先学下单词，：

这个QtConcurrent的命名控件提供了可以用来实现程序多线程的高级api， 而不用使用低级的线程的原始的api, 诸如：mutexes, read-write locks, wait conditions, or semaphores.

程序可以通过QtConcurrent类可以根据处理器的内核数量来自动调节使用线程的数量。这就意味着今天编写的应用程序可以在部署在未来的多核的机器上。

它为了进行并行的列表处理包含了一些功能性编程风格的api， 包括 MapReduce, FilterReduce他们通过内存的共享（非分布式的）系统来实现的，还有一些GUI应用程序用来进行管理异步计算的类们。

• Concurrent Map and Map-Reduce
  • QtConcurrent::map() applies a function to every item in a container, modifying the items in-place.
  • QtConcurrent::mapped() is like map(), except that it returns a new container with the modifications.
  • QtConcurrent::mappedReduced() is like mapped(), except that the modified results are reduced or folded into a single result.
• Concurrent Filter and Filter-Reduce
  • QtConcurrent::filter() removes all items from a container based on the result of a filter function.
  • QtConcurrent::filtered() is like filter(), except that it returns a new container with the filtered results.
  • QtConcurrent::filteredReduced() is like filtered(), except that the filtered results are reduced or folded into a single result.
• Concurrent Run
  • QtConcurrent::run() runs a function in another thread.
• QFuture represents the result of an asynchronous computation.
• QFutureIterator allows iterating through results available via QFuture.
• QFutureWatcher allows monitoring a QFuture using signals-and-slots.
• QFutureSynchronizer is a convenience class that automatically synchronizes several QFutures.

Qt Concurrent 支持少量的几个 STL-compatible容器和迭代器类型， 但是它和Qt 的拥有可以随机访问迭代器的容易协作的非常好， 如QList, QVector, 这个map和filter函数接收包括容器和 begin/end iterators.

支持的STL迭代器有：

Iterator Type	Example classes	Support status
Input Iterator		Not Supported
Output Iterator		Not Supported
Forward Iterator	std::slist	Supported
Bidirectional Iterator	QLinkedList, std::list	Supported
Random Access Iterator	QList, QVector, std::vector	Supported and Recommended

随机访问的迭代器可以运行的很快在Qt Concurrent正在迭代大量轻量级的items时， 因为他们可以允许在容器中跳过某些点。 另外， 使用随机迭代器访问可以允许Qt Concurrent来提供运行进行的信息通过    QFuture::progressValue () and  QFutureWatcher::progressValueChanged ().

这个不合时宜的修正一些函数如 mapped() 和 filtered() 复制了一个容器在调用的时候， 如果你正在使用STL容器来复制操作可能会消耗一些时间， 为了避免这种情况，我们建议指定容器开始和结束时使用的迭代器。

 以Qt自带的一个wordCount的例子来看并发的性能：

#include <QList>
#include <QMap>
#include <QTextStream>
#include <QString>
#include <QStringList>
#include <QDir>
#include <QTime>
#include <QApplication>
#include <QDebug>

#include <qtconcurrentmap.h>

using namespace QtConcurrent;

/*
    Utility function that recursivily searches for files.
*/
QStringList findFiles(const QString &startDir, QStringList filters)
{
    QStringList names;
    QDir dir(startDir);
    foreach (QString file, dir.entryList(filters, QDir::Files))
        names += startDir + "/" + file;

    foreach (QString subdir, dir.entryList(QDir::AllDirs | QDir::NoDotAndDotDot))
        names += findFiles(startDir + "/" + subdir, filters);
    return names;
}

typedef QMap<QString, int> WordCount;

/*
    Single threaded word counter function.
*/
WordCount singleThreadedWordCount(QStringList files)
{
    WordCount wordCount;
    foreach (QString file, files) {
        QFile f(file);
        f.open(QIODevice::ReadOnly);
        QTextStream textStream(&f);
        while (textStream.atEnd() == false)
            foreach(QString word, textStream.readLine().split(" "))
                wordCount[word] += 1;

    }
    return wordCount;
}


// countWords counts the words in a single file. This function is
// called in parallel by several threads and must be thread
// safe.
WordCount countWords(const QString &file)
{
    QFile f(file);
    f.open(QIODevice::ReadOnly);
    QTextStream textStream(&f);
    WordCount wordCount;

    while (textStream.atEnd() == false)
        foreach (QString word, textStream.readLine().split(" "))
            wordCount[word] += 1;

    return wordCount;
}

// reduce adds the results from map to the final
// result. This functor will only be called by one thread
// at a time.
void reduce(WordCount &result, const WordCount &w)
{
    QMapIterator<QString, int> i(w);
    while (i.hasNext()) {
        i.next();
        result[i.key()] += i.value();
    }
}

int main(int argc, char** argv)
{
    QApplication app(argc, argv);
    qDebug() << "finding files...";
    QStringList files = findFiles("../../", QStringList() << "*.cpp" << "*.h");
    qDebug() << files.count() << "files";

    qDebug() << "warmup";
    {
        QTime time;
        time.start();
        WordCount total = singleThreadedWordCount(files);
    }

    qDebug() << "warmup done";

    int singleThreadTime = 0;
    {
        QTime time;
        time.start();
        WordCount total = singleThreadedWordCount(files);
        singleThreadTime = time.elapsed();
        qDebug() << "single thread" << singleThreadTime;
    }

    int mapReduceTime = 0;
    {
        QTime time;
        time.start();
        WordCount total = mappedReduced(files, countWords, reduce);
        mapReduceTime = time.elapsed();
        qDebug() << "MapReduce" << mapReduceTime;
    }
    qDebug() << "MapReduce speedup x" << ((double)singleThreadTime - (double)mapReduceTime) / (double)mapReduceTime + 1;
}

附上终端的执行结果，多线程并行结果比单线程的执行快了（947-692）毫秒。。。，对于大型程序来讲是很有意义的。