Let if flow: Java 8 Streams puzzles and more
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This talk covers Java 8 Streams in details and using programming puzzles will discuss about various techniques with Streams: how to do complex data processing , queries with Streams API, how to use all the goodies like map, flatMap,filter, how to group, and partition data, how to use infinite streams, parallel streams, creating lazy lists. If you are a beginner or a pro with Java 8 wanting to challenge your knowledge there is something for all!
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Let if flow: Java 8 Streams puzzles and more
- 1. Let it flow Java 8 stream puzzles and more Bhakti Mehta @bhakti_mehta
- 2. Introduction O Senior Software Engineer at Blue Jeans Network O Worked at Sun Microsystems/Oracle for 13 years O Committer to numerous open source projects including GlassFish Application Server
- 6. Evolution of Java O Java 8 has myriad of features O Most prominent are lamdas and streams API O Functional style to Java
- 7. Streams O Abstraction not a datastructure O Can transform data O Value in motion O Functional style will affect all collections O Automatic parallelism
- 8. Collections in Java 8 Contains whole data structure Eager computation
- 9. Streams in Java 8 Computed on demand Just in time Lazily constructed collection
- 10. Stream or loop GET the shortest list of cities of people Instead of List people = … Set shortCities = new HashSet<>(); for (Person p : people) { City c = p.getCity(); if (c.getName().length() < 5 ) { shortCities.add(c); }
- 11. Stream or loop We write List people = … Set shortCities = people.stream() .map(Person::getCity) .filter(c -> c.getName().length() < 5) .collect(toSet());
- 12. Stream or loop We write List people = … Set shortCities = people.stream() .map(Person::getCity) .filter(c -> c.getName().length() < 5) .collect(toSet()); More concise More readableComposable operationsCan be made parallel
- 13. Power of Stream O Streams provide the power to write compose functions and data flows through the functions
- 14. Components when working with streams
- 15. Intermediate operations filter map limitsorted distinct
- 17. Map function
- 18. FlatMap
- 19. FlatMap sample public class Teammate { private Set<String> languages; Set<String> getLanguages() { return languages; } List<Teammate> team = new ArrayList<>(); Teammate dev1 = new Teammate(); dev1.addLanguage("scala"); dev1.addLanguage(“go”); Teammate dev2 = new Teammate(); dev2.addLanguage("java"); team.add(dev1); team.add(dev2);
- 20. FlatMap sample List<String> teamLanguages = team.stream(). map(d -> d.getLanguages()). flatMap(l -> l.stream()). collect(Collectors.toList()); returns [“scala”,”go”,”java”]
- 21. Quiz Given a list of numbers return the Squares Given [1,2,3,4] return [1,4,9,16]
- 22. Quiz Given a list of numbers return the Squares Given [1,2,3,4] return [1,4,9,16] List<Integer>numbers = Arrays.asList(1,2,3,4); List<Integer> squares = numbers.stream().map (n->n*n).collect(toList());
- 26. Grouping Map<Animal.Category, List<Animal>> animalsByCategory = animals.stream(). collect(groupingBy(Animal::getCategory)); {Mammals=[Dolphin, Cat, Dog], Fish=[Ray, Shark], Reptiles=[Alligator, Crocodile]}
- 27. Getting a count Map<Animal.Category, List<Animal>> animalsByCategory = animals.stream(). collect(groupingBy(Animal::getCategory, counting())); {Mammals=2, Fish=2, Reptiles=2}
- 28. I Imperative style Iterate through the animals Classify in various categories Get counts of each cumbersome Verbose
- 29. Partitioning Map<Boolean, List<Item>> partitionedMenu = menu.stream().collect (partitioningBy(Item::isSeaFood)); { false= [brocolli chicken, orange chicken], true=[spicy shrimp, catfish]} Getting seafood from the menu
- 30. Via Filtering List<Item> seafood = menu.stream().filter (Item::isSeaFood).collect(toList()); gives [spicy shrimp, catfish]
- 31. Multilevel partitioning partitioningBy collector can be used in combination with other partioningBy collections to get multi level partitioning
- 32. Quiz Is this valid sample? menu.stream().collect (partitioningBy (Item::isSeaFood() ,partitioningBy (d->d.getCalories()>500)));
- 33. Quiz Is this valid sample? menu.stream().collect (partitioningBy (Item::isSeaFood() ,partitioningBy (d->d.getCalories()>500)));
- 34. Composability O Get the unique surnames in uppercase of the first 15 book authors that are 50 years old or older O library.stream() .map(book -> book.getAuthor()) .filter(author -> author.getAge() >= 50) .limit(15) .map(Author::getSurname) .ma p(String::toUpperCase) .distinct() .collect(toLi st()));
- 35. Infinite stream O Stream<Integer> evenNumbers = Stream.iterate(0, n -> n + 2);
- 36. Parallel streams O Parallel streams = simple concurrency O Parallel stream splits its elements in multiple chunks processing each chunk on a different thread O Potentially can use N cores => Nx speedup
- 37. Parallel Streams O Check the benchmark using sequential and parallel streams O Limit and findFirst may be expensive in parallel stream as they rely on the odrder of the elements. Use findAny if you are not constrained by the order
- 38. Summary O Great step by Java 8 towards supporting FP O Use FP and OoP together
- 39. Use Streams and prosper