Develop Reference

Execution of Tasks in ExecutorService without Thread pauses

I have a thread pool with 8 threads
private static final ExecutorService SERVICE = Executors.newFixedThreadPool(8);
My mechanism emulating the work of 100 user (100 Tasks):
List<Callable<Boolean>> callableTasks = new ArrayList<>();
for (int i = 0; i < 100; i++) { // Number of users == 100
callableTasks.add(new Task(client));
}
SERVICE.invokeAll(callableTasks);
SERVICE.shutdown();
The user performs the Task of generating a document.
Get UUID of Task;
Get Task status every 10 seconds;
If Task is ready get document.
public class Task implements Callable<Boolean> {
private final ReportClient client;
public Task(ReportClient client) {
this.client = client;
}
#Override
public Boolean call() {
final var uuid = client.createDocument(documentId);
GetStatusResponse status = null;
do {
try {
Thread.sleep(10000); // This stop current thread, but not a Task!!!!
} catch (InterruptedException e) {
return Boolean.FALSE;
}
status = client.getStatus(uuid);
} while (Status.PENDING.equals(status.status()));
final var document = client.getReport(uuid);
return Boolean.TRUE;
}
}
I want to give the idle time (10 seconds) to another task. But when the command Thread.sleep(10000); is called, the current thread suspends its execution. First 8 Tasks are suspended and 92 Tasks are pending 10 seconds. How can I do 100 Tasks in progress at the same time?

The Answer by Yevgeniy looks correct, regarding Java today. You want to have your cake and eat it too, in that you want a thread to sleep before repeating a task but you also want that thread to do other work. That is not possible today, but may be in the future.
Project Loom
In current Java, a Java thread is mapped directly to a host OS thread. In all common OSes such as macOS, BSD, Linux, Windows, and such, when code executing in a host thread blocks (stops to wait for sleep, or storage I/O, or network I/O, etc.) the thread too blocks. The blocked thread suspends, and the host OS generally runs another thread on that otherwise unused core. But the crucial point is that the suspended thread performs no further work until your blocking call to sleep returns.
This picture may change in the not-so-distant future. Project Loom seeks to add virtual threads to the concurrency facilities in Java.
In this new technology, many Java virtual threads are mapped to each host OS thread. Juggling the many Java virtual threads is managed by the JVM rather than by the OS. When the JVM detects a virtual thread’s executing code is blocking, that virtual thread is "parked", set aside by the JVM, with another virtual thread swapped out for execution on that "real" host OS thread. When the other thread returns from its blocking call, it can be reassigned to a "real" host OS thread for further execution. Under Project Loom, the host OS threads are kept busy, never idled while any pending virtual thread has work to do.
This swapping between virtual threads is highly efficient, so that thousands, even millions, of threads can be running at a time on conventional computer hardware.
Using virtual threads, your code will indeed work as you had hoped: A blocking call in Java will not block the host OS thread. But virtual threads are experimental, still in development, scheduled as a preview feature in Java 19. Early-access builds of Java 19 with Loom technology included are available now for you to try. But for production deployment today, you'll need to follow the advice in the Answer by Yevgeniy.
Take my coverage here with a grain of salt, as I am not an expert on concurrency. You can hear it from the actual experts, in the articles, interviews, and presentations by members of the Project Loom team including Ron Pressler and Alan Bateman.

EDIT: I just posted this answer and realized that you seem to be using that code to emulate real user interactions with some system. I would strongly recommend just using a load testing utility for that, rather than trying to come up with your own. However, in that case just using a CachedThreadPool might do the trick, although probably not a very robust or scalable solution.
Thread.sleep() behavior here is working as intended: it suspends the thread to let the CPU execute other threads.
Note that in this state a thread can be interrupted for a number of reasons unrelated to your code, and in that case your Task returns false: I'm assuming you actually have some retry logic down the line.
So you want two mutually exclusive things: on the one hand, if the document isn't ready, the thread should be free to do something else, but should somehow return and check that document's status again in 10 seconds.
That means you have to choose:
You definitely need that once-every-10-seconds check for each document - in that case, maybe use a cachedThreadPool and have it generate as many threads as necessary, just keep in mind that you'll carry the overhead for numerous threads doing virtually nothing.
Or, you can first initiate that asynchronous document creation process and then only check for status in your callables, retrying as needed.
Something like:
public class Task implements Callable<Boolean> {
private final ReportClient client;
private final UUID uuid;
// all args constructor omitted for brevity
#Override
public Boolean call() {
GetStatusResponse status = client.getStatus(uuid);
if (Status.PENDING.equals(status.status())) {
final var document = client.getReport(uuid);
return Boolean.TRUE;
} else {
return Boolean.FALSE; //retry next time
}
}
}
List<Callable<Boolean>> callableTasks = new ArrayList<>();
for (int i = 0; i < 100; i++) {
var uuid = client.createDocument(documentId); //not sure where documentId comes from here in your code
callableTasks.add(new Task(client, uuid));
}
List<Future<Boolean>> results = SERVICE.invokeAll(callableTasks);
// retry logic until all results come back as `true` here
This assumes that createDocument is relatively efficient, but that stage can be parallelized just as well, you just need to use a separate list of Runnable tasks and invoke them using the executor service.
Note that we also assume that the document's status will indeed eventually change to something other than PENDING, and that might very well not be the case. You might want to have a timeout for retries.

In your case, it seems like you need to check if a certain condition is met every x seconds. In fact, from your code the document generation seems asynchronous and what the Task keeps doing after that is just is waiting for the document generation to happen.
You could launch every document generation from your Thread-Main and use a ScheduledThreadPoolExecutor to verify every x seconds whether the document generation has been completed. At that point, you retrieve the result and cancel the corresponding Task's scheduling.
Basically, one ConcurrentHashMap is shared among the thread-main and the Tasks you've scheduled (mapRes), while the other, mapTask, is just used locally within the thread-main to keep track of the ScheduledFuture returned by every Task.
public class Main {
public static void main(String[] args) {
ScheduledThreadPoolExecutor pool = (ScheduledThreadPoolExecutor) Executors.newScheduledThreadPool(8);
//ConcurrentHashMap shared among the submitted tasks where each Task updates its corresponding outcome to true as soon as the document has been produced
ConcurrentHashMap<Integer, Boolean> mapRes = new ConcurrentHashMap<>();
for (int i = 0; i < 100; i++) {
mapRes.put(i, false);
}
String uuid;
ScheduledFuture<?> schedFut;
//HashMap containing the ScheduledFuture returned by scheduling each Task to cancel their repetition as soon as the document has been produced
Map<String, ScheduledFuture<?>> mapTask = new HashMap<>();
for (int i = 0; i < 100; i++) {
//Starting the document generation from the thread-main
uuid = client.createDocument(documentId);
//Scheduling each Task 10 seconds apart from one another and with an initial delay of i*10 to not start all of them at the same time
schedFut = pool.scheduleWithFixedDelay(new Task(client, uuid, mapRes), i * 10, 10000, TimeUnit.MILLISECONDS);
//Adding the ScheduledFuture to the map
mapTask.put(uuid, schedFut);
}
//Keep checking the outcome of each task until all of them have been canceled due to completion
while (!mapTasks.values().stream().allMatch(v -> v.isCancelled())) {
for (Integer key : mapTasks.keySet()) {
//Canceling the i-th task scheduling if:
// - Its result is positive (i.e. its verification is terminated)
// - The task hasn't been canceled already
if (mapRes.get(key) && !mapTasks.get(key).isCancelled()) {
schedFut = mapTasks.get(key);
schedFut.cancel(true);
}
}
//... eventually adding a sleep to check the completion every x seconds ...
}
pool.shutdown();
}
}
class Task implements Runnable {
private final ReportClient client;
private final String uuid;
private final ConcurrentHashMap mapRes;
public Task(ReportClient client, String uuid, ConcurrentHashMap mapRes) {
this.client = client;
this.uuid = uuid;
this.mapRes = mapRes;
}
#Override
public void run() {
//This is taken form your code and I'm assuming that if it's not pending then it's completed
if (!Status.PENDING.equals(client.getStatus(uuid).status())) {
mapRes.replace(uuid, true);
}
}
}
I've tested your case locally, by emulating a scenario where n Tasks wait for a folder with their same id to be created (or uuid in your case). I'll post it right here as a sample in case you'd like to try something simpler first.
public class Main {
public static void main(String[] args) {
ScheduledThreadPoolExecutor pool = (ScheduledThreadPoolExecutor) Executors.newScheduledThreadPool(2);
ConcurrentHashMap<Integer, Boolean> mapRes = new ConcurrentHashMap<>();
for (int i = 0; i < 16; i++) {
mapRes.put(i, false);
}
ScheduledFuture<?> schedFut;
Map<Integer, ScheduledFuture<?>> mapTasks = new HashMap<>();
for (int i = 0; i < 16; i++) {
schedFut = pool.scheduleWithFixedDelay(new MyTask(i, mapRes), i * 20, 3000, TimeUnit.MILLISECONDS);
mapTasks.put(i, schedFut);
}
while (!mapTasks.values().stream().allMatch(v -> v.isCancelled())) {
for (Integer key : mapTasks.keySet()) {
if (mapRes.get(key) && !mapTasks.get(key).isCancelled()) {
schedFut = mapTasks.get(key);
schedFut.cancel(true);
}
}
}
pool.shutdown();
}
}
class MyTask implements Runnable {
private int num;
private ConcurrentHashMap mapRes;
public MyTask(int num, ConcurrentHashMap mapRes) {
this.num = num;
this.mapRes = mapRes;
}
#Override
public void run() {
System.out.println("Task " + num + " is checking whether the folder exists: " + Files.exists(Path.of("./" + num)));
if (Files.exists(Path.of("./" + num))) {
mapRes.replace(num, true);
}
}
}

Understanding Parallel Execution of chained CompletableFutures

I have a question about how Java Streams and chained CompletableFutures perform.
My question is this: if I run the following code, calling execute() with 10 items in the list takes ~11 seconds to complete (number of items in the list plus 1). This is because I have two threads working in parallel: the first executes the digItUp operation, and once that's complete, the second executes the fillItBackIn operation, and the first starts processing digItUp on the next item in the list.
If I comment out line 36 (.collect(Collectors.toList())), the execute() method takes ~20 seconds to complete. The threads do not operate in parallel; for each item in the list, the digItUp operation completes, and then the fillItBackIn operation completes in sequence before the next item in the list is processed.
It's unclear to me why the exclusion of (.collect(Collectors.toList())) should change this behavior. Can someone explain?
The complete class:
package com.test;
import java.util.ArrayList;
import java.util.List;
import java.util.Random;
import java.util.concurrent.CompletableFuture;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.stream.Collectors;
public class SimpleExample {
private final ExecutorService diggingThreadPool = Executors.newFixedThreadPool(1);
private final ExecutorService fillingThreadPool = Executors.newFixedThreadPool(1);
public SimpleExample() {
}
public static void main(String[] args) {
List<Double> holesToDig = new ArrayList<>();
Random random = new Random();
for (int c = 0; c < 10; c++) {
holesToDig.add(random.nextDouble(1000));
}
new SimpleExample().execute(holesToDig);
}
public void execute(List<Double> holeVolumes) {
long start = System.currentTimeMillis();
holeVolumes.stream()
.map(volume -> {
CompletableFuture<Double> digItUpCF = CompletableFuture.supplyAsync(() -> digItUp(volume), diggingThreadPool);
return digItUpCF.thenApplyAsync(volumeDugUp -> fillItBackIn(volumeDugUp), fillingThreadPool);
})
.collect(Collectors.toList())
.forEach(cf -> {
Double volume = cf.join();
System.out.println("Dug a hole and filled it back in. Net volume: " + volume);
});
System.out.println("Dug up and filled back in " + holeVolumes.size() + " holes in " + (System.currentTimeMillis() - start) + " ms");
}
public Double digItUp(Double volume) {
try {
Thread.sleep(1000);
} catch (InterruptedException e) {
}
System.out.println("Dug hole with volume " + volume);
return volume;
}
public Double fillItBackIn(Double volumeDugUp) {
try {
Thread.sleep(1000);
} catch (InterruptedException e) {
}
System.out.println("Filled back in hole of volume " + volumeDugUp);
return 0.0;
}
}

The reason is that collect(Collectors.toList()) is a terminal operation, hence it triggers the stream pipeline (remember that streams are evaluated lazily). So when you call collect, all of the CompletableFuture instances are constructed and placed in the list. This means that there is a chain of CompletableFuture, where each one is in turn a chain composed of two stages, let's call them X and Y.
Every time the first thread executor finishes an X stage, it is free to process the X stage of the next composed CompletableFuture, while the other thread executor is processing stage Y of the previous CompletableFuture. This is the result that we intuitively expect.
On the other hand, when you don't call collect, then forEach is in this case the terminal operation. However, in this case every element in the stream is processed sequentially (to confirm try switching to parallelStream()), hence stages X and Y get executed for the first CompletableFuture. Only when stage Y from the previous stream element is finished, will forEach move to the second element in the stream pipeline, and only then will a new CompletableFuture be mapped from the original Double value.

Love this question and M A's answer is awesome! I had a similar use case, and I was using Rxjava there. It worked very well, but my colleagues challenged me to implement it without that. T.T
I tested your example and found a workaround to make it the same performance without collect. The trick is to let the cf.join() be executed in another thread.
.forEach(cf -> CompletableFuture.supplyAsync(cf::join, anotherThreadpool)
// another threadpool for the join, or you can omit it, using the default forkjoinpool.commonpool
.thenAccept(v -> System.out.println("Dug a hole and filled it back in. Net volume: " + v))
);
But I have to say, this might lead to potential issues as it lacks the support for backpressure...if the upstream is infinite and fast, but the consumer is too slow, all the fast-created CompletableFuture in the map operator would be accumulated and submitted to the first diggingThreadPool, finally causing RejectedExecutionException, OOM, etc.

Creating 2 threads and each running different tasks

I want to create two threads in my application that'll run two methods. I'm using the builder design pattern where inside the build method I have something like this, request is the Object that is passed:
Rules rule;
Request build() {
Request request = new Request(this);
//I want one threat to call this method
Boolean isExceeding = this.rule.volumeExceeding(request);
//Another thread to call this method
Boolean isRepeating = this.rule.volumeRepeating(request);
//Some sort of timer that will wait until both values are received,
//If one value takes too long to be received kill the thread and continue with
//whatever value was received.
..Logic based on 2 booleans..
return request;
}
Here's how this class looks like:
public class Rules {
public Boolean volumeExceeding(Request request) {
...some...logic...
return true/false;
}
public Boolean volumeRepeating(Request request) {
...some...logic...
return true/false;
}
}
I have commented in the code what I'd like to happen. Basically, I'd like to create two threads that'll run their respective method. It'll wait until both are finished, however, if one takes too long (example: more than 10ms) then return the value that was completed. How do I create this? I'm trying to understand the multithreading tutorials, but the examples are so generic that it's hard to take what they did and apply it to something more complicated.

One way to do that is to use CompletableFutures:
import java.util.concurrent.CompletableFuture;
class Main {
private static final long timeout = 1_000; // 1 second
static Boolean volumeExceeding(Object request) {
System.out.println(Thread.currentThread().getName());
final long startpoint = System.currentTimeMillis();
// do stuff with request but we do dummy stuff
for (int i = 0; i < 1_000_000; i++) {
if (System.currentTimeMillis() - startpoint > timeout) {
return false;
}
Math.log(Math.sqrt(i));
}
return true;
}
static Boolean volumeRepeating(Object request) {
System.out.println(Thread.currentThread().getName());
final long startpoint = System.currentTimeMillis();
// do stuff with request but we do dummy stuff
for (int i = 0; i < 1_000_000_000; i++) {
if (System.currentTimeMillis() - startpoint > timeout) {
return false;
}
Math.log(Math.sqrt(i));
}
return true;
}
public static void main(String[] args) {
final Object request = new Object();
CompletableFuture<Boolean> isExceedingFuture = CompletableFuture.supplyAsync(
() -> Main.volumeExceeding(request));
CompletableFuture<Boolean> isRepeatingFuture = CompletableFuture.supplyAsync(
() -> Main.volumeRepeating(request));
Boolean isExceeding = isExceedingFuture.join();
Boolean isRepeating = isRepeatingFuture.join();
System.out.println(isExceeding);
System.out.println(isRepeating);
}
}
Notice that one task takes significantly longer than the other.
What's happening? You supply those tasks to the common pool by using CompletableFuture for execution. Both tasks are executed by two different threads. What you've asked for is that a task is stopped when it takes too long. Therefore you can simply remember the time when a task has started and periodically check it against a timeout. Important: Do this check when the task would return while leaving the data in a consistent state. Also note that you can place multiple checks of course.
Here's a nice guide about CompletableFuture: Guide To CompletableFuture

If I understand your question correctly, then you should do this with a ticketing system (also known as provider-consumer pattern or producer-consumer pattern), so your threads are reused (which is a significant performance boost, if those operations are time critical).
The general idea should be:
application initialization
Initialize 2 or more "consumer" threads, which can work tickets (also called jobs).
runtime
Feed the consumer threads tickets (or jobs) that will be waited on for (about) as long as you like. However depending on the JVM, the waiting period will most likely not be exactly n milliseconds, as most often schedulers are more 'lax' in regards to waiting periods for timeouts. e.g. Thread.sleep() will almost always be off by a bunch of milliseconds (always late, never early - to my knowledge).
If the thread does not return after a given waiting period, then that result must be neglected (according to your logic), and the ticket (and thus the thread) must be informed to abort that ticket. It is important that you not interrupt the thread, since that can lead to exceptions, or prevent locks from being unlocked.
Remember, that halting or stopping threads from the outside is almost always problematic with locks, so I would suggest, your jobs visit a possible exit point periodically, so if you stop caring about a result, they can be safely terminated.

Parallel Processing of DTO in Java 7

I have requirement where need to process and map the DTOs with the values in for loop as below. Each of the mapping method here consumes nearly 10 minutes to complete its business logic and hence creating performance delay. I am working to refine the algorithms of business logic. However, please let me know if each of these mapping methods can be parallel processed to increase performance.
Since application is compatible only with Java 7 I cannot use streams of java 8.
for(Portfolio pf : portfolio) {
mapAddress(pf);
mapBusinessUnit(pf);
mapRelationShipDetails(pf)
--
--
--
}

You could split portfolios to different threads using either Runnable or Callable.
For example:
public class PortfolioService implements Callable<List<Portfolio>>
{
List<Portfolio> portfolios;
public PortfolioService(List<Portfolio> portfolios)
{
this.portfolios = portfolios;
}
public List<Portfolio> call()
{
for(Portfolio pf : portfolios) {
mapAddress(pf);
mapBusinessUnit(pf);
...
}
return portfolios;
}
}
However, this needs some modifications in your main class. I am using Callable here, since I don't know if you want to do something with all of these mapped Portfolios afterwards. However, if you want to let the threads do all of the work and don't need any return, use Runnable and modify the code.
1) You have to get your amount of cores:
int threads = Runtime.getRuntime().availableProcessors();
2) Now you split the workload per thread
// determine the average workload per thread
int blocksize = portfolios.size()/threads;
// doesn't always get all entries
int overlap = portfolios.size()%threads;
3) Start an ExecutorService, make a list of Future Elements, make reminder variable for old index of array slice
ExecutorService exs = Executors.newFixedThreadPool(threads);
List<Future<List<Portfoilio>>> futures = new ArrayList();
int oldIndex = 0;
4) Start threads
for(int i = 0; i<threads; i++)
{
int actualBlocksize = blocksize;
if(overlap != 0){
actualBlocksize++;
overlap--;
}
futures.add(exs.submit(new PortfolioService(portfolios.subList(oldIndex,actualBlocksize));
oldIndex = actualBlocksize;
}
5) Shutdown the ExecutorService and await it's termination
exs.shutdown();
try {exs.awaitTermination(6, TimeUnit.HOURS);}
catch (InterruptedException e) { }
6) do something with the future, if you want / have to.

Learning about Threads

I have written a simple program, that is intended to start a few threads. The threads should then pick a integer n from an integer array, use it to wait n and return the time t the thread waited back into an array for the results.
If one thread finishes it's task, it should pick the next one, that has not yet being assigned to another thread.
Of course: The order in the arrays has to be maintained, so that integers and results match.
My code runs smoothly as far I see.
However I use one line of code block I find in particular unsatisfying and hope there is a good way to fix this without changing too much:
while(Thread.activeCount() != 1); // first evil line
I kinda abuse this line to make sure all my threads finish getting all the tasks done, before I access my array with the results. I want to do that to prevent ill values, like 0.0, Null Pointer Exception... etc. (in short anything that would make an application with an actual use crash)
Any sort of constructive help is appreciated. I am also not sure, if my code still runs smoothly for very very long arrays of tasks for the threads, for example the results no longer match the order of the integer.
Any constructive help is appreciated.
First class:
public class ThreadArrayWriterTest {
int[] repitions;
int len = 0;
double[] timeConsumed;
public boolean finished() {
synchronized (repitions) {
return len <= 0;
}
}
public ThreadArrayWriterTest(int[] repitions) {
this.repitions = repitions;
this.len = repitions.length;
timeConsumed = new double[this.len];
}
public double[] returnTimes(int[] repititions, int numOfThreads, TimeConsumer timeConsumer) {
for (int i = 0; i < numOfThreads; i++) {
new Thread() {
public void run() {
while (!finished()) {
len--;
timeConsumed[len] = timeConsumer.returnTimeConsumed(repititions[len]);
}
}
}.start();
}
while (Thread.activeCount() != 1) // first evil line
;
return timeConsumed;
}
public static void main(String[] args) {
long begin = System.currentTimeMillis();
int[] repitions = { 3, 1, 3, 1, 2, 1, 3, 3, 3 };
int numberOfThreads = 10;
ThreadArrayWriterTest t = new ThreadArrayWriterTest(repitions);
double[] times = t.returnTimes(repitions, numberOfThreads, new TimeConsumer());
for (double d : times) {
System.out.println(d);
}
long end = System.currentTimeMillis();
System.out.println("Total time of execution: " + (end - begin));
}
}
Second class:
public class TimeConsumer {
double returnTimeConsumed(int repitions) {
long before = System.currentTimeMillis();
for (int i = 0; i < repitions; i++) {
try {
Thread.sleep(1000);
} catch (InterruptedException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
}
long after = System.currentTimeMillis();
double ret = after - before;
System.out.println("It takes: " + ret + "ms" + " for " + repitions + " runs through the for-loop");
return ret;
}
}

The easiest way to wait for all threads to complete is to keep a Collection of them and then call Thread.join() on each one in turn.

In addition to .join() you can use ExecutorService to manage pools of threads,
An Executor that provides methods to manage termination and methods
that can produce a Future for tracking progress of one or more
asynchronous tasks.
An ExecutorService can be shut down, which will cause it to reject new
tasks. Two different methods are provided for shutting down an
ExecutorService. The shutdown() method will allow previously submitted
tasks to execute before terminating, while the shutdownNow() method
prevents waiting tasks from starting and attempts to stop currently
executing tasks. Upon termination, an executor has no tasks actively
executing, no tasks awaiting execution, and no new tasks can be
submitted. An unused ExecutorService should be shut down to allow
reclamation of its resources.
Method submit extends base method Executor.execute(Runnable) by
creating and returning a Future that can be used to cancel execution
and/or wait for completion. Methods invokeAny and invokeAll perform
the most commonly useful forms of bulk execution, executing a
collection of tasks and then waiting for at least one, or all, to
complete.
ExecutorService executorService = Executors.newFixedThreadPool(maximumNumberOfThreads);
CompletionService completionService = new ExecutorCompletionService(executorService);
for (int i = 0; i < numberOfTasks; ++i) {
completionService.take();
}
executorService.shutdown();
Plus take a look at ThreadPoolExecutor

Since java provides more advanced threading API with concurrent package, You should have look into ExecutorService, which simplifies thread management mechanism.
Simple to solution to your problem.
Use Executors API to create thread pool
static ExecutorService newFixedThreadPool(int nThreads)
Creates a thread pool that reuses a fixed number of threads operating off a shared unbounded queue.
Use invokeAll to wait for all tasks to complete.
Sample code:
ExecutorService service = Executors.newFixedThreadPool(10);
List<MyCallable> futureList = new ArrayList<MyCallable>();
for ( int i=0; i<12; i++){
MyCallable myCallable = new MyCallable((long)i);
futureList.add(myCallable);
}
System.out.println("Start");
try{
List<Future<Long>> futures = service.invokeAll(futureList);
for(Future<Long> future : futures){
try{
System.out.println("future.isDone = " + future.isDone());
System.out.println("future: call ="+future.get());
}
catch(Exception err1){
err1.printStackTrace();
}
}
}catch(Exception err){
err.printStackTrace();
}
service.shutdown();
Refer to this related SE question for more details on achieving the same:
wait until all threads finish their work in java