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How to wait until a space becomes available in a threadpool [duplicate]

This question already has answers here:
ThreadPoolExecutor Block When its Queue Is Full?
(10 answers)
Closed 1 year ago.
I am trying to code a solution in which a single thread produces I/O-intensive tasks that can be performed in parallel. Each task have significant in-memory data. So I want to be able limit the number of tasks that are pending at a moment.
If I create ThreadPoolExecutor like this:
ThreadPoolExecutor executor = new ThreadPoolExecutor(numWorkerThreads, numWorkerThreads,
0L, TimeUnit.MILLISECONDS,
new LinkedBlockingQueue<Runnable>(maxQueue));
Then the executor.submit(callable) throws RejectedExecutionException when the queue fills up and all the threads are already busy.
What can I do to make executor.submit(callable) block when the queue is full and all threads are busy?
EDIT:
I tried this:
executor.setRejectedExecutionHandler(new ThreadPoolExecutor.CallerRunsPolicy());
And it somewhat achieves the effect that I want achieved but in an inelegant way (basically rejected threads are run in the calling thread, so this blocks the calling thread from submitting more).
EDIT: (5 years after asking the question)
To anyone reading this question and its answers, please don't take the accepted answer as one correct solution. Please read through all answers and comments.

I have done this same thing. The trick is to create a BlockingQueue where the offer() method is really a put(). (you can use whatever base BlockingQueue impl you want).
public class LimitedQueue<E> extends LinkedBlockingQueue<E>
{
public LimitedQueue(int maxSize)
{
super(maxSize);
}
#Override
public boolean offer(E e)
{
// turn offer() and add() into a blocking calls (unless interrupted)
try {
put(e);
return true;
} catch(InterruptedException ie) {
Thread.currentThread().interrupt();
}
return false;
}
}
Note that this only works for thread pool where corePoolSize==maxPoolSize so be careful there (see comments).

The currently accepted answer has a potentially significant problem - it changes the behavior of ThreadPoolExecutor.execute such that if you have a corePoolSize < maxPoolSize, the ThreadPoolExecutor logic will never add additional workers beyond the core.
From ThreadPoolExecutor.execute(Runnable):
if (isRunning(c) && workQueue.offer(command)) {
int recheck = ctl.get();
if (! isRunning(recheck) && remove(command))
reject(command);
else if (workerCountOf(recheck) == 0)
addWorker(null, false);
}
else if (!addWorker(command, false))
reject(command);
Specifically, that last 'else' block willl never be hit.
A better alternative is to do something similar to what OP is already doing - use a RejectedExecutionHandler to do the same put logic:
public void rejectedExecution(Runnable r, ThreadPoolExecutor executor) {
try {
if (!executor.isShutdown()) {
executor.getQueue().put(r);
}
} catch (InterruptedException e) {
Thread.currentThread().interrupt();
throw new RejectedExecutionException("Executor was interrupted while the task was waiting to put on work queue", e);
}
}
There are some things to watch out for with this approach, as pointed out in the comments (referring to this answer):
If corePoolSize==0, then there is a race condition where all threads in the pool may die before the task is visible
Using an implementation that wraps the queue tasks (not applicable to ThreadPoolExecutor) will result in issues unless the handler also wraps it the same way.
Keeping those gotchas in mind, this solution will work for most typical ThreadPoolExecutors, and will properly handle the case where corePoolSize < maxPoolSize.

Here is how I solved this on my end:
(note: this solution does block the thread that submits the Callable, so it prevents RejectedExecutionException from being thrown )
public class BoundedExecutor extends ThreadPoolExecutor{
private final Semaphore semaphore;
public BoundedExecutor(int bound) {
super(bound, Integer.MAX_VALUE, 60L, TimeUnit.SECONDS, new SynchronousQueue<Runnable>());
semaphore = new Semaphore(bound);
}
/**Submits task to execution pool, but blocks while number of running threads
* has reached the bound limit
*/
public <T> Future<T> submitButBlockIfFull(final Callable<T> task) throws InterruptedException{
semaphore.acquire();
return submit(task);
}
#Override
protected void afterExecute(Runnable r, Throwable t) {
super.afterExecute(r, t);
semaphore.release();
}
}

How about using the CallerBlocksPolicy class if you are using spring-integration?
This class implements the RejectedExecutionHandler interface, which is a handler for tasks that cannot be executed by a ThreadPoolExecutor.
You can use this policy like this.
executor.setRejectedExecutionHandler(new CallerBlocksPolicy());
The main difference between CallerBlocksPolicy and CallerRunsPolicy is whether it blocks or runs the task in the caller thread.
Please refer to this code.

I know this is an old question but had a similar issue that creating new tasks was very fast and if there were too many an OutOfMemoryError occur because existing task were not completed fast enough.
In my case Callables are submitted and I need the result hence I need to store all the Futures returned by executor.submit(). My solution was to put the Futures into a BlockingQueue with a maximum size. Once that queue is full, no more tasks are generated until some are completed (elements removed from queue). In pseudo-code:
final ExecutorService executor = Executors.newFixedThreadPool(numWorkerThreads);
final LinkedBlockingQueue<Future> futures = new LinkedBlockingQueue<>(maxQueueSize);
try {
Thread taskGenerator = new Thread() {
#Override
public void run() {
while (reader.hasNext) {
Callable task = generateTask(reader.next());
Future future = executor.submit(task);
try {
// if queue is full blocks until a task
// is completed and hence no future tasks are submitted.
futures.put(future);
} catch (InterruptedException ex) {
Thread.currentThread().interrupt();
}
}
executor.shutdown();
}
}
taskGenerator.start();
// read from queue as long as task are being generated
// or while Queue has elements in it
while (taskGenerator.isAlive()
|| !futures.isEmpty()) {
Future future = futures.take();
// do something
}
} catch (InterruptedException ex) {
Thread.currentThread().interrupt();
} catch (ExecutionException ex) {
throw new MyException(ex);
} finally {
executor.shutdownNow();
}

I had the similar problem and I implemented that by using beforeExecute/afterExecute hooks from ThreadPoolExecutor:
import java.util.concurrent.BlockingQueue;
import java.util.concurrent.ThreadPoolExecutor;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.locks.Condition;
import java.util.concurrent.locks.ReentrantLock;
/**
* Blocks current task execution if there is not enough resources for it.
* Maximum task count usage controlled by maxTaskCount property.
*/
public class BlockingThreadPoolExecutor extends ThreadPoolExecutor {
private final ReentrantLock taskLock = new ReentrantLock();
private final Condition unpaused = taskLock.newCondition();
private final int maxTaskCount;
private volatile int currentTaskCount;
public BlockingThreadPoolExecutor(int corePoolSize, int maximumPoolSize,
long keepAliveTime, TimeUnit unit,
BlockingQueue<Runnable> workQueue, int maxTaskCount) {
super(corePoolSize, maximumPoolSize, keepAliveTime, unit, workQueue);
this.maxTaskCount = maxTaskCount;
}
/**
* Executes task if there is enough system resources for it. Otherwise
* waits.
*/
#Override
protected void beforeExecute(Thread t, Runnable r) {
super.beforeExecute(t, r);
taskLock.lock();
try {
// Spin while we will not have enough capacity for this job
while (maxTaskCount < currentTaskCount) {
try {
unpaused.await();
} catch (InterruptedException e) {
t.interrupt();
}
}
currentTaskCount++;
} finally {
taskLock.unlock();
}
}
/**
* Signalling that one more task is welcome
*/
#Override
protected void afterExecute(Runnable r, Throwable t) {
super.afterExecute(r, t);
taskLock.lock();
try {
currentTaskCount--;
unpaused.signalAll();
} finally {
taskLock.unlock();
}
}
}
This should be good enough for you. Btw, original implementation was task size based because one task could be larger 100 time than another and submitting two huge tasks was killing the box, but running one big and plenty of small was Okay. If your I/O-intensive tasks are roughly the same size you could use this class, otherwise just let me know and I'll post size based implementation.
P.S. You would want to check ThreadPoolExecutor javadoc. It's really nice user guide from Doug Lea about how it could be easily customized.

I have implemented a solution following the decorator pattern and using a semaphore to control the number of executed tasks. You can use it with any Executor and:
Specify the maximum of ongoing tasks
Specify the maximum timeout to wait for a task execution permit (if the timeout passes and no permit is acquired, a RejectedExecutionException is thrown)
import static java.util.concurrent.TimeUnit.MILLISECONDS;
import java.time.Duration;
import java.util.Objects;
import java.util.concurrent.Executor;
import java.util.concurrent.RejectedExecutionException;
import java.util.concurrent.Semaphore;
import javax.annotation.Nonnull;
public class BlockingOnFullQueueExecutorDecorator implements Executor {
private static final class PermitReleasingDecorator implements Runnable {
#Nonnull
private final Runnable delegate;
#Nonnull
private final Semaphore semaphore;
private PermitReleasingDecorator(#Nonnull final Runnable task, #Nonnull final Semaphore semaphoreToRelease) {
this.delegate = task;
this.semaphore = semaphoreToRelease;
}
#Override
public void run() {
try {
this.delegate.run();
}
finally {
// however execution goes, release permit for next task
this.semaphore.release();
}
}
#Override
public final String toString() {
return String.format("%s[delegate='%s']", getClass().getSimpleName(), this.delegate);
}
}
#Nonnull
private final Semaphore taskLimit;
#Nonnull
private final Duration timeout;
#Nonnull
private final Executor delegate;
public BlockingOnFullQueueExecutorDecorator(#Nonnull final Executor executor, final int maximumTaskNumber, #Nonnull final Duration maximumTimeout) {
this.delegate = Objects.requireNonNull(executor, "'executor' must not be null");
if (maximumTaskNumber < 1) {
throw new IllegalArgumentException(String.format("At least one task must be permitted, not '%d'", maximumTaskNumber));
}
this.timeout = Objects.requireNonNull(maximumTimeout, "'maximumTimeout' must not be null");
if (this.timeout.isNegative()) {
throw new IllegalArgumentException("'maximumTimeout' must not be negative");
}
this.taskLimit = new Semaphore(maximumTaskNumber);
}
#Override
public final void execute(final Runnable command) {
Objects.requireNonNull(command, "'command' must not be null");
try {
// attempt to acquire permit for task execution
if (!this.taskLimit.tryAcquire(this.timeout.toMillis(), MILLISECONDS)) {
throw new RejectedExecutionException(String.format("Executor '%s' busy", this.delegate));
}
}
catch (final InterruptedException e) {
// restore interrupt status
Thread.currentThread().interrupt();
throw new IllegalStateException(e);
}
this.delegate.execute(new PermitReleasingDecorator(command, this.taskLimit));
}
#Override
public final String toString() {
return String.format("%s[availablePermits='%s',timeout='%s',delegate='%s']", getClass().getSimpleName(), this.taskLimit.availablePermits(),
this.timeout, this.delegate);
}
}

I think it is as simple as using a ArrayBlockingQueue instead of a a LinkedBlockingQueue.
Ignore me... that's totally wrong. ThreadPoolExecutor calls Queue#offer not put which would have the effect you require.
You could extend ThreadPoolExecutor and provide an implementation of execute(Runnable) that calls put in place of offer.
That doesn't seem like a completely satisfactory answer I'm afraid.

Java Concurrency in Practice “Listing 7.9. Interrupting a task in a dedicated thread.”. What is the purpose of scheduled taskThread.interrupt()?

I am reading Java Concurrency in Practice and encounter the following code snippet.
public static void timedRun(final Runnable r,
long timeout, TimeUnit unit)
throws InterruptedException {
class RethrowableTask implements Runnable {
private volatile Throwable t;
public void run() {
try { r.run(); }
catch (Throwable t) { this.t = t; }
}
void rethrow() {
if (t != null)
throw launderThrowable(t);
}
}
RethrowableTask task = new RethrowableTask();
final Thread taskThread = new Thread(task);
taskThread.start();
cancelExec.schedule(new Runnable() {
public void run() { taskThread.interrupt(); }
}, timeout, unit);
taskThread.join(unit.toMillis(timeout));
task.rethrow();
}
timedRun method is used to run task r within a time range. This feature can be implemented by taskThread.join(unit.toMillis(timeout));. So, why do we need scheduled taskThread.interrupt();?

This feature can be implemented by taskThread.join(unit.toMillis(timeout));
This isn't true. The time limit of the join just determines when the joining thread will give up waiting. It doesn't affect the thread being limited with a timeout. The scheduled interrupt tells the running thread to shut itself down after the timeout has expired. If it weren't there, that thread would continue to consume resources. Presumably the point of the method is to prevent that.

Executor: Wait for specific tasks to finish

The server application I am running gets multiple requests for tasks which I want to handle using a task system.
Each task is represented as a Runnable that will demand n number of threads from a thread pool where n is smaller or equal to the thread pool size. The thread pool of course is necessary in order to not overload the CPU with too many threads.
However, some of those tasks can be multi threaded and some can not. That is why it might be necessary for one task to wait for all its specific threads to finish in order to merge the results from those threads for the final result.
If one uses multiple Thread instances one might join those like this:
try {
// Wait for all threads to finish their tasks
for (Thread thread : threads) {
thread.join();
}
} catch (InterruptedException e) {
e.printStackTrace();
}
// Finish job here ..
but I'd need something like this using java.util.concurrent.Executor or anything similar that works with a thread pool.

You can use ExecutorService along with a CyclicBarrier for each task as follows:
public class ThreadedTask implements Runnable {
CyclicBarrier barrier;
public ThreadedTask(CyclicBarrier barrier) {
this.barrier = barrier;
}
#Override
public void run() {
// do something
barrier.await();
}
}
ExecutorService executor = Executors.newFixedThreadPool(pool_size);
...
CyclicBarrier barrier = new CyclicBarrier(n+1);
for(int i=0; i<n; i++) {
// launch all tasks
executor.submit(new ThreadedTask(barrier));
}
// waits for the tasks to finish or timeout
barrier.await(seconds, TimeUnit.SECONDS);

If I understand you correctly, you will need something like this (but your architecture seems too complicated):
class MyTask implements Runnable {
#Override
public void run() {
// some work
}
}
After that:
ExecutorService executorService = Executors.newFixedThreadPool(2000);
ArrayList<Future> futures = new ArrayList<>();
futures.add(executorService.submit(new MyTask()));
futures.add(executorService.submit(new MyTask()));
futures.add(executorService.submit(new MyTask()));
for (Future future: futures) {
try {
future.get(100, TimeUnit.SECONDS);
} catch (Throwable cause) {
// process cause
}
}
Each future.get() will wait for task ending (max 100 seconds in this example).

Why does ExecutorService keep executing when threads are blocking?

I am trying to write a part of a multithreaded program where each thread from a fixed thread pool tries to fetch an object from a Queue and if the Queue is empty the thread waits.
The problem I am experiencing is that the memory used by the program keeps increasing.
public class Ex3 {
public static LinkedBlockingQueue<Integer> myLBQ = new LinkedBlockingQueue<Integer>(10);
public static void main(String argc[]) throws Exception {
ExecutorService executor = Executors.newFixedThreadPool(3);
myLBQ.add(new Integer(1));
for (;;) {
executor.execute(new MyHandler(myLBQ));
}
}
}
class MyHandler implements Runnable {
LinkedBlockingQueue<Integer> myLBQ;
MyHandler(LinkedBlockingQueue<Integer> myLBQ) {
this.myLBQ = myLBQ;
}
public void run() {
try {
myLBQ.take();
} catch (InterruptedException e) {
e.printStackTrace();
}
}
}
I don't understand why the executor.execute keeps firing when the threads should be waiting for an item to be added to the Queue. How do I modify my code to reflect this?

This adds tasks to the executor as fast as it can.
for (;;) {
executor.execute(new MyHandler(myLBQ));
}
This will consume about 200 MB per second. It doesn't have anything to do with whether there are tasks to perform or not.
If you don't want to do this I suggest you move the loop to the runnable and add only one. This will cause it to wait for tasks forever.
A better approach is to use the ExecutorService's builtin queue to queue tasks.
ExecutorService executor = Executors.newFixedThreadPool(3);
final int taskId = 1;
executor.submit(new Runnable() {
#Override
public void run() {
doSomething(taskId);
}
});
executor.shutdown();
This does the same thing, but is much simpler IMHO.

it's because you're creating a gazillion instances of MyHandler and inserting them in the internal queue of the executor.
That infinite for loop is quite mean.

ThreadPoolExecutor Block When its Queue Is Full?

I am trying to execute lots of tasks using a ThreadPoolExecutor. Below is a hypothetical example:
def workQueue = new ArrayBlockingQueue<Runnable>(3, false)
def threadPoolExecutor = new ThreadPoolExecutor(3, 3, 1L, TimeUnit.HOURS, workQueue)
for(int i = 0; i < 100000; i++)
threadPoolExecutor.execute(runnable)
The problem is that I quickly get a java.util.concurrent.RejectedExecutionException since the number of tasks exceeds the size of the work queue. However, the desired behavior I am looking for is to have the main thread block until there is room in the queue. What is the best way to accomplish this?

In some very narrow circumstances, you can implement a java.util.concurrent.RejectedExecutionHandler that does what you need.
RejectedExecutionHandler block = new RejectedExecutionHandler() {
rejectedExecution(Runnable r, ThreadPoolExecutor executor) {
executor.getQueue().put( r );
}
};
ThreadPoolExecutor pool = new ...
pool.setRejectedExecutionHandler(block);
Now. This is a very bad idea for the following reasons
It's prone to deadlock because all the threads in the pool may die before the thing you put in the queue is visible. Mitigate this by setting a reasonable keep alive time.
The task is not wrapped the way your Executor may expect. Lots of executor implementations wrap their tasks in some sort of tracking object before execution. Look at the source of yours.
Adding via getQueue() is strongly discouraged by the API, and may be prohibited at some point.
A almost-always-better strategy is to install ThreadPoolExecutor.CallerRunsPolicy which will throttle your app by running the task on the thread which is calling execute().
However, sometimes a blocking strategy, with all its inherent risks, is really what you want. I'd say under these conditions
You only have one thread calling execute()
You have to (or want to) have a very small queue length
You absolutely need to limit the number of threads running this work (usually for external reasons), and a caller-runs strategy would break that.
Your tasks are of unpredictable size, so caller-runs could introduce starvation if the pool was momentarily busy with 4 short tasks and your one thread calling execute got stuck with a big one.
So, as I say. It's rarely needed and can be dangerous, but there you go.
Good Luck.

What you need to do is to wrap your ThreadPoolExecutor into Executor which explicitly limits amount of concurrently executed operations inside it:
private static class BlockingExecutor implements Executor {
final Semaphore semaphore;
final Executor delegate;
private BlockingExecutor(final int concurrentTasksLimit, final Executor delegate) {
semaphore = new Semaphore(concurrentTasksLimit);
this.delegate = delegate;
}
#Override
public void execute(final Runnable command) {
try {
semaphore.acquire();
} catch (InterruptedException e) {
e.printStackTrace();
return;
}
final Runnable wrapped = () -> {
try {
command.run();
} finally {
semaphore.release();
}
};
delegate.execute(wrapped);
}
}
You can adjust concurrentTasksLimit to the threadPoolSize + queueSize of your delegate executor and it will pretty much solve your problem

You could use a semaphore to block threads from going into the pool.
ExecutorService service = new ThreadPoolExecutor(
3,
3,
1,
TimeUnit.HOURS,
new ArrayBlockingQueue<>(6, false)
);
Semaphore lock = new Semaphore(6); // equal to queue capacity
for (int i = 0; i < 100000; i++ ) {
try {
lock.acquire();
service.submit(() -> {
try {
task.run();
} finally {
lock.release();
}
});
} catch (InterruptedException e) {
throw new RuntimeException(e);
}
}
Some gotchas:
Only use this pattern with a fixed thread pool. The queue is unlikely to be full often, thus new threads won't be created. Check out the java docs on ThreadPoolExecutor for more details: https://docs.oracle.com/javase/8/docs/api/java/util/concurrent/ThreadPoolExecutor.html There is a way around this, but it is out of scope of this answer.
Queue size should be higher than the number of core threads. If we were to make the queue size 3, what would end up happening is:
T0: all three threads are doing work, the queue is empty, no permits are available.
T1: Thread 1 finishes, releases a permit.
T2: Thread 1 polls the queue for new work, finds none, and waits.
T3: Main thread submits work into the pool, thread 1 starts work.
The example above translates to thread the main thread blocking thread 1. It may seem like a small period, but now multiply the frequency by days and months. All of a sudden, short periods of time add up to a large amount of time wasted.

This is what I ended up doing:
int NUM_THREADS = 6;
Semaphore lock = new Semaphore(NUM_THREADS);
ExecutorService pool = Executors.newCachedThreadPool();
for (int i = 0; i < 100000; i++) {
try {
lock.acquire();
} catch (InterruptedException e) {
throw new RuntimeException(e);
}
pool.execute(() -> {
try {
// Task logic
} finally {
lock.release();
}
});
}

A fairly straightforward option is to wrap your BlockingQueue with an implementation that calls put(..) when offer(..) is being invoked:
public class BlockOnOfferAdapter<T> implements BlockingQueue<T> {
(..)
public boolean offer(E o) {
try {
delegate.put(o);
} catch (InterruptedException e) {
Thread.currentThread().interrupt();
return false;
}
return true;
}
(.. implement all other methods simply by delegating ..)
}
This works because by default put(..) waits until there is capacity in the queue when it is full, see:
/**
* Inserts the specified element into this queue, waiting if necessary
* for space to become available.
*
* #param e the element to add
* #throws InterruptedException if interrupted while waiting
* #throws ClassCastException if the class of the specified element
* prevents it from being added to this queue
* #throws NullPointerException if the specified element is null
* #throws IllegalArgumentException if some property of the specified
* element prevents it from being added to this queue
*/
void put(E e) throws InterruptedException;
No catching of RejectedExecutionException or complicated locking necessary.

Here is my code snippet in this case:
public void executeBlocking( Runnable command ) {
if ( threadPool == null ) {
logger.error( "Thread pool '{}' not initialized.", threadPoolName );
return;
}
ThreadPool threadPoolMonitor = this;
boolean accepted = false;
do {
try {
threadPool.execute( new Runnable() {
#Override
public void run() {
try {
command.run();
}
// to make sure that the monitor is freed on exit
finally {
// Notify all the threads waiting for the resource, if any.
synchronized ( threadPoolMonitor ) {
threadPoolMonitor.notifyAll();
}
}
}
} );
accepted = true;
}
catch ( RejectedExecutionException e ) {
// Thread pool is full
try {
// Block until one of the threads finishes its job and exits.
synchronized ( threadPoolMonitor ) {
threadPoolMonitor.wait();
}
}
catch ( InterruptedException ignored ) {
// return immediately
break;
}
}
} while ( !accepted );
}
threadPool is a local instance of java.util.concurrent.ExecutorService which has been initialized already.

I solved this problem using a custom RejectedExecutionHandler, which simply blocks the calling thread for a little while and then tries to submit the task again:
public class BlockWhenQueueFull implements RejectedExecutionHandler {
public void rejectedExecution(Runnable r, ThreadPoolExecutor executor) {
// The pool is full. Wait, then try again.
try {
long waitMs = 250;
Thread.sleep(waitMs);
} catch (InterruptedException interruptedException) {}
executor.execute(r);
}
}
This class can just be used in the thread-pool executor as a RejectedExecutionHandler like any other. In this example:
executorPool = new def threadPoolExecutor = new ThreadPoolExecutor(3, 3, 1L, TimeUnit.HOURS, workQueue, new BlockWhenQueueFull())
The only downside I see is that the calling thread might get locked slightly longer than strictly necessary (up to 250ms). For many short-running tasks, perhaps decrease the wait-time to 10ms or so. Moreover, since this executor is effectively being called recursively, very long waits for a thread to become available (hours) might result in a stack overflow.
Nevertheless, I personally like this method. It's compact, easy to understand, and works well. Am I missing anything important?

Ok, old thread but this is what I found when searching for blocking thread executor. My code tries to get a semaphore when the task is submitted to the task queue. This blocks if there are no semaphores left. As soon as a task is done the semaphore is released with the decorator. Scary part is that there is a possibility of losing semaphore but that could be solved with for example a timed job that just clears semaphores on a timed basis.
So here my solution:
class BlockingThreadPoolTaskExecutor(concurrency: Int) : ThreadPoolTaskExecutor() {
companion object {
lateinit var semaphore: Semaphore
}
init {
semaphore = Semaphore(concurrency)
val semaphoreTaskDecorator = SemaphoreTaskDecorator()
this.setTaskDecorator(semaphoreTaskDecorator)
}
override fun <T> submit(task: Callable<T>): Future<T> {
log.debug("submit")
semaphore.acquire()
return super.submit(task)
}
}
private class SemaphoreTaskDecorator : TaskDecorator {
override fun decorate(runnable: Runnable): Runnable {
log.debug("decorate")
return Runnable {
try {
runnable.run()
} finally {
log.debug("decorate done")
semaphore.release()
}
}
}
}

One could overwrite ThreadPoolExecutor.execute(command) to use a Semaphore, e.g.:
/**
* The setup answering the question needs to have:
*
* permits = 3
* corePoolSize = permits (i.e. 3)
* maximumPoolSize = corePoolSize (i.e. 3)
* workQueue = anything different to null
*
* With this setup workQueue won’t actually be used but only
* to check if it’s empty, which should always be the case.
* Any more than permits as value for maximumPoolSize will have
* no effect because at any moment no more than permits calls to
* super.execute() will be allowed by the semaphore.
*/
public class ExecutionBlockingThreadPool extends ThreadPoolExecutor {
private final Semaphore semaphore;
// constructor setting super(…) parameters and initializing semaphore
//
// Below is a bare minimum constructor; using
// corePoolSize = maximumPoolSize = permits
// allows one to use SynchronousQueue because I expect
// none other that isEmpty() to be called on it; it also
// allows for using 0L SECONDS because no more than
// corePoolSize threads should be attempted to create.
public ExecutionBlockingThreadPool(int corePoolSize) {
super(corePoolSize, corePoolSize, 0L, SECONDS, new SynchronousQueue<Runnable>());
semaphore = new Semaphore(corePoolSize, true);
}
public void execute(Runnable command) {
semaphore.acquire();
super.execute(() -> {
try {
command.run();
} finally {
semaphore.release();
}
}
}
}

You can imlement RejectedTaskHandler and get all the rejected tasks when Queue size if full. By default executors have the Abort policy so you can add these task back to the queue from handler or whatever the choice is.
public class ExecutorRejectedTaskHandlerFixedThreadPool {
public static void main(String[] args) throws InterruptedException {
//maximum queue size : 2
BlockingQueue<Runnable> blockingQueue =
new LinkedBlockingQueue<Runnable>(2);
CustomThreadPoolExecutor executor =
new CustomThreadPoolExecutor(4, 5, 5, TimeUnit.SECONDS,
blockingQueue);
RejectedTaskHandler rejectedHandler = new RejectedTaskHandler();
executor.setRejectedExecutionHandler(rejectedHandler);
//submit 20 the tasks for execution
//Note: only 7 tasks(5-max pool size + 2-queue size) will be executed and rest will be rejected as queue will be overflowed
for (int i = 0; i < 20; i++) {
executor.execute(new Task());
}
System.out.println("Thread name " + Thread.currentThread().getName());
}
static class Task implements Runnable {
#Override
public void run() {
try {
Thread.sleep(500);
} catch (InterruptedException e) {
e.printStackTrace();
}
System.out.println("Thread - " + Thread.currentThread().getName() + " performing it's job");
}
}
static class RejectedTaskHandler implements RejectedExecutionHandler {
#Override
public void rejectedExecution(Runnable r, ThreadPoolExecutor executor) {
System.out.println("Task rejected" + r.toString());
}
}
public static class CustomThreadPoolExecutor extends ThreadPoolExecutor {
public CustomThreadPoolExecutor(int corePoolSize, int maximumPoolSize,
long keepAliveTime, TimeUnit unit,
BlockingQueue<Runnable> workQueue) {
super(corePoolSize, maximumPoolSize, keepAliveTime, unit, workQueue);
}
#Override
protected void beforeExecute(Thread t, Runnable r) {
super.beforeExecute(t, r);
}
#Override
protected void afterExecute(Runnable r, Throwable t) {
super.afterExecute(r, t);
}
}
}