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Understanding flatMap

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Understanding flatMap

Taking a walk on Java's functional side? Here are a few good things to know about how flatMap works and what it offers for Optionals and Streams.

· Java Zone ·
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Have you ever scrolled someone’s code and bumped into this weird method called flatMap, not knowing what it actually does from the context? Or maybe you compared it with method map but didn’t really see much difference? If that is the case, then this article is for you. 

flatMap is extremly useful when you try to do proper functional programming. In Java, it usually means using Streams and Optionals — concepts introduced in version 8. These two types can be thought of as some kind of wrapper over a type that adds some extra behaviour — Stream<T> wrapps type T, allowing you to store any number of elements of type T inside, whereas Optional<T> wraps some type T to explicitly say that the element of that type may or may not be present inside.

Both of them share the methods map and flatMap.

Before we move on, I want to make sure you understand what the map method is doing. It basically allows you to apply the method to the element inside the wrapper and possibly change its type:

Function<String, Long> toLong = Long::parseLong; // function that maps String to Long

Optional<String> someString = Optional.of("12L");
Optional<Long> someLong = someString.map(toLong); //aplying the function to the possible String inside

Stream<String> someStrings = Stream.of("10L", "11L");
Stream<Long> someLongs = someStrings.map(toLong); //applying the function to all Strings inside


After applying the function toLong to our wrappers, their inner types change to the second type of the toLong signature (the result type). 

Let’s examine the function Long::parseLong. If we call it using a string that is not actually a valid long, it will throw NumberFormatException. But what if Java's designers decide to implement it so it returns Optional<Long> instead of just Long and removed the exception? Our code for the Optional part would look like:

Function<String, Optional<Long>> toLongOpt = Long::parseLongOpt;//method I made up

Optional<String> someString = Optional.of("12L");
Optional<Optional<Long>> someLong = someString.map(toLongOpt); //:<


Wow, that is nasty! When we applied the new method to our wrapper, the inner type was changed from String to Optional<Long> (the result type of toLongOpt that we applied). We don’t really need to have a double Optional because just one is perfectly fine. Now, to get the value, we need to extract it twice, not mentioning how it would look like when we want to map it again without unwrapping… To restore it to the single type, we would need to write a method like this one:

public static <T> Optional<T> flatten(Optional<Optional<T>> optional) {
    return optional.orElse(Optional.empty());
}


This method will flatten our Optional<Optional<T>> to Optional<T> without changing the inner value. The code will look like this:

Function<String, Optional<Long>> toLongOpt = Long::parseLongOpt;

Optional<String> someString = Optional.of("12L");
Optional<Long> someLong = flatten(someString.map(toLongOpt));


This is exactly what the method flatMap is doing. It first applies the function returning another Optional to the object inside (if present) and then flattens the result before returning it, so you don’t have to do it yourself. This is how we can use it:

Function<String, Optional<Long>> toLongOpt = Long::parseLongOpt;

Optional<String> someString = Optional.of("12L");
Optional<Long> someLong = someString.flatMap(toLongOpt);


For Stream, we can use it in a situation where the function we want to map our elements with returns the Stream. (example signature: Function<String, Stream<Long>>).

That’s it. Just remember that flatMap = map + flatten.

If you want to, dive into the topic and read about the Functor and Monad concepts and the relationship between them. 

Download Building Reactive Microservices in Java: Asynchronous and Event-Based Application Design. Brought to you in partnership with Red Hat

Topics:
java ,functional programming ,flatmap ,optional ,stream ,tutorial

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