layout: true <footer> <span class="icon github"> <svg version="1.1" class="github-icon-svg" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px" viewBox="0 0 16 16" enable-background="new 0 0 16 16" xml:space="preserve"> <path fill-rule="evenodd" clip-rule="evenodd" fill="#C2C2C2" d="M7.999,0.431c-4.285,0-7.76,3.474-7.76,7.761c0,3.428,2.223,6.337,5.307,7.363c0.388,0.071,0.53-0.168,0.53-0.374c0-0.184-0.007-0.672-0.01-1.32c-2.159,0.469-2.614-1.04-2.614-1.04c-0.353-0.896-0.862-1.135-0.862-1.135c-0.705-0.481,0.053-0.472,0.053-0.472c0.779,0.055,1.189,0.8,1.189,0.8c0.692,1.186,1.816,0.843,2.258,0.645c0.071-0.502,0.271-0.843,0.493-1.037C4.86,11.425,3.049,10.76,3.049,7.786c0-0.847,0.302-1.54,0.799-2.082C3.768,5.507,3.501,4.718,3.924,3.65c0,0,0.652-0.209,2.134,0.796C6.677,4.273,7.34,4.187,8,4.184c0.659,0.003,1.323,0.089,1.943,0.261c1.482-1.004,2.132-0.796,2.132-0.796c0.423,1.068,0.157,1.857,0.077,2.054c0.497,0.542,0.798,1.235,0.798,2.082c0,2.981-1.814,3.637-3.543,3.829c0.279,0.24,0.527,0.713,0.527,1.437c0,1.037-0.01,1.874-0.01,2.129c0,0.208,0.14,0.449,0.534,0.373c3.081-1.028,5.302-3.935,5.302-7.362C15.76,3.906,12.285,0.431,7.999,0.431z"/> </svg> </span> <a href="https://github.com/sikoried"><span class="username">sikoried</span></a> </footer> --- # Reduction Korbinian Riedhammer --- # Advanced Stream Processing in Java Korbinian Riedhammer --- # Streams in Java ## Generation - `Stream.of(...)` with array or varargs - `Collection.stream()`, if supported - `Stream.generate(...)` using a generator - Popular APIs, e.g. `Pattern.compile("\\W").splitAsStream("hello world");` ## Intermediate Operations ## Terminal Operations --- # Intermediate Operations `filter(Predicate<T> p)` removes/skips unwanted elements in the stream. `map(Function<T, R> f)` transforms a `Stream<T>` into a `Stream<R>` using the provided `Function` `sorted(Comparator<T> comp)` returns a sorted stream `concat(Stream<T> s)` appends another stream `distinct()` removes duplicates `skip(int n)` and `limit(int n)` skip elements and truncate the stream `flatMap(...)` flattens a list-of-lists into a single stream ```java Stream<List<Integer>> lol = Stream.of( Arrays.asList(1, 2), Arrays.asList(3, 4), Arrays.asList(5) ); Stream<Integer> integerStream = lol.flatMap(al -> al.stream()); integerStream.forEach(System.out::print); // 12345 ``` --- # Terminal Operations Use `.forEach(Consumer<T> c)` to pass each element to the `Consumer` Use `reduce` to combine (and optionally map) elements of a stream. ```java Stream.of(1, 3, 3, 7).reduce(0, Integer::sum)); // 14 Stream.of(1, 3, 3, 7).reduce(BigInteger.ZERO, (bi, i) -> bi.add(BigInteger.valueOf(i)), (bi1, bi2) -> bi1.add(bi2))); // combine identity with first result // 14 ``` Use `collect` to collect/distribute elements to other structures. ```java List<Integer> list1 = new LinkedList<>(); Stream.of(1, 3, 3, 7).forEach(i -> list.add(i)); // or shorter, using collect List<Integer> list2 = Stream.of(1, 3, 3, 7).collect(Collectors.toList())); ``` --- # Collectors ```java // Accumulate names into a TreeSet Set<String> set = people.stream() .map(Person::getName) .collect(Collectors.toCollection(TreeSet::new)); // Convert elements to strings and concatenate them, separated by commas String joined = things.stream() .map(Object::toString) .collect(Collectors.joining(", ")); // Compute sum of salaries of employee int total = employees.stream() .collect(Collectors.summingInt(Employee::getSalary)); // Group employees by department Map<Department, List<Employee>> byDept = employees.stream() .collect(Collectors.groupingBy(Employee::getDepartment)); // Compute sum of salaries by department Map<Department, Integer> totalByDept = employees.stream() .collect(Collectors.groupingBy(Employee::getDepartment, Collectors.summingInt(Employee::getSalary))); // Partition students into passing and failing Map<Boolean, List<Student>> passingFailing = students.stream() .collect(Collectors.partitioningBy(s -> s.getGrade() <= 400)); ``` --- ## Finding Values in a Stream Use `findFirst()`, `min()` or `max()` to find values, returns `Optional<T>`! ## Verifying Values in a Stream Use the `allMatch()`, `anyMatch()` and `noneMatch()` functions with a `Predicate<T>`. ## Parallel Processing Use `parallelStream()` for concurrent processing. --- # Well Done! .skip[  ] --- # Well Done! .skip.w55[  ]