JDK1.8的新特性之Stream流的使用

package com.ilike.test;

import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import java.util.Random;
import java.util.stream.Stream;
import org.junit.Test;

/**
*
* @author 桑伟东
*
* Stream的三个操作步骤：
*
* 1.创建Stream
*
* 2.中间操作
*
* 3.终止操作(终端操作)
*
*
*/
public class TestStreamApi1 {

//创建Stream@Testpublic void test1(){    //1.可以通过Collection系列集合提供的Stream()或parallelStream    List<String> list=new ArrayList<String>();    Stream<String> stream=  list.stream();    //2.通过Arrays的静态方法stream获取数组流    Student[] students=new Student[10];    Stream<Student> stream2=Arrays.stream(students);    //3.通过Stream中的of()静态方法也可以获取流    Stream<String> stream3=Stream.of("aa","bb","cc");    //4.创建无限流    //迭代    Stream<Integer> stream4=Stream.iterate(0, (x)->x+2);    stream4.limit(10).forEach(System.out::println);    //生成    Stream.generate(()-> new Random().nextInt(100)).limit(10).forEach(System.out::println);}

}

package com.ilike.test;

import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import java.util.stream.Stream;

import org.junit.Test;

/**
*
* @author 桑伟东
*
* Stream的三个操作步骤：
*
* 1.创建Stream
*
* 2.中间操作
*
* 3.终止操作(终端操作)
*
*
*/
public class TestStreamApi2 {

List<Student> students=Arrays.asList(        new Student("张三", 23),        new Student("李四", 38),        new Student("王五", 55),        new Student("赵六", 18),        new Student("田七", 29),        new Student("田七", 29),        new Student("田七", 29));//中间操作/** * 排序 * sorted()——自然排序(Comparable) * sorted(Comparator com)——定制排序(Comparator) */@Testpublic void test5() {    List<String> list=Arrays.asList("aaa","bbb","ccc","ddd","eee");    list.stream()    .sorted()    .forEach(System.out::println);    System.out.println("----------------------");    students.stream()    .sorted((s1,s2)->{        if(s1.getAge().equals(s2.getAge())){            return s1.getName().compareTo(s2.getName());        }else{            return -s1.getAge().compareTo(s2.getAge());        }    })    .forEach(System.out::println);    }/** * 映射 * map——接受lambda ,将元素转换成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——接受一个函数作为参数，将流中的每一个值都换成另一个流，然后把所有流连接成一个流 */@Testpublic void test4() {    List<String> list=Arrays.asList("aaa","bbb","ccc","ddd","eee");    //流操作    list.stream()    .map((str)->str.toUpperCase())    .forEach(System.out::println);    System.out.println("----------------------");    students.stream()    .map(Student::getName)    .forEach(System.out::println);    System.out.println("----------------------");    Stream<Stream<Character>> stream=list.stream()            .map(TestStreamApi2::filterCharacter);    stream.forEach((sm)->{        sm.forEach(System.out::println);    });    System.out.println("----------------------");    Stream<Character> stream2=  list.stream()    .flatMap(TestStreamApi2::filterCharacter);    stream2.forEach(System.out::println);}public static Stream<Character> filterCharacter(String str) {    List<Character> list=new ArrayList<Character>();    for (Character ch : str.toCharArray()) {        list.add(ch);    }    return list.stream();}/** * 筛选与切片 * filter——接受lambda ，从流中排除某些元素 * limit—— 阶段流，使其不超过指定数量 * 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互补 * distinct——筛选，通过硫所生成元素的hashCode()和equals去除重复元素 *  */@Testpublic void test3() {students.stream()    .filter((s)->{        System.out.println("短路！");        return s.getAge()>25;    })    .skip(2)    .distinct()    .forEach(System.out::println);}@Testpublic void test2() {students.stream()    .filter((s)->{        System.out.println("短路！");        return s.getAge()>25;    })    .limit(2)    .forEach(System.out::println);}//内部迭代:迭代操作有Stream API完成@Testpublic void test1() {    //1.获取流    Stream<Student> stream=students.stream()     //2.中间操作：不会执行任何操作    .filter((s)->{        System.out.println("StreamAPI的中间操作！");        return s.getAge()>35;    });    //3.终止操作:一次性执行全部的内容,"即惰性求值"    stream.forEach(System.out::println);}

}

package com.ilike.test;

import java.util.Arrays;
import java.util.DoubleSummaryStatistics;
import java.util.HashSet;
import java.util.List;
import java.util.Map;
import java.util.Optional;
import java.util.Set;
import java.util.concurrent.ConcurrentMap;
import java.util.stream.Collectors;
import org.junit.Test;

import com.ilike.test.Student.Status;

/**
*
* @author 桑伟东
*
* 终止操作
*
*/
public class TestStreamApi3 {
List students=Arrays.asList(
new Student(“张三”, 23,5555,Status.BUSY),
new Student(“李四”, 38,6666,Status.FREE),
new Student(“王五”, 55,8888,Status.VOCATION),
new Student(“赵六”, 18,7777,Status.FREE),
new Student(“田七”, 29,9999,Status.BUSY),
new Student(“田七”, 29,9999,Status.BUSY));

/** * 收集 * collect——将流转换为其他形式。接收一个Collector接口的实现，用于给Stream中元素做汇总的方法 */ @Testpublic void test10() {    String str= students.stream()             .map(Student::getName)             .collect(Collectors.joining(","));    System.out.println(str); } @Testpublic void test9() {DoubleSummaryStatistics dss= students.stream()             .collect(Collectors.summarizingDouble(Student::getSalary));System.out.println(dss.getAverage());System.out.println(dss.getMax());System.out.println(dss.getCount());System.out.println(dss.getSum()); }//分区 @Test    public void test8() {     Map<Boolean, List<Student>> map=students.stream().collect(Collectors.partitioningBy((s)-> s.getSalary()>7000));     System.out.println(map); }//多级分组 @Test    public void test7() {     Map<Status, ConcurrentMap<String, List<Student>>> map= students.stream()             .collect(Collectors.groupingBy(Student::getStatus, Collectors.groupingByConcurrent((s)->{                 if(((Student)s).getAge()<=35){                     return "青年";                 }else if(((Student)s).getAge()<=50){                     return "中年";                 }else{                     return "老年";                 }             })));     System.out.println(map); }//分组 @Test    public void test6() {     Map<Status, List<Student>>  map= students.stream()             .collect(Collectors.groupingBy(Student::getStatus));     System.out.println(map); } @Test    public void test5() {     //总数    long count=students.stream().collect(Collectors.counting());    System.out.println(count);     System.out.println("-------------------------------");    //平均值    Double avg=students.stream().collect(Collectors.averagingDouble(Student::getSalary));    System.out.println(avg);     System.out.println("-------------------------------");     //总和     Double sum= students.stream().collect(Collectors.summingDouble(Student::getSalary));     System.out.println(sum);     System.out.println("-------------------------------");     //最大值     Optional<Student> optional=students.stream()             .collect(Collectors.maxBy((s1,s2)-> Integer.compare(s1.getSalary(), s2.getSalary())));     System.out.println(optional.get());     //最小值     Optional<Integer> optional2= students.stream()             .map(Student::getSalary)             .collect(Collectors.minBy(Integer::compare));     System.out.println(optional2.get()); } @Test    public void test4() {     List<String> names= students.stream()     .map(Student::getName)     .collect(Collectors.toList());     names.forEach(System.out::println);     System.out.println("-------------------------------");     Set<String> set= students.stream()             .map(Student::getName)             .collect(Collectors.toSet());     set.forEach(System.out::println);     System.out.println("-------------------------------");     HashSet<String> set2= students.stream()             .map(Student::getName)             .collect(Collectors.toCollection(HashSet::new));     set2.forEach(System.out::println); }/** * 归约 * reduce(T identity,BinaryOperator ) /reduce(BinaryOperator)——可以将流中元素反复结合起来，得到一个值 */ @Test    public void test3() {     List<Integer> list=Arrays.asList(1,2,3,4,5,6,7,8,9,10);     Integer  sum= list.stream().reduce(0, (x,y)->x+y);     System.out.println(sum);     System.out.println("-------------------------------");     Optional<Integer> optional  = students.stream().map(Student::getSalary).reduce(Integer::sum);     System.out.println(optional.get()); }/** * 查找与匹配 * 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 * findFoirst——返回第一个元素 * findAny——返回流中的任意元素 * count——返回流中元素的总个数 * max——返回流中元素的最大值 * min——返回流中元素的最小值 *///统计相关 @Test    public void test2() {    Long long1= students.stream().count();    System.out.println(long1);    Optional<Student> optional=students.stream()            .max((s1,s2)->Integer.compare(s1.getSalary(), s2.getSalary()));    System.out.println(optional.get());    Optional<Integer> optional2=    students.stream()    .map(Student::getAge)    .min(Integer::compare);    System.out.println(optional2.get()); }@Testpublic void test1() {    boolean b=  students.stream().allMatch((s)->s.getStatus().equals(Status.BUSY));    System.out.println(b);    System.out.println("-----------------------------------");    boolean b2=students.stream().anyMatch((s)->s.getStatus().equals(Status.BUSY));    System.out.println(b2);    System.out.println("-----------------------------------");    boolean b3=students.stream().noneMatch((s)->s.getStatus().equals(Status.BUSY));    System.out.println(b3);    System.out.println("-----------------------------------");    //按工资排序，并返回第一个    Optional<Student> opt=students.stream().sorted((s1,s2)->{        return -s1.getSalary().compareTo(s2.getSalary());    }).findFirst();    System.out.println(opt.get());    System.out.println("-----------------------------------");    //找一个空闲的人    Optional<Student> opt2=students.parallelStream()     .filter((s)->s.getStatus().equals(Status.FREE))     .findAny();    System.out.println(opt2.get());}

}