视频链接:https://www.bilibili.com/video/BV1ut411g7E9?p=14&spm_id_from=pageDriver
Java内置四大核心函数式接口:
名称 | 函数式接口 | 内置函数 | 用途 |
---|---|---|---|
消费型接口 | Consumer< T > | void accept(T t) | 对类型为T的对象应用操作: |
提供型接口 | Supplier< T > | T get() | 返回类型为T的对象: |
函数型接口 | Function< T, R > | R apply(T t) | 对类型为T的对象应用操作,并返回结果为R类型的对象: |
断言型接口 | Predicate< T > | boolean test(T t) | 确定类型为T的对象是否满足某约束,并返回boolean值: |
public class TestLambda3 { //Predicate<T> 断言型接口: @Test public void test4(){ List<String> list = Arrays.asList("Hello", "atguigu", "Lambda", "www", "ok"); List<String> strList = filterStr(list, (s) -> s.length() > 3); for (String str : strList) { System.out.println(str); } } //需求:将满足条件的字符串,放入集合中 public List<String> filterStr(List<String> list, Predicate<String> pre){ List<String> strList = new ArrayList<>(); for (String str : list) { if(pre.test(str)){ strList.add(str); } } return strList; } //Function<T, R> 函数型接口: @Test public void test3(){ String newStr = strHandler("\t\t\t 我大尚硅谷威武 ", (str) -> str.trim()); System.out.println(newStr); String subStr = strHandler("我大尚硅谷威武", (str) -> str.substring(2, 5)); System.out.println(subStr); } //需求:用于处理字符串 public String strHandler(String str, Function<String, String> fun){ return fun.apply(str); } //Supplier<T> 供给型接口 : @Test public void test2(){ List<Integer> numList = getNumList(10, () -> (int)(Math.random() * 100)); for (Integer num : numList) { System.out.println(num); } } //需求:产生指定个数的整数,并放入集合中 public List<Integer> getNumList(int num, Supplier<Integer> sup){ List<Integer> list = new ArrayList<>(); for (int i = 0; i < num; i++) { Integer n = sup.get(); list.add(n); } return list; } //Consumer<T> 消费型接口 : @Test public void test1(){ happy(10000, (m) -> System.out.println("你们刚哥喜欢大宝剑,每次消费:" + m + "元")); } public void happy(double money, Consumer<Double> con){ con.accept(money); } }
注意:
类型[] :: new;
public class TestMethodRef { //数组引用 @Test public void test8(){ Function<Integer, String[]> fun = (args) -> new String[args]; String[] strs = fun.apply(10); System.out.println(strs.length); System.out.println("--------------------------"); Function<Integer, Employee[]> fun2 = Employee[] :: new; Employee[] emps = fun2.apply(20); System.out.println(emps.length); } //构造器引用 @Test public void test7(){ Function<String, Employee> fun = Employee::new; BiFunction<String, Integer, Employee> fun2 = Employee::new; } @Test public void test6(){ Supplier<Employee> sup = () -> new Employee(); System.out.println(sup.get()); System.out.println("------------------------------------"); Supplier<Employee> sup2 = Employee::new; System.out.println(sup2.get()); } //类名 :: 实例方法名 @Test public void test5(){ BiPredicate<String, String> bp = (x, y) -> x.equals(y); System.out.println(bp.test("abcde", "abcde")); System.out.println("-----------------------------------------"); BiPredicate<String, String> bp2 = String::equals; System.out.println(bp2.test("abc", "abc")); System.out.println("-----------------------------------------"); Function<Employee, String> fun = (e) -> e.show(); System.out.println(fun.apply(new Employee())); System.out.println("-----------------------------------------"); Function<Employee, String> fun2 = Employee::show; System.out.println(fun2.apply(new Employee())); } //类名 :: 静态方法名 @Test public void test4(){ Comparator<Integer> com = (x, y) -> Integer.compare(x, y); System.out.println("-------------------------------------"); Comparator<Integer> com2 = Integer::compare; } @Test public void test3(){ BiFunction<Double, Double, Double> fun = (x, y) -> Math.max(x, y); System.out.println(fun.apply(1.5, 22.2)); System.out.println("--------------------------------------------------"); BiFunction<Double, Double, Double> fun2 = Math::max; System.out.println(fun2.apply(1.2, 1.5)); } //对象的引用 :: 实例方法名 @Test public void test2(){ Employee emp = new Employee(101, "张三", 18, 9999.99); Supplier<String> sup = () -> emp.getName(); System.out.println(sup.get()); System.out.println("----------------------------------"); Supplier<String> sup2 = emp::getName; System.out.println(sup2.get()); } @Test public void test1(){ PrintStream ps = System.out; Consumer<String> con = (str) -> ps.println(str); con.accept("Hello World!"); System.out.println("--------------------------------"); Consumer<String> con2 = ps::println; con2.accept("Hello Java8!"); Consumer<String> con3 = System.out::println; } }
操作步骤:
创建 Stream
中间操作
终止操作(终端操作)
public class TestStreamaAPI { //1. 创建 Stream @Test public void test1(){ //1. Collection 提供了两个方法 stream() 与 parallelStream() List<String> list = new ArrayList<>(); Stream<String> stream = list.stream(); //获取一个顺序流 Stream<String> parallelStream = list.parallelStream(); //获取一个并行流 //2. 通过 Arrays 中的 stream() 获取一个数组流 Integer[] nums = new Integer[10]; Stream<Integer> stream1 = Arrays.stream(nums); //3. 通过 Stream 类中静态方法 of() Stream<Integer> stream2 = Stream.of(1,2,3,4,5,6); //4. 创建无限流 //迭代 Stream<Integer> stream3 = Stream.iterate(0, (x) -> x + 2).limit(10); stream3.forEach(System.out::println); //生成 Stream<Double> stream4 = Stream.generate(Math::random).limit(2); stream4.forEach(System.out::println); } }
filter——接收 Lambda , 从流中排除某些元素。
limit——截断流,使其元素不超过给定数量。
skip(n) —— 跳过元素,返回一个扔掉了前 n 个元素的流。若流中元素不足 n 个,则返回一个空流。与 limit(n) 互补
distinct——筛选,通过流所生成元素的 hashCode() 和 equals() 去除重复元素
//2. 中间操作 List<Employee> emps = Arrays.asList( new Employee(102, "李四", 59, 6666.66), new Employee(101, "张三", 18, 9999.99), new Employee(103, "王五", 28, 3333.33), new Employee(104, "赵六", 8, 7777.77), new Employee(104, "赵六", 8, 7777.77), new Employee(104, "赵六", 8, 7777.77), new Employee(105, "田七", 38, 5555.55) ); //内部迭代:迭代操作 Stream API 内部完成 @Test public void test2(){ //所有的中间操作不会做任何的处理 Stream<Employee> stream = emps.stream() .filter((e) -> { System.out.println("测试中间操作"); return e.getAge() <= 35; }); //只有当做终止操作时,所有的中间操作会一次性的全部执行,称为“惰性求值” stream.forEach(System.out::println); } //外部迭代 @Test public void test3(){ Iterator<Employee> it = emps.iterator(); while(it.hasNext()){ System.out.println(it.next()); } } @Test public void test4(){ emps.stream() .filter((e) -> { System.out.println("短路!"); // && || return e.getSalary() >= 5000; }).limit(3) .forEach(System.out::println); } @Test public void test5(){ emps.parallelStream() .filter((e) -> e.getSalary() >= 5000) .skip(2) .forEach(System.out::println); } @Test public void test6(){ emps.stream() .distinct() .forEach(System.out::println); }
map:接收 Lambda ,将元素转换为其他形式或提取信息;接受一个函数作为参数,该函数会被应用到每个元素上,并将其映射成一个新的元素
flatMap:接收一个函数作为参数,将流中每一个值都换成另一个流,然后把所有流重新连接成一个流
@Test public void test02(){ List<String> list = Arrays.asList("a", "b", "c"); list.stream() .map((str) -> str.toUpperCase()) .forEach(System.out::println); } public Stream<Character> filterCharacter(String str){ List<Character> list = new ArrayList<>(); for (char c : str.toCharArray()) { list.add(c); } return list.stream(); } @Test public void test03(){ List<String> list = Arrays.asList("a", "b", "c"); TestStreamaAPI test02= new TestStreamaAPI (); //如果用map list.stream() .Map(test02::filterCharacter) .forEach((sm)->{ sm.forEach(System.out::println); }); //用flatMap list.stream() .flatMap(test02::filterCharacter) .forEach(System.out::println); }
sorted():自然排序
sorted(Comparator c):定制排序
@Test public void test04(){ List<Integer> list = Arrays.asList(1,2,3,4,5); list.stream() .sorted() //comparaTo() .forEach(System.out::println); } @Test public void test05(){ emps.stream() .sorted((e1, e2) -> { //compara() if (e1.getAge().equals(e2.getAge())){ return e1.getName().compareTo(e2.getName()); } else { return e1.getAge().compareTo(e2.getAge()); } }) .forEach(System.out::println); } }
allMatch:检查是否匹配所有元素
anyMatch:检查是否至少匹配一个元素
noneMatch:检查是否没有匹配所有元素
findFirst:返回第一个元素
findAny:返回当前流中的任意元素
count:返回流中元素的总个数
max:返回流中最大值
min:返回流中最小值
public enum Status { FREE, BUSY, VOCATION; } @Test public void test01(){ List<Status> list = Arrays.asList(Status.FREE, Status.BUSY, Status.VOCATION); boolean flag1 = list.stream() .allMatch((s) -> s.equals(Status.BUSY)); System.out.println(flag1); boolean flag2 = list.stream() .anyMatch((s) -> s.equals(Status.BUSY)); System.out.println(flag2); boolean flag3 = list.stream() .noneMatch((s) -> s.equals(Status.BUSY)); System.out.println(flag3); // 避免空指针异常 Optional<Status> op1 = list.stream() .findFirst(); // 如果Optional为空 找一个替代的对象 Status s1 = op1.orElse(Status.BUSY); System.out.println(s1); Optional<Status> op2 = list.stream() .findAny(); System.out.println(op2); long count = list.stream() .count(); System.out.println(count); }
归约:reduce(T identity, BinaryOperator) / reduce(BinaryOperator) 可以将流中的数据反复结合起来,得到一个值
收集:collect 将流转换成其他形式;接收一个 Collector 接口的实现,用于给流中元素做汇总的方法
/** * Java: * - reduce:需提供默认值(初始值) * Kotlin: * - fold:不需要默认值(初始值) * - reduce:需提供默认值(初始值) */ @Test public void test01(){ List<Integer> list = Arrays.asList(1, 2, 3, 4, 5, 6, 7, 8, 9); Integer integer = list.stream() .reduce(0, (x, y) -> x + y); System.out.println(integer); } @Test public void test02(){ //放入List List<String> list = emps.stream() .map(Employee::getName) .collect(Collectors.toList()); list.forEach(System.out::println); //放入Set Set<String> set = emps.stream() .map(Employee::getName) .collect(Collectors.toSet()); set.forEach(System.out::println); //放入LinkedHashSet LinkedHashSet<String> linkedHashSet = emps.stream() .map(Employee::getName) .collect(Collectors.toCollection(LinkedHashSet::new)); linkedHashSet.forEach(System.out::println); } @Test public void test03(){ //总数 Long count = emps.stream() .collect(Collectors.counting()); System.out.println(count); //平均值 Double avg = emps.stream() .collect(Collectors.averagingDouble(Employee::getSalary)); System.out.println(avg); //总和 Double sum = emps.stream() .collect(Collectors.summingDouble(Employee::getSalary)); System.out.println(sum); //最大值 Optional<Employee> max = emps.stream() .collect(Collectors.maxBy((e1, e2) -> Double.compare(e1.getSalary(), e2.getSalary()))); System.out.println(max.get()); //最小值 Optional<Double> min = emps.stream() .map(Employee::getSalary) .collect(Collectors.minBy(Double::compare)); System.out.println(min.get()); } @Test public void test04(){ //分组 Map<Integer, List<Employee>> map = emps.stream() .collect(Collectors.groupingBy(Employee::getId)); System.out.println(map); //多级分组 Map<Integer, Map<String, List<Employee>>> mapMap = emps.stream() .collect(Collectors.groupingBy(Employee::getId, Collectors.groupingBy((e) -> { if (e.getAge() > 35) { return "开除"; } else { return "继续加班"; } }))); System.out.println(mapMap); //分区 Map<Boolean, List<Employee>> listMap = emps.stream() .collect(Collectors.partitioningBy((e) -> e.getSalary() > 4321)); System.out.println(listMap); } @Test public void test05(){ //总结 DoubleSummaryStatistics dss = emps.stream() .collect(Collectors.summarizingDouble(Employee::getSalary)); System.out.println(dss.getMax()); System.out.println(dss.getMin()); System.out.println(dss.getSum()); System.out.println(dss.getCount()); System.out.println(dss.getAverage()); //连接 String str = emps.stream() .map(Employee::getName) .collect(Collectors.joining("-")); //可传入分隔符 System.out.println(str); }
案例一: 给定一个数字列表,如何返回一个由每个数的平方构成的列表呢?(如:给定【1,2,3,4,5】,返回【1,4,9,16,25】)
@Test public void test01(){ List<Integer> list = Arrays.asList(1, 2, 3, 4, 5); list.stream() .map((x) -> x * x) .forEach(System.out::println); }
案例二: 怎样使用 map 和 reduce 数一数流中有多少个 Employee 呢?
List<Employee> emps = Arrays.asList( new Employee(101, "Z3", 19, 9999.99), new Employee(102, "L4", 20, 7777.77), new Employee(103, "W5", 35, 6666.66), new Employee(104, "Tom", 44, 1111.11), new Employee(105, "Jerry", 60, 4444.44) ); @Test public void test02(){ Optional<Integer> result = emps.stream() .map((e) -> 1) .reduce(Integer::sum); System.out.println(result.get());
案例三:
public class TestTransaction { List<Transaction> transactions = null; @Before public void before(){ Trader raoul = new Trader("Raoul", "Cambridge"); Trader mario = new Trader("Mario", "Milan"); Trader alan = new Trader("Alan", "Cambridge"); Trader brian = new Trader("Brian", "Cambridge"); transactions = Arrays.asList( new Transaction(brian, 2011, 300), new Transaction(raoul, 2012, 1000), new Transaction(raoul, 2011, 400), new Transaction(mario, 2012, 710), new Transaction(mario, 2012, 700), new Transaction(alan, 2012, 950) ); } //1. 找出2011年发生的所有交易, 并按交易额排序(从低到高) @Test public void test1(){ transactions.stream() .filter((t) -> t.getYear() == 2011) .sorted((t1, t2) -> Integer.compare(t1.getValue(), t2.getValue())) .forEach(System.out::println); } //2. 交易员都在哪些不同的城市工作过? @Test public void test2(){ transactions.stream() .map((t) -> t.getTrader().getCity()) .distinct() .forEach(System.out::println); } //3. 查找所有来自剑桥的交易员,并按姓名排序 @Test public void test3(){ transactions.stream() .filter((t) -> t.getTrader().getCity().equals("Cambridge")) .map(Transaction::getTrader) .sorted((t1, t2) -> t1.getName().compareTo(t2.getName())) .distinct() .forEach(System.out::println); } //4. 返回所有交易员的姓名字符串,按字母顺序排序 @Test public void test4(){ transactions.stream() .map((t) -> t.getTrader().getName()) .sorted() .forEach(System.out::println); System.out.println("-----------------------------------"); String str = transactions.stream() .map((t) -> t.getTrader().getName()) .sorted() .reduce("", String::concat); System.out.println(str); System.out.println("------------------------------------"); transactions.stream() .map((t) -> t.getTrader().getName()) .flatMap(TestTransaction::filterCharacter) .sorted((s1, s2) -> s1.compareToIgnoreCase(s2)) .forEach(System.out::print); } public static Stream<String> filterCharacter(String str){ List<String> list = new ArrayList<>(); for (Character ch : str.toCharArray()) { list.add(ch.toString()); } return list.stream(); } //5. 有没有交易员是在米兰工作的? @Test public void test5(){ boolean bl = transactions.stream() .anyMatch((t) -> t.getTrader().getCity().equals("Milan")); System.out.println(bl); } //6. 打印生活在剑桥的交易员的所有交易额 @Test public void test6(){ Optional<Integer> sum = transactions.stream() .filter((e) -> e.getTrader().getCity().equals("Cambridge")) .map(Transaction::getValue) .reduce(Integer::sum); System.out.println(sum.get()); } //7. 所有交易中,最高的交易额是多少 @Test public void test7(){ Optional<Integer> max = transactions.stream() .map((t) -> t.getValue()) .max(Integer::compare); System.out.println(max.get()); } //8. 找到交易额最小的交易 @Test public void test8(){ Optional<Transaction> op = transactions.stream() .min((t1, t2) -> Integer.compare(t1.getValue(), t2.getValue())); System.out.println(op.get()); } }
public class ForkJoinCalculate extends RecursiveTask<Long> { private static final long serialVersionUID = 1234567890L; private long start; private long end; private static final long THRESHPLD = 10000; public ForkJoinCalculate(long start, long end) { this.start = start; this.end = end; } @Override protected Long compute() { long length = end - start; if (length <= THRESHPLD) { long sum = 0; for (long i = start; i <= end; i++) { sum += i; } } else { long middle = (start + end) / 2; ForkJoinCalculate left = new ForkJoinCalculate(start, end); left.fork(); //拆分子任务 压入线程队列 ForkJoinCalculate right = new ForkJoinCalculate(middle + 1, end); right.fork(); return left.join() + right.join(); } return null; } } public class TestForkJoin { /** * ForkJoin 框架 */ @Test public void test01(){ Instant start = Instant.now(); ForkJoinPool pool = new ForkJoinPool(); ForkJoinCalculate task = new ForkJoinCalculate(0, 100000000L); Long sum = pool.invoke(task); System.out.println(sum); Instant end = Instant.now(); System.out.println(Duration.between(start, end).getNano()); } /** * 普通 for循环 */ @Test public void test02(){ Instant start = Instant.now(); Long sum = 0L; for (long i = 0; i < 100000000L; i++) { sum += i; } Instant end = Instant.now(); System.out.println(Duration.between(start, end).getNano()); } }