我发现Merge Sort的大多数示例都在一个线程中运行。这首先打败了使用Merge Sort算法的一些优势。有人可以使用多线程在java中显示编写合并排序算法的正确方法。
解决方案应使用最新版本的java中的功能。 Stackoverflow上的许多解决方案都使用普通线程。我正在寻找一个使用RecursiveTask演示ForkJoin的解决方案,这似乎是RecursiveTask类的主要用例。
重点应该是展示一种具有卓越性能特征的算法,包括可能的时间和空间复杂性。
注意:这两个提议的重复问题都不适用,因为它们都没有提供使用递归任务的解决方案,这是该问题的具体要求。
答案 0 :(得分:4)
合并排序最方便的多线程范例是fork-join范例。这是从Java 8及更高版本提供的。以下代码演示了使用fork-join的合并排序。
import java.util.*;
import java.util.concurrent.*;
public class MergeSort<N extends Comparable<N>> extends RecursiveTask<List<N>> {
private List<N> elements;
public MergeSort(List<N> elements) {
this.elements = new ArrayList<>(elements);
}
@Override
protected List<N> compute() {
if(this.elements.size() <= 1)
return this.elements;
else {
final int pivot = this.elements.size() / 2;
MergeSort<N> leftTask = new MergeSort<N>(this.elements.subList(0, pivot));
MergeSort<N> rightTask = new MergeSort<N>(this.elements.subList(pivot, this.elements.size()));
leftTask.fork();
rightTask.fork();
List<N> left = leftTask.join();
List<N> right = rightTask.join();
return merge(left, right);
}
}
private List<N> merge(List<N> left, List<N> right) {
List<N> sorted = new ArrayList<>();
while(!left.isEmpty() || !right.isEmpty()) {
if(left.isEmpty())
sorted.add(right.remove(0));
else if(right.isEmpty())
sorted.add(left.remove(0));
else {
if( left.get(0).compareTo(right.get(0)) < 0 )
sorted.add(left.remove(0));
else
sorted.add(right.remove(0));
}
}
return sorted;
}
public static void main(String[] args) {
ForkJoinPool forkJoinPool = ForkJoinPool.commonPool();
List<Integer> result = forkJoinPool.invoke(new MergeSort<Integer>(Arrays.asList(7,2,9,10,1)));
System.out.println("result: " + result);
}
}
虽然不那么直截了当,但下面的代码变量消除了对ArrayList的过度复制。初始未排序列表仅创建一次,对子列表的调用不需要自己执行任何复制。在我们每次算法分叉时复制数组列表之前。此外,现在,当合并列表而不是创建新列表并在每次重复使用左侧列表并将值插入其中时复制值时。通过避免额外的复制步骤,我们提高了性能。我们在这里使用LinkedList,因为与ArrayList相比,插入相当便宜。我们也消除了删除调用,这在ArrayList上也很昂贵。
import java.util.*;
import java.util.concurrent.*;
public class MergeSort<N extends Comparable<N>> extends RecursiveTask<List<N>> {
private List<N> elements;
public MergeSort(List<N> elements) {
this.elements = elements;
}
@Override
protected List<N> compute() {
if(this.elements.size() <= 1)
return new LinkedList<>(this.elements);
else {
final int pivot = this.elements.size() / 2;
MergeSort<N> leftTask = new MergeSort<N>(this.elements.subList(0, pivot));
MergeSort<N> rightTask = new MergeSort<N>(this.elements.subList(pivot, this.elements.size()));
leftTask.fork();
rightTask.fork();
List<N> left = leftTask.join();
List<N> right = rightTask.join();
return merge(left, right);
}
}
private List<N> merge(List<N> left, List<N> right) {
int leftIndex = 0;
int rightIndex = 0;
while(leftIndex < left.size() || rightIndex < right.size()) {
if(leftIndex >= left.size())
left.add(leftIndex++, right.get(rightIndex++));
else if(rightIndex >= right.size())
return left;
else {
if( left.get(leftIndex).compareTo(right.get(rightIndex)) < 0 )
leftIndex++;
else
left.add(leftIndex++, right.get(rightIndex++));
}
}
return left;
}
public static void main(String[] args) {
ForkJoinPool forkJoinPool = ForkJoinPool.commonPool();
List<Integer> result = forkJoinPool.invoke(new MergeSort<Integer>(Arrays.asList(7,2,9,-7,777777,10,1)));
System.out.println("result: " + result);
}
}
我们还可以通过使用迭代器而不是在执行合并时直接调用get来进一步改进代码。这样做的原因是,通过索引获取LinkedList具有较差的时间性能(线性),因此通过使用迭代器,我们消除了由于在每次获取时内部迭代链表而导致的减速。在迭代器上对next的调用是常量时间,而不是调用get的线性时间。修改以下代码以改为使用迭代器。
import java.util.*;
import java.util.concurrent.*;
public class MergeSort<N extends Comparable<N>> extends RecursiveTask<List<N>> {
private List<N> elements;
public MergeSort(List<N> elements) {
this.elements = elements;
}
@Override
protected List<N> compute() {
if(this.elements.size() <= 1)
return new LinkedList<>(this.elements);
else {
final int pivot = this.elements.size() / 2;
MergeSort<N> leftTask = new MergeSort<N>(this.elements.subList(0, pivot));
MergeSort<N> rightTask = new MergeSort<N>(this.elements.subList(pivot, this.elements.size()));
leftTask.fork();
rightTask.fork();
List<N> left = leftTask.join();
List<N> right = rightTask.join();
return merge(left, right);
}
}
private List<N> merge(List<N> left, List<N> right) {
ListIterator<N> leftIter = left.listIterator();
ListIterator<N> rightIter = right.listIterator();
while(leftIter.hasNext() || rightIter.hasNext()) {
if(!leftIter.hasNext()) {
leftIter.add(rightIter.next());
rightIter.remove();
}
else if(!rightIter.hasNext())
return left;
else {
N rightElement = rightIter.next();
if( leftIter.next().compareTo(rightElement) < 0 )
rightIter.previous();
else {
leftIter.previous();
leftIter.add(rightElement);
}
}
}
return left;
}
public static void main(String[] args) {
ForkJoinPool forkJoinPool = ForkJoinPool.commonPool();
List<Integer> result = forkJoinPool.invoke(new MergeSort<Integer>(Arrays.asList(7,2,9,-7,777777,10,1)));
System.out.println("result: " + result);
}
}
最后是代码的最复杂版本,此迭代使用完全就地操作。仅创建初始ArrayList,并且不会创建其他集合。因此,逻辑特别难以遵循(因此我将其保存为最后一次)。但是应该尽可能接近理想的实现。
import java.util.*;
import java.util.concurrent.*;
public class MergeSort<N extends Comparable<N>> extends RecursiveTask<List<N>> {
private List<N> elements;
public MergeSort(List<N> elements) {
this.elements = elements;
}
@Override
protected List<N> compute() {
if(this.elements.size() <= 1)
return this.elements;
else {
final int pivot = this.elements.size() / 2;
MergeSort<N> leftTask = new MergeSort<N>(this.elements.subList(0, pivot));
MergeSort<N> rightTask = new MergeSort<N>(this.elements.subList(pivot, this.elements.size()));
leftTask.fork();
rightTask.fork();
List<N> left = leftTask.join();
List<N> right = rightTask.join();
merge(left, right);
return this.elements;
}
}
private void merge(List<N> left, List<N> right) {
int leftIndex = 0;
int rightIndex = 0;
while(leftIndex < left.size() ) {
if(rightIndex == 0) {
if( left.get(leftIndex).compareTo(right.get(rightIndex)) > 0 ) {
swap(left, leftIndex++, right, rightIndex++);
} else {
leftIndex++;
}
} else {
if(rightIndex >= right.size()) {
if(right.get(0).compareTo(left.get(left.size() - 1)) < 0 )
merge(left, right);
else
return;
}
else if( right.get(0).compareTo(right.get(rightIndex)) < 0 ) {
swap(left, leftIndex++, right, 0);
} else {
swap(left, leftIndex++, right, rightIndex++);
}
}
}
if(rightIndex < right.size() && rightIndex != 0)
merge(right.subList(0, rightIndex), right.subList(rightIndex, right.size()));
}
private void swap(List<N> left, int leftIndex, List<N> right, int rightIndex) {
//N leftElement = left.get(leftIndex);
left.set(leftIndex, right.set(rightIndex, left.get(leftIndex)));
}
public static void main(String[] args) {
ForkJoinPool forkJoinPool = ForkJoinPool.commonPool();
List<Integer> result = forkJoinPool.invoke(new MergeSort<Integer>(new ArrayList<>(Arrays.asList(5,9,8,7,6,1,2,3,4))));
System.out.println("result: " + result);
}
}