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();
}