Java 8

An Introduction byJason Swartz

Agenda

1. Lambda Expressions2. Streaming Collections3. Monadic Collections

1. Lambda Expressions

Math Function

f(x) = x * x

Java Function

int sqr(int x) { return x * x; }

Anonymous Function

x -> x * x

Java Anonymous Function

x -> x * x

Java Anonymous Function

(x) -> x * x

Java Anonymous Function

(x, y) -> x + y

Java Anonymous Function

() -> 42

Java Anonymous Function

f = x -> x * x;int y = f.apply(5);

Java Anonymous Function

f = (x, y) -> x + y;int y = f.applyAsInt(5, 7);

Java Anonymous Function

r = () -> { System.out.println("Hello");};r.run();

Java Method Reference

c = System.out::println;c.accept("Hello");

Now You Know Lambdas

2. Streaming Collections

Doubling Items In A List

List<Integer> nums = Arrays .asList(1, 2, 3);

int sqr(int x) { return x * x; }

Doubling Items In A List

nums2 = new ArrayList<Integer>();for (int i : nums) { nums2.add(sqr(i));}

Doubling Items In A List

nums.stream()

Doubling Items In A List

nums.stream() .map(this::sqr)

Doubling Items In A List

nums = nums.stream() .map(this::sqr) .collect(Collectors.toList());

Doubling Items In A List

nums = nums.stream() .map(x -> x * x) .collect(Collectors.toList());

Doubling Items In A List

nums = nums.parallelStream() .map(x -> x * x) .collect(Collectors.toList());

Doubling Items In A List

nums = nums.clusterStream() .map(x -> x * x) .collect(Collectors.toList());

Doubling Items In A List

nums = nums.dataCenterStream() .map(x -> x * x) .collect(Collectors.toList());

Welcome toDeclarativeProgramming

Mapping To A List of Lists

nums.stream() .map(x -> Arrays.list(x, x * x)) .collect(Collectors.toList());

Flatmap That List

nums = nums.stream() .flatMap(x -> Arrays.list(x, x * x)) .collect(Collectors.toList());

Filtering Items In A List

nums = nums.stream() .filter(x -> x % 2 == 0) .collect(Collectors.toList());

Reducing A List

sum = nums.stream() .reduce((a,i) -> a + i) .get();

In Summary

sum = nums.stream() .map(x -> x * x) .flatMap(x -> Arrays.list(x, x * x)) .filter(x -> x % 2 == 0) .reduce((a,i) -> a + i) .get();

map()

flatmap()reduce()

filter()

Now You Know Streams

3. Monadic Collections

Have you done this?

User u = getUser(“Fred”);String name = u.getName();

Exception in thread "main" java.lang.NullPointerException

Null values stink

Use Optional<T>, not null

Optional<User> u = getUser("Fred");if (! u.isPresent()) return;

String name = u.get().name;

Use Optional<T>, not null

Optional<User> u = getUser("Fred");Optional<String> name = u .map(user -> user.name);

Another Example

Checking a user name

User u = getUser(“Fred”);Boolean result = null;if (u != null) Result = checkName(u.getName());else Result = false;

Checking a user name

Optional<User> u = getUser("Fred");Boolean result;if (u.isPresent()) result = confirmName(u.get().name);else result = false;

Confirming a user name with map()

Boolean result = getUser("Fred") .map(u -> u.name) .map(this::confirmName) .orElse(false);

Optional is just a monad, a monoid in the category of endofunctors. What’s the problem?

Optional is just a monad, a monoid in the category of endofunctors. What’s the problem?

Optional is a zero- or one-sized collection that helps you cleanly handle missing values.

More Monadic Collections?

CompletableFuture is a zero- or one-sized collection that helps you cleanly handle future values.

Javaslang’s Try is a zero- or one-sized collection that helps you cleanly handle exception-thrown values.

Javaslang’s Lazy is a zero- or one-sized collection that helps you cleanly postpone calculating values.

Now You KnowMonadic Collections

Thanks For Watching!