最近使用WCF作为通迅框架开发一套信息系统,系统使用传统C/S框架,系统有可能会部署在互联网上,因此决定对传输的数据进行GZIP压缩,原来在使用.NET Remoting时,可以使用插入自定义的ChannelSink来实现数据压缩,作为.NET Remoting的替代方案的WCF,实现起来也很容易，且方法不止一种，主要解决方法主要有以下四种：
- 通过自定义MessageEncoder和MessageEncodingBindingElement 来完成。具体的实现，可以参阅张玉彬的文章《》和MSDN的文章《》。
- 直接创建用于压缩和解压缩的信道，在CodePlex中具有这么一个；
- 自定义MessageFormatter实现序列化后的压缩和反序列化前的解压，详见WCF大师中的博客有《》
- 自定义MessageInspector实现这就是我们今天将要讨论的解决方案。
相比较，第三和第四实现相对简单，配置很简单，它们的内部实现方法很类似，我的消息压缩类也来源于WCF大师的博客《》的消息压缩类，区别在于第三在自定义MessageFormatter中对消息进行压缩和解压缩，而第四是在自定义MessageInspector中对消息进行压缩和解压缩。下面给出第四种实现方法(网络上也很多)：
一、Compress－压缩与解压缩类
////// 压缩解压缩类 /// public class Compress { public static byte[] Zip(byte[] sourceBytes) { using (MemoryStream mStream = new MemoryStream()) { GZipStream gStream = new GZipStream(mStream, CompressionMode.Compress); gStream.Write(sourceBytes, 0, sourceBytes.Length); gStream.Close(); return mStream.ToArray(); } } public static byte[] UnZip(byte[] sourceBytes) { using (MemoryStream mStream = new MemoryStream()) { using (GZipStream gStream = new GZipStream(new MemoryStream(sourceBytes), CompressionMode.Decompress)) { int readBytes = 0; byte[] buffer = new byte[1024]; while ((readBytes = gStream.Read(buffer, 0, buffer.Length)) > 0) { mStream.Write(buffer, 0, readBytes); } return mStream.ToArray(); } } } }
二、MessageCompressor—消息压缩与解压类
////// 消息压缩类 /// public static class MessageCompress { public static string Namespace = "http://myjece"; public static Message CompressMessage(Message sourceMessage) { byte[] buffer; string sourceBody; using (XmlDictionaryReader reader1 = sourceMessage.GetReaderAtBodyContents()) { sourceBody = reader1.ReadOuterXml(); buffer = Encoding.UTF8.GetBytes(sourceBody); } XmlTextReader reader; if (buffer.Length > 256) { byte[] compressedData = Compress.Zip(buffer); string compressedBody = CreateCompressedBody(compressedData); reader = new XmlTextReader(new StringReader(compressedBody), new NameTable()); sourceMessage.AddCompressionHeader(); } else { reader = new XmlTextReader(new StringReader(sourceBody), new NameTable()); } Message message = Message.CreateMessage(sourceMessage.Version, null, (XmlReader)reader); message.Headers.CopyHeadersFrom(sourceMessage); message.Properties.CopyProperties(sourceMessage.Properties); sourceMessage.Close(); return message; } public static Message DeCompressMessage(Message sourceMessage) { if (!sourceMessage.IsCompressed()) { return sourceMessage; } else { sourceMessage.RemoveCompressionHeader(); string deCompressedBody = Encoding.UTF8.GetString(Compress.UnZip(sourceMessage.GetCompressedBody())); XmlTextReader reader = new XmlTextReader(new StringReader(deCompressedBody), new NameTable()); Message message = Message.CreateMessage(sourceMessage.Version, null, (XmlReader)reader); message.Headers.CopyHeadersFrom(sourceMessage); message.Properties.CopyProperties(sourceMessage.Properties); message.AddCompressionHeader(); //sourceMessage.Close(); return message; } } public static bool IsCompressed(this Message message) { return message.Headers.FindHeader("Compression", Namespace) > -1; } public static void AddCompressionHeader(this Message message) { message.Headers.Add(MessageHeader.CreateHeader("Compression", Namespace, "GZip")); } public static void RemoveCompressionHeader(this Message message) { message.Headers.RemoveAll("Compression", Namespace); } public static string CreateCompressedBody(byte[] content) { StringWriter output = new StringWriter(); using (XmlWriter writer2 = XmlWriter.Create(output)) { writer2.WriteStartElement("CompressedBody", Namespace); writer2.WriteBase64(content, 0, content.Length); writer2.WriteEndElement(); } return output.ToString(); } public static byte[] GetCompressedBody(this Message message) { byte[] buffer; using (XmlReader reader1 = message.GetReaderAtBodyContents()) { buffer = Convert.FromBase64String(reader1.ReadElementString("CompressedBody", Namespace)); } return buffer; } }
三、ClientCompressionInspector-客户端对消息进行压缩与解压缩的消息检查器
private class ClientCompressionInspector : IClientMessageInspector { #region IClientMessageInspector Members public void AfterReceiveReply(ref System.ServiceModel.Channels.Message reply, object correlationState) { reply = MessageCompress.DeCompressMessage(reply); } public object BeforeSendRequest(ref System.ServiceModel.Channels.Message request, System.ServiceModel.IClientChannel channel) { //加入一个消息头，表明客户端支持gzip消息压缩与解压缩 request.Headers.Add(MessageHeader.CreateHeader("AcceptEncoding", "http://myjece", "gzip")); request = MessageCompress.CompressMessage(request); return null; } #endregion }
public class ClientCompressionBehavior : BehaviorExtensionElement, IEndpointBehavior { public override Type BehaviorType { get { return typeof(ClientCompressionBehavior); } } protected override object CreateBehavior() { return new ClientCompressionBehavior(); } #region IEndpointBehavior Members public void AddBindingParameters(ServiceEndpoint endpoint, System.ServiceModel.Channels.BindingParameterCollection bindingParameters) { return; } public void ApplyClientBehavior(ServiceEndpoint endpoint, System.ServiceModel.Dispatcher.ClientRuntime clientRuntime) { clientRuntime.MessageInspectors.Add(new ClientCompressInspector()); } public void ApplyDispatchBehavior(ServiceEndpoint endpoint, System.ServiceModel.Dispatcher.EndpointDispatcher endpointDispatcher) { } public void Validate(ServiceEndpoint endpoint) { return; } } 四、ServiceCompressInspector-服务端对消息进行压缩与解压缩的消息检查器
public class ServiceCompressInspector : IDispatchMessageInspector { public object AfterReceiveRequest(ref System.ServiceModel.Channels.Message request, System.ServiceModel.IClientChannel channel, System.ServiceModel.InstanceContext instanceContext) { request = MessageCompress.DeCompressMessage(request); return null; } public void BeforeSendReply(ref System.ServiceModel.Channels.Message reply, object correlationState) { if (GetHeader("AcceptEncoding") == "gzip") { reply = MessageCompress.CompressMessage(reply); } } public static string GetHeader(string headerName) { if (OperationContext.Current.IncomingMessageHeaders.FindHeader(headerName, "http://myjece") >= 0) { return OperationContext.Current.IncomingMessageHeaders.GetHeader (headerName, "http://myjece"); } else { return null; } } } public class ServiceCompressBehavior : BehaviorExtensionElement, IServiceBehavior { public void AddBindingParameters(ServiceDescription serviceDescription, System.ServiceModel.ServiceHostBase serviceHostBase, System.Collections.ObjectModel.Collection endpoints, System.ServiceModel.Channels.BindingParameterCollection bindingParameters) { //throw new NotImplementedException(); } public void ApplyDispatchBehavior(ServiceDescription serviceDescription, System.ServiceModel.ServiceHostBase serviceHostBase) { foreach (ChannelDispatcher chDisp in serviceHostBase.ChannelDispatchers) { foreach (EndpointDispatcher epDisp in chDisp.Endpoints) { epDisp.DispatchRuntime.MessageInspectors.Add(new ServiceCompressInspector()); } } } public void Validate(ServiceDescription serviceDescription, System.ServiceModel.ServiceHostBase serviceHostBase) { //throw new NotImplementedException(); } public override Type BehaviorType { get { return typeof(ServiceCompressBehavior); } } protected override object CreateBehavior() { return new ServiceCompressBehavior(); } } 五、服务端配置
在system.serviceModel节点下添加：
好了，上面的基本的实现，可以通过在客户端行为器中添加AcceptEncoding=gzip的消息头来确定服务端返回的消息是否也可以（需要）进行压缩，实际运行结果也正常，但后来发现在进行大量byte[]类型数据传输时，发现有延时，几百K有数据，在局域网（排除网络问题）内，尽然达到2秒左右延时，开始怀疑的GZIP压缩类有问题，后发现，压缩类的对数据进行压缩时，耗时极小，一般几毫秒到几十毫秒之间，最后，只能逐语句进行排查，发现问题在消息压缩类中的：
using (XmlDictionaryReader reader1 = sourceMessage.GetReaderAtBodyContents()) { sourceBody = reader1.ReadOuterXml(); buffer = Encoding.UTF8.GetBytes(sourceBody); } Message在经过每一层消息检查器时，都是以Message方法进行传递，只有到达TransportBinding上编码器时，才会对Message进行编码，或文本，或二进制，但在我上面的消息压缩中，先从原Message中获取Body内容，然后对Body进行压缩，再把压缩Body封装进新的Message中,问题就出在获取Body内容中，XmlDictionaryReader 的ReadOuterXml()方法相当对Body进行了XML的编码，所以导致了性能问题。解决问题的根本在于找到一个能获取到Body内容，又能避免提前对Body内容进行XML编码的方法。
将上述代码改为以下代码后，性能得以大幅提升：
MemoryStream ms = new MemoryStream(); XmlDictionaryWriter writer = XmlDictionaryWriter.CreateTextWriter(ms, Encoding.UTF8); sourceMessage.WriteBodyContents(writer); writer.Flush(); buffer=ms.ToArray();
但最终获取到的buffer是一致的，是什么原因导致它们之间有巨大的性能差异就不得而知了……