Sayat SatybaldiyevSoftware Dev. @ Green Apple

Twitter: Sayat_Stb

Google Developers Group Almaty

Google Developers GroupAlmaty

• Некоммерческое сообщество, в основе которого лежит обмен опытом и знаниями технологии Google для разработчиков - Android, Google Maps, App Engine, Chrome, Web Toolkit, Google Plus и другие.

• Среди нас есть программисты, архитекторы, дизайнеры, IT-менеджеры, студенты и руководители. И мы всегда рады новым знакомствам :)

Спонсор фуршета

•

История

Lisp, Schema, Haskell

Как можно выбрать все зеленые яблоки из коллекции красных, желтых и зеленых яблок?

Functional vs Imperative

List<Apple> result = new ArrayList<>();

for(Apple apple: input){

if(apple.getColor.equals("green")){

result.add(apple);

}

}

return result;

Functional vs Imperative

filterApples(input,

(Apple a) -> { a.getColor().equals("green")}

)

Принципы ФП

• Higher Order Functionspass, create, return

• Side Effects Freef(x, y) = x^2 + y ^2

• Immutabilityeasy to reason, multithreaded

Common FP operations

map

Common FP operations

filter

Common FP operations

reduce

Java 8 Lambda Project

The first ever big release since 1.5!

aka Functional Style

First Lambdas

button.addActionListener(new ActionListener() { public void actionPerformed(ActionEvent event) { System.out.println("button clicked")}

});

First Lambdas

button.addActionListener(new ActionListener() { public void actionPerformed(ActionEvent event) { System.out.println("button clicked")}

});

button.addActionListener(event -> System.out.println("button clicked"));

Синтаксис Lambda Выражений

• Lambda - anonymous function(arg1, arg2...) -> { body }

(int x, int y) -> x + y(x, y) -> x + y() -> System.out.println(“Hello World”)

Functional Interface

T => Boolean@FunctionalInterfacepublic interface Predicate<T>{

boolean test(T t)

}T => void@FunctionalInterfacepublic interface Consumer<T>{

void accept(T t)}T => R@FunctionalInterfacepublic interface Function<T, R>{

R apply(T t)}

Def: A functional interface is an interface with a single abstract method that is used as the type of a lambda expression.

Functional Interface

Represents a function that accepts one argument and produces a result.T => R@FunctionalInterfacepublic interface Function<T, R>{

R apply(T t)}

Function<Apple, String> = (Apple a ) -> a.toString()

Functional Interface

Represents a predicate (boolean-valued function) of one argument. - Filter

T => Boolean@FunctionalInterface

public interface Predicate<T>{boolean test(T t)

}

Predicate<Integer> atLeast5 = ( x ) -> x > 5;

Functional Interface

Represents an operation that accepts a single input argument and returns no result.

T => void@FunctionalInterfacepublic interface Consumer<T>{

void accept(T t)}

Consumer<Apple> = (Apple a) -> System.out.println(a.toString())

Stream APIs

Streams

• No Storage• Lazy Evaluations• Infinite/Finite Stream• Single Usage• Ordered/Unordered• Parallel/Sequential

Streams

Declarative Style

what to do NOT howList<String> myList = Arrays.asList("a1", "a2", "b1", "c2", "c1");

myList

.stream()

.filter(s -> s.startsWith("c"))

.map(String::toUpperCase)

.sorted()

.forEach(System.out::println);

Streams

Pipes-and-filter Style API

Creating Stream API

Arrays.stream()

Stream<Integer> = Stream.of(1, 2, 3)

Infinite

Stream.iterate(0, n-> n + 10)

ex: with limit - fixed size

Stream Operatons

filter(Predicate<T>)

map(Function<R, T>)

sorted(Comparator<T>)

limit(long maxSize)

distinct()

Terminal Stream Operation

Terminal

sum()

max()/min()

average()

forEach()

collect()

Parallel Stream

Количество зеленых яблок в колекции?

int count = 0;for (Apple apple : allApples) {

if (apple.equals("green")) { count++;

} } return count;

Количество зеленых яблок в колекции?

int count = 0;Iterator<Apple> iterator = allApples.iterator(); while(iterator.hasNext()) {

Apple apple = iterator.next(); if (apple.equals("green")) {

count++; }

}

Parallel Streams

public int parallelArraySum() { return albums.parallelStream()

.mapToInt((Track tr) -> tr.getLength) .sum();

} ● Fork and Join Framework● NOT keep order of stream

Performance

private int addIntegers(List<Integer> values) { return values.parallelStream()

.mapToInt(i -> i) .sum();

}

Performance

Performance

Data size

Source data structure

# cores

FP in Java 8

1. FP(ish) programming

2. Declarative

3. Working with Data Processing

Спасибо за внимание

Google Developers Group Almaty

www.GDGalmaty.org

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