java的Stream流处理示例小结

// 1. 从集合创建
List<String> list = Arrays.asList("a", "b", "c");
Stream<String> stream1 = list.stream();       // 顺序流
Stream<String> parallelStream = list.parallelStream(); // 并行流
// 2. 从数组创建
String[] array = {"a", "b", "c"};
Stream<String> stream2 = Arrays.stream(array);
// 3. 使用Stream.of()
Stream<String> stream3 = Stream.of("a", "b", "c");
// 4. 使用Stream.generate() 无限流
Stream<Double> randomStream = Stream.generate(Math::random).limit(5);
// 5. 使用Stream.iterate() 迭代流
Stream<Integer> iterateStream = Stream.iterate(0, n -> n + 2).limit(10);

// filter(Predicate) 过滤符合条件的元素
List<String> filtered = list.stream()
    .filter(s -> s.startsWith("a"))
    .collect(Collectors.toList());

// map(Function) 将元素转换为其他形式
List<Integer> lengths = list.stream()
    .map(String::length)
    .collect(Collectors.toList());
// flatMap 将多个流合并为一个流
List<String> flatMapped = list.stream()
    .flatMap(s -> Stream.of(s.split("")))
    .collect(Collectors.toList());

// distinct() 去重
List<String> distinct = list.stream().distinct().collect(Collectors.toList());
// sorted() 自然排序
List<String> sorted = list.stream().sorted().collect(Collectors.toList());
// sorted(Comparator) 自定义排序
List<String> customSorted = list.stream()
    .sorted((s1, s2) -> s2.compareTo(s1))
    .collect(Collectors.toList());

// limit(long) 限制元素数量
// skip(long) 跳过前N个元素
// peek(Consumer) 查看流中元素（主要用于调试）

// forEach(Consumer) 遍历每个元素
list.stream().forEach(System.out::println);

// collect(Collector) 将流转换为集合或其他形式
List<String> collectedList = stream.collect(Collectors.toList());
Set<String> collectedSet = stream.collect(Collectors.toSet());
Map<String, Integer> map = stream.collect(
    Collectors.toMap(Function.identity(), String::length));

// count() 计数
long count = list.stream().count();
// max/min(Comparator) 最大/最小值
Optional<String> max = list.stream().max(Comparator.naturalOrder());
// reduce 归约操作
Optional<Integer> sum = Stream.of(1, 2, 3).reduce(Integer::sum);

// anyMatch 任意元素匹配
boolean anyStartsWithA = list.stream().anyMatch(s -> s.startsWith("a"));
// allMatch 所有元素匹配
boolean allStartsWithA = list.stream().allMatch(s -> s.startsWith("a"));
// noneMatch 没有元素匹配
boolean noneStartsWithZ = list.stream().noneMatch(s -> s.startsWith("z"));

// IntStream, LongStream, DoubleStream
IntStream intStream = IntStream.range(1, 100); // 1-99
DoubleStream doubleStream = DoubleStream.of(1.1, 2.2);
// 常用数值操作
int sum = IntStream.rangeClosed(1, 100).sum(); // 1-100的和
OptionalDouble avg = IntStream.of(1, 2, 3).average();

// 创建并行流
List<String> parallelProcessed = list.parallelStream()
    .filter(s -> s.length() > 1)
    .collect(Collectors.toList());
// 注意事项：
// 1. 确保操作是线程安全的
// 2. 避免有状态的操作
// 3. 数据量足够大时才使用并行流

// 分组
Map<Integer, List<String>> groupByLength = list.stream()
    .collect(Collectors.groupingBy(String::length));
// 分区
Map<Boolean, List<String>> partition = list.stream()
    .collect(Collectors.partitioningBy(s -> s.startsWith("a")));
// 连接字符串
String joined = list.stream().collect(Collectors.joining(", "));
// 汇总统计
IntSummaryStatistics stats = list.stream()
    .collect(Collectors.summarizingInt(String::length));

List<Person> people = ...;
// 获取所有成年人的姓名列表
List<String> adultNames = people.stream()
    .filter(p -> p.getAge() >= 18)
    .map(Person::getName)
    .collect(Collectors.toList());
// 按城市分组
Map<String, List<Person>> byCity = people.stream()
    .collect(Collectors.groupingBy(Person::getCity));
// 计算每个城市的平均年龄
Map<String, Double> avgAgeByCity = people.stream()
    .collect(Collectors.groupingBy(
        Person::getCity,
        Collectors.averagingInt(Person::getAge)
    ));

// 读取文件并处理
try (Stream<String> lines = Files.lines(Paths.get("data.txt"))) {
    long wordCount = lines
        .flatMap(line -> Arrays.stream(line.split("\\s+")))
        .filter(word -> word.length() > 0)
        .count();
} catch (IOException e) {
    e.printStackTrace();
}