Please read the question carefully before marking this as duplicate.
Below is the snippet of the pseudo code. My question is- Does the below code not defeat the very notion of parallel asynchronous processing?
The reason I ask this is because in the below code the main thread would submit a task to be executed in a different thread. After submitting the task in the queue, it blocks on Future.get() method for the task to return the value. I would rather have the task executed in the main thread rather than submitting to a different thread and waiting for the results. What is that I gained by executing the task in a new thread?
I am aware that you could wait for a limited time etc, but then what if I really care about the result? The problem gets worse if there are multiple tasks to be executed. It seems to me that we are just doing the work synchronously. I am aware of the Guava library which provides a non blocking listener interface. But I am interested to know if my understanding is correct for the Future.get() API. If it is correct, why is the Future.get() designed to block thereby defeating the whole process of parallel processing?
Note - For the record, I use JAVA 6
public static void main(String[] args){
private ExectorService executorService = ...
Future future = executorService.submit(new Callable(){
public Object call() throws Exception {
System.out.println("Asynchronous Callable");
return "Callable Result";
}
});
System.out.println("future.get() = " + future.get());
}
A Future interface provides methods to check if the computation is complete, to wait for its completion and to retrieve the results of the computation. The result is retrieved using Future's get() method when the computation has completed, and it blocks until it is completed.
Future vs CompletableFuture. CompletableFuture is an extension to Java's Future API which was introduced in Java 5. A Future is used as a reference to the result of an asynchronous computation.
Yes, documentation of Future. get() says: Waits if necessary for the computation to complete, and then retrieves its result. so, it will block until results of computation are available, or the computation was interrupted (cancelled or resulting in exception).
It represents the result of a computation that will be completed at a later point of time in future. ExecutorService. submit() method returns immediately and gives you a Future. Once you have obtained a future, you can execute other tasks in parallel while your submitted task is executing, and then use future.
Future
offers you method isDone()
which is not blocking and returns true if computation has completed, false otherwise.
Future.get()
is used to retrieve the result of computation.
You have a couple of options:
isDone()
and if the result is ready ask for it by invoking get()
, notice how there is no blockingget()
get(long timeout, TimeUnit unit)
The whole Future API
thing is there to have easy way obtaining values from threads executing parallel tasks. This can be done synchronously or asynchronously if you prefer, as described in bullets above.
UPDATE WITH CACHE EXAMPLE
Here is a cache implementation from Java Concurrency In Practice, an excellent use case for Future
.
Future
for other callers. This is all easily achieved with Future
API.
package net.jcip.examples;
import java.util.concurrent.*;
/**
* Memoizer
* <p/>
* Final implementation of Memoizer
*
* @author Brian Goetz and Tim Peierls
*/
public class Memoizer <A, V> implements Computable<A, V> {
private final ConcurrentMap<A, Future<V>> cache
= new ConcurrentHashMap<A, Future<V>>();
private final Computable<A, V> c;
public Memoizer(Computable<A, V> c) {
this.c = c;
}
public V compute(final A arg) throws InterruptedException {
while (true) {
Future<V> f = cache.get(arg);
// computation not started
if (f == null) {
Callable<V> eval = new Callable<V>() {
public V call() throws InterruptedException {
return c.compute(arg);
}
};
FutureTask<V> ft = new FutureTask<V>(eval);
f = cache.putIfAbsent(arg, ft);
// start computation if it's not started in the meantime
if (f == null) {
f = ft;
ft.run();
}
}
// get result if ready, otherwise block and wait
try {
return f.get();
} catch (CancellationException e) {
cache.remove(arg, f);
} catch (ExecutionException e) {
throw LaunderThrowable.launderThrowable(e.getCause());
}
}
}
}
Below is the snippet of the pseudo code. My question is- Does the below code not defeat the very notion of parallel asynchronous processing?
It all depends on your use case:
If you really want to block till you get the result, use blocking get()
If you can wait for a specific period to know the status instead of infinite blocking duration, use get()
with time-out
If you can continue without analysing the result immediately and inspect the result at future time, use CompletableFuture (java 8)
A Future that may be explicitly completed (setting its value and status), and may be used as a CompletionStage, supporting dependent functions and actions that trigger upon its completion.
You can implement callback mechanism from your Runnable/Callable. Have a look at below SE question:
Java executors: how to be notified, without blocking, when a task completes?
I would like to give my share on this one, more on theoretical point of view as there are some technical answers already. I would like to base my answer on the comment:
Let me give you my example. The tasks I submit to the service end up raising HTTP requests, The result of the HTTP request can take a lot of time. But I do need the result of each HTTP request. The tasks are submitted in a loop. If I wait for each task to return (get), then I am loosing parallelism here, ain't I?
which agrees with what is said in the question.
Say you have three kids, and you want to make a cake, for your birthday. Since you want to make the greatest of cakes you need a lot of different stuff to prepare it. So what you do is split the ingredients on three different lists, because where you live there exist just 3 supermarkets that sell different products, and assign each of your kids a single task, simultaneously
.
Now, before you can start preparing the cake (let's assume again, that you need all the ingredients beforehand) you will have to wait for the kid that have to do the longest route. Now, the fact that you need to wait for all the ingredients before starting to make the cake is your necessity, not a dependency among tasks. Your kids have been working on the tasks simoultaneously as long as they could (e.g: until the first kid completed the task). So, to conclude, here you have the paralelilsm.
The sequential example is described when you have 1 kid and you assign all three tasks to him/her.
In the example you have given you might as well run everything in your main()
method and go your merry way.
But let us assume you have three steps of computation that you are currently running sequentially. Just for understanding let us assume that step1 takes t1 seconds, step2 takes t2 seconds, and step3 takes t3 seconds to complete. So total computation time is t1+t2+t3
. Also, let us assume that t2>t1>=t3
.
Now let us consider a scenario when we executed these three steps in parallel using Future
to hold each computational results. You can check if each task is done using non-blocking isDone()
call on corresponding futures. Now what happens? theoretically your execution is as fast as how t2
completes right? So we did gain some benefits from parallelism.
Also, in Java8 , there is CompletableFuture
that supports functional style call backs.
If you don't care about the results, then spawn a new thread and from that thread use ExectorService
API for task submission. In that way, your parent thread i.e main
thread will not be blocking in any way, it would simply spawn a new thread and then will start further execution, while the new thread will submit your tasks.
For creating new thread - either do it yourself by having a ThreadFactory
for your async thread creation or use some implementation of java.util.concurrent.Executor
.
If this is in a JEE application and you are using Spring framework then you can easily create a new asynchronous thread using @async
annotation.
Hope this helps!
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