web service for some period of time, since the data is not changing.
After implementing this basic caching, in some further testing I found out that I didn't consider how concurrent threads could access the Cache at the same time. I found that within the matter of ~100ms, about 50 threads were trying to fetch the object from the Cache, finding that it had expired, hitting the web service to fetch the data, and then putting the object back in the cache.
The original code looked something like this:
private SomeData[] getSomeDataByEmail(WebServiceInterface service, String email) {
final String key = "Data-" + email;
SomeData[] data = (SomeData[]) StaticCache.get(key);
if (data == null) {
data = service.getSomeDataForEmail(email);
StaticCache.set(key, data, CACHE_TIME);
}
else {
logger.debug("getSomeDataForEmail: using cached object");
}
return data;
}
So, to make sure that only one thread was calling the web service when the object at key expired, I thought I needed to synchronize the Cache get/set operation, and it seemed like using the cache key would be a good candidate for an object to synchronize on (this way, calls to this method for email b#b.com would not be blocked by method calls to a#a.com).
I updated the method to look like this:
private SomeData[] getSomeDataByEmail(WebServiceInterface service, String email) {
SomeData[] data = null;
final String key = "Data-" + email;
synchronized(key) {
data =(SomeData[]) StaticCache.get(key);
if (data == null) {
data = service.getSomeDataForEmail(email);
StaticCache.set(key, data, CACHE_TIME);
}
else {
logger.debug("getSomeDataForEmail: using cached object");
}
}
return data;
}
I also added logging lines for things like "before synchronization block", "inside synchronization block", "about to leave synchronization block", and "after synchronization block", so I could determine if I was effectively synchronizing the get/set operation.
However it doesn't seem like this has worked. My test logs have output like:
(log output is 'threadname' 'logger name' 'message')
http-80-Processor253 jsp.view-page - getSomeDataForEmail: about to enter synchronization block
http-80-Processor253 jsp.view-page - getSomeDataForEmail: inside synchronization block
http-80-Processor253 cache.StaticCache - get: object at key [SomeData-test#test.com] has expired
http-80-Processor253 cache.StaticCache - get: key [SomeData-test#test.com] returning value [null]
http-80-Processor263 jsp.view-page - getSomeDataForEmail: about to enter synchronization block
http-80-Processor263 jsp.view-page - getSomeDataForEmail: inside synchronization block
http-80-Processor263 cache.StaticCache - get: object at key [SomeData-test#test.com] has expired
http-80-Processor263 cache.StaticCache - get: key [SomeData-test#test.com] returning value [null]
http-80-Processor131 jsp.view-page - getSomeDataForEmail: about to enter synchronization block
http-80-Processor131 jsp.view-page - getSomeDataForEmail: inside synchronization block
http-80-Processor131 cache.StaticCache - get: object at key [SomeData-test#test.com] has expired
http-80-Processor131 cache.StaticCache - get: key [SomeData-test#test.com] returning value [null]
http-80-Processor104 jsp.view-page - getSomeDataForEmail: inside synchronization block
http-80-Processor104 cache.StaticCache - get: object at key [SomeData-test#test.com] has expired
http-80-Processor104 cache.StaticCache - get: key [SomeData-test#test.com] returning value [null]
http-80-Processor252 jsp.view-page - getSomeDataForEmail: about to enter synchronization block
http-80-Processor283 jsp.view-page - getSomeDataForEmail: about to enter synchronization block
http-80-Processor2 jsp.view-page - getSomeDataForEmail: about to enter synchronization block
http-80-Processor2 jsp.view-page - getSomeDataForEmail: inside synchronization block
I wanted to see only one thread at a time entering/exiting the synchronization block around the get/set operations.
Is there an issue in synchronizing on String objects? I thought the cache-key would be a good choice as it is unique to the operation, and even though the final String key is declared within the method, I was thinking that each thread would be getting a reference to the same object and therefore would synchronization on this single object.
What am I doing wrong here?
Update: after looking further at the logs, it seems like methods with the same synchronization logic where the key is always the same, such as
final String key = "blah";
...
synchronized(key) { ...
do not exhibit the same concurrency problem - only one thread at a time is entering the block.
Update 2: Thanks to everyone for the help! I accepted the first answer about intern()ing Strings, which solved my initial problem - where multiple threads were entering synchronized blocks where I thought they shouldn't, because the key's had the same value.
As others have pointed out, using intern() for such a purpose and synchronizing on those Strings does indeed turn out to be a bad idea - when running JMeter tests against the webapp to simulate the expected load, I saw the used heap size grow to almost 1GB in just under 20 minutes.
Currently I'm using the simple solution of just synchronizing the entire method - but I really like the code samples provided by martinprobst and MBCook, but since I have about 7 similar getData() methods in this class currently (since it needs about 7 different pieces of data from a web service), I didn't want to add almost-duplicate logic about getting and releasing locks to each method. But this is definitely very, very valuable info for future usage. I think these are ultimately the correct answers on how best to make an operation like this thread-safe, and I'd give out more votes to these answers if I could!

Without putting my brain fully into gear, from a quick scan of what you say it looks as though you need to intern() your Strings:
final String firstkey = "Data-" + email;
final String key = firstkey.intern();
Two Strings with the same value are otherwise not necessarily the same object.
Note that this may introduce a new point of contention, since deep in the VM, intern() may have to acquire a lock. I have no idea what modern VMs look like in this area, but one hopes they are fiendishly optimised.
I assume you know that StaticCache still needs to be thread-safe. But the contention there should be tiny compared with what you'd have if you were locking on the cache rather than just the key while calling getSomeDataForEmail.
Response to question update:
I think that's because a string literal always yields the same object. Dave Costa points out in a comment that it's even better than that: a literal always yields the canonical representation. So all String literals with the same value anywhere in the program would yield the same object.
Edit
Others have pointed out that synchronizing on intern strings is actually a really bad idea - partly because creating intern strings is permitted to cause them to exist in perpetuity, and partly because if more than one bit of code anywhere in your program synchronizes on intern strings, you have dependencies between those bits of code, and preventing deadlocks or other bugs may be impossible.
Strategies to avoid this by storing a lock object per key string are being developed in other answers as I type.
Here's an alternative - it still uses a singular lock, but we know we're going to need one of those for the cache anyway, and you were talking about 50 threads, not 5000, so that may not be fatal. I'm also assuming that the performance bottleneck here is slow blocking I/O in DoSlowThing() which will therefore hugely benefit from not being serialised. If that's not the bottleneck, then:
If the CPU is busy then this approach may not be sufficient and you need another approach.
If the CPU is not busy, and access to server is not a bottleneck, then this approach is overkill, and you might as well forget both this and per-key locking, put a big synchronized(StaticCache) around the whole operation, and do it the easy way.
Obviously this approach needs to be soak tested for scalability before use -- I guarantee nothing.
This code does NOT require that StaticCache is synchronized or otherwise thread-safe. That needs to be revisited if any other code (for example scheduled clean-up of old data) ever touches the cache.
IN_PROGRESS is a dummy value - not exactly clean, but the code's simple and it saves having two hashtables. It doesn't handle InterruptedException because I don't know what your app wants to do in that case. Also, if DoSlowThing() consistently fails for a given key this code as it stands is not exactly elegant, since every thread through will retry it. Since I don't know what the failure criteria are, and whether they are liable to be temporary or permanent, I don't handle this either, I just make sure threads don't block forever. In practice you may want to put a data value in the cache which indicates 'not available', perhaps with a reason, and a timeout for when to retry.
// do not attempt double-check locking here. I mean it.
synchronized(StaticObject) {
data = StaticCache.get(key);
while (data == IN_PROGRESS) {
// another thread is getting the data
StaticObject.wait();
data = StaticCache.get(key);
}
if (data == null) {
// we must get the data
StaticCache.put(key, IN_PROGRESS, TIME_MAX_VALUE);
}
}
if (data == null) {
// we must get the data
try {
data = server.DoSlowThing(key);
} finally {
synchronized(StaticObject) {
// WARNING: failure here is fatal, and must be allowed to terminate
// the app or else waiters will be left forever. Choose a suitable
// collection type in which replacing the value for a key is guaranteed.
StaticCache.put(key, data, CURRENT_TIME);
StaticObject.notifyAll();
}
}
}
Every time anything is added to the cache, all threads wake up and check the cache (no matter what key they're after), so it's possible to get better performance with less contentious algorithms. However, much of that work will take place during your copious idle CPU time blocking on I/O, so it may not be a problem.
This code could be commoned-up for use with multiple caches, if you define suitable abstractions for the cache and its associated lock, the data it returns, the IN_PROGRESS dummy, and the slow operation to perform. Rolling the whole thing into a method on the cache might not be a bad idea.

Synchronizing on an intern'd String might not be a good idea at all - by interning it, the String turns into a global object, and if you synchronize on the same interned strings in different parts of your application, you might get really weird and basically undebuggable synchronization issues such as deadlocks. It might seem unlikely, but when it happens you are really screwed. As a general rule, only ever synchronize on a local object where you're absolutely sure that no code outside of your module might lock it.
In your case, you can use a synchronized hashtable to store locking objects for your keys.
E.g.:
Object data = StaticCache.get(key, ...);
if (data == null) {
Object lock = lockTable.get(key);
if (lock == null) {
// we're the only one looking for this
lock = new Object();
synchronized(lock) {
lockTable.put(key, lock);
// get stuff
lockTable.remove(key);
}
} else {
synchronized(lock) {
// just to wait for the updater
}
data = StaticCache.get(key);
}
} else {
// use from cache
}
This code has a race condition, where two threads might put an object into the lock table after each other. This should however not be a problem, because then you only have one more thread calling the webservice and updating the cache, which shouldn't be a problem.
If you're invalidating the cache after some time, you should check whether data is null again after retrieving it from the cache, in the lock != null case.
Alternatively, and much easier, you can make the whole cache lookup method ("getSomeDataByEmail") synchronized. This will mean that all threads have to synchronize when they access the cache, which might be a performance problem. But as always, try this simple solution first and see if it's really a problem! In many cases it should not be, as you probably spend much more time processing the result than synchronizing.

Strings are not good candidates for synchronization. If you must synchronize on a String ID, it can be done by using the string to create a mutex (see "synchronizing on an ID"). Whether the cost of that algorithm is worth it depends on whether invoking your service involves any significant I/O.
Also:
I hope the StaticCache.get() and set() methods are threadsafe.
String.intern() comes at a cost (one that varies between VM implementations) and should be used with care.

Here is a safe short Java 8 solution that uses a map of dedicated lock objects for synchronization:
private static final Map<String, Object> keyLocks = new ConcurrentHashMap<>();
private SomeData[] getSomeDataByEmail(WebServiceInterface service, String email) {
final String key = "Data-" + email;
synchronized (keyLocks.computeIfAbsent(key, k -> new Object())) {
SomeData[] data = StaticCache.get(key);
if (data == null) {
data = service.getSomeDataForEmail(email);
StaticCache.set(key, data);
}
}
return data;
}
It has a drawback that keys and lock objects would retain in map forever.
This can be worked around like this:
private SomeData[] getSomeDataByEmail(WebServiceInterface service, String email) {
final String key = "Data-" + email;
synchronized (keyLocks.computeIfAbsent(key, k -> new Object())) {
try {
SomeData[] data = StaticCache.get(key);
if (data == null) {
data = service.getSomeDataForEmail(email);
StaticCache.set(key, data);
}
} finally {
keyLocks.remove(key); // vulnerable to race-conditions
}
}
return data;
}
But then popular keys would be constantly reinserted in map with lock objects being reallocated.
Update: And this leaves race condition possibility when two threads would concurrently enter synchronized section for the same key but with different locks.
So it may be more safe and efficient to use expiring Guava Cache:
private static final LoadingCache<String, Object> keyLocks = CacheBuilder.newBuilder()
.expireAfterAccess(10, TimeUnit.MINUTES) // max lock time ever expected
.build(CacheLoader.from(Object::new));
private SomeData[] getSomeDataByEmail(WebServiceInterface service, String email) {
final String key = "Data-" + email;
synchronized (keyLocks.getUnchecked(key)) {
SomeData[] data = StaticCache.get(key);
if (data == null) {
data = service.getSomeDataForEmail(email);
StaticCache.set(key, data);
}
}
return data;
}
Note that it's assumed here that StaticCache is thread-safe and wouldn't suffer from concurrent reads and writes for different keys.

Others have suggested interning the strings, and that will work.
The problem is that Java has to keep interned strings around. I was told it does this even if you're not holding a reference because the value needs to be the same the next time someone uses that string. This means interning all the strings may start eating up memory, which with the load you're describing could be a big problem.
I have seen two solutions to this:
You could synchronize on another object
Instead of the email, make an object that holds the email (say the User object) that holds the value of email as a variable. If you already have another object that represents the person (say you already pulled something from the DB based on their email) you could use that. By implementing the equals method and the hashcode method you can make sure Java considers the objects the same when you do a static cache.contains() to find out if the data is already in the cache (you'll have to synchronize on the cache).
Actually, you could keep a second Map for objects to lock on. Something like this:
Map<String, Object> emailLocks = new HashMap<String, Object>();
Object lock = null;
synchronized (emailLocks) {
lock = emailLocks.get(emailAddress);
if (lock == null) {
lock = new Object();
emailLocks.put(emailAddress, lock);
}
}
synchronized (lock) {
// See if this email is in the cache
// If so, serve that
// If not, generate the data
// Since each of this person's threads synchronizes on this, they won't run
// over eachother. Since this lock is only for this person, it won't effect
// other people. The other synchronized block (on emailLocks) is small enough
// it shouldn't cause a performance problem.
}
This will prevent 15 fetches on the same email address at one. You'll need something to prevent too many entries from ending up in the emailLocks map. Using LRUMaps from Apache Commons would do it.
This will need some tweaking, but it may solve your problem.
Use a different key
If you are willing to put up with possible errors (I don't know how important this is) you could use the hashcode of the String as the key. ints don't need to be interned.
Summary
I hope this helps. Threading is fun, isn't it? You could also use the session to set a value meaning "I'm already working on finding this" and check that to see if the second (third, Nth) thread needs to attempt to create the or just wait for the result to show up in the cache. I guess I had three suggestions.

You can use the 1.5 concurrency utilities to provide a cache designed to allow multiple concurrent access, and a single point of addition (i.e. only one thread ever performing the expensive object "creation"):
private ConcurrentMap<String, Future<SomeData[]> cache;
private SomeData[] getSomeDataByEmail(final WebServiceInterface service, final String email) throws Exception {
final String key = "Data-" + email;
Callable<SomeData[]> call = new Callable<SomeData[]>() {
public SomeData[] call() {
return service.getSomeDataForEmail(email);
}
}
FutureTask<SomeData[]> ft; ;
Future<SomeData[]> f = cache.putIfAbsent(key, ft= new FutureTask<SomeData[]>(call)); //atomic
if (f == null) { //this means that the cache had no mapping for the key
f = ft;
ft.run();
}
return f.get(); //wait on the result being available if it is being calculated in another thread
}
Obviously, this doesn't handle exceptions as you'd want to, and the cache doesn't have eviction built in. Perhaps you could use it as a basis to change your StaticCache class, though.

Use a decent caching framework such as ehcache.
Implementing a good cache is not as easy as some people believe.
Regarding the comment that String.intern() is a source of memory leaks, that is actually not true.
Interned Strings are garbage collected,it just might take longer because on certain JVM'S (SUN) they are stored in Perm space which is only touched by full GC's.

Your main problem is not just that there might be multiple instances of String with the same value. The main problem is that you need to have only one monitor on which to synchronize for accessing the StaticCache object. Otherwise multiple threads might end up concurrently modifying StaticCache (albeit under different keys), which most likely doesn't support concurrent modification.

The call:
final String key = "Data-" + email;
creates a new object every time the method is called. Because that object is what you use to lock, and every call to this method creates a new object, then you are not really synchronizing access to the map based on the key.
This further explain your edit. When you have a static string, then it will work.
Using intern() solves the problem, because it returns the string from an internal pool kept by the String class, that ensures that if two strings are equal, the one in the pool will be used. See
http://java.sun.com/j2se/1.4.2/docs/api/java/lang/String.html#intern()

This question seems to me a bit too broad, and therefore it instigated equally broad set of answers. So I'll try to answer the question I have been redirected from, unfortunately that one has been closed as duplicate.
public class ValueLock<T> {
private Lock lock = new ReentrantLock();
private Map<T, Condition> conditions = new HashMap<T, Condition>();
public void lock(T t){
lock.lock();
try {
while (conditions.containsKey(t)){
conditions.get(t).awaitUninterruptibly();
}
conditions.put(t, lock.newCondition());
} finally {
lock.unlock();
}
}
public void unlock(T t){
lock.lock();
try {
Condition condition = conditions.get(t);
if (condition == null)
throw new IllegalStateException();// possibly an attempt to release what wasn't acquired
conditions.remove(t);
condition.signalAll();
} finally {
lock.unlock();
}
}
Upon the (outer) lock operation the (inner) lock is acquired to get an exclusive access to the map for a short time, and if the correspondent object is already in the map, the current thread will wait,
otherwise it will put new Condition to the map, release the (inner) lock and proceed,
and the (outer) lock is considered obtained.
The (outer) unlock operation, first acquiring an (inner) lock, will signal on Condition and then remove the object from the map.
The class does not use concurrent version of Map, because every access to it is guarded by single (inner) lock.
Please notice, the semantic of lock() method of this class is different that of ReentrantLock.lock(), the repeated lock() invocations without paired unlock() will hang current thread indefinitely.
An example of usage that might be applicable to the situation, the OP described
ValueLock<String> lock = new ValueLock<String>();
// ... share the lock
String email = "...";
try {
lock.lock(email);
//...
} finally {
lock.unlock(email);
}

This is rather late, but there is quite a lot of incorrect code presented here.
In this example:
private SomeData[] getSomeDataByEmail(WebServiceInterface service, String email) {
SomeData[] data = null;
final String key = "Data-" + email;
synchronized(key) {
data =(SomeData[]) StaticCache.get(key);
if (data == null) {
data = service.getSomeDataForEmail(email);
StaticCache.set(key, data, CACHE_TIME);
}
else {
logger.debug("getSomeDataForEmail: using cached object");
}
}
return data;
}
The synchronization is incorrectly scoped. For a static cache that supports a get/put API, there should be at least synchronization around the get and getIfAbsentPut type operations, for safe access to the cache. The scope of synchronization will be the cache itself.
If updates must be made to the data elements themselves, that adds an additional layer of synchronization, which should be on the individual data elements.
SynchronizedMap can be used in place of explicit synchronization, but care must still be observed. If the wrong APIs are used (get and put instead of putIfAbsent) then the operations won't have the necessary synchronization, despite the use of the synchronized map. Notice the complications introduced by the use of putIfAbsent: Either, the put value must be computed even in cases when it is not needed (because the put cannot know if the put value is needed until the cache contents are examined), or requires a careful use of delegation (say, using Future, which works, but is somewhat of a mismatch; see below), where the put value is obtained on demand if needed.
The use of Futures is possible, but seems rather awkward, and perhaps a bit of overengineering. The Future API is at it's core for asynchronous operations, in particular, for operations which may not complete immediately. Involving Future very probably adds a layer of thread creation -- extra probably unnecessary complications.
The main problem of using Future for this type of operation is that Future inherently ties in multi-threading. Use of Future when a new thread is not necessary means ignoring a lot of the machinery of Future, making it an overly heavy API for this use.

Latest update 2019,
If you are searching for new ways of implementing synchronization in JAVA, this answer is for you.
I found this amazing blog by Anatoliy Korovin this will help you understand the syncronized deeply.
How to Synchronize Blocks by the Value of the Object in Java.
This helped me hope new developers will find this useful too.

Why not just render a static html page that gets served to the user and regenerated every x minutes?

I'd also suggest getting rid of the string concatenation entirely if you don't need it.
final String key = "Data-" + email;
Is there other things/types of objects in the cache that use the email address that you need that extra "Data-" at the beginning of the key?
if not, i'd just make that
final String key = email;
and you avoid all that extra string creation too.

In case others have a similar problem, the following code works, as far as I can tell:
import java.util.Map;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.atomic.AtomicInteger;
import java.util.function.Supplier;
public class KeySynchronizer<T> {
private Map<T, CounterLock> locks = new ConcurrentHashMap<>();
public <U> U synchronize(T key, Supplier<U> supplier) {
CounterLock lock = locks.compute(key, (k, v) ->
v == null ? new CounterLock() : v.increment());
synchronized (lock) {
try {
return supplier.get();
} finally {
if (lock.decrement() == 0) {
// Only removes if key still points to the same value,
// to avoid issue described below.
locks.remove(key, lock);
}
}
}
}
private static final class CounterLock {
private AtomicInteger remaining = new AtomicInteger(1);
private CounterLock increment() {
// Returning a new CounterLock object if remaining = 0 to ensure that
// the lock is not removed in step 5 of the following execution sequence:
// 1) Thread 1 obtains a new CounterLock object from locks.compute (after evaluating "v == null" to true)
// 2) Thread 2 evaluates "v == null" to false in locks.compute
// 3) Thread 1 calls lock.decrement() which sets remaining = 0
// 4) Thread 2 calls v.increment() in locks.compute
// 5) Thread 1 calls locks.remove(key, lock)
return remaining.getAndIncrement() == 0 ? new CounterLock() : this;
}
private int decrement() {
return remaining.decrementAndGet();
}
}
}
In the case of the OP, it would be used like this:
private KeySynchronizer<String> keySynchronizer = new KeySynchronizer<>();
private SomeData[] getSomeDataByEmail(WebServiceInterface service, String email) {
String key = "Data-" + email;
return keySynchronizer.synchronize(key, () -> {
SomeData[] existing = (SomeData[]) StaticCache.get(key);
if (existing == null) {
SomeData[] data = service.getSomeDataForEmail(email);
StaticCache.set(key, data, CACHE_TIME);
return data;
}
logger.debug("getSomeDataForEmail: using cached object");
return existing;
});
}
If nothing should be returned from the synchronized code, the synchronize method can be written like this:
public void synchronize(T key, Runnable runnable) {
CounterLock lock = locks.compute(key, (k, v) ->
v == null ? new CounterLock() : v.increment());
synchronized (lock) {
try {
runnable.run();
} finally {
if (lock.decrement() == 0) {
// Only removes if key still points to the same value,
// to avoid issue described below.
locks.remove(key, lock);
}
}
}
}

I've added a small lock class that can lock/synchronize on any key, including strings.
See implementation for Java 8, Java 6 and a small test.
Java 8:
public class DynamicKeyLock<T> implements Lock
{
private final static ConcurrentHashMap<Object, LockAndCounter> locksMap = new ConcurrentHashMap<>();
private final T key;
public DynamicKeyLock(T lockKey)
{
this.key = lockKey;
}
private static class LockAndCounter
{
private final Lock lock = new ReentrantLock();
private final AtomicInteger counter = new AtomicInteger(0);
}
private LockAndCounter getLock()
{
return locksMap.compute(key, (key, lockAndCounterInner) ->
{
if (lockAndCounterInner == null) {
lockAndCounterInner = new LockAndCounter();
}
lockAndCounterInner.counter.incrementAndGet();
return lockAndCounterInner;
});
}
private void cleanupLock(LockAndCounter lockAndCounterOuter)
{
if (lockAndCounterOuter.counter.decrementAndGet() == 0)
{
locksMap.compute(key, (key, lockAndCounterInner) ->
{
if (lockAndCounterInner == null || lockAndCounterInner.counter.get() == 0) {
return null;
}
return lockAndCounterInner;
});
}
}
#Override
public void lock()
{
LockAndCounter lockAndCounter = getLock();
lockAndCounter.lock.lock();
}
#Override
public void unlock()
{
LockAndCounter lockAndCounter = locksMap.get(key);
lockAndCounter.lock.unlock();
cleanupLock(lockAndCounter);
}
#Override
public void lockInterruptibly() throws InterruptedException
{
LockAndCounter lockAndCounter = getLock();
try
{
lockAndCounter.lock.lockInterruptibly();
}
catch (InterruptedException e)
{
cleanupLock(lockAndCounter);
throw e;
}
}
#Override
public boolean tryLock()
{
LockAndCounter lockAndCounter = getLock();
boolean acquired = lockAndCounter.lock.tryLock();
if (!acquired)
{
cleanupLock(lockAndCounter);
}
return acquired;
}
#Override
public boolean tryLock(long time, TimeUnit unit) throws InterruptedException
{
LockAndCounter lockAndCounter = getLock();
boolean acquired;
try
{
acquired = lockAndCounter.lock.tryLock(time, unit);
}
catch (InterruptedException e)
{
cleanupLock(lockAndCounter);
throw e;
}
if (!acquired)
{
cleanupLock(lockAndCounter);
}
return acquired;
}
#Override
public Condition newCondition()
{
LockAndCounter lockAndCounter = locksMap.get(key);
return lockAndCounter.lock.newCondition();
}
}
Java 6:
public class DynamicKeyLock implements Lock
{
private final static ConcurrentHashMap locksMap = new ConcurrentHashMap();
private final T key;
public DynamicKeyLock(T lockKey) {
this.key = lockKey;
}
private static class LockAndCounter {
private final Lock lock = new ReentrantLock();
private final AtomicInteger counter = new AtomicInteger(0);
}
private LockAndCounter getLock()
{
while (true) // Try to init lock
{
LockAndCounter lockAndCounter = locksMap.get(key);
if (lockAndCounter == null)
{
LockAndCounter newLock = new LockAndCounter();
lockAndCounter = locksMap.putIfAbsent(key, newLock);
if (lockAndCounter == null)
{
lockAndCounter = newLock;
}
}
lockAndCounter.counter.incrementAndGet();
synchronized (lockAndCounter)
{
LockAndCounter lastLockAndCounter = locksMap.get(key);
if (lockAndCounter == lastLockAndCounter)
{
return lockAndCounter;
}
// else some other thread beat us to it, thus try again.
}
}
}
private void cleanupLock(LockAndCounter lockAndCounter)
{
if (lockAndCounter.counter.decrementAndGet() == 0)
{
synchronized (lockAndCounter)
{
if (lockAndCounter.counter.get() == 0)
{
locksMap.remove(key);
}
}
}
}
#Override
public void lock()
{
LockAndCounter lockAndCounter = getLock();
lockAndCounter.lock.lock();
}
#Override
public void unlock()
{
LockAndCounter lockAndCounter = locksMap.get(key);
lockAndCounter.lock.unlock();
cleanupLock(lockAndCounter);
}
#Override
public void lockInterruptibly() throws InterruptedException
{
LockAndCounter lockAndCounter = getLock();
try
{
lockAndCounter.lock.lockInterruptibly();
}
catch (InterruptedException e)
{
cleanupLock(lockAndCounter);
throw e;
}
}
#Override
public boolean tryLock()
{
LockAndCounter lockAndCounter = getLock();
boolean acquired = lockAndCounter.lock.tryLock();
if (!acquired)
{
cleanupLock(lockAndCounter);
}
return acquired;
}
#Override
public boolean tryLock(long time, TimeUnit unit) throws InterruptedException
{
LockAndCounter lockAndCounter = getLock();
boolean acquired;
try
{
acquired = lockAndCounter.lock.tryLock(time, unit);
}
catch (InterruptedException e)
{
cleanupLock(lockAndCounter);
throw e;
}
if (!acquired)
{
cleanupLock(lockAndCounter);
}
return acquired;
}
#Override
public Condition newCondition()
{
LockAndCounter lockAndCounter = locksMap.get(key);
return lockAndCounter.lock.newCondition();
}
}
Test:
public class DynamicKeyLockTest
{
#Test
public void testDifferentKeysDontLock() throws InterruptedException
{
DynamicKeyLock<Object> lock = new DynamicKeyLock<>(new Object());
lock.lock();
AtomicBoolean anotherThreadWasExecuted = new AtomicBoolean(false);
try
{
new Thread(() ->
{
DynamicKeyLock<Object> anotherLock = new DynamicKeyLock<>(new Object());
anotherLock.lock();
try
{
anotherThreadWasExecuted.set(true);
}
finally
{
anotherLock.unlock();
}
}).start();
Thread.sleep(100);
}
finally
{
Assert.assertTrue(anotherThreadWasExecuted.get());
lock.unlock();
}
}
#Test
public void testSameKeysLock() throws InterruptedException
{
Object key = new Object();
DynamicKeyLock<Object> lock = new DynamicKeyLock<>(key);
lock.lock();
AtomicBoolean anotherThreadWasExecuted = new AtomicBoolean(false);
try
{
new Thread(() ->
{
DynamicKeyLock<Object> anotherLock = new DynamicKeyLock<>(key);
anotherLock.lock();
try
{
anotherThreadWasExecuted.set(true);
}
finally
{
anotherLock.unlock();
}
}).start();
Thread.sleep(100);
}
finally
{
Assert.assertFalse(anotherThreadWasExecuted.get());
lock.unlock();
}
}
}

In your case you could use something like this (this doesn't leak any memory):
private Synchronizer<String> synchronizer = new Synchronizer();
private SomeData[] getSomeDataByEmail(WebServiceInterface service, String email) {
String key = "Data-" + email;
return synchronizer.synchronizeOn(key, () -> {
SomeData[] data = (SomeData[]) StaticCache.get(key);
if (data == null) {
data = service.getSomeDataForEmail(email);
StaticCache.set(key, data, CACHE_TIME);
} else {
logger.debug("getSomeDataForEmail: using cached object");
}
return data;
});
}
to use it you just add a dependency:
compile 'com.github.matejtymes:javafixes:1.3.0'

You should be very careful using short lived objects with synchronization. Every Java object has an attached monitor and by default this monitor is deflated; however if 2 threads contend on acquiring the monitor, the monitor gets inflated. If the object would be long lived, this isn't a problem. However if the object is short lived, then cleaning up this inflated monitor can be a serious hit on GC times (so higher latencies and reduced throughput). And it can even be tricky to spot on the GC times since it isn't always listed.
If you do want to synchronize, you could use a java.util.concurrent.Lock. Or make use of a manually crafted striped lock and use the hash of the string as an index on that striped lock. This striped lock you keep around so you don't get the GC problems.
So something like this:
static final Object[] locks = newLockArray();
Object lock = locks[hashToIndex(key.hashcode(),locks.length];
synchronized(lock){
....
}
int hashToIndex(int hash, int length) {
if (hash == Integer.MIN_VALUE return 0;
return abs(hash) % length;
}

other way synchronizing on string object :
String cacheKey = ...;
Object obj = cache.get(cacheKey)
if(obj==null){
synchronized (Integer.valueOf(Math.abs(cacheKey.hashCode()) % 127)){
obj = cache.get(cacheKey)
if(obj==null){
//some cal obtain obj value,and put into cache
}
}
}

You can safely use String.intern for synchronize if you can reasonably guarantee that the string value is unique across your system. UUIDS are a good way to approach this. You can associate a UUID with your actual string key, either via a cache, a map, or maybe even store the uuid as a field on your entity object.
#Service
public class MySyncService{
public Map<String, String> lockMap=new HashMap<String, String>();
public void syncMethod(String email) {
String lock = lockMap.get(email);
if(lock==null) {
lock = UUID.randomUUID().toString();
lockMap.put(email, lock);
}
synchronized(lock.intern()) {
//do your sync code here
}
}