简洁的Java8-java8新特性详解编程语言

Stream

标签： Java基础

再次回到阿里, 感觉变化好大: 一是服务资源Docker化, 最牛逼的阿里DB团队竟然把DB放到了容器中, 还放到了线上环境; 二是全集团Java8(记得离开时还是1.6、1.5, 甚至还有1.4), 在外面创业公司都还停留在1.7的时代, 阿里竟率先使用了Java8, 而且还做了高性能的定制, 因此阿里人也就有机会在生产环境体验到Java8如丝般的顺滑流畅. 而本篇就从对Java8影响最大的Stream开始说起.

引入

如果说Runnable接口是将执行逻辑从Thread中剥离了的话, 那Stream则是将数据计算逻辑从Collection中抽离了出来, 使Collection只专注于数据的存储, 而不用分心计算.

打开Collection Api可以看到多了一个stream() default接口:

/**

Stream允许以声明方式处理集合等可以转换为Stream<T>的数据, 他有很多特点:

内部迭代

与原有的Iterator不同, Stream将迭代操作(类似for/for-each
)全部固化到了Api内部实现, 用户只需传入表达计算逻辑的lambda表达式(可以理解为Supplier、Function这些的@FunctionalInterface的实现),

Stream
便会自动迭代数据触发计算逻辑并生成结果. 内部迭代主要解决了两方面的问题: 避免集合处理时的套路和晦涩; 便于库内部实现的多核并行优化.

流水线

很多Stream操作会再返回一个Stream, 这样多个操作就可以链接起来, 形成一个大的流水线, 使其看起来像是对数据源进行数据库式查询, 这也就让自动优化成为可能, 如隐式并行.

隐式并行如将

.stream()替换为.parallelStream(), Stream则会自动启用Fork/Join框架, 并行执行各条流水线, 并最终自动将结果进行合并.

延迟计算

由于Stream大部分的操作(如filter()、generate()、map()…)都是接受一段lambda表达式, 逻辑类似接口实现(可以看成是回调), 因此代码并不是立即执行的, 除非流水线上触发一个终端操作, 否则中间操作不会执行任何处理.

短路求值

有些操作不需要处理整个流就能够拿到结果, 很多像anyMatch()、allMatch()、limit(), 只要找到一个元素他们的工作就可以结束, 也就没有必要执行后面的操作, 因此如果后面有大量耗时的操作, 此举可大大节省性能.

下面一个示例直观的感受下Stream带来的便利:

public void joiningList() { // 生成一段[0,20)序列

Stream 构成

一个流管道(Stream pipeline)通常由3部分构成: 数据源(Source) -> 中间操作/转换(Transforming) -> 终端操作/执行(Operations): Stream由数据源生成, 经由中间操作串联起来的一条流水线的转换, 最后由终端操作触发执行拿到结果.

Source - 对应Stream的生成: -> 如何生成一个Stream;
Transforming - 对应Stream的转换: -> 如前面的map()、filter()、limit(), 将原Stream转换为另一形态;
Operations - 对应Stream的执行: -> 他会真正引发前面一系列Transforming的执行, 并生成一个结果(如List、Array、Optional<T>), 或一个side effect.

我们分别来介绍这些Stream的构成部分:

数据源-Stream生成

除了前面介绍过的collection.stream(), 流的生成方式多种多样, 可简单概括为3类: 通用流、数值流、其他, 其中以通用流最为常用, 数值流是Java为int、long、double三种数值类型防拆装箱成本所做的优化:

1. 通用流

API	description
`Arrays.stream(T[] array)`	Returns a sequential Stream with the specified array as its source.
`Stream.empty()`	Returns an empty sequential Stream.
`Stream.generate(Supplier<T> s)`	Returns an infinite sequential unordered stream where each element is generated by the provided `Supplier<T>`.
`Stream.iterate(T seed, UnaryOperator<T> f)`	Returns an infinite sequential ordered Stream produced by iterative application of a function `f` to an initial element seed, producing a Stream consisting of seed, f(seed), f(f(seed)), etc.
`Stream.of(T... values)`	Returns a sequential ordered stream whose elements are the specified values.
`Stream.concat(Stream<? extends T> a, Stream<? extends T> b)`	Creates a lazily concatenated stream whose elements are all the elements of the first stream followed by all the elements of the second stream.
`StreamSupport.stream(Spliterator<T> spliterator, boolean parallel)`	Creates a new sequential or parallel Stream from a Spliterator.

2. 数值流

API	description
`Arrays.stream(Xxx[] array)`	Returns a sequential `Int/Long/DoubleStream` with the specified array as its source.
`XxxStream.empty()`	Returns an empty sequential `Int/Long/DoubleStream`.
`XxxStream.generate(XxxSupplier s)`	Returns an infinite sequential unordered stream where each element is generated by the provided `Int/Long/DoubleSupplier`.
`XxxStream.iterate(Xxx seed, XxxUnaryOperator f)`	Returns an infinite sequential ordered `Int/Long/DoubleStream`like as `Stream.iterate(T seed, UnaryOperator<T> f)`
`XxxStream.of(Xxx... values)`	Returns a sequential ordered stream whose elements are the specified values.
`XxxStream.concat(XxxStream a, XxxStream b)`	Creates a lazily concatenated stream whose elements are all the elements of the first stream followed by all the elements of the second stream.
`Int/LongStream.range(startInclusive, endExclusive)`	Returns a sequential ordered `Int/LongStream` from startInclusive (inclusive) to endExclusive (exclusive) by an incremental step of 1.
`Int/LongStream.rangeClosed(startInclusive, endInclusive)`	Returns a sequential ordered `Int/LongStream` from startInclusive (inclusive) to endInclusive (inclusive) by an incremental step of 1.

3. 其他

I/O Stream

BufferedReader.lines()

File Stream

Files.lines(Path path)
Files.find(Path start, int maxDepth, BiPredicate<Path,BasicFileAttributes> matcher, FileVisitOption... options)
DirectoryStream<Path> newDirectoryStream(Path dir)
Files.walk(Path start, FileVisitOption... options)

JarFile.stream()

Random

Random.ints()
Random.longs()
Random.doubles()

Pattern

splitAsStream(CharSequence input)
…

另外, 三种数值流之间, 以及数值流与通用流之间都可以相互转换:
1. 数值流转换: doubleStream.mapToInt(DoubleToIntFunction mapper)、intStream.asLongStream() …
2. 数值流转通用流: longStream.boxed()、intStream.mapToObj(IntFunction<? extends U> mapper) …
3. 通用流转数值流: stream.flatMapToInt(Function<? super T,? extends IntStream> mapper)、stream.mapToDouble(ToDoubleFunction<? super T> mapper)…

中间操作-Stream转换

所有的中间操作都会返回另一个Stream, 这让多个操作可以链接起来组成中间操作链, 从而形成一条流水线, 因此它的特点就是前面提到的延迟执行: 触发流水线上触发一个终端操作, 否则中间操作不执行任何处理.

API	Description
`filter(Predicate<? super T> predicate)`	Returns a stream consisting of the elements of this stream that match the given predicate.
`distinct()`	Returns a stream consisting of the distinct elements (according to `Object.equals(Object)`) of this stream.
`limit(long maxSize)`	Returns a stream consisting of the elements of this stream, truncated to be no longer than maxSize in length.
`skip(long n)`	Returns a stream consisting of the remaining elements of this stream after discarding the first n elements of the stream.
`sorted(Comparator<? super T> comparator)`	Returns a stream consisting of the elements of this stream, sorted according to the provided `Comparator`.
`map(Function<? super T,? extends R> mapper)`	Returns a stream consisting of the results of applying the given function to the elements of this stream.
`flatMap(Function<? super T,? extends Stream<? extends R>> mapper)`	Returns a stream consisting of the results of replacing each element of this stream with the contents of a mapped stream produced by applying the provided mapping function to each element.
`peek(Consumer<? super T> action)`	Returns a stream consisting of the elements of this stream, additionally performing the provided action on each element as elements are consumed from the resulting stream.

这里着重讲解下flatMap()
, 因为我在第一次接触他时也没明白他到底能做什么: 假设我们有这样一个字符串list:List<String> strs = Arrays.asList("hello", "alibaba", "world");

如何列出里面各不相同的字符呢?

首先我们想到的是String包含一个split()方法, 将字符串分解为子串, 于是我们这样写:

Stream<Stream<String>> streamStream = strs.stream() .map(str -> Arrays.stream(str.split("")));1212

我们将String分解成String[]后再由Arrays.stream()将String[]映射成Stream<String>, 但这个结果是我们不想看到的: 我们明明想要的是Stream<String>却得到的是Stream<Stream<String>>
, 他把我们想要的结果包到Stream里面了. 这时候就需要我们的flatMap()
出场了:

Stream<String> stringStream = strs.stream() .flatMap(str -> Arrays.stream(str.split("")));1212

flatMap()把Stream中的层级结构扁平化了, 将内层Stream内的元素抽取出来, 最终新的Stream就没有内层Stream了.

可以简单概括为: flatMap()方法让你把一个流中的每个值都换成另一个Stream, 然后把所有的Stream连接起来成为一个Stream.

终端操作-Stream执行

终端操作不仅担负着触发流水线执行的任务, 他还需要拿到流水线执行的结果, 其结果为任何不是流的值, 如List、Array、boolean、Optional<T>, 甚至是void(forEach()):

Api	Description
`count()`	Returns the count of elements in this stream.
`max(Comparator<? super T> comparator)`	Returns the maximum element of this stream according to the provided `Comparator`.
`min(Comparator<? super T> comparator)`	Returns the minimum element of this stream according to the provided `Comparator`.
`allMatch(Predicate<? super T> predicate)`	Returns whether all elements of this stream match the provided `predicate`.
`anyMatch(Predicate<? super T> predicate)`	Returns whether any elements of this stream match the provided `predicate`.
`noneMatch(Predicate<? super T> predicate)`	Returns whether no elements of this stream match the provided `predicate`.
`findAny()`	Returns an `Optional` describing some element of the stream, or an empty `Optional`if the stream is empty.
`findFirst()`	Returns an `Optional` describing the first element of this stream, or an empty `Optional` if the stream is empty.
`reduce(BinaryOperator<T> accumulator)`	Performs a reduction on the elements of this stream, using an associative accumulation function, and returns an `Optional` describing the reduced value, if any.
`toArray()`	Returns an array containing the elements of this stream.
`forEach(Consumer<? super T> action)`	Performs an action for each element of this stream.
`forEachOrdered(Consumer<? super T> action)`	Performs an action for each element of this stream, in the encounter order of the stream if the stream has a defined encounter order.
`collect(Collector<? super T,A,R> collector)`	Performs a mutable reduction operation on the elements of this stream using a `Collector`.

像IntStream/LongStream/DoubleStream还提供了average()、sum()、summaryStatistics()这样的操作, 拿到一个对Stream进行汇总了的结果.

other

java.util.stream.Stream接口集成自java.util.stream.BaseStream
接口, 而BaseStream
接口也提供了很多工具方法(如将串行流转换为并行流的parallel()
方法)供我们使用:

Api	Description
`S onClose(Runnable closeHandler)`	Returns an equivalent stream with an additional close handler.
`void close()`	Closes this stream, causing all close handlers for this stream pipeline to be called.
`S unordered()`	Returns an equivalent stream that is unordered.
`Iterator<T> iterator()`	Returns an iterator for the elements of this stream.
`Spliterator<T> spliterator()`	Returns a spliterator for the elements of this stream.
`S sequential()`	Returns an equivalent stream that is sequential.
`S parallel()`	Returns an equivalent stream that is parallel.
`boolean isParallel()`	Returns whether this stream, if a terminal operation were to be executed, would execute in parallel.

综合实战

下面, 我们针对一系列交易提出一些问题综合实践上面列举的Api:

DO定义

/**

Stream操作

/**

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