In Akka, a `Future <http://en.wikipedia.org/wiki/Futures_and_promises>`_ 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).
There are generally two ways of getting a reply from an ``Actor``: the first is by a sent message (``actor ! msg``), which only works if the original sender was an ``Actor``) and the second is through a ``Future``.
This will cause the current thread to block and wait for the ``Actor`` to 'complete' the ``Future`` with it's reply. Blocking is discouraged though as it can cause performance problem.
The blocking operations are located in ``Await.result`` and ``Await.ready`` to make it easy to spot where blocking occurs. Alternatives to blocking are discussed further within this documentation.
Also note that the ``Future`` returned by an ``Actor`` is a ``Future[Any]`` since an ``Actor`` is dynamic. That is why the ``asInstanceOf`` is used in the above sample.
When using non-blocking it is better to use the ``mapTo`` method to safely try to cast a ``Future`` to an expected type:
The ``mapTo`` method will return a new ``Future`` that contains the result if the cast was successful, or a ``ClassCastException`` if not. Handling ``Exception``\s will be discussed further within this documentation.
A common use case within Akka is to have some computation performed concurrently without needing the extra utility of an ``Actor``. If you find yourself creating a pool of ``Actor``\s for the sole reason of performing a calculation in parallel, there is an easier (and faster) way:
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 ``Actor``, this ``Future`` is properly typed, and we also avoid the overhead of managing an ``Actor``.
Akka's ``Future`` has 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.
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:
In this example we are joining two strings together within a ``Future``. Instead of waiting for this to complete, we apply our function that calculates the length of the string using the ``map`` method. Now we have a second ``Future`` that will eventually contain an ``Int``. When our original ``Future`` 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``.
The ``map`` method is fine if we are modifying a single ``Future``, but if 2 or more ``Future``\s are involved ``map`` will not allow you to combine them together:
Something to keep in mind when doing this is even though it looks like parts of the above example can run in parallel, each step of the for comprehension is run sequentially. This will happen on separate threads for each step but there isn't much benefit over running the calculations all within a single ``Future``. The real benefit comes when the ``Future``\s are created first, and then combining them together.
The example for comprehension above is an example of composing ``Future``\s. A common use case for this is combining the replies of several ``Actor``\s into a single calculation without resorting to calling ``Await.result`` or ``Await.ready`` to block for each result. First an example of using ``Await.result``:
Here we wait for the results from the first 2 ``Actor``\s before sending that result to the third ``Actor``. We called ``Await.result`` 3 times, which caused our little program to block 3 times before getting our final result. Now compare that to this example:
Here we have 2 actors processing a single message each. Once the 2 results are available (note that we don't block to get these results!), they are being added together and sent to a third ``Actor``, which replies with a string, which we assign to 'result'.
This is fine when dealing with a known amount of Actors, but can grow unwieldy if we have more then a handful. The ``sequence`` and ``traverse`` helper methods can make it easier to handle more complex use cases. Both of these methods are ways of turning, for a subclass ``T`` of ``Traversable``, ``T[Future[A]]`` into a ``Future[T[A]]``. For example:
To better explain what happened in the example, ``Future.sequence`` is taking the ``List[Future[Int]]`` and turning it into a ``Future[List[Int]]``. We can then use ``map`` to work with the ``List[Int]`` directly, and we find the sum of the ``List``.
The ``traverse`` method is similar to ``sequence``, but it takes a ``T[A]`` and a function ``A => Future[B]`` to return a ``Future[T[B]]``, where ``T`` is again a subclass of Traversable. For example, to use ``traverse`` to sum the first 100 odd numbers:
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 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.
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:
Same as with ``fold``, the execution will be done by the Thread that completes the last of the Futures, you can also parallelize it by chunking your futures into sub-sequences and reduce them, and then reduce the reduced results again.
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 ``Actor`` 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 ``Await.result`` will cause it to be thrown again so it can be handled properly.
In this example, if the actor replied with a ``akka.actor.Status.Failure`` containing the ``ArithmeticException``, our ``Future`` would have a result of 0. The ``recover`` method works very similarly to the standard try/catch blocks, so multiple ``Exception``\s can be handled in this manner, and if an ``Exception`` is not handled this way it will be behave as if we hadn't used the ``recover`` method.
