Futures (Java)¶
Introduction¶
In Akka, a Future is a data structure used to retrieve the result of some concurrent operation. This operation is usually performed by an Actor or by the Dispatcher directly. This result can be accessed synchronously (blocking) or asynchronously (non-blocking).
Use with Actors¶
There are generally two ways of getting a reply from an UntypedActor: the first is by a sent message (actorRef.sendOneWay(msg);), which only works if the original sender was an UntypedActor) and the second is through a Future.
Using the ActorRef‘s sendRequestReplyFuture method to send a message will return a Future. To wait for and retrieve the actual result the simplest method is:
Future[Object] future = actorRef.sendRequestReplyFuture[Object](msg);
Object result = future.get(); //Block until result is available, usually bad practice
This will cause the current thread to block and wait for the UntypedActor to ‘complete’ the Future with it’s reply. Due to the dynamic nature of Akka’s UntypedActors this result can be anything. The safest way to deal with this is to specify the result to an Object as is shown in the above example. You can also use the expected result type instead of Any, but if an unexpected type were to be returned you will get a ClassCastException. For more elegant ways to deal with this and to use the result without blocking, refer to Functional Futures.
Use Directly¶
A common use case within Akka is to have some computation performed concurrently without needing the extra utility of an UntypedActor. If you find yourself creating a pool of UntypedActors for the sole reason of performing a calculation in parallel, there is an easier (and faster) way:
import akka.dispatch.Future;
import static akka.dispatch.Futures.future;
import java.util.concurrent.Callable;
Future<String> f = future(new Callable<String>() {
public String call() {
return "Hello" + "World!";
}
});
String result = f.get(); //Blocks until timeout, default timeout is set in akka.conf, otherwise 5 seconds
In the above code the block passed to future will be executed by the default Dispatcher, with the return value of the block used to complete the Future (in this case, the result would be the string: “HelloWorld”). Unlike a Future that is returned from an UntypedActor, this Future is properly typed, and we also avoid the overhead of managing an UntypedActor.
Functional Futures¶
A recent addition to Akka’s Future is several monadic methods that are very similar to the ones used by Scala‘s collections. These allow you to create ‘pipelines’ or ‘streams’ that the result will travel through.
Future is a Monad¶
The first method for working with Future functionally is map. This method takes a Function which performs some operation on the result of the Future, and returning a new result. The return value of the map method is another Future that will contain the new result:
import akka.dispatch.Future;
import static akka.dispatch.Futures.future;
import static akka.japi.Function;
import java.util.concurrent.Callable;
Future<String> f1 = future(new Callable<String>() {
public String call() {
return "Hello" + "World";
}
});
Future<Integer> f2 = f1.map(new Function<String, Integer>() {
public Integer apply(String s) {
return s.length();
}
});
Integer result = f2.get();
In this example we are joining two strings together within a Future. Instead of waiting for f1 to complete, we apply our function that calculates the length of the string using the map method. Now we have a second Future, f2, that will eventually contain an Integer. When our original Future, f1, completes, it will also apply our function and complete the second Future with it’s result. When we finally get the result, it will contain the number 10. Our original Future still contains the string “HelloWorld” and is unaffected by the map.
Something to note when using these methods: if the Future is still being processed when one of these methods are called, it will be the completing thread that actually does the work. If the Future is already complete though, it will be run in our current thread. For example:
import akka.dispatch.Future;
import static akka.dispatch.Futures.future;
import static akka.japi.Function;
import java.util.concurrent.Callable;
Future<String> f1 = future(new Callable<String>() {
public String call() {
Thread.sleep(1000);
return "Hello" + "World";
}
});
Future<Integer> f2 = f1.map(new Function<String, Integer>() {
public Integer apply(String s) {
return s.length();
}
});
Integer result = f2.get();
The original Future will take at least 1 second to execute now, which means it is still being processed at the time we call map. The function we provide gets stored within the Future and later executed automatically by the dispatcher when the result is ready.
If we do the opposite:
import akka.dispatch.Future;
import static akka.dispatch.Futures.future;
import static akka.japi.Function;
import java.util.concurrent.Callable;
Future<String> f1 = future(new Callable<String>() {
public String call() {
return "Hello" + "World";
}
});
Thread.sleep(1000);
Future<Integer> f2 = f1.map(new Function<String, Integer>() {
public Integer apply(String s) {
return s.length();
}
});
Integer result = f2.get();
Our little string has been processed long before our 1 second sleep has finished. Because of this, the dispatcher has moved onto other messages that need processing and can no longer calculate the length of the string for us, instead it gets calculated in the current thread just as if we weren’t using a Future.
Normally this works quite well as it means there is very little overhead to running a quick function. If there is a possibility of the function taking a non-trivial amount of time to process it might be better to have this done concurrently, and for that we use flatMap:
import akka.dispatch.Future;
import static akka.dispatch.Futures.future;
import static akka.japi.Function;
import java.util.concurrent.Callable;
Future<String> f1 = future(new Callable<String>() {
public String call() {
return "Hello" + "World";
}
});
Future<Integer> f2 = f1.flatMap(new Function<String, Future<Integer>>() {
public Future<Integer> apply(final String s) {
return future(
new Callable<Integer>() {
public Integer call() {
return s.length();
}
});
}
});
Integer result = f2.get();
Now our second Future is executed concurrently as well. This technique can also be used to combine the results of several Futures into a single calculation, which will be better explained in the following sections.
Composing Futures¶
It is very often desirable to be able to combine different Futures with eachother, below are some examples on how that can be done in a non-blocking fashion.
import akka.dispatch.Future;
import static akka.dispatch.Futures.sequence;
import akka.japi.Function;
import java.util.LinkedList;
LinkedList<Future<Integer>> listOfFutureInts = ... //Some source generating a list of Future<Integer>:s
// now we have a Future[List[Int]]
Future<LinkedList<Integer>> futureListOfInts = sequence(listOfFutureInts);
// Find the sum of the odd numbers
Long totalSum = futureListOfInts.map(
new Function<LinkedList<Integer>, Long>() {
public Long apply(LinkedList<Integer> ints) {
long sum = 0;
for(Integer i : ints)
sum += i;
return sum;
}
}).get();
To better explain what happened in the example, Future.sequence is taking the LinkedList<Future<Integer>> and turning it into a Future<LinkedList<Integer>>. We can then use map to work with the LinkedList<Integer> directly, and we aggregate the sum of the LinkedList.
The traverse method is similar to sequence, but it takes a sequence of A``s and applies a function from ``A to Future<B> and returns a Future<LinkedList<B>>, enabling parallel map over the sequence, if you use Futures.future to create the Future.
import akka.dispatch.Future;
import static akka.dispatch.Futures.traverse;
import static akka.dispatch.Futures.future;
import java.util.LinkedList;
import akka.japi.Function;
LinkedList<String> listStrings = ... //Just a list of Strings
Future<LinkedList<String>> result = traverse(listStrings, new Function<String,Future<String>>(){
public Future<String> apply(final String r) {
return future(new Callable<String>() {
public String call() {
return r.toUpperCase();
}
});
}
});
result.get(); //Returns a the list of strings as upper case
It’s as simple as that!
Then there’s a method that’s called fold that takes a start-value, a sequence of Future:s and a function from the type of the start-value, a timeout, and the type of the futures and returns something with the same type as the start-value, and then applies the function to all elements in the sequence of futures, non-blockingly, the execution will run on the Thread of the last completing Future in the sequence.
import akka.dispatch.Future;
import static akka.dispatch.Futures.fold;
import java.util.Iterable;
import akka.japi.Function2;
Iterable<Future<String>> futures = ... //A sequence of Futures, in this case Strings
Future<String> result = fold("", 15000, futures, new Function2<String, String, String>(){ //Start value is the empty string, timeout is 15 seconds
public String apply(String r, String t) {
return r + t; //Just concatenate
}
});
result.get(); // Will produce a String that says "testtesttesttest"(... and so on).
That’s all it takes!
If the sequence passed to fold is empty, it will return the start-value, in the case above, that will be 0. In some cases you don’t have a start-value and you’re able to use the value of the first completing Future in the sequence as the start-value, you can use reduce, it works like this:
import akka.dispatch.Future;
import static akka.dispatch.Futures.reduce;
import java.util.Iterable;
import akka.japi.Function2;
Iterable<Future<String>> futures = ... //A sequence of Futures, in this case Strings
Future<String> result = reduce(futures, 15000, new Function2<String, String, String>(){ //Timeout is 15 seconds
public String apply(String r, String t) {
return r + t; //Just concatenate
}
});
result.get(); // Will produce a String that says "testtesttesttest"(... and so on).
Same as with fold, the execution will be done by the Thread that completes the last of the Futures, you can also parallize it by chunking your futures into sub-sequences and reduce them, and then reduce the reduced results again.
This is just a sample of what can be done.
Exceptions¶
Since the result of a Future is created concurrently to the rest of the program, exceptions must be handled differently. It doesn’t matter if an UntypedActor or the dispatcher is completing the Future, if an Exception is caught the Future will contain it instead of a valid result. If a Future does contain an Exception, calling get will cause it to be thrown again so it can be handled properly.