JAVA8-自定义Collector 自定义Collector实现Collector接口package com.example.study.java8.collector; import java.util.*; import java.util.function.BiConsumer; import java.util.function.BinaryOperator; import java.util.function.Function; import java.util.function.Supplier; import java.util.stream.Collector; /** * 自定义Collector * T:元素类型 * List<T>:要创建的类型 * List<T>:最后要返回的类型 */ public class ToListCollector<T> implements Collector<T, List<T>, List<T>> { private void log(final String log) { System.out.println(Thread.currentThread().getName()+"-"+log); } //一定时可变的supplier，不是固定值 @Override public Supplier<List<T>> supplier() { log("supplier"); return ArrayList::new; } //要进行的操作 @Override public BiConsumer<List<T>, T> accumulator() { log("accumulator"); return List::add; } //将结果整合 @Override public BinaryOperator<List<T>> combiner() { log("combiner"); return (list1,list2)->{ list1.addAll(list2); return list1; }; } //返回结果 @Override public Function<List<T>, List<T>> finisher() { log("finisher"); // return t->t; return Function.identity(); } //特征值:CONCURRENT-并行,UNORDERED-排序，IDENTITY_FINISH-入参就出参 @Override public Set<Characteristics> characteristics() { log("characteristics"); return Collections.unmodifiableSet(EnumSet.of(Characteristics.IDENTITY_FINISH, Characteristics.CONCURRENT)); } } 使用测试package com.example.study.java8.collector; import java.util.Arrays; import java.util.List; import java.util.stream.Collector; /** * 使用自定义Collector测试 */ public class CustomToListCollector { public static void main(String[] args) { String[] arrs = new String[]{"chinese","japanse","english","freach","Korean"}; //测试 //对应接口中的： //Supplier<A> supplier(), BiConsumer<A, T> accumulator(),Function<A, R> finisher(); Collector<String, List<String>, List<String>> collector = new ToListCollector<String>(); List<String> list = Arrays.stream(arrs).filter(s -> s.length() > 6).collect(collector); System.out.println(list); System.out.println("================================"); //parallelStream（），并行使用测试 List<String> parallelList = Arrays.asList(new String[]{"chinese", "japanse", "english", "freach", "Korean"}) .parallelStream() .filter(s -> s.length() > 6) .collect(collector); System.out.println(parallelList); } } 输出结果main-supplier main-accumulator main-combiner main-characteristics main-characteristics [chinese, japanse, english] ================================ main-characteristics main-characteristics main-supplier main-accumulator main-combiner main-characteristics main-characteristics [chinese, japanse, english]由于数据量少，并没有出现并行。

JAVA8-Collector interface源码分析 Collector interface源码分析源码public interface Collector<T, A, R> { Supplier<A> supplier(); BiConsumer<A, T> accumulator(); Function<A, R> finisher(); BinaryOperator<A> combiner(); Set<Characteristics> characteristics(); }说明：1.T is the generic type of the items in the stream to be collected.2.A is the type of the accumulator, the object on which the partial result will be accumulated during thecollection process.3.R is the type of the object (typically, but not always, the collection) resulting from the collectoperation.T:传入参数类型，A：需要进行处理的方法，R：处理后返回的结果特征值：CONCURRENT：并行的UNORDERED：无序的IDENTITY_FINISH：传入什么，返回什么范例toList()源码1、入口menu.stream().filter(t->t.isVegetarian()).collect(Collectors.toList())2、Collectors.toList()源码： public static <T> Collector<T, ?, List<T>> toList() { return new CollectorImpl<>((Supplier<List<T>>) ArrayList::new, List::add, (left, right) -> { left.addAll(right); return left; }, CH_ID); }3、最后也就是Collector接口 CollectorImpl(Supplier<A> supplier, BiConsumer<A, T> accumulator, BinaryOperator<A> combiner, Set<Characteristics> characteristics) { this(supplier, accumulator, combiner, castingIdentity(), characteristics); }流程图1、Collector执行流程图 执行过程:通过Supplier supplier创建一个Container容器。查看stream里面是否还有元素。如果有，通过带2个入参一个返回结果参数的BiConsumer<A, T> accumulator进行数据处理。处理完后通过finisher返回执行结果。collect源码： 说明：1、获取容器container = collector.supplier().get(); 2、通过accumulator进行处理forEach(u -> accumulator.accept(container, u));3、执行完，返回执行结果return collector.characteristics().contains(Collector.Characteristics.IDENTITY_FINISH)2、combiner并行执行执行流程图 产生多个supplier并行处理，然后将多个处理结果combiner成一个，然后将结果返回。