Java8之Stream 集合聚合操作集锦(含日常练习Demo)

        Stream 是用函数式编程方式在集合类上进行复杂操作的工具,其集成了Java 8中的众多新特性之一的聚合操作,开发者可以更容易地使用Lambda表达式,并且更方便地实现对集合的查找、遍历、过滤以及常见计算等。

直接上代码:

基础实体类:

练习代码:

        public static void main(String[] args) {
		Student stuA = new Student(1, "A", "M", 184);
		Student stuB = new Student(2, "B", "G", 163);
		Student stuC = new Student(3, "C", "M", 175);
		Student stuD = new Student(4, "D", "G", 158);
		Student stuE = new Student(5, "A", "M", 158);
		List<Student> list = new ArrayList<>();
		list.add(stuA);
		list.add(stuB);
		list.add(stuC);
		list.add(stuD);
		list.add(stuE);
		
		// stream-forEach循环
		System.out.println("***********stream-forEach***********");
		list.stream().forEach(stu -> System.out.println("stream-forEach: " + stu.getName()));
		
		// stream-filter过滤即执行逻辑
		System.out.println("***********stream-filter count***********");
		long count = list.stream().filter(stu -> stu.height > 180).count();
		list.stream().filter(stu -> stu.height > 180)
		             .forEach(stu -> System.out.println("stream-filter: " + stu));
		
		// Stream-toMap 为了避免key冲突情况,(key1, key2) -> key1 表示冲突时取前者
		System.out.println("***********Stream-toMap 字段:对象***********");
		Map<String, Student> maps = list.stream()
				.collect(Collectors.toMap(Student::getName, Function.identity(), (key1, key2) -> key1));
		System.out.println("key-对象" + maps);
		
		Map<String, Object> newMaps = list.stream()
				.collect(Collectors.toMap(Student::getName, Student::getHeight, (key1, key2) -> key1));
		System.out.println("key-字段" + newMaps);
		
		// Stream-distinct 去重
		System.out.println("***********Stream-distinct去重  必须重写equals和hashcode方法***********");
		list.stream()
			.distinct()
			.forEach(b -> System.out.println("Stream-distinct去重  " + b.getName()+ "," + b.getHeight()));
		
		list.stream()
			.filter(StreamUtil.distinctByKey(b -> b.getSex()))
			.forEach(b -> System.out.println("Stream-distinct指定字段去重  " + b.getName()+ "," + b.getSex())); 
		
		// 过滤后得到新集合
		System.out.println("***********Stream操作后获取聚合集合***********");
		List<Student> newList = list.stream().filter(stu -> stu.height > 165)
											 .collect(Collectors.toList());
		System.out.println("新集合: " + newList);
		
		// stream-聚合操作  最大值,最小值
		System.out.println("**************stream-聚合操作  最大值,最小值************");
		System.out.println("sum: " + list.stream().mapToDouble(Student::getHeight).sum());
		System.out.println("max: " + list.stream().mapToDouble(Student::getHeight).max().getAsDouble());
		System.out.println("min: " + list.stream().mapToDouble(Student::getHeight).min().getAsDouble());
		System.out.println("avg: " + list.stream().mapToDouble(Student::getHeight).average().getAsDouble());
		
		// Stream排序
		System.out.println("**************stream-聚合操作  排序************");
		List<Student> collect = list.stream().filter(stu -> stu.getHeight() > 165)
					 .sorted((e1,e2) -> Float.compare(e1.getHeight(), e2.getHeight()))
					 .collect(Collectors.toList());
		System.out.println("stream 排序" + collect);
	}

指定字段去重:

public class StreamUtil {
	
	/**
	 * 指定字段去重
	 * @param keyExtractor
	 * @return
	 */
	static <T> Predicate<T> distinctByKey(Function<? super T, ?> keyExtractor) {
	        Map<Object,Boolean> seen = new ConcurrentHashMap<>();
	        return t -> seen.putIfAbsent(keyExtractor.apply(t), Boolean.TRUE) == null;
	} 

}

日常练习Demo:

package com.mine.stream;

import java.util.Arrays;
import java.util.Collections;
import java.util.Comparator;
import java.util.List;
import java.util.stream.Collectors;

/**
 * 
 * @author 柯贤铭
 * @date   2019年3月22日
 * @email  [email protected]
 */
public class TestForStream {

	public static void main(String[] args) {
		List<Transaction> transactions = null;
		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, 400),
				new Transaction(mario, 2012, 710),
				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)
		// 方式一:
		Long begin = System.currentTimeMillis();
		List<Transaction> newTr = transactions.stream().filter(tran -> tran.getYear() == 2011)
				                              .collect(Collectors.toList());
		newTr.sort(Comparator.comparing(t -> t.getValue()));
		Long end = System.currentTimeMillis();
		System.out.println("耗时: " + (end - begin) + " " + newTr);
		
		// 方式二: 差距是35倍左右!
		Long begin2 = System.currentTimeMillis();
		List<Transaction> collect = transactions.stream().filter(tran -> tran.getYear() == 2011)
												 .sorted((e1,e2) -> Integer.compare(e1.getValue(), e2.getValue()))
												 .collect(Collectors.toList());
		Long end2 = System.currentTimeMillis();
		System.out.println("耗时: " + (end2 - begin2) + " " + collect);
		
		// ②交易员都在哪些不同的城市工作过?
		// 方式一:
		transactions.stream()
					.filter(StreamUtil.distinctByKey(tran -> tran.getTrader().getCity()))
					.collect(Collectors.toList())
					.forEach(t -> System.out.println(t.getTrader().getCity()));
		
		// 方式二:
		List<String> collCityTwo = transactions.stream()
											.map(e -> e.getTrader().getCity())
											.distinct()
											.collect(Collectors.toList());
		System.out.println("城市为: " + collCityTwo);
		
		//③查找所有来自剑桥的交易员,并按姓名排序
		List<Trader> collPerson = transactions.stream().filter(tran -> tran.getTrader().getCity().equals("Cambridge"))
											  .map(Transaction::getTrader)
											  .sorted((e1,e2) -> e1.getName().compareTo(e2.getName()))
											  .collect(Collectors.toList());
		System.out.println(collPerson);
		
		// ⑤有没有交易员是在米兰工作的?
		long count = transactions.stream().filter(tran -> tran.getTrader().getCity().equals("Milan")).count();
		System.out.println("是否有人在米兰工作: " + (count > 0));
		
		// ⑥打印生活在剑桥的交易员的所有交易额总和
		int sum = transactions.stream()
				              .filter(e -> e.getTrader().getCity().equals("Cambridge"))
				              .mapToInt(Transaction::getValue)
				              .sum();
		System.out.println("总额为: " + sum);
		
		// ⑦所有交易中,最高的交易额是多少
		int max = transactions.stream()
	              .mapToInt(Transaction::getValue)
	              .max()
	              .getAsInt();
		System.out.println("最大值是: " + max);
		
		// ⑧找到交易额最小的交易
		Transaction transaction = transactions.stream()
								              .min((e1,e2) -> Integer.compare(e1.getValue(), e2.getValue()))
								              .get();
		System.out.println("最小值交易是: " + transaction);
	}
}


class Trader {
	private String name;
	private String city;
	public String getName() {
		return name;
	}
	public void setName(String name) {
		this.name = name;
	}
	public String getCity() {
		return city;
	}
	public void setCity(String city) {
		this.city = city;
	}
	@Override
	public String toString() {
		return "Trader [name=" + name + ", city=" + city + "]";
	}
	public Trader(String name, String city) {
		super();
		this.name = name;
		this.city = city;
	}
}

class Transaction {
	private Trader trader;
	private int year;
	private int value;
	public Trader getTrader() {
		return trader;
	}
	public void setTrader(Trader trader) {
		this.trader = trader;
	}
	public int getYear() {
		return year;
	}
	public void setYear(int year) {
		this.year = year;
	}
	public int getValue() {
		return value;
	}
	public void setValue(int value) {
		this.value = value;
	}
	@Override
	public String toString() {
		return "Transaction [trader=" + trader + ", year=" + year + ", value=" + value + "]";
	}
	public Transaction(Trader trader, int year, int value) {
		super();
		this.trader = trader;
		this.year = year;
		this.value = value;
	}
}

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转载自blog.csdn.net/weixin_40834464/article/details/88744807