10.流（五）- 收集器.md · 死牛胖子/tutorial-java8

### 收集器

#### 预定义收集器

##### 计数
```
list.stream().collect(Collectors.counting());
```
简洁一点
```
list.stream().count();
```

##### 最大值
```
List<Integer> list = Arrays.asList(2,1,3,4);
list.stream().collect(Collectors.maxBy(Integer::compareTo)).ifPresent(System.out::println);
```
简洁一点
```
list.stream().max(Integer::compareTo).ifPresent(System.out::println);
```

##### 最小值
```
List<Integer> list = Arrays.asList(2,1,3,4);
list.stream().collect(Collectors.minBy(Integer::compareTo)).ifPresent(System.out::println);
```
简洁一点
```
list.stream().min(Integer::compareTo).ifPresent(System.out::println);
```

##### 汇总
```
List<Integer> list = Arrays.asList(2,1,3,4);
list.stream().collect(Collectors.summingInt(i -> i));
```

##### 平均值
```
List<Integer> list = Arrays.asList(2,1,3,4);
list.stream().collect(Collectors.averagingInt(i -> i));
```

##### 多个值一次性获取
```
List<Integer> list = Arrays.asList(2,1,3,4);
IntSummaryStatistics summarizing = list.stream().collect(Collectors.summarizingInt(i -> i));
summarizing.getMax();
summarizing.getMin();
summarizing.getSum();
summarizing.getAverage();
summarizing.getCount();
```

##### 连接字符串
```
List<String> list = Arrays.asList("Hello", "World");
list.stream().collect(Collectors.joining(" "));
```

#### reducing收集器

> reducing(初始值, 转换函数, 操作函数)
> reducing(操作函数)

使用 reducing 收集器实现 sum
```
List<Integer> list = Arrays.asList(1, 2, 3, 4, 5);
int sum = list.stream().collect(Collectors.reducing(0, i -> i, Integer::sum));
```

**测试**

1、使用 reducing 实现 count \
2、使用 reducing 实现 max \
3、使用 reducing 实现 min

**答案**
```
// count
List<Integer> list = Arrays.asList(1, 2, 3, 4, 5);
int count = list.stream().collect(Collectors.reducing(0, i -> 1, Integer::sum));

// max
List<Integer> list = Arrays.asList(1, 2, 3, 4, 5);
int max = list.stream().collect(Collectors.reducing(Integer::max)).get();

// min
List<Integer> list = Arrays.asList(1, 2, 3, 4, 5);
int min = list.stream().collect(Collectors.reducing(Integer::min)).get();
```

**练习**

1、用reducing连接字符串

##### 分组
```
// 按颜色分组
Map<String, List<Apple>> dishesByType = list.stream().collect(groupingBy(Apple::getColor));
```

##### 个性化分组
```
// 按重量分组,50以下为轻，50-70为正常，80为重
Map<String, List<Apple>> map2 = list.stream().collect(Collectors.groupingBy(o -> {
    if (o.getWeight() <= 50) return "light";
    if (o.getWeight() > 50 && o.getWeight() <= 70) return "common";
    return "weight";
}));
```

##### 多级分组
对 groupingBy 进行嵌套使用
```
// 先按颜色分组，然后再按重量分组
Map<String, Map<String, List<Apple>>> map1 = list.stream().collect(Collectors.groupingBy(Apple::getColor, Collectors.groupingBy(o -> {
    if (o.getWeight() <= 50) return "light";
    if (o.getWeight() > 50 && o.getWeight() <= 70) return "common";
    return "weight";
})));
```

改变 groupingBy 的输出结果
```
// 查找每种颜色中的苹果个数
Map<String, Long> map2 = list.stream()
        .collect(Collectors.groupingBy(Apple::getColor, Collectors.counting()));
```

使用 collectingAndThen 进行结果收集
```
// 查找每种颜色中最重的苹果
Map<String, Apple> map3 = list.stream()
        .collect(Collectors.groupingBy(Apple::getColor,
                Collectors.collectingAndThen(Collectors.maxBy(Comparator.comparing(Apple::getWeight)), Optional::get)));
```

使用 mapping 进行结果收集
```
// 查找每种颜色中有哪几种重量级别
Map<String, Set<String>> map4 = list.stream()
        .collect(Collectors.groupingBy(Apple::getColor, Collectors.mapping(o -> {
            if (o.getWeight() <= 50) return "light";
            if (o.getWeight() > 50 && o.getWeight() <= 70) return "common";
            return "weight";
        }, Collectors.toSet())));
```

#### 分区

> 分区是分组的特殊情况：由一个谓词（返回一个布尔值的函数）作为分类函数，它称分区函数
> 分区函数返回一个布尔值，这意味着得到的分组Map的键类型是Boolean，于是它最多可以分为两组——true是一组，false是一组

```
Map<Boolean, List<Apple>> partitionedApple = menu.stream().collect(partitioningBy(apple -> "red".equals(apple.getColor()));
```

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