stream流的使用

清疚 2024-03-31 10:36 14阅读 0赞

参考博客：https://blog.csdn.net/zhuweifeng/article/details/117995217

### anyMatch ###

![在这里插入图片描述][40635c00c02f4a50bd13502fe48b4af4.png]  
eg.  
void stream\_anyMatch() \{

List<Integer> list = List.of(2,5,8,9,4,20,11,43,55);
    
        boolean bo = list.stream().anyMatch(a -> a>11);
    
        System.out.println(bo);
    
        boolean bo2 = list.stream().anyMatch(a -> a>110);
    
        System.out.println(bo2);

### Collectors.toMap ###

![在这里插入图片描述][33c0650533f443e98daf5e2820121439.png]  
![在这里插入图片描述][cc9b5182796e46abad1cfbab1e922a95.png]  
**使用lambda表达式中Collectors.toMap()方法将一个list转化成一个Map**：  
![在这里插入图片描述][403c0404a037493db16b097c85776a6a.png]  
![在这里插入图片描述][82f37af68aad47dfb49058cdead7bd5a.png]  
![在这里插入图片描述][884221bfc74142a98da7606e8f499794.png]

### Collectors.groupingBy ###

![在这里插入图片描述][6279172c08c143e29f508a9e8901189b.png]  
**分组**  
按照类目分组：  
Map<String, List> prodMap= prodList.stream().collect(Collectors.groupingBy(Product::getCategory));

//\{“啤酒”:\[\{“category”:“啤酒”,“id”:4,“name”:“青岛啤酒”,“num”:3,“price”:10\},\{“category”:“啤酒”,“id”:5,“name”:“百威啤酒”,“num”:10,“price”:15\}\],“零食”:\[\{“category”:“零食”,“id”:1,“name”:“面包”,“num”:1,“price”:15.5\},\{“category”:“零食”,“id”:2,“name”:“饼干”,“num”:2,“price”:20\},\{“category”:“零食”,“id”:3,“name”:“月饼”,“num”:3,“price”:30\}\]\}  
按照几个属性拼接分组：  
Map<String, List> prodMap = prodList.stream().collect(Collectors.groupingBy(item -> item.getCategory() + “\_” + item.getName()));

//\{“零食\_月饼”:\[\{“category”:“零食”,“id”:3,“name”:“月饼”,“num”:3,“price”:30\}\],“零食\_面包”:\[\{“category”:“零食”,“id”:1,“name”:“面包”,“num”:1,“price”:15.5\}\],“啤酒\_百威啤酒”:\[\{“category”:“啤酒”,“id”:5,“name”:“百威啤酒”,“num”:10,“price”:15\}\],“啤酒\_青岛啤酒”:\[\{“category”:“啤酒”,“id”:4,“name”:“青岛啤酒”,“num”:3,“price”:10\}\],“零食\_饼干”:\[\{“category”:“零食”,“id”:2,“name”:“饼干”,“num”:2,“price”:20\}\]\}  
根据不同条件分组  
Map<String, List> prodMap= prodList.stream().collect(Collectors.groupingBy(item -> \{  
if(item.getNum() < 3) \{  
return “3”;  
\}else \{  
return “other”;  
\}  
\}));

//\{“other”:\[\{“category”:“零食”,“id”:3,“name”:“月饼”,“num”:3,“price”:30\},\{“category”:“啤酒”,“id”:4,“name”:“青岛啤酒”,“num”:3,“price”:10\},\{“category”:“啤酒”,“id”:5,“name”:“百威啤酒”,“num”:10,“price”:15\}\],“3”:\[\{“category”:“零食”,“id”:1,“name”:“面包”,“num”:1,“price”:15.5\},\{“category”:“零食”,“id”:2,“name”:“饼干”,“num”:2,“price”:20\}\]\}

多级分组  
要实现多级分组，我们可以使用一个由双参数版本的Collectors.groupingBy工厂方法创 建的收集器，它除了普通的分类函数之外，还可以接受collector类型的第二个参数。那么要进 行二级分组的话，我们可以把一个内层groupingBy传递给外层groupingBy，并定义一个为流 中项目分类的二级标准。  
Map<String, Map<String, List>> prodMap= prodList.stream().collect(Collectors.groupingBy(Product::getCategory, Collectors.groupingBy(item -> \{  
if(item.getNum() < 3) \{  
return “3”;  
\}else \{  
return “other”;  
\}  
\})));

//\{“啤酒”:\{“other”:\[\{“category”:“啤酒”,“id”:4,“name”:“青岛啤酒”,“num”:3,“price”:10\},\{“category”:“啤酒”,“id”:5,“name”:“百威啤酒”,“num”:10,“price”:15\}\]\},“零食”:\{“other”:\[\{“category”:“零食”,“id”:3,“name”:“月饼”,“num”:3,“price”:30\}\],“3”:\[\{“category”:“零食”,“id”:1,“name”:“面包”,“num”:1,“price”:15.5\},\{“category”:“零食”,“id”:2,“name”:“饼干”,“num”:2,“price”:20\}\]\}\}

**按子组收集数据**  
求总数  
Map<String, Long> prodMap = prodList.stream().collect(Collectors.groupingBy(Product::getCategory, Collectors.counting()));

//\{“啤酒”:2,“零食”:3\}  
求和

Map<String, Integer> prodMap = prodList.stream().collect(Collectors.groupingBy(Product::getCategory, Collectors.summingInt(Product::getNum)));

//\{“啤酒”:13,“零食”:6\}

把收集器的结果转换为另一种类型

Map<String, Product> prodMap = prodList.stream().collect(Collectors.groupingBy(Product::getCategory, Collectors.collectingAndThen(Collectors.maxBy(Comparator.comparingInt(Product::getNum)), Optional::get)));

//\{“啤酒”:\{“category”:“啤酒”,“id”:5,“name”:“百威啤酒”,“num”:10,“price”:15\},“零食”:\{“category”:“零食”,“id”:3,“name”:“月饼”,“num”:3,“price”:30\}\}

联合其他收集器  
Map<String, Set> prodMap = prodList.stream().collect(Collectors.groupingBy(Product::getCategory, Collectors.mapping(Product::getName, Collectors.toSet())));

//\{“啤酒”:\[“青岛啤酒”,“百威啤酒”\],“零食”:\[“面包”,“饼干”,“月饼”\]\}

### Function.identity()的含义 ###

![在这里插入图片描述][4080535124644b2bb270f4a16c935e14.png]  
![在这里插入图片描述][6faf9d9bdc964cfbb73fdc5b4b082c3f.png]  
![在这里插入图片描述][7836224eb33c4a8895fb3e8673d1f01f.png]

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