Depth Comparator & Collector
From source depth Comparator
Comparator from Java1.2 came out, but in 1.8, when they added a lot of the default method.
compare()
equals()
reversed() //倒序
thenComparing(Comparator<? super T> other) //然后,再去比较.
thenComparing( Function<? super T, ? extends U> keyExtractor,
Comparator<? super U> keyComparator) //先通过第一个比较器,再执行第二个比较器...串联
thenComparing()
thenComparingInt()
thenComparingLong()
thenComparingDouble()
reverseOrder()
naturalOrder()
nullsFirst()
nullsLast()
comparing () //静态方法
comparing()
comparingInt()
comparingLong()
comparingDouble()Look Comparator from ### Demo Code
package com.dawa.jdk8.stream2;
import java.util.Arrays;
import java.util.Collections;
import java.util.Comparator;
import java.util.List;
//关于比较器comparator,案例详解.
public class MyComparator {
public static void main(String[] args) {
List<String> list = Arrays.asList("hello", "world", "welcome", "nihao");
//按照字母排序
Collections.sort(list);
System.out.println(list);
//按照字符串的长度.
Collections.sort(list, (item1, item2) -> item1.length() - item2.length());
System.out.println(list);
//按照字符串的长度降序排序.
Collections.sort(list, (item1, item2) -> item2.length() - item1.length());
//使用方法引用
//长度排序
Collections.sort(list, Comparator.comparingInt(String::length));
System.out.println(list);
//长度倒叙排序
Collections.sort(list, Comparator.comparingInt(String::length).reversed());
System.out.println(list);
//使用lambda表达式实现上述两个方法
// Collections.sort(list,Comparator.comparingInt(item->item.length()).reversed());
//这里,reversed()方法,参数要的是Object类型.
//参数的类型推断.
Collections.sort(list,Comparator.comparingInt((String item)->item.length()).reversed());
//这样写就行了.
//问题:之前为什么会成功? 因为是从Stream<T> 类型开始推断的,可以获取到原属性的元素.
//问题:为什么上述的类型推断失败了/? 看sort方法的 Comparator类的泛型<T>,T是传入参数的泛型- <? super T>.
// String上的类型.你没指定,编译器也没办法帮你指定.
// public static <T> void sort(List<T> list, Comparator<? super T> c) {
// list.sort(c);
// }
//如: Collections.sort(list,Comparator.comparingInt((Boolean item)->1).reversed());
//这样不会被兼容.因为Boolean 不是 String的上类型.
//如: Collections.sort(list,Comparator.comparingInt((Object item)->1).reversed());
//这样就是可以的.
//如: Collections.sort(list,Comparator.comparingInt(item->item.length());
//这样也是可以的.
}
}
@SuppressWarnings({"unchecked", "rawtypes"})
public static <T> void sort(List<T> list, Comparator<? super T> c) {
list.sort(c);
}About: <? Super T> Note the use of generics.
Semantic broader, but the actual result type is in fact a type T itself. The need to carefully think about.
Series Comparator comparator use
//通过两层比较,1:排序(升序) ,2:字母顺序排序. 使用thenComparing()
Collections.sort(list,Comparator.comparingInt(String::length).thenComparing(String.CASE_INSENSITIVE_ORDER));
thenComparing () method below source
/**
* Returns a lexicographic-order comparator with another comparator.
* If this {@code Comparator} considers two elements equal, i.e.
* {@code compare(a, b) == 0}, {@code other} is used to determine the order.
*
* <p>The returned comparator is serializable if the specified comparator
* is also serializable.
*
* @apiNote
* For example, to sort a collection of {@code String} based on the length
* and then case-insensitive natural ordering, the comparator can be
* composed using following code,
*
不区分大小写,的实现. 技术上述案例.
* <pre>{@code
* Comparator<String> cmp = Comparator.comparingInt(String::length)
* .thenComparing(String.CASE_INSENSITIVE_ORDER);
* }</pre>
*
* @param other the other comparator to be used when this comparator
* compares two objects that are equal.
* @return a lexicographic-order comparator composed of this and then the
* other comparator
* @throws NullPointerException if the argument is null.
* @since 1.8
*/
default Comparator<T> thenComparing(Comparator<? super T> other) {
Objects.requireNonNull(other);
return (Comparator<T> & Serializable) (c1, c2) -> {
int res = compare(c1, c2);
return (res != 0) ? res : other.compare(c1, c2);
};
}The results of previous comparator is equal to 0, this thenComparing () will be called. As the length of the three the same three numbers, only secondarily sorted.
That is, if the first comparator, can be sorted, to use a first, a second and then a second sort fails.
Another implementation
Collections.
sort(list,Comparator.comparingInt(String::length).
thenComparing((item1,item2)->item1.toLowerCase().compareTo(item2)));Another implementation
Collections.sort(list,Comparator.comparingInt(String::length).thenComparing(Comparator.comparing(String::toUpperCase)));Another implementation
Collections.sort(list,Comparator.comparingInt(String::length).thenComparing(Comparator.comparing(String::toLowerCase,Comparator.reverseOrder())));Above a few cases, mainly realized for different use thenComparing () method.
What, then, following output of this method is that?
Collections.sort(list,Comparator.comparingInt(String::length).thenComparing(Comparator.comparing(String::toLowerCase,Comparator.reverseOrder())));Repeat it again: the results of previous comparator is equal to 0, this thenComparing () will be called. As the length of the three the same three numbers, will be the secondary sort is to say if the first comparator. the sorting, to use a first, a second and then a second sort fails.
Multi-level sorting
Collections.sort(list,Comparator.comparingInt(String::length).reversed()
.thenComparing(Comparator.comparing(String::toLowerCase, Comparator.reverseOrder()))
.thenComparing(Comparator.reverseOrder()));Before JDK1.8, which provides a method Collections are a few from after JDK1.8, add a large number of implementation and concrete realization of specialization.
To avoid the boxing and unboxing operations. This may also affect performance.
Custom Collector implementation class
Implement Collector Interface
public interface Collector<T, A, R> {
Supplier<A> supplier();
BiConsumer<A, T> accumulator();
BinaryOperator<A> combiner();
Function<A, R> finisher();
Set<Characteristics> characteristics();
public static<T, R> Collector<T, R, R> of(Supplier<R> supplier,
BiConsumer<R, T> accumulator,
BinaryOperator<R> combiner,
Characteristics... characteristics) {
Objects.requireNonNull(supplier);
Objects.requireNonNull(accumulator);
Objects.requireNonNull(combiner);
Objects.requireNonNull(characteristics);
Set<Characteristics> cs = (characteristics.length == 0)
? Collectors.CH_ID
: Collections.unmodifiableSet(EnumSet.of(Collector.Characteristics.IDENTITY_FINISH,
characteristics));
return new Collectors.CollectorImpl<>(supplier, accumulator, combiner, cs);
}
public static<T, A, R> Collector<T, A, R> of(Supplier<A> supplier,
BiConsumer<A, T> accumulator,
BinaryOperator<A> combiner,
Function<A, R> finisher,
Characteristics... characteristics) {
Objects.requireNonNull(supplier);
Objects.requireNonNull(accumulator);
Objects.requireNonNull(combiner);
Objects.requireNonNull(finisher);
Objects.requireNonNull(characteristics);
Set<Characteristics> cs = Collectors.CH_NOID;
if (characteristics.length > 0) {
cs = EnumSet.noneOf(Characteristics.class);
Collections.addAll(cs, characteristics);
cs = Collections.unmodifiableSet(cs);
}
return new Collectors.CollectorImpl<>(supplier, accumulator, combiner, finisher, cs);
}
Characteristics {
CONCURRENT,
UNORDERED,
IDENTITY_FINISH
}
}
Custom collector
package com.dawa.jdk8.stream2;
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;
import static java.util.stream.Collector.Characteristics.IDENTITY_FINISH;
public class MySetCollector<T> implements Collector<T,Set<T>,Set<T>> {
@Override
public Supplier<Set<T>> supplier() {
System.out.println("supplier invoked");
return HashSet<T>::new;// 返回一个HasHSet容器.
}
@Override
public BiConsumer<Set<T>, T> accumulator() {
System.out.println("accumalator invoked");//累加器
return Set<T>::add;
// return HashSet<T>::add; //不行,没有静态方法支持. 应该是 Supplier返回值的父类接口. 不能使用具体类型的set.
}
@Override
public BinaryOperator<Set<T>> combiner() {
System.out.println("combiner invoked");//并行流的时候,合并中间结果
return (set1,set2)->{
set1.addAll(set2);return set1;
};
}
@Override
public Function<Set<T>, Set<T>> finisher() {//合并结果类型.结果容器
System.out.println("finisher invoked");
// return ts -> ts;
return Function.identity(); //底层是一样的. 同一性.
}
@Override
public Set<Characteristics> characteristics() {
System.out.println("charcteristics invoked ");
return Collections.unmodifiableSet(EnumSet.of(IDENTITY_FINISH));
}
public static void main(String[] args) {
List<String> list = Arrays.asList("hello", "world", "welcome");
Set<String> collect = list.stream().collect(new MySetCollector<>());
System.out.println(collect);
}
}
Collector depth from source
The first step: the code to call collect ()
public static void main(String[] args) {
List<String> list = Arrays.asList("hello", "world", "welcome");
Set<String> collect = list.stream().collect(new MySetCollector<>());
System.out.println(collect);
}Implementation class collect () method: Step
@Override
@SuppressWarnings("unchecked")
public final <R, A> R collect(Collector<? super P_OUT, A, R> collector) {
A container;
if (isParallel()
&& (collector.characteristics().contains(Collector.Characteristics.CONCURRENT))
&& (!isOrdered() || collector.characteristics().contains(Collector.Characteristics.UNORDERED))) {
container = collector.supplier().get();
BiConsumer<A, ? super P_OUT> accumulator = collector.accumulator();
forEach(u -> accumulator.accept(container, u));
}
else {
container = evaluate(ReduceOps.makeRef(collector));
}
return collector.characteristics().contains(Collector.Characteristics.IDENTITY_FINISH)
? (R) container
: collector.finisher().apply(container);
}IDENTITY_FINISH field is particularly important, as used herein,
The third step: makeRef (), and gradually the caller three functional interface objects
public static <T, I> TerminalOp<T, I>
makeRef(Collector<? super T, I, ?> collector) {
Supplier<I> supplier = Objects.requireNonNull(collector).supplier();
BiConsumer<I, ? super T> accumulator = collector.accumulator();
BinaryOperator<I> combiner = collector.combiner();
class ReducingSink extends Box<I>
implements AccumulatingSink<T, I, ReducingSink> {
@Override
public void begin(long size) {
state = supplier.get();
}
@Override
public void accept(T t) {
accumulator.accept(state, t);
}
@Override
public void combine(ReducingSink other) {
state = combiner.apply(state, other.state);
}
}
return new ReduceOp<T, I, ReducingSink>(StreamShape.REFERENCE) {
@Override
public ReducingSink makeSink() {
return new ReducingSink();
}
@Override
public int getOpFlags() {
return collector.characteristics().contains(Collector.Characteristics.UNORDERED)
? StreamOpFlag.NOT_ORDERED
: 0;
}
};
}Collector of some "pit"
Use this case to understand the operation of the process.
把一个set集合进行收集,我们对结果做一个增强.(原来是直接放在set当中了.)我们现在放在Map当中.
声明一个Collector类,要求.
- 输入:Set
- 输出:Map<String,String>
示例输入:["hello","world","hello world"]
示例输出:[{hello,hello},{world,world},{hello world,hello world}
泛型:<T,T,T>
彻底理解Characteristics.IDENTITY_FINISH属性
package com.dawa.jdk8.stream2;
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;
public class MySetCollector2<T> implements Collector<T, Set<T>, Map<T,T>> {
@Override
public Supplier<Set<T>> supplier() {
System.out.println("supplier invoked");
return HashSet<T>::new;
}
@Override
public BiConsumer<Set<T>, T> accumulator() {
System.out.println("accumulator invoked");
return Set::add;
}
@Override
public BinaryOperator<Set<T>> combiner() {
System.out.println("combiner invoked");
return (set1, set2) -> {
set1.addAll(set2);
return set1;
};
}
@Override
public Function<Set<T>, Map<T, T>> finisher() { //这里一定会被调用.因为结果类型和最终类型不同
//示例输入:["hello","world","hello world"]
//示例输出:[{hello,hello},{world,world},{hello world,hello world}
System.out.println("finisher invoked");
return set ->{
Map<T, T> map = new HashMap<>();
set.stream().forEach(item -> map.put(item, item));
return map;
};
}
@Override
public Set<Characteristics> characteristics() {
System.out.println("characteristics invoked");
return Collections.unmodifiableSet(EnumSet.of(Characteristics.UNORDERED));
}
public static void main(String[] args) {
List<String> list = Arrays.asList("hello", "world", "hello", "welocome", "a", "b", "c", "d", "e");
HashSet<String> set = new HashSet<>(list);
System.out.println("set:"+list);
Map<String, String> collect = set.stream().collect(new MySetCollector2<>());
System.out.println(collect);
}
}如果多一个参数:
return Collections.unmodifiableSet(EnumSet.of(Characteristics.UNORDERED,Characteristics.IDENTITY_FINISH));则会出现类型转换异常.
/**
* Indicates that the finisher function is the identity function and
* can be elided. If set, it must be the case that an unchecked cast
* from A to R will succeed.
*/
IDENTITY_FINISH如果定义这个属性,则代表 indentity和 finish 是同一个类型的,要执行强制类型转换.所以会出现上述异常.
收集器是什么特性的,都是由这个Characteristics类来由你定义的.
所以你必须要理解你写的程序的类型.才能正确的使用这个枚举定义类.
彻底理解Characteristics.CONCURRENT属性
分支合并框架ForkJoinPoll(并行流)
对程序进行一定的改造,打印出相应的线程名称
@Override
public BiConsumer<Set<T>, T> accumulator() {
System.out.println("accumulator invoked");
return (set,item)->{
System.out.println("accumulator:"+ Thread.currentThread().getName());
set.add(item);
};
}- 串行情况下:
Map<String, String> collect = set.Stream().collect(new MySetCollector2<>());运行结果如下:
- 并行情况下
Map<String, String> collect = set.parallelStream().collect(new MySetCollector2<>());运行结果如下.
如果加上 Characteristics.CONCURRENT.
@Override
public Set<Characteristics> characteristics() {
System.out.println("characteristics invoked");
return Collections.unmodifiableSet(EnumSet.of(Characteristics.UNORDERED,Characteristics.CONCURRENT));
}则可能会出来一个异常
Caused by: java.util.ConcurrentModificationException如果不加 ,则不会出现异常
多执行几次,会有一定的发现.
查看属性的源码.
/**
* Indicates that this collector is <em>concurrent</em>, meaning that
* the result container can support the accumulator function being
* called concurrently with the same result container from multiple
* threads.
*
* <p>If a {@code CONCURRENT} collector is not also {@code UNORDERED},
* then it should only be evaluated concurrently if applied to an
* unordered data source.
*/
CONCURRENT,出现问题的原因:是在打印了set集合.
/**
* This exception may be thrown by methods that have detected concurrent
* modification of an object when such modification is not permissible.
* <p>
* For example, it is not generally permissible for one thread to modify a Collection
* while another thread is iterating over it. In general, the results of the
* iteration are undefined under these circumstances. Some Iterator
* implementations (including those of all the general purpose collection implementations
* provided by the JRE) may choose to throw this exception if this behavior is
* detected. Iterators that do this are known as <i>fail-fast</i> iterators,
* as they fail quickly and cleanly, rather that risking arbitrary,
* non-deterministic behavior at an undetermined time in the future.
* <p>
* Note that this exception does not always indicate that an object has
* been concurrently modified by a <i>different</i> thread. If a single
* thread issues a sequence of method invocations that violates the
* contract of an object, the object may throw this exception. For
* example, if a thread modifies a collection directly while it is
* iterating over the collection with a fail-fast iterator, the iterator
* will throw this exception.
*
* <p>Note that fail-fast behavior cannot be guaranteed as it is, generally
* speaking, impossible to make any hard guarantees in the presence of
* unsynchronized concurrent modification. Fail-fast operations
* throw {@code ConcurrentModificationException} on a best-effort basis.
* Therefore, it would be wrong to write a program that depended on this
* exception for its correctness: <i>{@code ConcurrentModificationException}
* should be used only to detect bugs.</i>
*
* @author Josh Bloch
* @see Collection
* @see Iterator
* @see Spliterator
* @see ListIterator
* @see Vector
* @see LinkedList
* @see HashSet
* @see Hashtable
* @see TreeMap
* @see AbstractList
* @since 1.2
*/
public class ConcurrentModificationException extends RuntimeException {
}并发修改异常.
因为如果加上这个属性,那么这个就有一个结果集
并行的时候,会对set进行操作,但是你同时又在遍历打印, 两个赶到一起了.然后就会抛出这个异常.
这就是抛出这个异常的根本原因.
注意:如果是并行的话,千万要避免 打印遍历 你要操作的对象.
如果不加这个属性,那么combiner()方法的中间结果集就会被调用,所以就不会出现抢占资源的现象.
扩展: sequential() && parallerl()方法的调用.
Set<String> collect = list.stream().parallel().sequential().sequential().parallel().collect(new MySetCollector<>());只有最后一个会生效.
sequential()
/**
* Returns an equivalent stream that is sequential. May return
* itself, either because the stream was already sequential, or because
* the underlying stream state was modified to be sequential.
*
* <p>This is an <a href="package-summary.html#StreamOps">intermediate
* operation</a>.
*
* @return a sequential stream
*/
S sequential();parallerl()
/**
* Returns an equivalent stream that is parallel. May return
* itself, either because the stream was already parallel, or because
* the underlying stream state was modified to be parallel.
*
* <p>This is an <a href="package-summary.html#StreamOps">intermediate
* operation</a>.
*
* @return a parallel stream
*/
S parallel();关于Supplier()容器的定义.
修改代码.查看 串行 和并行的 区别.
@Override
public Supplier<Set<T>> supplier() {
System.out.println("supplier invoked");
// return HashSet<T>::new;// 返回一个HasHSet容器.
System.out.println("-----");
return HashSet::new;
}结论:串行的时候,会生成单个初始容器 / 并行的时候,会生成多个初始容器.
关于串行和并行的效率问题
并不是说串行的效率就一定比并行的效率低.这都是要看实际情况的.
最多会生成系统最大CPU核心
超线程技术
Collectors类方法详解
题外话:当你具备一些底层基础知识之后,你看一些东西会觉得是理所当然的.
如果你不具备这些知识的话,是看不懂的.云里雾里的.
关注一下JDK提供的方法是怎么实现的.对于Collectors静态工厂类来说,其实现一共分为两种方式.
- 通过CollectorImpl来实现
- 通过reducing来实现 (reducing本身又是通过CollectorImpl来实现)
所以,所有的方法都是通过CollectorImpl来实现的.
- 4个变量
static final Set<Collector.Characteristics> CH_CONCURRENT_ID
= Collections.unmodifiableSet(EnumSet.of(Collector.Characteristics.CONCURRENT,
Collector.Characteristics.UNORDERED,
Collector.Characteristics.IDENTITY_FINISH));
static final Set<Collector.Characteristics> CH_CONCURRENT_NOID
= Collections.unmodifiableSet(EnumSet.of(Collector.Characteristics.CONCURRENT,
Collector.Characteristics.UNORDERED));
static final Set<Collector.Characteristics> CH_ID
= Collections.unmodifiableSet(EnumSet.of(Collector.Characteristics.IDENTITY_FINISH));
static final Set<Collector.Characteristics> CH_UNORDERED_ID
= Collections.unmodifiableSet(EnumSet.of(Collector.Characteristics.UNORDERED,
Collector.Characteristics.IDENTITY_FINISH));
static final Set<Collector.Characteristics> CH_NOID = Collections.emptySet();- toCollection()方法
public static <T, C extends Collection<T>>
Collector<T, ?, C> toCollection(Supplier<C> collectionFactory) {
return new CollectorImpl<>(collectionFactory, Collection<T>::add,
(r1, r2) -> { r1.addAll(r2); return r1; },
CH_ID);
}- toList()方法.是toCollection的一种特例.
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);
}- toSet()方法.是toCollection的一种特例.
public static <T>
Collector<T, ?, Set<T>> toSet() {
return new CollectorImpl<>((Supplier<Set<T>>) HashSet::new, Set::add,
(left, right) -> { left.addAll(right); return left; },
CH_UNORDERED_ID);
}- joining(): 融合成一个字符串. 此外,还有两个重载的.单参数的和多参数的.
public static Collector<CharSequence, ?, String> joining() {
return new CollectorImpl<CharSequence, StringBuilder, String>(
StringBuilder::new, StringBuilder::append,
(r1, r2) -> { r1.append(r2); return r1; },
StringBuilder::toString, CH_NOID);
}- mapping() 映射函数
public static <T, U, A, R>
Collector<T, ?, R> mapping(Function<? super T, ? extends U> mapper,
Collector<? super U, A, R> downstream) {
BiConsumer<A, ? super U> downstreamAccumulator = downstream.accumulator();
return new CollectorImpl<>(downstream.supplier(),
(r, t) -> downstreamAccumulator.accept(r, mapper.apply(t)),
downstream.combiner(), downstream.finisher(),
downstream.characteristics());
}collectingAndThen() 收集,并且做处理
原理:把IDENTITY_FINISH标识符给去掉.
为什么要去掉:不去掉的话,表示不会执行 finisher()方法.
public static<T,A,R,RR> Collector<T,A,RR> collectingAndThen(Collector<T,A,R> downstream,
Function<R,RR> finisher) {
Set<Collector.Characteristics> characteristics = downstream.characteristics();
if (characteristics.contains(Collector.Characteristics.IDENTITY_FINISH)) {
if (characteristics.size() == 1)
characteristics = Collectors.CH_NOID;
else {
characteristics = EnumSet.copyOf(characteristics);
characteristics.remove(Collector.Characteristics.IDENTITY_FINISH);
characteristics = Collections.unmodifiableSet(characteristics);
}
}
return new CollectorImpl<>(downstream.supplier(),
downstream.accumulator(),
downstream.combiner(),
downstream.finisher().andThen(finisher),
characteristics);
}- counting() 计算.
public static <T> Collector<T, ?, Long>
counting() {
return reducing(0L, e -> 1L, Long::sum);
}- minBy()
public static <T> Collector<T, ?, Optional<T>>
minBy(Comparator<? super T> comparator) {
return reducing(BinaryOperator.minBy(comparator));
}- maxBy()
public static <T> Collector<T, ?, Optional<T>>
maxBy(Comparator<? super T> comparator) {
return reducing(BinaryOperator.maxBy(comparator));
}summingInt(),Long(),Double
为什么要用一个 int[1]? 最后还要返回一个数组中的单个数组呢?直接用一个数组行不行.
因为:不行,因为直接用数字,数字是不能被传递的. 数组本身是一个引用.是可以改变的.数组本身就是一个容器.
public static <T> Collector<T, ?, Integer>
summingInt(ToIntFunction<? super T> mapper) {
return new CollectorImpl<>(
() -> new int[1],
(a, t) -> { a[0] += mapper.applyAsInt(t); },
(a, b) -> { a[0] += b[0]; return a; },
a -> a[0], CH_NOID);
}- averagingInt(),Long(),Double
public static <T> Collector<T, ?, Double>
averagingInt(ToIntFunction<? super T> mapper) {
return new CollectorImpl<>(
() -> new long[2],
(a, t) -> { a[0] += mapper.applyAsInt(t); a[1]++; },
(a, b) -> { a[0] += b[0]; a[1] += b[1]; return a; },
a -> (a[1] == 0) ? 0.0d : (double) a[0] / a[1], CH_NOID);
}- reducing () the focus function.
public static <T> Collector<T, ?, T>
reducing(T identity, BinaryOperator<T> op) {
return new CollectorImpl<>(
boxSupplier(identity),
(a, t) -> { a[0] = op.apply(a[0], t); },
(a, b) -> { a[0] = op.apply(a[0], b[0]); return a; },
a -> a[0],
CH_NOID);
}- Achieve groupingBy () method. (Does not support concurrent)
public static <T, K> Collector<T, ?, Map<K, List<T>>>
groupingBy(Function<? super T, ? extends K> classifier) {
return groupingBy(classifier, toList());//调用下面2个参数的重载和toList()方法
} public static <T, K, A, D>
Collector<T, ?, Map<K, D>> groupingBy(Function<? super T, ? extends K> classifier,
Collector<? super T, A, D> downstream) {
return groupingBy(classifier, HashMap::new, downstream);//调用下面的三个参数的重载
}downstream downstream (to accept a returned a. return called downstream)
T: the type of classifier function, the input parameters.
K: classifier function returns the type of the result.
D: type of the result value is returned.
HashMap :: new: is returned to the client's Map /
Benefits: In order to give users better direct return HashMap.
Disadvantages: limitations can only return to the HashMap type.
//groupBy函数的最底层实现.
/**
* Returns a {@code Collector} implementing a cascaded "group by" operation
* on input elements of type {@code T}, grouping elements according to a
* classification function, and then performing a reduction operation on
* the values associated with a given key using the specified downstream
* {@code Collector}. The {@code Map} produced by the Collector is created
* with the supplied factory function.
*
* <p>The classification function maps elements to some key type {@code K}.
* The downstream collector operates on elements of type {@code T} and
* produces a result of type {@code D}. The resulting collector produces a
* {@code Map<K, D>}.
*
* <p>For example, to compute the set of last names of people in each city,
* where the city names are sorted:
* <pre>{@code
* Map<City, Set<String>> namesByCity
* = people.stream().collect(groupingBy(Person::getCity, TreeMap::new,
* mapping(Person::getLastName, toSet())));
* }</pre>
*
* @implNote
* The returned {@code Collector} is not concurrent. For parallel stream
* pipelines, the {@code combiner} function operates by merging the keys
* from one map into another, which can be an expensive operation. If
* preservation of the order in which elements are presented to the downstream
* collector is not required, using {@link #groupingByConcurrent(Function, Supplier, Collector)}
* may offer better parallel performance.
*
* @param <T> the type of the input elements
* @param <K> the type of the keys
* @param <A> the intermediate accumulation type of the downstream collector
* @param <D> the result type of the downstream reduction
* @param <M> the type of the resulting {@code Map}
* @param classifier a classifier function mapping input elements to keys
* @param downstream a {@code Collector} implementing the downstream reduction
* @param mapFactory a function which, when called, produces a new empty
* {@code Map} of the desired type
* @return a {@code Collector} implementing the cascaded group-by operation
*
* @see #groupingBy(Function, Collector)
* @see #groupingBy(Function)
* @see #groupingByConcurrent(Function, Supplier, Collector)
*/
public static <T, K, D, A, M extends Map<K, D>>
Collector<T, ?, M> groupingBy(Function<? super T, ? extends K> classifier,
Supplier<M> mapFactory,
Collector<? super T, A, D> downstream) {
Supplier<A> downstreamSupplier = downstream.supplier();
BiConsumer<A, ? super T> downstreamAccumulator = downstream.accumulator();
BiConsumer<Map<K, A>, T> accumulator = (m, t) -> {
K key = Objects.requireNonNull(classifier.apply(t), "element cannot be mapped to a null key");
A container = m.computeIfAbsent(key, k -> downstreamSupplier.get());
downstreamAccumulator.accept(container, t);
};
BinaryOperator<Map<K, A>> merger = Collectors.<K, A, Map<K, A>>mapMerger(downstream.combiner());
@SuppressWarnings("unchecked")
Supplier<Map<K, A>> mangledFactory = (Supplier<Map<K, A>>) mapFactory;
if (downstream.characteristics().contains(Collector.Characteristics.IDENTITY_FINISH)) {
return new CollectorImpl<>(mangledFactory, accumulator, merger, CH_ID);
}
else {
@SuppressWarnings("unchecked")
Function<A, A> downstreamFinisher = (Function<A, A>) downstream.finisher();
Function<Map<K, A>, M> finisher = intermediate -> {
intermediate.replaceAll((k, v) -> downstreamFinisher.apply(v));
@SuppressWarnings("unchecked")
M castResult = (M) intermediate;
return castResult;
};
return new CollectorImpl<>(mangledFactory, accumulator, merger, finisher, CH_NOID);
}
}Parametric analysis:
1. Classifier: Input type T and returns the key K Map of the return type is a type K.
2. Container: HashMap
3. The downstream collector: D is the return type of the downstream collector.
Logical analysis.
- groupingByConcurrent () :( supports concurrent) (provided that you do not need the requirements of the order.)
public static <T, K>
Collector<T, ?, ConcurrentMap<K, List<T>>>
groupingByConcurrent(Function<? super T, ? extends K> classifier) {
return groupingByConcurrent(classifier, ConcurrentHashMap::new, toList());
}
//ConcurrentHashMap 实现起来支持并发.public static <T, K, A, D, M extends ConcurrentMap<K, D>>
Collector<T, ?, M> groupingByConcurrent(Function<? super T, ? extends K> classifier,
Supplier<M> mapFactory,
Collector<? super T, A, D> downstream) {
Supplier<A> downstreamSupplier = downstream.supplier();
BiConsumer<A, ? super T> downstreamAccumulator = downstream.accumulator();
BinaryOperator<ConcurrentMap<K, A>> merger = Collectors.<K, A, ConcurrentMap<K, A>>mapMerger(downstream.combiner());
@SuppressWarnings("unchecked")
Supplier<ConcurrentMap<K, A>> mangledFactory = (Supplier<ConcurrentMap<K, A>>) mapFactory;
BiConsumer<ConcurrentMap<K, A>, T> accumulator;
//支持并发的同步的源码:
if (downstream.characteristics().contains(Collector.Characteristics.CONCURRENT)) {
accumulator = (m, t) -> {
K key = Objects.requireNonNull(classifier.apply(t), "element cannot be mapped to a null key");
A resultContainer = m.computeIfAbsent(key, k -> downstreamSupplier.get());
downstreamAccumulator.accept(resultContainer, t);
};
}
else {
accumulator = (m, t) -> {
K key = Objects.requireNonNull(classifier.apply(t), "element cannot be mapped to a null key");
A resultContainer = m.computeIfAbsent(key, k -> downstreamSupplier.get());
synchronized (resultContainer) {//同步锁.
downstreamAccumulator.accept(resultContainer, t);
}
};
}
if (downstream.characteristics().contains(Collector.Characteristics.IDENTITY_FINISH)) {
return new CollectorImpl<>(mangledFactory, accumulator, merger, CH_CONCURRENT_ID);
}
else {
@SuppressWarnings("unchecked")
Function<A, A> downstreamFinisher = (Function<A, A>) downstream.finisher();
Function<ConcurrentMap<K, A>, M> finisher = intermediate -> {
intermediate.replaceAll((k, v) -> downstreamFinisher.apply(v));
@SuppressWarnings("unchecked")
M castResult = (M) intermediate;
return castResult;
};
return new CollectorImpl<>(mangledFactory, accumulator, merger, finisher, CH_CONCURRENT_NOID);
}
}- partitioningBy () partitioning methods. ()
public static <T>
Collector<T, ?, Map<Boolean, List<T>>> partitioningBy(Predicate<? super T> predicate) {
return partitioningBy(predicate, toList());//调用完全的重载方法.
}public static <T, D, A>
Collector<T, ?, Map<Boolean, D>> partitioningBy(Predicate<? super T> predicate,
Collector<? super T, A, D> downstream) {
BiConsumer<A, ? super T> downstreamAccumulator = downstream.accumulator();
BiConsumer<Partition<A>, T> accumulator = (result, t) ->
downstreamAccumulator.accept(predicate.test(t) ? result.forTrue : result.forFalse, t);
BinaryOperator<A> op = downstream.combiner();
BinaryOperator<Partition<A>> merger = (left, right) ->
new Partition<>(op.apply(left.forTrue, right.forTrue),
op.apply(left.forFalse, right.forFalse));
Supplier<Partition<A>> supplier = () ->
new Partition<>(downstream.supplier().get(),
downstream.supplier().get());
if (downstream.characteristics().contains(Collector.Characteristics.IDENTITY_FINISH)) {
return new CollectorImpl<>(supplier, accumulator, merger, CH_ID);
}
else {
Function<Partition<A>, Map<Boolean, D>> finisher = par ->
new Partition<>(downstream.finisher().apply(par.forTrue),
downstream.finisher().apply(par.forFalse));
return new CollectorImpl<>(supplier, accumulator, merger, finisher, CH_NOID);
}
}Provide their own internal static class:
/**
* Implementation class used by partitioningBy.
*/
private static final class Partition<T>
extends AbstractMap<Boolean, T>
implements Map<Boolean, T> {
final T forTrue;
final T forFalse;
Partition(T forTrue, T forFalse) {
this.forTrue = forTrue;
this.forFalse = forFalse;
}
@Override
public Set<Map.Entry<Boolean, T>> entrySet() {
return new AbstractSet<Map.Entry<Boolean, T>>() {
@Override
public Iterator<Map.Entry<Boolean, T>> iterator() {
Map.Entry<Boolean, T> falseEntry = new SimpleImmutableEntry<>(false, forFalse);
Map.Entry<Boolean, T> trueEntry = new SimpleImmutableEntry<>(true, forTrue);
return Arrays.asList(falseEntry, trueEntry).iterator();
}
@Override
public int size() {
return 2;
}
};
}
}...
Stream class
public interface Stream<T> extends BaseStream<T, Stream<T>> {}BaseStream class
package java.util.stream;
import java.nio.charset.Charset;
import java.nio.file.Files;
import java.nio.file.Path;
import java.util.Collection;
import java.util.Iterator;
import java.util.Spliterator;
import java.util.concurrent.ConcurrentHashMap;
import java.util.function.IntConsumer;
import java.util.function.Predicate;
/**
* Base interface for streams, which are sequences of elements supporting
* sequential and parallel aggregate operations. The following example
* illustrates an aggregate operation using the stream types {@link Stream}
* and {@link IntStream}, computing the sum of the weights of the red widgets:
*
* <pre>{@code
* int sum = widgets.stream()
* .filter(w -> w.getColor() == RED)
* .mapToInt(w -> w.getWeight())
* .sum();
* }</pre>
*
* See the class documentation for {@link Stream} and the package documentation
* for <a href="package-summary.html">java.util.stream</a> for additional
* specification of streams, stream operations, stream pipelines, and
* parallelism, which governs the behavior of all stream types.
*
* @param <T> the type of the stream elements
* @param <S> the type of the stream implementing {@code BaseStream}
* @since 1.8
* @see Stream
* @see IntStream
* @see LongStream
* @see DoubleStream
* @see <a href="package-summary.html">java.util.stream</a>
*/
public interface BaseStream<T, S extends BaseStream<T, S>>
extends AutoCloseable {
/**
* Returns an iterator for the elements of this stream.
*
* <p>This is a <a href="package-summary.html#StreamOps">terminal
* operation</a>.
*
* @return the element iterator for this stream
*/
Iterator<T> iterator();
/**
* Returns a spliterator for the elements of this stream.
*
* <p>This is a <a href="package-summary.html#StreamOps">terminal
* operation</a>.
*
* @return the element spliterator for this stream
*/
Spliterator<T> spliterator();
/**
* Returns whether this stream, if a terminal operation were to be executed,
* would execute in parallel. Calling this method after invoking an
* terminal stream operation method may yield unpredictable results.
*
* @return {@code true} if this stream would execute in parallel if executed
*/
boolean isParallel();
/**
* Returns an equivalent stream that is sequential. May return
* itself, either because the stream was already sequential, or because
* the underlying stream state was modified to be sequential.
*
* <p>This is an <a href="package-summary.html#StreamOps">intermediate
* operation</a>.
*
* @return a sequential stream
*/
S sequential();
/**
* Returns an equivalent stream that is parallel. May return
* itself, either because the stream was already parallel, or because
* the underlying stream state was modified to be parallel.
*
* <p>This is an <a href="package-summary.html#StreamOps">intermediate
* operation</a>.
*
* @return a parallel stream
*/
S parallel();
/**
* Returns an equivalent stream that is
* <a href="package-summary.html#Ordering">unordered</a>. May return
* itself, either because the stream was already unordered, or because
* the underlying stream state was modified to be unordered.
*
* <p>This is an <a href="package-summary.html#StreamOps">intermediate
* operation</a>.
*
* @return an unordered stream
*/
S unordered();
/**
* Returns an equivalent stream with an additional close handler. Close
* handlers are run when the {@link #close()} method
* is called on the stream, and are executed in the order they were
* added. All close handlers are run, even if earlier close handlers throw
* exceptions. If any close handler throws an exception, the first
* exception thrown will be relayed to the caller of {@code close()}, with
* any remaining exceptions added to that exception as suppressed exceptions
* (unless one of the remaining exceptions is the same exception as the
* first exception, since an exception cannot suppress itself.) May
* return itself.
*
* <p>This is an <a href="package-summary.html#StreamOps">intermediate
* operation</a>.
*
* @param closeHandler A task to execute when the stream is closed
* @return a stream with a handler that is run if the stream is closed
*/
S onClose(Runnable closeHandler);
/**
* Closes this stream, causing all close handlers for this stream pipeline
* to be called.
*
* @see AutoCloseable#close()
*/
@Override
void close();
}
Extended: AutoCloseable Interface
package java.lang;
/**
* An object that may hold resources (such as file or socket handles)
* until it is closed. The {@link #close()} method of an {@code AutoCloseable}
* object is called automatically when exiting a {@code
* try}-with-resources block for which the object has been declared in
* the resource specification header. This construction ensures prompt
* release, avoiding resource exhaustion exceptions and errors that
* may otherwise occur.
一个对象在关闭之前,会持有一些资源. 句柄之类的.
在退出块的时候,会自动调用close()
避免资源被耗尽等异常.
*
* @apiNote
* <p>It is possible, and in fact common, for a base class to
* implement AutoCloseable even though not all of its subclasses or
* instances will hold releasable resources. For code that must operate
* in complete generality, or when it is known that the {@code AutoCloseable}
* instance requires resource release, it is recommended to use {@code
* try}-with-resources constructions. However, when using facilities such as
* {@link java.util.stream.Stream} that support both I/O-based and
* non-I/O-based forms, {@code try}-with-resources blocks are in
* general unnecessary when using non-I/O-based forms.
*
* @author Josh Bloch
* @since 1.7
*/
public interface AutoCloseable {
/**
* Closes this resource, relinquishing any underlying resources.
* This method is invoked automatically on objects managed by the
* {@code try}-with-resources statement.
*
* <p>While this interface method is declared to throw {@code
* Exception}, implementers are <em>strongly</em> encouraged to
* declare concrete implementations of the {@code close} method to
* throw more specific exceptions, or to throw no exception at all
* if the close operation cannot fail.
*
* <p> Cases where the close operation may fail require careful
* attention by implementers. It is strongly advised to relinquish
* the underlying resources and to internally <em>mark</em> the
* resource as closed, prior to throwing the exception. The {@code
* close} method is unlikely to be invoked more than once and so
* this ensures that the resources are released in a timely manner.
* Furthermore it reduces problems that could arise when the resource
* wraps, or is wrapped, by another resource.
*
* <p><em>Implementers of this interface are also strongly advised
* to not have the {@code close} method throw {@link
* InterruptedException}.</em>
*
* This exception interacts with a thread's interrupted status,
* and runtime misbehavior is likely to occur if an {@code
* InterruptedException} is {@linkplain Throwable#addSuppressed
* suppressed}.
*
* More generally, if it would cause problems for an
* exception to be suppressed, the {@code AutoCloseable.close}
* method should not throw it.
*
* <p>Note that unlike the {@link java.io.Closeable#close close}
* method of {@link java.io.Closeable}, this {@code close} method
* is <em>not</em> required to be idempotent. In other words,
* calling this {@code close} method more than once may have some
* visible side effect, unlike {@code Closeable.close} which is
* required to have no effect if called more than once.
*
* However, implementers of this interface are strongly encouraged
* to make their {@code close} methods idempotent.
*
* @throws Exception if this resource cannot be closed
*/
void close() throws Exception;
}
Example use this interface to understand
public class AutoCloseableTest implements AutoCloseable {
public static void main(String[] args) {
try(AutoCloseableTest autoCloseableTest = new AutoCloseableTest()) {
autoCloseableTest.doSomething();
} catch (Exception e) {
e.printStackTrace();
} //这种写法.try with source.
}
@Override
public void close() throws Exception {
System.out.println("close invoked");
}
public void doSomething(){
System.out.println("doSomething invoked");
}
}The result: (implements this interface, automatically performs close () method.)
to sum up:
- JDK interface built-in functions to be reflected here.
Look at the underlying reasons:
Not because you want to go to the development process
After reading the source code, when you use the confidence is very full.
In the face of problems, you can quickly fix the problem out.
study method
1. Look good code
2. to learn other people's stuff
3. will become its own thing with more.
Additional an episode
