上期对stream流大致总结了一下，后面又做了一些练习，大家可以参考一下。
- 首先需要建一个 Product的实体类，后面会用到
@Data
@AllArgsConstructor
@NoArgsConstructor
public class Product {
private Long id;
private Integer num;
private BigDecimal price;
private String name;
private String category;
}
- 下面是一些具体的案例
Product prod1 = new Product(1L, 1, new BigDecimal("15.5"), "面包", "零食");
Product prod2 = new Product(2L, 2, new BigDecimal("20"), "饼干", "零食");
Product prod3 = new Product(3L, 3, new BigDecimal("30"), "月饼", "零食");
Product prod4 = new Product(4L, 3, new BigDecimal("10"), "青岛啤酒", "啤酒");
Product prod5 = new Product(5L, 10, new BigDecimal("15"), "百威啤酒", "啤酒");
List<product> proList = Lists.newArrayList(prod1,prod2,prod3,prod4,prod5);
@Test
public void testG(){
Map<string, list<product>> proMap = proList.stream().collect(Collectors.groupingBy(Product::getCategory));
for(Map.Entry<string,list<product>> entry : proMap.entrySet()){
System.out.println("key" + entry.getKey() + " value" + entry.getValue());
}
}
@Test
public void testCollect1(){
//求总数
Long sum = proList.stream().collect(Collectors.counting());
//求平均数量
Double averageNum = proList.stream().collect(Collectors.averagingInt(Product::getNum));
//求最高价格
Optional<bigdecimal> max = proList.stream()
.map(Product::getPrice)
.collect(Collectors.maxBy(BigDecimal::compareTo));
//求数量之和
Long collect = proList.stream().collect(Collectors.summingLong(Product::getNum));
//一次性统计所有信息
LongSummaryStatistics proLSS = proList.stream().collect(Collectors.summarizingLong(Product::getNum));
log.info("求总数:{}", sum);
log.info("求总求平均数量数:{}" ,averageNum);
log.info("求最高价格:{}" ,max.get());
log.info("求数量之和:{}" ,collect);
//System.out.println("求总数" + sum);
//System.out.println("求平均数量" + averageNum);
// System.out.println("求最高价格" + max);
// System.out.println("求数量之和" + collect);
System.out.println("一次性统计所有信息" + proLSS);
//将产品按数量是否大于5分区
Map<boolean, list<product>> partList = proList.stream().collect(Collectors.partitioningBy(n -> n.getNum() > 5));
log.info("按数量是否大于5分区:{}",partList);
//将产品按类别分组
Map<string, list<product>> groupList = proList.stream().collect(Collectors.groupingBy(p -> p.getCategory()));
Map<string, list<product>> groupList1 = proList.stream().collect(Collectors.groupingBy(Product::getCategory));
log.info("将产品按类别分组:{}",groupList);
log.info("将产品按类别分组:{}",groupList1);
}
@Test
public void testJoiningReducing(){
//将所有产品的 名称 拼接成一个字符串
String names = proList.stream().map(Product::getName).collect(Collectors.joining("_"));
log.info("所有产品名:{}",names);
List<string> strList = Arrays.asList("A", "B", "C", "D");
String strJoining = strList.stream().collect(Collectors.joining("+_+"));
log.info("字符串:{}",strJoining);
Integer collect = proList.stream().collect(Collectors.reducing(0, Product::getNum, (x, y) -> (x + y + 1)));
log.info("collect:{}",collect);
//stream中的reduce
Optional<integer> reduce = proList.stream().map(Product::getNum).reduce(Integer::compare);
log.info("stream->reduce:{}",reduce.get());
}
@Test
public void testSorted1(){
//按 数量升序排列
List<product> sortedList = proList.stream().sorted(Comparator.comparing(Product::getNum))
.collect(Collectors.toList());
log.info("sorted:{}",sortedList);
//按数量倒叙排
List<product> sortedListReversed = proList.stream().sorted(Comparator.comparing(Product::getNum).reversed())
.collect(Collectors.toList());
log.info("sored.reversed:{}",sortedListReversed);
//先按数量排，再按价格排 (默认升序）
List<product> collect = proList.stream().sorted(Comparator.comparing(Product::getNum).thenComparing(Product::getPrice))
.collect(Collectors.toList());
log.info("先按数量排，再按价格排 :{}",collect);
//先按数量排，再按价格排 (降序排）
List<product> collect1 = proList.stream()
.sorted(Comparator.comparing(Product::getNum).thenComparing(Product::getPrice).reversed())
.collect(Collectors.toList());
log.info("先按数量排，再按价格降序排 :{}",collect1);
//先按数量排 再按价格 自定义排
List<product> collect2 = proList.stream().sorted((p1, p2) -> {
if (p1.getNum() == p2.getNum()){
return p1.getPrice().compareTo(p2.getPrice()) ;
}else {
return p2.getNum() - p1.getNum();
}
}).collect(Collectors.toList());
log.info("先按数量排 再按价格 自定义排:{}",collect2);
}
//测试stream中reduce (规约 也成为缩减 是把一个流缩减成一个值 能实现对集合求和，求积 和求最值的操作)
@Test
public void testStreamReduce() {
//求商品 价格的总和 方式1
Optional<bigdecimal> sum = proList.stream().map(Product::getPrice)
.reduce((x, y) -> x.add(y));
log.info("求和:{}",sum.get());
//求商品 数量的总和 方式2
Optional<integer> sum1 = proList.stream().map(Product::getNum)
.reduce(Integer::sum);
log.info("求和:{}",sum1.get());
//求商品 价格的总和 方式2
Optional<bigdecimal> sum2 = proList.stream().map(Product::getPrice)
.reduce(BigDecimal::add);
log.info("求和sum2:{}",sum2.get());
//求商品 价格的总和 方式3
BigDecimal sum3 = proList.stream().map(Product::getPrice)
.reduce(new BigDecimal("0"),BigDecimal::add);
log.info("求和sum3:{}",sum3);
//求乘积
Optional<integer> product = proList.stream().map(Product::getNum).reduce((x, y) -> x * y);
log.info("乘积:{}",product);
//求最大值 方式 1
Optional<bigdecimal> maxPrice = proList.stream().map(Product::getPrice)
.reduce((x, y) -> x.compareTo(y) == 1 ? x : y);
log.info("商品价格的最大值:{}",maxPrice);
//求最大值 方式2
BigDecimal max2 = proList.stream().map(Product::getPrice)
.reduce(new BigDecimal(1), BigDecimal::max);
log.info("求 最大值 方式2:{}",max2);
}
</bigdecimal></integer></bigdecimal></integer></bigdecimal></product></product></product></product></product></integer></string></string,></string,></boolean,></bigdecimal></string,list<product></string,></product>
Original: https://www.cnblogs.com/huoyl/p/Java8Stream2.html
Author: h*z
Title: Java8Stream流2
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