I'm new to both lambdas and asynchronous code in Java 8. I keep getting some weird results...
I have the following code:
import java.util.concurrent.CompletableFuture;
public class Program {
public static void main(String[] args) {
for (int i = 0; i < 100; i++) {
String test = "Test_" + i;
final int a = i;
CompletableFuture<Boolean> cf = CompletableFuture.supplyAsync(() -> doPost(test));
cf.thenRun(() -> System.out.println(a)) ;
}
}
private static boolean doPost(String t) {
System.out.println(t);
return true;
}
}
The actual code is a lot longer, as the doPost method will post some data to a web service. However, I'm able to replicate my issue with this bare-bones code.
I want to have the doPost method execute 100 times, but asynchronously for performance reasons (in order to push data to the web service faster than doing 100 synchronous calls would be).
In the code above, the ´doPost´ method is run a random amount of times, but always no more than 20-25 times. There are no exceptions thrown. It seems that either some thread handling mechanism is silently refusing to create new threads and execute their code, or the threads are silently crashing without crashing the program.
I also have an issue where, if I add more functionality to the doPost method than shown above, it reaches a point where the method simply silently breaks. I've tried adding a System.out.println("test") right before the return statement in that case, but it is never called. The loop which loops 100 times does run 100 iterations though.
This behaviour is confusing, to say the least.
What am I missing? Why is the function supplied as an argument to supplyAsync run a seemingly random number of times?
EDIT: Just wanted to point out that the situation is not exactly the same as in the question this was marked as a possible duplicate of, as that question dealt with arbitrarily deeply nested futures, and this one deals with parallell ones. However, the reason why they are failing is virtually identical. The cases seem distinct enough to merit separate questions to me, but others might disagree...
By default CompletableFuture uses own ForkJoinPool.commonPool() (see CompletableFuture implementation). And this default pool creates only daemon threads, e.g. they won't block the main application from terminating if they still alive.
You have the following choices:
Collect all CompletionStage to some array and then make java.util.concurrent.CompletableFuture#allOf().toCompletableFuture().join() - this will guarantee all the stages are completed before going after join()
Use *Async operations with your own thread pool which contains only non-daemon threads, like in the following example:
public static void main(String[] args) throws InterruptedException {
ExecutorService pool = Executors.newFixedThreadPool(10, r -> {
Thread t = new Thread(r);
t.setDaemon(false); // must be not daemon
return t;
});
for (int i = 0; i < 100; i++) {
final int a = i;
// the operation must be Async with our thread pool
CompletableFuture<Boolean> cf = CompletableFuture.supplyAsync(() -> doPost(a), pool);
cf.thenRun(() -> System.out.printf("%s: Run_%s%n", Thread.currentThread().getName(), a));
}
pool.shutdown(); // without this the main application will be blocked forever
}
private static boolean doPost(int t) {
System.out.printf("%s: Post_%s%n", Thread.currentThread().getName(), t);
return true;
}
Related
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);
}
}
}
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.
This is a java concurrency question. 10 jobs need to be done, each of them will have 32 worker threads. Worker thread will increase a counter . Once the counter is 32, it means this job is done and then clean up counter map. From the console output, I expect that 10 "done" will be output, pool size is 0 and counterThread size is 0.
The issues are :
most of time, "pool size: 0 and countThreadMap size:3" will be
printed out. even those all threads are gone, but 3 jobs are not
finished yet.
some time, I can see nullpointerexception in line 27. I have used ConcurrentHashMap and AtomicLong, why still have concurrency
exception.
Thanks
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.ThreadPoolExecutor;
import java.util.concurrent.atomic.AtomicLong;
public class Test {
final ConcurrentHashMap<Long, AtomicLong[]> countThreadMap = new ConcurrentHashMap<Long, AtomicLong[]>();
final ExecutorService cachedThreadPool = Executors.newCachedThreadPool();
final ThreadPoolExecutor tPoolExecutor = ((ThreadPoolExecutor) cachedThreadPool);
public void doJob(final Long batchIterationTime) {
for (int i = 0; i < 32; i++) {
Thread workerThread = new Thread(new Runnable() {
#Override
public void run() {
if (countThreadMap.get(batchIterationTime) == null) {
AtomicLong[] atomicThreadCountArr = new AtomicLong[2];
atomicThreadCountArr[0] = new AtomicLong(1);
atomicThreadCountArr[1] = new AtomicLong(System.currentTimeMillis()); //start up time
countThreadMap.put(batchIterationTime, atomicThreadCountArr);
} else {
AtomicLong[] atomicThreadCountArr = countThreadMap.get(batchIterationTime);
atomicThreadCountArr[0].getAndAdd(1);
countThreadMap.put(batchIterationTime, atomicThreadCountArr);
}
if (countThreadMap.get(batchIterationTime)[0].get() == 32) {
System.out.println("done");
countThreadMap.remove(batchIterationTime);
}
}
});
tPoolExecutor.execute(workerThread);
}
}
public void report(){
while(tPoolExecutor.getActiveCount() != 0){
//
}
System.out.println("pool size: "+ tPoolExecutor.getActiveCount() + " and countThreadMap size:"+countThreadMap.size());
}
public static void main(String[] args) throws Exception {
Test test = new Test();
for (int i = 0; i < 10; i++) {
Long batchIterationTime = System.currentTimeMillis();
test.doJob(batchIterationTime);
}
test.report();
System.out.println("All Jobs are done");
}
}
Let’s dig through all the mistakes of thread related programming, one man can make:
Thread workerThread = new Thread(new Runnable() {
…
tPoolExecutor.execute(workerThread);
You create a Thread but don’t start it but submit it to an executor. It’s a historical mistake of the Java API to let Thread implement Runnable for no good reason. Now, every developer should be aware, that there is no reason to treat a Thread as a Runnable. If you don’t want to start a thread manually, don’t create a Thread. Just create the Runnable and pass it to execute or submit.
I want to emphasize the latter as it returns a Future which gives you for free what you are attempting to implement: the information when a task has been finished. It’s even easier when using invokeAll which will submit a bunch of Callables and return when all are done. Since you didn’t tell us anything about your actual task, it’s not clear whether you can let your tasks simply implement Callable (may return null) instead of Runnable.
If you can’t use Callables or don’t want to wait immediately on submission, you have to remember the returned Futures and query them at a later time:
static final ExecutorService cachedThreadPool = Executors.newCachedThreadPool();
public static List<Future<?>> doJob(final Long batchIterationTime) {
final Random r=new Random();
List<Future<?>> list=new ArrayList<>(32);
for (int i = 0; i < 32; i++) {
Runnable job=new Runnable() {
public void run() {
// pretend to do something
LockSupport.parkNanos(TimeUnit.SECONDS.toNanos(r.nextInt(10)));
}
};
list.add(cachedThreadPool.submit(job));
}
return list;
}
public static void main(String[] args) throws Exception {
Test test = new Test();
Map<Long,List<Future<?>>> map=new HashMap<>();
for (int i = 0; i < 10; i++) {
Long batchIterationTime = System.currentTimeMillis();
while(map.containsKey(batchIterationTime))
batchIterationTime++;
map.put(batchIterationTime,doJob(batchIterationTime));
}
// print some statistics, if you really need
int overAllDone=0, overallPending=0;
for(Map.Entry<Long,List<Future<?>>> e: map.entrySet()) {
int done=0, pending=0;
for(Future<?> f: e.getValue()) {
if(f.isDone()) done++;
else pending++;
}
System.out.println(e.getKey()+"\t"+done+" done, "+pending+" pending");
overAllDone+=done;
overallPending+=pending;
}
System.out.println("Total\t"+overAllDone+" done, "+overallPending+" pending");
// wait for the completion of all jobs
for(List<Future<?>> l: map.values())
for(Future<?> f: l)
f.get();
System.out.println("All Jobs are done");
}
But note that if you don’t need the ExecutorService for subsequent tasks, it’s much easier to wait for all jobs to complete:
cachedThreadPool.shutdown();
cachedThreadPool.awaitTermination(Long.MAX_VALUE, TimeUnit.DAYS);
System.out.println("All Jobs are done");
But regardless of how unnecessary the manual tracking of the job status is, let’s delve into your attempt, so you may avoid the mistakes in the future:
if (countThreadMap.get(batchIterationTime) == null) {
The ConcurrentMap is thread safe, but this does not turn your concurrent code into sequential one (that would render multi-threading useless). The above line might be processed by up to all 32 threads at the same time, all finding that the key does not exist yet so possibly more than one thread will then be going to put the initial value into the map.
AtomicLong[] atomicThreadCountArr = new AtomicLong[2];
atomicThreadCountArr[0] = new AtomicLong(1);
atomicThreadCountArr[1] = new AtomicLong(System.currentTimeMillis());
countThreadMap.put(batchIterationTime, atomicThreadCountArr);
That’s why this is called the “check-then-act” anti-pattern. If more than one thread is going to process that code, they all will put their new value, being confident that this was the right thing as they have checked the initial condition before acting but for all but one thread the condition has changed when acting and they are overwriting the value of a previous put operation.
} else {
AtomicLong[] atomicThreadCountArr = countThreadMap.get(batchIterationTime);
atomicThreadCountArr[0].getAndAdd(1);
countThreadMap.put(batchIterationTime, atomicThreadCountArr);
Since you are modifying the AtomicInteger which is already stored into the map, the put operation is useless, it will put the very array that it retrieved before. If there wasn’t the mistake that there can be multiple initial values as described above, the put operation had no effect.
}
if (countThreadMap.get(batchIterationTime)[0].get() == 32) {
Again, the use of a ConcurrentMap doesn’t turn the multi-threaded code into sequential code. While it is clear that the only last thread will update the atomic integer to 32 (when the initial race condition doesn’t materialize), it is not guaranteed that all other threads have already passed this if statement. Therefore more than one, up to all threads can still be at this point of execution and see the value of 32. Or…
System.out.println("done");
countThreadMap.remove(batchIterationTime);
One of the threads which have seen the 32 value might execute this remove operation. At this point, there might be still threads not having executed the above if statement, now not seeing the value 32 but producing a NullPointerException as the array supposed to contain the AtomicInteger is not in the map anymore. This is what happens, occasionally…
After creating your 10 jobs, your main thread is still running - it doesn't wait for your jobs to complete before it calls report on the test. You try to overcome this with the while loop, but tPoolExecutor.getActiveCount() is potentially coming out as 0 before the workerThread is executed, and then the countThreadMap.size() is happening after the threads were added to your HashMap.
There are a number of ways to fix this - but I will let another answer-er do that because I have to leave at the moment.
So I have a method that starts five threads. I want to write a unit test just to check that the five threads have been started. How do I do that? Sample codes are much appreciated.
Instead of writing your own method to start threads, why not use an Executor, which can be injected into your class? Then you can easily test it by passing in a dummy Executor.
Edit: Here's a simple example of how your code could be structured:
public class ResultCalculator {
private final ExecutorService pool;
private final List<Future<Integer>> pendingResults;
public ResultCalculator(ExecutorService pool) {
this.pool = pool;
this.pendingResults = new ArrayList<Future<Integer>>();
}
public void startComputation() {
for (int i = 0; i < 5; i++) {
Future<Integer> future = pool.submit(new Robot(i));
pendingResults.add(future);
}
}
public int getFinalResult() throws ExecutionException {
int total = 0;
for (Future<Integer> robotResult : pendingResults) {
total += robotResult.get();
}
return total;
}
}
public class Robot implements Callable<Integer> {
private final int input;
public Robot(int input) {
this.input = input;
}
#Override
public Integer call() {
// Some very long calculation
Thread.sleep(10000);
return input * input;
}
}
And here's how you'd call it from your main():
public static void main(String args) throws Exception {
// Note that the number of threads is now specified here
ExecutorService pool = Executors.newFixedThreadPool(5);
ResultCalculator calc = new ResultCalculator(pool);
try {
calc.startComputation();
// Maybe do something while we're waiting
System.out.printf("Result is: %d\n", calc.getFinalResult());
} finally {
pool.shutdownNow();
}
}
And here's how you'd test it (assuming JUnit 4 and Mockito):
#Test
#SuppressWarnings("unchecked")
public void testStartComputationAddsRobotsToQueue() {
ExecutorService pool = mock(ExecutorService.class);
Future<Integer> future = mock(Future.class);
when(pool.submit(any(Callable.class)).thenReturn(future);
ResultCalculator calc = new ResultCalculator(pool);
calc.startComputation();
verify(pool, times(5)).submit(any(Callable.class));
}
Note that all this code is just a sketch which I have not tested or even tried to compile yet. But it should give you an idea of how the code can be structured.
Rather than saying you are going to "test the five threads have been started", it would be better to step back and think about what the five threads are actually supposed to do. Then test to make sure that that "something" is actually being done.
If you really just want to test that the threads have been started, there are a few things you could do. Are you keeping references to the threads somewhere? If so, you could retrieve the references, count them, and call isAlive() on each one (checking that it returns true).
I believe there is some method on some Java platform class which you can call to find how many threads are running, or to find all the threads which are running in a ThreadGroup, but you would have to search to find out what it is.
More thoughts in response to your comment
If your code is as simple as new Thread(runnable).start(), I wouldn't bother to test that the threads are actually starting. If you do so, you're basically just testing that the Java platform works (it does). If your code for initializing and starting the threads is more complicated, I would stub out the thread.start() part and make sure that the stub is called the desired number of times, with the correct arguments, etc.
Regardless of what you do about that, I would definitely test that the task is completed correctly when running in multithreaded mode. From personal experience, I can tell you that as soon as you start doing anything remotely complicated with threads, it is devilishly easy to get subtle bugs which only show up under certain conditions, and perhaps only occasionally. Dealing with the complexity of multithreaded code is a very slippery slope.
Because of that, if you can do it, I would highly recommend you do more than just simple unit testing. Do stress tests where you run your task with many threads, on a multicore machine, on very large data sets, and make sure all the answers are exactly as expected.
Also, although you are expecting a performance increase from using threads, I highly recommend that you benchmark your program with varying numbers of threads, to make sure that the desired performance increase is actually achieved. Depending on how your system is designed, it's possible to wind up with concurrency bottlenecks which may make your program hardly faster with threads than without. In some cases, it can even be slower!
I submitted 5 jobs to an ExecutorCompletionService, but it seems like the jobs are executed in sequence. The ExecutorService that is passed to the constructor of ExecutorCompletionService is created using newCacheThreadPool form. Am I doing anything wrong ?
UPDATE Each job is basically doing a database query & some calculation. The code for the ExecutorCompletionService is lifted as-is off the javadoc. I just replaced the Callables with my own custom Callable implementations.
The ExecutorCompletionService has nothing to do with how jobs are executed, it's simply a convenient way of retrieving the results.
Executors.newCachedThreadPool by default executes tasks in separate threads, which can be parallel, given that:
tasks are independent, and don't e.g. synchronize on the same object inside;
you have multiple hardware CPU threads.
The last point deserves an explanation. Although there are no guarantees, in practice the Sun JVM favours the currently executing thread so it's never swapped out in favour of another one. That means that your 5 tasks might end up being executed serially due to the JVM implementation and not having e.g. a multi-core machine.
I assume you meant Executors.newCachedThreadPool(). If so, execution should be parallelized as you expect.
Each job is basically doing a database query & some calculation. The code for the ExecutorCompletionService is lifted as-is off the javadoc. I just replaced the Callables with my own custom Callable implementations.
In that case, are you sure you're not mistaken in thinking they're executed sequentially because you're retrieving the results sequentially?
Throw in some debug logging lines in your callables to rule this out, and/or have a look at this limited usage scenario:
public static void main(String... args) throws InterruptedException, ExecutionException {
List<Callable<String>> list = new ArrayList<Callable<String>>();
list.add(new PowersOfX(2));
list.add(new PowersOfX(3));
list.add(new PowersOfX(5));
solve(Executors.newCachedThreadPool(), list);
}
static void solve(Executor e, Collection<Callable<String>> solvers) throws InterruptedException, ExecutionException {
CompletionService<String> ecs = new ExecutorCompletionService<String>(e);
for (Callable<String> s : solvers)
ecs.submit(s);
int n = solvers.size();
for (int i = 0; i < n; ++i) {
String r = ecs.take().get();
if (r != null)
System.out.println("Retrieved: " + r);
}
}
static class PowersOfX implements Callable<String> {
int x;
public PowersOfX(int x) {this.x = x;}
#Override
public String call() throws Exception {
StringBuilder sb = new StringBuilder();
for (int i = 0; i < 10; i++) {
sb.append(Math.pow(2, i)).append('\t');
System.out.println(Math.pow(x, i));
Thread.sleep(2000);
}
return sb.toString();
}
}
Executing this you'll see the numbers are generated intermixed (and thus executed concurrently), but retrieving the results alone wont show you this level detail..
The execution will depend on a number of things. For example:
the length of time it takes to complete a job
the number of threads in the thread pool (a cached thread pool will only create threads if it thinks they are needed)
Executing in sequence is not necessarily wrong.