Java 8 - An Introduction by Jason Swartz
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The document provides an introduction to Java 8, covering key features such as lambda expressions, streaming collections, and monadic collections. It explains how to use lambda expressions for functions and methods, demonstrates data manipulation with streaming collections, and introduces the concept of optional types for handling potential null values. The presentation concludes by highlighting the significance of monadic collections in managing missing and future values.
Java 8 - An Introduction by Jason Swartz
- 1. Java 8 An Introduction by Jason Swartz
- 2. Agenda 1. Lambda Expressions 2. Streaming Collections 3. Monadic Collections
- 4. Math Function f(x) = x * x
- 5. Java Function int sqr(int x) { return x * x; }
- 6. Anonymous Function x -> x * x
- 7. Java Anonymous Function x -> x * x
- 8. Java Anonymous Function (x) -> x * x
- 9. Java Anonymous Function (x, y) -> x + y
- 10. Java Anonymous Function () -> 42
- 11. Java Anonymous Function f = x -> x * x; int y = f.apply(5);
- 12. Java Anonymous Function f = (x, y) -> x + y; int y = f.applyAsInt(5, 7);
- 13. Java Anonymous Function r = () -> { System.out.println("Hello"); }; r.run();
- 14. Java Method Reference c = System.out::println; c.accept("Hello");
- 15. Now You Know Lambdas
- 17. Doubling Items In A List List<Integer> nums = Arrays .asList(1, 2, 3); int sqr(int x) { return x * x; }
- 18. Doubling Items In A List nums2 = new ArrayList<Integer>(); for (int i : nums) { nums2.add(sqr(i)); }
- 19. Doubling Items In A List nums.stream()
- 20. Doubling Items In A List nums.stream() .map(this::sqr)
- 21. Doubling Items In A List nums = nums.stream() .map(this::sqr) .collect(Collectors.toList());
- 22. Doubling Items In A List nums = nums.stream() .map(x -> x * x) .collect(Collectors.toList());
- 23. Doubling Items In A List nums = nums.parallelStream() .map(x -> x * x) .collect(Collectors.toList());
- 24. Doubling Items In A List nums = nums.clusterStream() .map(x -> x * x) .collect(Collectors.toList());
- 25. Doubling Items In A List nums = nums.dataCenterStream() .map(x -> x * x) .collect(Collectors.toList());
- 27. Mapping To A List of Lists nums.stream() .map(x -> Arrays.list(x, x * x)) .collect(Collectors.toList());
- 28. Flatmap That List nums = nums.stream() .flatMap(x -> Arrays.list(x, x * x)) .collect(Collectors.toList());
- 29. Filtering Items In A List nums = nums.stream() .filter(x -> x % 2 == 0) .collect(Collectors.toList());
- 30. Reducing A List sum = nums.stream() .reduce((a,i) -> a + i) .get();
- 31. 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();
- 33. Now You Know Streams
- 35. Have you done this? User u = getUser(“Fred”); String name = u.getName(); Exception in thread "main" java.lang. NullPointerException
- 37. Use Optional<T>, not null Optional<User> u = getUser("Fred"); if (! u.isPresent()) return; String name = u.get().name;
- 38. Use Optional<T>, not null Optional<User> u = getUser("Fred"); Optional<String> name = u .map(user -> user.name);
- 39. Another Example
- 40. Checking a user name User u = getUser(“Fred”); Boolean result = null; if (u != null) Result = checkName(u.getName()); else Result = false;
- 41. Checking a user name Optional<User> u = getUser("Fred"); Boolean result; if (u.isPresent()) result = confirmName(u.get().name); else result = false;
- 42. Confirming a user name with map() Boolean result = getUser("Fred") .map(u -> u.name) .map(this::confirmName) .orElse(false);
- 43. Optional is just a monad, a monoid in the category of endofunctors. What’s the problem?
- 44. Optional is just a monad, a monoid in the category of endofunctors. What’s the problem?
- 45. Optional is a zero- or one- sized collection that helps you cleanly handle missing values.
- 47. CompletableFuture is a zero- or one-sized collection that helps you cleanly handle future values.
- 48. Javaslang’s Try is a zero- or one-sized collection that helps you cleanly handle exception-thrown values.
- 49. Javaslang’s Lazy is a zero- or one-sized collection that helps you cleanly postpone calculating values.
- 50. Now You Know Monadic Collections