同步 I/O 意味着在 I/O 操作完成之前，方法被阻塞，I/O 操作完成后，方法返回其数据。使用异步 I/O，用户可以调用 BeginRead。主线程可以继续进行其他工作，稍后，用户将能够处理数据。另外，多个 I/O 请求可以被同时挂起。
要在此数据可用时得到通知，您可以调用 EndRead 或 EndWrite，传入与您发出的 I/O 请求对应的 IAsyncResult。您还可以提供回调方法，该回调方法应调用 EndRead 或 EndWrite 以计算读取或写入了多少字节。当许多 I/O 请求被同时挂起时，异步 I/O 可以提供较好的性能，但通常要求对您的应用程序进行一些重要的调整以使其正常工作。
Stream 类支持对同一个流混合执行同步读写和异步读写，而不论操作系统是否允许这样做。Stream 将按照同步实现的方式提供异步读写操作的默认实现，并按照异步实现的方式提供同步读写操作的默认实现。
当实现 Stream 的派生类时，需要为同步或异步 Read 和 Write 方法提供实现。尽管允许重写 Read 和 Write，并且异步方法（BeginRead、EndRead、BeginWrite 和 EndWrite）的默认实现可配合同步方法的实现使用，但这样做不能提供最佳性能。同样，如果您提供了一个异步方法的实现，同步 Read 和 Write 方法也将正常工作；但如果您专门实现同步方法，性能通常会更好。ReadByte 和 WriteByte 的默认实现调用带有一个元素字节数组的同步 Read 和 Write 方法。当从 Stream 派生类时，如果有内部字节缓冲区，强烈建议重写这些方法以访问内部缓冲区，这样性能将得到提高。
连接到后备存储器的流重写同步或异步 Read 和 Write 方法，以获取默认情况下另一种方法的功能。如果流不支持异步或同步操作，实施者只需让适当的方法引发异常即可。
下面的示例是一个假设的批量图像处理器的异步实现，其后是同步实现的示例。本代码用于在目录中的每个文件上执行耗费 CPU 资源的操作。
C#
using System;
using System.IO;
using System.Threading;
using System.Runtime.InteropServices;
using System.Runtime.Remoting.Messaging;
using System.Security.Permissions;
using Microsoft.Win32.SafeHandles;
public class BulkImageProcAsync
{
public const String ImageBaseName = "tmpImage-";
public const int numImages = 200;
public const int numPixels = 512 * 512;
// ProcessImage has a simple O(N) loop, and you can vary the number
// of times you repeat that loop to make the application more CPU-
// bound or more IO-bound.
public static int processImageRepeats = 20;
// Threads must decrement NumImagesToFinish, and protect
// their access to it through a mutex.
public static int NumImagesToFinish = numImages;
public static Object[] NumImagesMutex = new Object[0];
// WaitObject is signalled when all image processing is done.
public static Object[] WaitObject = new Object[0];
public class ImageStateObject
{
public byte[] pixels;
public int imageNum;
public FileStream fs;
}
[SecurityPermissionAttribute(SecurityAction.Demand, Flags=SecurityPermissionFlag.UnmanagedCode)]
public static void MakeImageFiles()
{
int sides = (int)Math.Sqrt(numPixels);
Console.Write("Making {0} {1}x{1} images... ", numImages,
sides);
byte[] pixels = new byte[numPixels];
int i;
for (i = 0; i < numPixels; i++)
pixels[i] = (byte)i;
FileStream fs;
for (i = 0; i < numImages; i++)
{
fs = new FileStream(ImageBaseName + i + ".tmp",
FileMode.Create, FileAccess.Write, FileShare.None,
8192, false);
fs.Write(pixels, 0, pixels.Length);
FlushFileBuffers(fs.SafeFileHandle);
fs.Close();
}
fs = null;
Console.WriteLine("Done.");
}
public static void ReadInImageCallback(IAsyncResult asyncResult)
{
ImageStateObject state = (ImageStateObject)asyncResult.AsyncState;
Stream stream = state.fs;
int bytesRead = stream.EndRead(asyncResult);
if (bytesRead != numPixels)
throw new Exception(String.Format
("In ReadInImageCallback, got the wrong number of " +
"bytes from the image: {0}.", bytesRead));
ProcessImage(state.pixels, state.imageNum);
stream.Close();
// Now write out the image.
// Using asynchronous I/O here appears not to be best practice.
// It ends up swamping the threadpool, because the threadpool
// threads are blocked on I/O requests that were just queued to
// the threadpool.
FileStream fs = new FileStream(ImageBaseName + state.imageNum +
".done", FileMode.Create, FileAccess.Write, FileShare.None,
4096, false);
fs.Write(state.pixels, 0, numPixels);
fs.Close();
// This application model uses too much memory.
// Releasing memory as soon as possible is a good idea,
// especially global state.
state.pixels = null;
fs = null;
// Record that an image is finished now.
lock (NumImagesMutex)
{
NumImagesToFinish--;
if (NumImagesToFinish == 0)
{
Monitor.Enter(WaitObject);
Monitor.Pulse(WaitObject);
Monitor.Exit(WaitObject);
}
}
}
public static void ProcessImage(byte[] pixels, int imageNum)
{
Console.WriteLine("ProcessImage {0}", imageNum);
int y;
// Perform some CPU-intensive operation on the image.
for (int x = 0; x < processImageRepeats; x += 1)
for (y = 0; y < numPixels; y += 1)
pixels[y] += 1;
Console.WriteLine("ProcessImage {0} done.", imageNum);
}
public static void ProcessImagesInBulk()
{
Console.WriteLine("Processing images... ");
long t0 = Environment.TickCount;
NumImagesToFinish = numImages;
AsyncCallback readImageCallback = new
AsyncCallback(ReadInImageCallback);
for (int i = 0; i < numImages; i++)
{
ImageStateObject state = new ImageStateObject();
state.pixels = new byte[numPixels];
state.imageNum = i;
// Very large items are read only once, so you can make the
// buffer on the FileStream very small to save memory.
FileStream fs = new FileStream(ImageBaseName + i + ".tmp",
FileMode.Open, FileAccess.Read, FileShare.Read, 1, true);
state.fs = fs;
fs.BeginRead(state.pixels, 0, numPixels, readImageCallback,
state);
}
// Determine whether all images are done being processed.
// If not, block until all are finished.
bool mustBlock = false;
lock (NumImagesMutex)
{
if (NumImagesToFinish > 0)
mustBlock = true;
}
if (mustBlock)
{
Console.WriteLine("All worker threads are queued. " +
" Blocking until they complete. numLeft: {0}",
NumImagesToFinish);
Monitor.Enter(WaitObject);
Monitor.Wait(WaitObject);
Monitor.Exit(WaitObject);
}
long t1 = Environment.TickCount;
Console.WriteLine("Total time processing images: {0}ms",
(t1 - t0));
}
public static void Cleanup()
{
for (int i = 0; i < numImages; i++)
{
File.Delete(ImageBaseName + i + ".tmp");
File.Delete(ImageBaseName + i + ".done");
}
}
public static void TryToClearDiskCache()
{
// Try to force all pending writes to disk, and clear the
// disk cache of any data.
byte[] bytes = new byte[100 * (1 << 20)];
for (int i = 0; i < bytes.Length; i++)
bytes[i] = 0;
bytes = null;
GC.Collect();
Thread.Sleep(2000);
}
public static void Main(String[] args)
{
Console.WriteLine("Bulk image processing sample application," +
" using asynchronous IO");
Console.WriteLine("Simulates applying a simple " +
"transformation to {0} \"images\"", numImages);
Console.WriteLine("(Async FileStream & Threadpool benchmark)");
Console.WriteLine("Warning - this test requires {0} " +
"bytes of temporary space", (numPixels * numImages * 2));
if (args.Length == 1)
{
processImageRepeats = Int32.Parse(args[0]);
Console.WriteLine("ProcessImage inner loop - {0}.",
processImageRepeats);
}
MakeImageFiles();
TryToClearDiskCache();
ProcessImagesInBulk();
Cleanup();
}
[DllImport("KERNEL32", SetLastError = true)]
private static extern void FlushFileBuffers(SafeFileHandle handle);
}
以下是同一假设的同步示例。
C#
using System;
using System.IO;
using System.Threading;
using System.Runtime.InteropServices;
using System.Runtime.Remoting.Messaging;
using System.Security.Permissions;
using Microsoft.Win32.SafeHandles;
public class BulkImageProcSync
{
public const String ImageBaseName = "tmpImage-";
public const int numImages = 200;
public const int numPixels = 512 * 512;
// ProcessImage has a simple O(N) loop, and you can vary the number
// of times you repeat that loop to make the application more CPU-
// bound or more IO-bound.
public static int processImageRepeats = 20;
[SecurityPermissionAttribute(SecurityAction.Demand, Flags=SecurityPermissionFlag.UnmanagedCode)]
public static void MakeImageFiles()
{
int sides = (int)Math.Sqrt(numPixels);
Console.Write("Making {0} {1}x{1} images... ", numImages,
sides);
byte[] pixels = new byte[numPixels];
int i;
for (i = 0; i < numPixels; i++)
pixels[i] = (byte)i;
FileStream fs;
for (i = 0; i < numImages; i++)
{
fs = new FileStream(ImageBaseName + i + ".tmp",
FileMode.Create, FileAccess.Write, FileShare.None,
8192, false);
fs.Write(pixels, 0, pixels.Length);
FlushFileBuffers(fs.SafeFileHandle);
fs.Close();
}
fs = null;
Console.WriteLine("Done.");
}
public static void ProcessImage(byte[] pixels, int imageNum)
{
Console.WriteLine("ProcessImage {0}", imageNum);
int y;
// Perform some CPU-intensive operation on the image.
for (int x = 0; x < processImageRepeats; x += 1)
for (y = 0; y < numPixels; y += 1)
pixels[y] += 1;
Console.WriteLine("ProcessImage {0} done.", imageNum);
}
public static void ProcessImagesInBulk()
{
Console.WriteLine("Processing images... ");
long t0 = Environment.TickCount;
byte[] pixels = new byte[numPixels];
FileStream input;
FileStream output;
for (int i = 0; i < numImages; i++)
{
input = new FileStream(ImageBaseName + i + ".tmp",
FileMode.Open, FileAccess.Read, FileShare.Read,
4196, false);
input.Read(pixels, 0, numPixels);
input.Close();
ProcessImage(pixels, i);
output = new FileStream(ImageBaseName + i + ".done",
FileMode.Create, FileAccess.Write, FileShare.None,
4196, false);
output.Write(pixels, 0, numPixels);
output.Close();
}
input = null;
output = null;
long t1 = Environment.TickCount;
Console.WriteLine("Total time processing images: {0}ms",
(t1 - t0));
}
public static void Cleanup()
{
for (int i = 0; i < numImages; i++)
{
File.Delete(ImageBaseName + i + ".tmp");
File.Delete(ImageBaseName + i + ".done");
}
}
public static void TryToClearDiskCache()
{
byte[] bytes = new byte[100 * (1 << 20)];
for (int i = 0; i < bytes.Length; i++)
bytes[i] = 0;
bytes = null;
GC.Collect();
Thread.Sleep(2000);
}
public static void Main(String[] args)
{
Console.WriteLine("Bulk image processing sample application," +
" using synchronous I/O.");
Console.WriteLine("Simulates applying a simple " +
"transformation to {0} \"images.\"", numImages);
Console.WriteLine("(ie, Sync FileStream benchmark).");
Console.WriteLine("Warning - this test requires {0} " +
"bytes of temporary space", (numPixels * numImages * 2));
if (args.Length == 1)
{
processImageRepeats = Int32.Parse(args[0]);
Console.WriteLine("ProcessImage inner loop � {0}",
processImageRepeats);
}
MakeImageFiles();
TryToClearDiskCache();
ProcessImagesInBulk();
Cleanup();
}
[DllImport("KERNEL32", SetLastError = true)]
private static extern void FlushFileBuffers(SafeFileHandle handle);
} |
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