Java8 Stream流多字段求和、汇聚的实例

2024-04-02 19:04:59 208人浏览泡泡鱼

Python 官方文档：入门教程 => 点击学习

摘要

目录Stream流多字段求和、汇聚实现方法对象类型数据处理Map类型数据处理Stream分组求和使用笔记分组求和使用Stream流多字段求和、汇聚实现方法利用 Collector

Stream流多字段求和、汇聚

实现方法

利用

Collectors.toMap(Function keyMapper, Function valueMapper, BinaryOperator mergeFunction)

keyMapper：代表你最终想要获得的Map<Key, Value> 的Key
valueMapper：代表你最终想要获得的Map<Key, Value> 的Value
mergeFunction：表示碰到Key冲突是处理过程，{x, y}中x是已汇聚对象，y表示当前处理对象

对象类型数据处理

public static Map<String, Model> streamGroupSum(List<Model> datas){
    return datas.stream().collect(Collectors.toMap(k -> k.getCode(), v -> v, (x, y) -> x.addCount().addAll(y)));
  }

Model

@Data
class Model{
    private String code;
    private int count = 0;
    private Integer sum1;
    private Integer sum2;
    public Model(String code, Integer sum1, Integer sum2){
      this.code = code;
      this.sum1 = sum1;
      this.sum2 = sum2;
    }
    public Model addCount(){
      this.count++;
      return this;
    }
    
    public Model addAll(Model y){
      return add(Model::setSum1, Model::getSum1, y)
          .add(Model::setSum2, Model::getSum2, y);
    }
    
    public Model add(BiConsumer<Model, Integer> set, Function<Model, Integer> get, Model y){
      set.accept(this, get.apply(this) + get.apply(y));
      return this;
    }
  }

Map类型数据处理

public static void main (String[] args) {
    List<Map<String, Object>> datas = getDatas();
    streamMapSum(datas);
  }
  public static Map<Object, Map<String, Object>> streamMapSum (List<Map<String, Object>> datas) {
    return datas.stream()
        .collect(Collectors.toMap(k -> k.get("name"), v -> {
              v.put("count", 1);
              return v;
            }
            , (x, y) -> {
             	x.put("count", (int) x.get("count") + 1);
             	x.put("aaa", (int) x.get("aaa") + (int) y.get("aaa"));
             	x.put("bbb", (int) x.get("bbb") + (int) y.get("bbb"));
             	x.put("ccc", (int) x.get("ccc") + (int) y.get("ccc"));
             	return x;
             	
             }
         )
    );
              
  }
  public static int add (Map<String, Object> x, Map<String, Object> y, String key) {
    return (int) x.get(key) + (int) y.get(key);
  }
  public static Map<String, Object> ofMap (Object... objs) {
    System.out.println("ofMap");
    Map<String, Object> map = new LinkedHashMap<>();
    for (int i = 0; i < objs.length; i = i + 2) {
      map.put(objs[i].toString(), objs[i + 1]);
    }
    return map;
  }
  public static List<Map<String, Object>> getDatas () {
    List<Map<String, Object>> list = new ArrayList<>();
    list.add(ofMap("name", "张三", "aaa", 3, "bbb", 5, "ccc", 6));
    list.add(ofMap("name", "张三", "aaa", 8, "bbb", 51, "ccc", 521));
    list.add(ofMap("name", "李四", "aaa", 9, "bbb", 53, "ccc", 23));
    return list;
  }

Stream分组求和使用笔记

话不多说，直接贴代码，分组使用

class Foo {
    private int code;
    private int count;
    public Foo(int code, int count) {
        this.code = code;
        this.count = count;
    }
    public int getCode() {
        return code;
    }
    public void setCode(int code) {
        this.code = code;
    }
    public int getCount() {
        return count;
    }
    public void setCount(int count) {
        this.count = count;
    }
}


public static void main(String[] args) {
        Foo foo1 = new Foo(1, 2);
        Foo foo2 = new Foo(2, 23);
        Foo foo3 = new Foo(2, 6);
        List<Foo> list = new ArrayList<>(4);
        list.add(foo1);
        list.add(foo2);
        list.add(foo3);
        Map<Integer, List<Foo>> collect = list.stream().collect(Collectors.groupingBy(Foo::getCode));
        List<Foo> list1 = collect.get(1);
        List<Foo> list2 = collect.get(2);
        list1.forEach(e -> System.out.println(e.getCode() + ":" + e.getCount()));
        System.out.println("-----------这里是分界线-----------------------------");
        list2.forEach(e -> System.out.println(e.getCode() + ":" + e.getCount()));
    }

输出结果：

1:2
-----------这里是分界线-----------------------------
2:23
2:6

分组求和使用

public static void main(String[] args) {
        Foo foo1 = new Foo(1, 2);
        Foo foo2 = new Foo(2, 23);
        Foo foo3 = new Foo(2, 6);
        List<Foo> list = new ArrayList<>(4);
        list.add(foo1);
        list.add(foo2);
        list.add(foo3);
        Map<Integer, IntSummaryStatistics> collect = list.stream().collect(Collectors.groupingBy(Foo::getCode, Collectors.summarizingInt(Foo::getCount)));
        IntSummaryStatistics statistics1 = collect.get(1);
        IntSummaryStatistics statistics2 = collect.get(2);
        System.out.println(statistics1.getSum());
        System.out.println(statistics1.getAverage());
        System.out.println(statistics1.getMax());
        System.out.println(statistics1.getMin());
        System.out.println(statistics1.getCount());
        System.out.println(statistics2.getSum());
        System.out.println(statistics2.getAverage());
        System.out.println(statistics2.getMax());
        System.out.println(statistics2.getMin());
        System.out.println(statistics2.getCount());
    }

输出结果：