Netty实现高性能RPC服务器

 

在本人写的前一篇文章中，谈及有关如何利用Netty开发实现，高性能RPC服务器的一些设计思路、设计原理，以及具体的实现方案（具体参见：谈谈如何使用Netty开发实现高性能的RPC服务器）。在文章的最后提及到，其实基于该方案设计的RPC服务器的处理性能，还有优化的余地。于是利用周末的时间，在原来NettyRPC框架的基础上，加以优化重构，本次主要优化改造点如下：

　　1、NettyRPC中对RPC消息进行编码、解码采用的是Netty自带的ObjectEncoder、ObjectDecoder（对象编码、解码器），该编码、解码器基于的是Java的原生序列化机制，从已有的文章以及测试数据来看，Java的原生序列化性能效率不高，而且产生的序列化二进制码流太大，故本次在优化中，引入RPC消息序列化协议的概念。所谓消息序列化协议，就是针对RPC消息的序列化、反序列化过程进行特殊的定制，引入第三方编解码框架。本次引入的第三方编解码框架有Kryo、Hessian。这里，不得不再次提及一下，对象序列化、反序列化的概念，在RPC的远程服务调用过程中，需要把消息对象通过网络传输，这个就要用到序列化将对象转变成字节流，到达另外一端之后，再反序列化回来变成消息对象。

　　2、引入Google Guava并发编程框架对NettyRPC的NIO线程池、业务线程池进行重新梳理封装。

　　3、利用第三方编解码框架（Kryo、Hessian）的时候，考虑到高并发的场景下，频繁的创建、销毁序列化对象，会非常消耗JVM的内存资源，影响整个RPC服务器的处理性能，因此引入对象池化（Object Pooling）技术。众所周知，创建新对象并初始化，可能会消耗很多的时间。当需要产生大量对象的时候，可能会对性能造成一定的影响。为了解决这个问题，除了提升硬件条件之外，对象池化技术就是这方面的银弹，而Apache Commons Pool框架就是对象池化技术的一个很好的实现（开源项目路径：http://commons.apache.org/proper/commons-pool/download_pool.cgi）。本文中的Hessian池化工作，主要是基于Apache Commons Pool框架，进行封装处理。

　　本文将着重，从上面的三个方面，对重构优化之后的NettyRPC服务器的实现思路、实现方式进行重点讲解。首先请大家简单看下，本次优化之后的NettyRPC服务器支持的序列化协议，如下图所示：

  

　　可以很清楚的看到，优化之后的NettyRPC可以支持Kryo、Hessian、Java本地序列化三种消息序列化方式。其中Java本地序列化方式，相信大家应该很熟悉了，再次不在重复讲述。现在我们重点讲述一下，另外两种序列化方式：

　　1、Kryo序列化。它是针对Java，而定制实现的高效对象序列化框架，相比Java本地原生序列化方式，Kryo在处理性能上、码流大小上等等方面有很大的优化改进。目前已知的很多著名开源项目，都引入采用了该序列化方式。比如alibaba开源的dubbo RPC等等。本文中采用的Kryo的默认版本是基于：kryo-3.0.3。它的下载链接是：https://github.com/EsotericSoftware/kryo/releases/tag/kryo-parent-3.0.3。为什么采用这个版本？主要原因我上面也说明了，出于应对高并发场景下，频繁地创建、销毁序列化对象，会非常消耗JVM的内存资源、以及时间。Kryo的这个发行版本中，集成引入了序列化对象池功能模块（KryoFactory、KryoPool），这样我们就不必再利用Apache Commons Pool对其进行二次封装。

　　2、Hessian序列化。Hessian本身是一种序列化协议，它比Java原生的序列化、反序列化速度更快、序列化出来的数据也更小。它是采用二进制格式进行数据传输，而且，目前支持多种语言格式。本文中采用的是：hessian-4.0.37 版本，它的下载链接是：http://hessian.caucho.com/#Java。

　　接下来，先来看下优化之后的NettyRPC的消息协议编解码包（newlandframework.netty.rpc.serialize.support、newlandframework.netty.rpc.serialize.support.kryo、newlandframework.netty.rpc.serialize.support.hessian）的结构，如下图所示：

     

　　其中RPC请求消息结构代码如下：

/**
 * @filename:MessageRequest.java
 *
 * Newland Co. Ltd. All rights reserved.
 *
 * @Description:rpc服务请求结构
 * @author tangjie
 * @version 1.0
 *
 */
package newlandframework.netty.rpc.model;

import java.io.Serializable;
import org.apache.commons.lang.builder.ReflectionToStringBuilder;

public class MessageRequest implements Serializable {

    private String messageId;
    private String className;
    private String methodName;
    private Class<?>[] typeParameters;
    private Object[] parametersVal;

    public String getMessageId() {
        return messageId;
    }

    public void setMessageId(String messageId) {
        this.messageId = messageId;
    }

    public String getClassName() {
        return className;
    }

    public void setClassName(String className) {
        this.className = className;
    }

    public String getMethodName() {
        return methodName;
    }

    public void setMethodName(String methodName) {
        this.methodName = methodName;
    }

    public Class<?>[] getTypeParameters() {
        return typeParameters;
    }

    public void setTypeParameters(Class<?>[] typeParameters) {
        this.typeParameters = typeParameters;
    }

    public Object[] getParameters() {
        return parametersVal;
    }

    public void setParameters(Object[] parametersVal) {
        this.parametersVal = parametersVal;
    }

    public String toString() {
        return ReflectionToStringBuilder.toStringExclude(this, new String[]{"typeParameters", "parametersVal"});
    }
}

　　RPC应答消息结构，如下所示：

/**
 * @filename:MessageResponse.java
 *
 * Newland Co. Ltd. All rights reserved.
 *
 * @Description:rpc服务应答结构
 * @author tangjie
 * @version 1.0
 *
 */
package newlandframework.netty.rpc.model;

import java.io.Serializable;
import org.apache.commons.lang.builder.ReflectionToStringBuilder;

public class MessageResponse implements Serializable {

    private String messageId;
    private String error;
    private Object resultDesc;

    public String getMessageId() {
        return messageId;
    }

    public void setMessageId(String messageId) {
        this.messageId = messageId;
    }

    public String getError() {
        return error;
    }

    public void setError(String error) {
        this.error = error;
    }

    public Object getResult() {
        return resultDesc;
    }

    public void setResult(Object resultDesc) {
        this.resultDesc = resultDesc;
    }

    public String toString() {
        return ReflectionToStringBuilder.toString(this);
    }
}

　　现在，我们就来对上述的RPC请求消息、应答消息进行编解码框架的设计。由于NettyRPC中的协议类型，目前已经支持Kryo序列化、Hessian序列化、Java原生本地序列化方式。考虑到可扩展性，故要抽象出RPC消息序列化，协议类型对象（RpcSerializeProtocol），它的代码实现如下所示：

/**
 * @filename:RpcSerializeProtocol.java
 *
 * Newland Co. Ltd. All rights reserved.
 *
 * @Description:RPC消息序序列化协议类型
 * @author tangjie
 * @version 1.0
 *
 */
package newlandframework.netty.rpc.serialize.support;

import org.apache.commons.lang.builder.ReflectionToStringBuilder;
import org.apache.commons.lang.builder.ToStringStyle;

public enum RpcSerializeProtocol {

    //目前由于没有引入跨语言RPC通信机制，暂时采用支持同构语言Java序列化/反序列化机制的第三方插件
    //NettyRPC目前已知的序列化插件有:Java原生序列化、Kryo、Hessian
    JDKSERIALIZE("jdknative"), KRYOSERIALIZE("kryo"), HESSIANSERIALIZE("hessian");

    private String serializeProtocol;

    private RpcSerializeProtocol(String serializeProtocol) {
        this.serializeProtocol = serializeProtocol;
    }

    public String toString() {
        ReflectionToStringBuilder.setDefaultStyle(ToStringStyle.SHORT_PREFIX_STYLE);
        return ReflectionToStringBuilder.toString(this);
    }

    public String getProtocol() {
        return serializeProtocol;
    }
}

　　针对不同编解码序列化的框架（这里主要是指Kryo、Hessian），再抽象、萃取出一个RPC消息序列化/反序列化接口（RpcSerialize）、RPC消息编解码接口（MessageCodecUtil）。

/**
 * @filename:RpcSerialize.java
 *
 * Newland Co. Ltd. All rights reserved.
 *
 * @Description:RPC消息序列化/反序列化接口定义
 * @author tangjie
 * @version 1.0
 *
 */
package newlandframework.netty.rpc.serialize.support;

import java.io.IOException;
import java.io.InputStream;
import java.io.OutputStream;

public interface RpcSerialize {

    void serialize(OutputStream output, Object object) throws IOException;

    Object deserialize(InputStream input) throws IOException;
}

/**
 * @filename:MessageCodecUtil.java
 *
 * Newland Co. Ltd. All rights reserved.
 *
 * @Description:RPC消息编解码接口
 * @author tangjie
 * @version 1.0
 *
 */
package newlandframework.netty.rpc.serialize.support;

import io.netty.buffer.ByteBuf;
import java.io.IOException;

public interface MessageCodecUtil {

    //RPC消息报文头长度4个字节
    final public static int MESSAGE_LENGTH = 4;

    public void encode(final ByteBuf out, final Object message) throws IOException;

    public Object decode(byte[] body) throws IOException;
}

　　最后我们的NettyRPC框架要能自由地支配、定制Netty的RPC服务端、客户端，采用何种序列化来进行RPC消息对象的网络传输。因此，要再抽象一个RPC消息序列化协议选择器接口（RpcSerializeFrame），对应的实现如下：

/**
 * @filename:RpcSerializeFrame.java
 *
 * Newland Co. Ltd. All rights reserved.
 *
 * @Description:RPC消息序序列化协议选择器接口
 * @author tangjie
 * @version 1.0
 *
 */
package newlandframework.netty.rpc.serialize.support;

import io.netty.channel.ChannelPipeline;

public interface RpcSerializeFrame {

    public void select(RpcSerializeProtocol protocol, ChannelPipeline pipeline);
}

　　现在有了上面定义的一系列的接口，现在就可以定制实现，基于Kryo、Hessian方式的RPC消息序列化、反序列化模块了。先来看下整体的类图结构：

　　首先是RPC消息的编码器MessageEncoder，它继承自Netty的MessageToByteEncoder编码器。主要是把RPC消息对象编码成二进制流的格式，对应实现如下：

/**
 * @filename:MessageEncoder.java
 *
 * Newland Co. Ltd. All rights reserved.
 *
 * @Description:RPC消息编码接口
 * @author tangjie
 * @version 1.0
 *
 */
package newlandframework.netty.rpc.serialize.support;

import io.netty.buffer.ByteBuf;
import io.netty.channel.ChannelHandlerContext;
import io.netty.handler.codec.MessageToByteEncoder;

public class MessageEncoder extends MessageToByteEncoder<Object> {

    private MessageCodecUtil util = null;

    public MessageEncoder(final MessageCodecUtil util) {
        this.util = util;
    }

    protected void encode(final ChannelHandlerContext ctx, final Object msg, final ByteBuf out) throws Exception {
        util.encode(out, msg);
    }
}

　　接下来是RPC消息的解码器MessageDecoder，它继承自Netty的ByteToMessageDecoder。主要针对二进制流反序列化成消息对象。当然了，在之前的一篇文章中我曾经提到，NettyRPC是基于TCP协议的，TCP在传输数据的过程中会出现所谓的“粘包”现象，所以我们的MessageDecoder要对RPC消息体的长度进行校验，如果不满足RPC消息报文头中指定的消息体长度，我们直接重置一下ByteBuf读索引的位置，具体可以参考如下的代码方式，进行RPC消息协议的解析：

/**
 * @filename:MessageDecoder.java
 *
 * Newland Co. Ltd. All rights reserved.
 *
 * @Description:RPC消息解码接口
 * @author tangjie
 * @version 1.0
 *
 */
package newlandframework.netty.rpc.serialize.support;

import io.netty.buffer.ByteBuf;
import io.netty.channel.ChannelHandlerContext;
import io.netty.handler.codec.ByteToMessageDecoder;
import java.io.IOException;
import java.util.List;
import java.util.logging.Level;
import java.util.logging.Logger;

public class MessageDecoder extends ByteToMessageDecoder {

    final public static int MESSAGE_LENGTH = MessageCodecUtil.MESSAGE_LENGTH;
    private MessageCodecUtil util = null;

    public MessageDecoder(final MessageCodecUtil util) {
        this.util = util;
    }

    protected void decode(ChannelHandlerContext ctx, ByteBuf in, List<Object> out) {
        //出现粘包导致消息头长度不对，直接返回
        if (in.readableBytes() < MessageDecoder.MESSAGE_LENGTH) {
            return;
        }

        in.markReaderIndex();
        //读取消息的内容长度
        int messageLength = in.readInt();

        if (messageLength < 0) {
            ctx.close();
        }

        //读到的消息长度和报文头的已知长度不匹配。那就重置一下ByteBuf读索引的位置
        if (in.readableBytes() < messageLength) {
            in.resetReaderIndex();
            return;
        } else {
            byte[] messageBody = new byte[messageLength];
            in.readBytes(messageBody);

            try {
                Object obj = util.decode(messageBody);
                out.add(obj);
            } catch (IOException ex) {
                Logger.getLogger(MessageDecoder.class.getName()).log(Level.SEVERE, null, ex);
            }
        }
    }
}

　　现在，我们进一步实现，利用Kryo序列化方式，对RPC消息进行编解码的模块。首先是要实现NettyRPC消息序列化接口（RpcSerialize）的方法。

/**
 * @filename:KryoSerialize.java
 *
 * Newland Co. Ltd. All rights reserved.
 *
 * @Description:Kryo序列化/反序列化实现
 * @author tangjie
 * @version 1.0
 *
 */
package newlandframework.netty.rpc.serialize.support.kryo;

import newlandframework.netty.rpc.serialize.support.RpcSerialize;
import com.esotericsoftware.kryo.Kryo;
import com.esotericsoftware.kryo.io.Input;
import com.esotericsoftware.kryo.io.Output;
import com.esotericsoftware.kryo.pool.KryoPool;
import java.io.IOException;
import java.io.InputStream;
import java.io.OutputStream;

public class KryoSerialize implements RpcSerialize {

    private KryoPool pool = null;

    public KryoSerialize(final KryoPool pool) {
        this.pool = pool;
    }

    public void serialize(OutputStream output, Object object) throws IOException {
        Kryo kryo = pool.borrow();
        Output out = new Output(output);
        kryo.writeClassAndObject(out, object);
        out.close();
        pool.release(kryo);
    }

    public Object deserialize(InputStream input) throws IOException {
        Kryo kryo = pool.borrow();
        Input in = new Input(input);
        Object result = kryo.readClassAndObject(in);
        in.close();
        pool.release(kryo);
        return result;
    }
}

 　　接着利用Kryo库里面的对象池，对RPC消息对象进行编解码。首先是Kryo对象池工厂（KryoPoolFactory），这个也是我为什么选择kryo-3.0.3版本的原因了。代码如下：

/**
 * @filename:KryoPoolFactory.java
 *
 * Newland Co. Ltd. All rights reserved.
 *
 * @Description:Kryo对象池工厂
 * @author tangjie
 * @version 1.0
 *
 */
package newlandframework.netty.rpc.serialize.support.kryo;

import com.esotericsoftware.kryo.Kryo;
import com.esotericsoftware.kryo.pool.KryoFactory;
import com.esotericsoftware.kryo.pool.KryoPool;
import newlandframework.netty.rpc.model.MessageRequest;
import newlandframework.netty.rpc.model.MessageResponse;
import org.objenesis.strategy.StdInstantiatorStrategy;

public class KryoPoolFactory {

    private static KryoPoolFactory poolFactory = null;

    private KryoFactory factory = new KryoFactory() {
        public Kryo create() {
            Kryo kryo = new Kryo();
            kryo.setReferences(false);
            //把已知的结构注册到Kryo注册器里面，提高序列化/反序列化效率
            kryo.register(MessageRequest.class);
            kryo.register(MessageResponse.class);
            kryo.setInstantiatorStrategy(new StdInstantiatorStrategy());
            return kryo;
        }
    };

    private KryoPool pool = new KryoPool.Builder(factory).build();

    private KryoPoolFactory() {
    }

    public static KryoPool getKryoPoolInstance() {
        if (poolFactory == null) {
            synchronized (KryoPoolFactory.class) {
                if (poolFactory == null) {
                    poolFactory = new KryoPoolFactory();
                }
            }
        }
        return poolFactory.getPool();
    }

    public KryoPool getPool() {
        return pool;
    }
}

　　Kryo对RPC消息进行编码、解码的工具类KryoCodecUtil，实现了RPC消息编解码接口（MessageCodecUtil），具体实现方式如下：

/**
 * @filename:KryoCodecUtil.java
 *
 * Newland Co. Ltd. All rights reserved.
 *
 * @Description:Kryo编解码工具类
 * @author tangjie
 * @version 1.0
 *
 */
package newlandframework.netty.rpc.serialize.support.kryo;

import com.esotericsoftware.kryo.pool.KryoPool;
import io.netty.buffer.ByteBuf;
import java.io.ByteArrayInputStream;
import java.io.ByteArrayOutputStream;
import java.io.IOException;
import newlandframework.netty.rpc.serialize.support.MessageCodecUtil;
import com.google.common.io.Closer;

public class KryoCodecUtil implements MessageCodecUtil {

    private KryoPool pool;
    private static Closer closer = Closer.create();

    public KryoCodecUtil(KryoPool pool) {
        this.pool = pool;
    }

    public void encode(final ByteBuf out, final Object message) throws IOException {
        try {
            ByteArrayOutputStream byteArrayOutputStream = new ByteArrayOutputStream();
            closer.register(byteArrayOutputStream);
            KryoSerialize kryoSerialization = new KryoSerialize(pool);
            kryoSerialization.serialize(byteArrayOutputStream, message);
            byte[] body = byteArrayOutputStream.toByteArray();
            int dataLength = body.length;
            out.writeInt(dataLength);
            out.writeBytes(body);
        } finally {
            closer.close();
        }
    }

    public Object decode(byte[] body) throws IOException {
        try {
            ByteArrayInputStream byteArrayInputStream = new ByteArrayInputStream(body);
            closer.register(byteArrayInputStream);
            KryoSerialize kryoSerialization = new KryoSerialize(pool);
            Object obj = kryoSerialization.deserialize(byteArrayInputStream);
            return obj;
        } finally {
            closer.close();
        }
    }
}

　　最后是，Kryo自己的编码器、解码器，其实只要调用Kryo编解码工具类（KryoCodecUtil）里面的encode、decode方法就可以了。现在贴出具体的代码：

/**
 * @filename:KryoDecoder.java
 *
 * Newland Co. Ltd. All rights reserved.
 *
 * @Description:Kryo解码器
 * @author tangjie
 * @version 1.0
 *
 */
package newlandframework.netty.rpc.serialize.support.kryo;

import newlandframework.netty.rpc.serialize.support.MessageCodecUtil;
import newlandframework.netty.rpc.serialize.support.MessageDecoder;

public class KryoDecoder extends MessageDecoder {

    public KryoDecoder(MessageCodecUtil util) {
        super(util);
    }
}

/**
 * @filename:KryoEncoder.java
 *
 * Newland Co. Ltd. All rights reserved.
 *
 * @Description:Kryo编码器
 * @author tangjie
 * @version 1.0
 *
 */
package newlandframework.netty.rpc.serialize.support.kryo;

import newlandframework.netty.rpc.serialize.support.MessageCodecUtil;
import newlandframework.netty.rpc.serialize.support.MessageEncoder;

public class KryoEncoder extends MessageEncoder {

    public KryoEncoder(MessageCodecUtil util) {
        super(util);
    }
}

　　最后，我们再来实现一下，利用Hessian实现RPC消息的编码、解码器代码模块。首先还是Hessian序列化/反序列化实现（HessianSerialize），它同样实现了RPC消息序列化/反序列化接口（RpcSerialize），对应的代码如下：

/**
 * @filename:HessianSerialize.java
 *
 * Newland Co. Ltd. All rights reserved.
 *
 * @Description:Hessian序列化/反序列化实现
 * @author tangjie
 * @version 1.0
 *
 */
package newlandframework.netty.rpc.serialize.support.hessian;

import com.caucho.hessian.io.Hessian2Input;
import com.caucho.hessian.io.Hessian2Output;
import java.io.IOException;
import java.io.InputStream;
import java.io.OutputStream;
import newlandframework.netty.rpc.serialize.support.RpcSerialize;

public class HessianSerialize implements RpcSerialize {

    public void serialize(OutputStream output, Object object) {
        Hessian2Output ho = new Hessian2Output(output);
        try {
            ho.startMessage();
            ho.writeObject(object);
            ho.completeMessage();
            ho.close();
            output.close();
        } catch (IOException e) {
            e.printStackTrace();
        }
    }

    public Object deserialize(InputStream input) {
        Object result = null;
        try {
            Hessian2Input hi = new Hessian2Input(input);
            hi.startMessage();
            result = hi.readObject();
            hi.completeMessage();
            hi.close();
        } catch (IOException e) {
            e.printStackTrace();
        }
        return result;
    }
}

　　现在利用对象池（Object Pooling）技术，对Hessian序列化/反序列化类（HessianSerialize）进行池化处理，对应的代码如下：

/**
 * @filename:HessianSerializeFactory.java
 *
 * Newland Co. Ltd. All rights reserved.
 *
 * @Description:Hessian序列化/反序列化对象工厂池
 * @author tangjie
 * @version 1.0
 *
 */
package newlandframework.netty.rpc.serialize.support.hessian;

import org.apache.commons.pool2.BasePooledObjectFactory;
import org.apache.commons.pool2.PooledObject;
import org.apache.commons.pool2.impl.DefaultPooledObject;

public class HessianSerializeFactory extends BasePooledObjectFactory<HessianSerialize> {

    public HessianSerialize create() throws Exception {
        return createHessian();
    }

    public PooledObject<HessianSerialize> wrap(HessianSerialize hessian) {
        return new DefaultPooledObject<HessianSerialize>(hessian);
    }

    private HessianSerialize createHessian() {
        return new HessianSerialize();
    }
}

/**
 * @filename:HessianSerializePool.java
 *
 * Newland Co. Ltd. All rights reserved.
 *
 * @Description:Hessian序列化/反序列化池
 * @author tangjie
 * @version 1.0
 *
 */
package newlandframework.netty.rpc.serialize.support.hessian;

import org.apache.commons.pool2.impl.GenericObjectPool;
import org.apache.commons.pool2.impl.GenericObjectPoolConfig;

public class HessianSerializePool {

    //Netty采用Hessian序列化/反序列化的时候，为了避免重复产生对象，提高JVM内存利用率，故引入对象池技术，经过测试
    //遇到高并发序列化/反序列化的场景的时候，序列化效率明显提升不少。
    private GenericObjectPool<HessianSerialize> hessianPool;
    private static HessianSerializePool poolFactory = null;

    private HessianSerializePool() {
        hessianPool = new GenericObjectPool<HessianSerialize>(new HessianSerializeFactory());
    }

    public static HessianSerializePool getHessianPoolInstance() {
        if (poolFactory == null) {
            synchronized (HessianSerializePool.class) {
                if (poolFactory == null) {
                    poolFactory = new HessianSerializePool();
                }
            }
        }
        return poolFactory;
    }

    //预留接口，后续可以通过Spring Property Placeholder依赖注入
    public HessianSerializePool(final int maxTotal, final int minIdle, final long maxWaitMillis, final long minEvictableIdleTimeMillis) {
        hessianPool = new GenericObjectPool<HessianSerialize>(new HessianSerializeFactory());
        GenericObjectPoolConfig config = new GenericObjectPoolConfig();
        //最大池对象总数
        config.setMaxTotal(maxTotal);
        //最小空闲数
        config.setMinIdle(minIdle);
        //最大等待时间， 默认的值为-1，表示无限等待
        config.setMaxWaitMillis(maxWaitMillis);
        //退出连接的最小空闲时间 默认1800000毫秒
        config.setMinEvictableIdleTimeMillis(minEvictableIdleTimeMillis);
        hessianPool.setConfig(config);
    }

    public HessianSerialize borrow() {
        try {
            return getHessianPool().borrowObject();
        } catch (final Exception ex) {
            ex.printStackTrace();
            return null;
        }
    }

    public void restore(final HessianSerialize object) {
        getHessianPool().returnObject(object);
    }

    public GenericObjectPool<HessianSerialize> getHessianPool() {
        return hessianPool;
    }
}

　　Hessian序列化对象经过池化处理之后，我们通过Hessian编解码工具类，来“借用”Hessian序列化对象（HessianSerialize），当然了，你借出来之后，一定要还回去嘛。Hessian编解码工具类的实现方式如下：

/**
 * @filename:HessianCodecUtil.java
 *
 * Newland Co. Ltd. All rights reserved.
 *
 * @Description:Hessian编解码工具类
 * @author tangjie
 * @version 1.0
 *
 */
package newlandframework.netty.rpc.serialize.support.hessian;

import com.google.common.io.Closer;
import io.netty.buffer.ByteBuf;
import java.io.ByteArrayInputStream;
import java.io.ByteArrayOutputStream;
import java.io.IOException;
import newlandframework.netty.rpc.serialize.support.MessageCodecUtil;

public class HessianCodecUtil implements MessageCodecUtil {

    HessianSerializePool pool = HessianSerializePool.getHessianPoolInstance();
    private static Closer closer = Closer.create();

    public HessianCodecUtil() {

    }

    public void encode(final ByteBuf out, final Object message) throws IOException {
        try {
            ByteArrayOutputStream byteArrayOutputStream = new ByteArrayOutputStream();
            closer.register(byteArrayOutputStream);
            HessianSerialize hessianSerialization = pool.borrow();
            hessianSerialization.serialize(byteArrayOutputStream, message);
            byte[] body = byteArrayOutputStream.toByteArray();
            int dataLength = body.length;
            out.writeInt(dataLength);
            out.writeBytes(body);
            pool.restore(hessianSerialization);
        } finally {
            closer.close();
        }
    }

    public Object decode(byte[] body) throws IOException {
        try {
            ByteArrayInputStream byteArrayInputStream = new ByteArrayInputStream(body);
            closer.register(byteArrayInputStream);
            HessianSerialize hessianSerialization = pool.borrow();
            Object object = hessianSerialization.deserialize(byteArrayInputStream);
            pool.restore(hessianSerialization);
            return object;
        } finally {
            closer.close();
        }
    }
}

　　最后Hessian对RPC消息的编码器、解码器参考实现代码如下所示：

/**
 * @filename:HessianDecoder.java
 *
 * Newland Co. Ltd. All rights reserved.
 *
 * @Description:Hessian解码器
 * @author tangjie
 * @version 1.0
 *
 */
package newlandframework.netty.rpc.serialize.support.hessian;

import newlandframework.netty.rpc.serialize.support.MessageCodecUtil;
import newlandframework.netty.rpc.serialize.support.MessageDecoder;

public class HessianDecoder extends MessageDecoder {

    public HessianDecoder(MessageCodecUtil util) {
        super(util);
    }
}

/**
 * @filename:HessianEncoder.java
 *
 * Newland Co. Ltd. All rights reserved.
 *
 * @Description:Hessian编码器
 * @author tangjie
 * @version 1.0
 *
 */
package newlandframework.netty.rpc.serialize.support.hessian;

import newlandframework.netty.rpc.serialize.support.MessageCodecUtil;
import newlandframework.netty.rpc.serialize.support.MessageEncoder;

public class HessianEncoder extends MessageEncoder {

    public HessianEncoder(MessageCodecUtil util) {
        super(util);
    }
}

　　到目前为止，NettyRPC所针对的Kryo、Hessian序列化协议模块，已经设计实现完毕，现在我们就要把这个协议，嵌入NettyRPC的核心模块包（newlandframework.netty.rpc.core），下面只给出优化调整之后的代码，其它代码模块的内容，可以参考我上一篇的文章：谈谈如何使用Netty开发实现高性能的RPC服务器。好了，我们先来看下，NettyRPC核心模块包（newlandframework.netty.rpc.core）的层次结构：

     

　　先来看下，NettyRPC服务端的实现部分。首先是，Rpc服务端管道初始化（MessageRecvChannelInitializer），跟上一版本对比，主要引入了序列化消息对象（RpcSerializeProtocol），具体实现代码如下：

/**
 * @filename:MessageRecvChannelInitializer.java
 *
 * Newland Co. Ltd. All rights reserved.
 *
 * @Description:Rpc服务端管道初始化
 * @author tangjie
 * @version 1.0
 *
 */
package newlandframework.netty.rpc.core;

import io.netty.channel.ChannelInitializer;
import io.netty.channel.ChannelPipeline;
import io.netty.channel.socket.SocketChannel;
import java.util.Map;
import newlandframework.netty.rpc.serialize.support.RpcSerializeProtocol;

public class MessageRecvChannelInitializer extends ChannelInitializer<SocketChannel> {

    private RpcSerializeProtocol protocol;
    private RpcRecvSerializeFrame frame = null;

    MessageRecvChannelInitializer buildRpcSerializeProtocol(RpcSerializeProtocol protocol) {
        this.protocol = protocol;
        return this;
    }

    MessageRecvChannelInitializer(Map<String, Object> handlerMap) {
        frame = new RpcRecvSerializeFrame(handlerMap);
    }

    protected void initChannel(SocketChannel socketChannel) throws Exception {
        ChannelPipeline pipeline = socketChannel.pipeline();
        frame.select(protocol, pipeline);
    }
}

　　Rpc服务器执行模块（MessageRecvExecutor）中，默认的序列化采用Java原生本地序列化机制，并且优化了线程池异步调用的层次结构。具体代码如下：

/**
 * @filename:MessageRecvExecutor.java
 *
 * Newland Co. Ltd. All rights reserved.
 *
 * @Description:Rpc服务器执行模块
 * @author tangjie
 * @version 1.0
 *
 */
package newlandframework.netty.rpc.core;

import com.google.common.util.concurrent.FutureCallback;
import com.google.common.util.concurrent.Futures;
import com.google.common.util.concurrent.ListenableFuture;
import com.google.common.util.concurrent.ListeningExecutorService;
import com.google.common.util.concurrent.MoreExecutors;
import io.netty.bootstrap.ServerBootstrap;
import io.netty.channel.ChannelFuture;
import io.netty.channel.ChannelFutureListener;
import io.netty.channel.ChannelHandlerContext;
import io.netty.channel.ChannelOption;
import io.netty.channel.EventLoopGroup;
import io.netty.channel.nio.NioEventLoopGroup;
import io.netty.channel.socket.nio.NioServerSocketChannel;
import java.nio.channels.spi.SelectorProvider;
import java.util.Iterator;
import java.util.Map;
import java.util.Set;
import java.util.concurrent.Callable;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.ThreadFactory;
import java.util.concurrent.ThreadPoolExecutor;
import java.util.logging.Level;
import newlandframework.netty.rpc.model.MessageKeyVal;
import newlandframework.netty.rpc.model.MessageRequest;
import newlandframework.netty.rpc.model.MessageResponse;
import newlandframework.netty.rpc.serialize.support.RpcSerializeProtocol;
import org.springframework.beans.BeansException;
import org.springframework.beans.factory.InitializingBean;
import org.springframework.context.ApplicationContext;
import org.springframework.context.ApplicationContextAware;

public class MessageRecvExecutor implements ApplicationContextAware, InitializingBean {

    private String serverAddress;
    //默认JKD本地序列化协议
    private RpcSerializeProtocol serializeProtocol = RpcSerializeProtocol.JDKSERIALIZE;

    private final static String DELIMITER = ":";

    private Map<String, Object> handlerMap = new ConcurrentHashMap<String, Object>();

    private static ListeningExecutorService threadPoolExecutor;

    public MessageRecvExecutor(String serverAddress, String serializeProtocol) {
        this.serverAddress = serverAddress;
        this.serializeProtocol = Enum.valueOf(RpcSerializeProtocol.class, serializeProtocol);
    }

    public static void submit(Callable<Boolean> task, ChannelHandlerContext ctx, MessageRequest request, MessageResponse response) {
        if (threadPoolExecutor == null) {
            synchronized (MessageRecvExecutor.class) {
                if (threadPoolExecutor == null) {
                    threadPoolExecutor = MoreExecutors.listeningDecorator((ThreadPoolExecutor) RpcThreadPool.getExecutor(16, -1));
                }
            }
        }

        ListenableFuture<Boolean> listenableFuture = threadPoolExecutor.submit(task);
        //Netty服务端把计算结果异步返回
        Futures.addCallback(listenableFuture, new FutureCallback<Boolean>() {
            public void onSuccess(Boolean result) {
                ctx.writeAndFlush(response).addListener(new ChannelFutureListener() {
                    public void operationComplete(ChannelFuture channelFuture) throws Exception {
                        System.out.println("RPC Server Send message-id respone:" + request.getMessageId());
                    }
                });
            }

            public void onFailure(Throwable t) {
                t.printStackTrace();
            }
        }, threadPoolExecutor);
    }

    public void setApplicationContext(ApplicationContext ctx) throws BeansException {
        try {
            MessageKeyVal keyVal = (MessageKeyVal) ctx.getBean(Class.forName("newlandframework.netty.rpc.model.MessageKeyVal"));
            Map<String, Object> rpcServiceObject = keyVal.getMessageKeyVal();

            Set s = rpcServiceObject.entrySet();
            Iterator<Map.Entry<String, Object>> it = s.iterator();
            Map.Entry<String, Object> entry;

            while (it.hasNext()) {
                entry = it.next();
                handlerMap.put(entry.getKey(), entry.getValue());
            }
        } catch (ClassNotFoundException ex) {
            java.util.logging.Logger.getLogger(MessageRecvExecutor.class.getName()).log(Level.SEVERE, null, ex);
        }
    }

    public void afterPropertiesSet() throws Exception {
        //netty的线程池模型设置成主从线程池模式，这样可以应对高并发请求
        //当然netty还支持单线程、多线程网络IO模型，可以根据业务需求灵活配置
        ThreadFactory threadRpcFactory = new NamedThreadFactory("NettyRPC ThreadFactory");

        //方法返回到Java虚拟机的可用的处理器数量
        int parallel = Runtime.getRuntime().availableProcessors() * 2;

        EventLoopGroup boss = new NioEventLoopGroup();
        EventLoopGroup worker = new NioEventLoopGroup(parallel, threadRpcFactory, SelectorProvider.provider());

        try {
            ServerBootstrap bootstrap = new ServerBootstrap();
            bootstrap.group(boss, worker).channel(NioServerSocketChannel.class)
                    .childHandler(new MessageRecvChannelInitializer(handlerMap).buildRpcSerializeProtocol(serializeProtocol))
                    .option(ChannelOption.SO_BACKLOG, 128)
                    .childOption(ChannelOption.SO_KEEPALIVE, true);

            String[] ipAddr = serverAddress.split(MessageRecvExecutor.DELIMITER);

            if (ipAddr.length == 2) {
                String host = ipAddr[0];
                int port = Integer.parseInt(ipAddr[1]);
                ChannelFuture future = bootstrap.bind(host, port).sync();
                System.out.printf("[author tangjie] Netty RPC Server start success!\nip:%s\nport:%d\nprotocol:%s\n\n", host, port, serializeProtocol);
                future.channel().closeFuture().sync();
            } else {
                System.out.printf("[author tangjie] Netty RPC Server start fail!\n");
            }
        } finally {
            worker.shutdownGracefully();
            boss.shutdownGracefully();
        }
    }
}

　　Rpc服务器消息处理（MessageRecvHandler）也跟随着调整：

/**
 * @filename:MessageRecvHandler.java
 *
 * Newland Co. Ltd. All rights reserved.
 *
 * @Description:Rpc服务器消息处理
 * @author tangjie
 * @version 1.0
 *
 */
package newlandframework.netty.rpc.core;

import io.netty.channel.ChannelHandlerContext;
import io.netty.channel.ChannelInboundHandlerAdapter;
import java.util.Map;
import newlandframework.netty.rpc.model.MessageRequest;
import newlandframework.netty.rpc.model.MessageResponse;

public class MessageRecvHandler extends ChannelInboundHandlerAdapter {

    private final Map<String, Object> handlerMap;

    public MessageRecvHandler(Map<String, Object> handlerMap) {
        this.handlerMap = handlerMap;
    }

    public void channelRead(ChannelHandlerContext ctx, Object msg) throws Exception {
        MessageRequest request = (MessageRequest) msg;
        MessageResponse response = new MessageResponse();
        MessageRecvInitializeTask recvTask = new MessageRecvInitializeTask(request, response, handlerMap);
        //不要阻塞nio线程，复杂的业务逻辑丢给专门的线程池
        MessageRecvExecutor.submit(recvTask, ctx, request, response);
    }

    public void exceptionCaught(ChannelHandlerContext ctx, Throwable cause) {
        //网络有异常要关闭通道
        ctx.close();
    }
}

　　Rpc服务器消息线程任务处理（MessageRecvInitializeTask）完成的任务也更加单纯，即根据RPC消息的请求报文，利用反射得到最终的计算结果，并把结果写入RPC应答报文结构。代码如下：

/**
 * @filename:MessageRecvInitializeTask.java
 *
 * Newland Co. Ltd. All rights reserved.
 *
 * @Description:Rpc服务器消息线程任务处理
 * @author tangjie
 * @version 1.0
 *
 */
package newlandframework.netty.rpc.core;

import io.netty.channel.ChannelHandlerContext;
import java.util.Map;
import java.util.concurrent.Callable;
import newlandframework.netty.rpc.model.MessageRequest;
import newlandframework.netty.rpc.model.MessageResponse;
import org.apache.commons.lang.reflect.MethodUtils;

public class MessageRecvInitializeTask implements Callable<Boolean> {

    private MessageRequest request = null;
    private MessageResponse response = null;
    private Map<String, Object> handlerMap = null;
    private ChannelHandlerContext ctx = null;

    public MessageResponse getResponse() {
        return response;
    }

    public MessageRequest getRequest() {
        return request;
    }

    public void setRequest(MessageRequest request) {
        this.request = request;
    }

    MessageRecvInitializeTask(MessageRequest request, MessageResponse response, Map<String, Object> handlerMap) {
        this.request = request;
        this.response = response;
        this.handlerMap = handlerMap;
        this.ctx = ctx;
    }

    public Boolean call() {
        response.setMessageId(request.getMessageId());
        try {
            Object result = reflect(request);
            response.setResult(result);
            return Boolean.TRUE;
        } catch (Throwable t) {
            response.setError(t.toString());
            t.printStackTrace();
            System.err.printf("RPC Server invoke error!\n");
            return Boolean.FALSE;
        }
    }

    private Object reflect(MessageRequest request) throws Throwable {
        String className = request.getClassName();
        Object serviceBean = handlerMap.get(className);
        String methodName = request.getMethodName();
        Object[] parameters = request.getParameters();
        return MethodUtils.invokeMethod(serviceBean, methodName, parameters);
    }
}

　　刚才说到了，NettyRPC的服务端，可以选择具体的序列化协议，目前是通过硬编码方式实现。后续可以考虑，通过Spring IOC方式，依赖注入。其对应代码如下：

/**
 * @filename:RpcRecvSerializeFrame.java
 *
 * Newland Co. Ltd. All rights reserved.
 *
 * @Description:RPC服务端消息序列化协议框架
 * @author tangjie
 * @version 1.0
 *
 */
package newlandframework.netty.rpc.core;

import io.netty.channel.ChannelPipeline;
import io.netty.handler.codec.LengthFieldBasedFrameDecoder;
import io.netty.handler.codec.LengthFieldPrepender;
import io.netty.handler.codec.serialization.ClassResolvers;
import io.netty.handler.codec.serialization.ObjectDecoder;
import io.netty.handler.codec.serialization.ObjectEncoder;
import java.util.Map;
import newlandframework.netty.rpc.serialize.support.MessageCodecUtil;
import newlandframework.netty.rpc.serialize.support.RpcSerializeFrame;
import newlandframework.netty.rpc.serialize.support.RpcSerializeProtocol;
import newlandframework.netty.rpc.serialize.support.hessian.HessianCodecUtil;
import newlandframework.netty.rpc.serialize.support.hessian.HessianDecoder;
import newlandframework.netty.rpc.serialize.support.hessian.HessianEncoder;
import newlandframework.netty.rpc.serialize.support.kryo.KryoCodecUtil;
import newlandframework.netty.rpc.serialize.support.kryo.KryoDecoder;
import newlandframework.netty.rpc.serialize.support.kryo.KryoEncoder;
import newlandframework.netty.rpc.serialize.support.kryo.KryoPoolFactory;

public class RpcRecvSerializeFrame implements RpcSerializeFrame {

    private Map<String, Object> handlerMap = null;

    public RpcRecvSerializeFrame(Map<String, Object> handlerMap) {
        this.handlerMap = handlerMap;
    }

    //后续可以优化成通过spring ioc方式注入
    public void select(RpcSerializeProtocol protocol, ChannelPipeline pipeline) {
        switch (protocol) {
            case JDKSERIALIZE: {
                pipeline.addLast(new LengthFieldBasedFrameDecoder(Integer.MAX_VALUE, 0, MessageCodecUtil.MESSAGE_LENGTH, 0, MessageCodecUtil.MESSAGE_LENGTH));
                pipeline.addLast(new LengthFieldPrepender(MessageCodecUtil.MESSAGE_LENGTH));
                pipeline.addLast(new ObjectEncoder());
                pipeline.addLast(new ObjectDecoder(Integer.MAX_VALUE, ClassResolvers.weakCachingConcurrentResolver(this.getClass().getClassLoader())));
                pipeline.addLast(new MessageRecvHandler(handlerMap));
                break;
            }
            case KRYOSERIALIZE: {
                KryoCodecUtil util = new KryoCodecUtil(KryoPoolFactory.getKryoPoolInstance());
                pipeline.addLast(new KryoEncoder(util));
                pipeline.addLast(new KryoDecoder(util));
                pipeline.addLast(new MessageRecvHandler(handlerMap));
                break;
            }
            case HESSIANSERIALIZE: {
                HessianCodecUtil util = new HessianCodecUtil();
                pipeline.addLast(new HessianEncoder(util));
                pipeline.addLast(new HessianDecoder(util));
                pipeline.addLast(new MessageRecvHandler(handlerMap));
                break;
            }
        }
    }
}

　　到目前为止，NettyRPC的服务端的设计实现，已经告一段落。

　　现在继续实现一下NettyRPC的客户端模块。其中，Rpc客户端管道初始化（MessageSendChannelInitializer）模块调整之后，同样也支持选择具体的消息序列化协议（RpcSerializeProtocol）。代码如下：

/**
 * @filename:MessageSendChannelInitializer.java
 *
 * Newland Co. Ltd. All rights reserved.
 *
 * @Description:Rpc客户端管道初始化
 * @author tangjie
 * @version 1.0
 *
 */
package newlandframework.netty.rpc.core;

import io.netty.channel.ChannelInitializer;
import io.netty.channel.ChannelPipeline;
import io.netty.channel.socket.SocketChannel;
import newlandframework.netty.rpc.serialize.support.RpcSerializeProtocol;

public class MessageSendChannelInitializer extends ChannelInitializer<SocketChannel> {

    private RpcSerializeProtocol protocol;
    private RpcSendSerializeFrame frame = new RpcSendSerializeFrame();

    MessageSendChannelInitializer buildRpcSerializeProtocol(RpcSerializeProtocol protocol) {
        this.protocol = protocol;
        return this;
    }

    protected void initChannel(SocketChannel socketChannel) throws Exception {
        ChannelPipeline pipeline = socketChannel.pipeline();
        frame.select(protocol, pipeline);
    }
}

　　Rpc客户端执行模块（MessageSendExecutor）代码实现如下：

/**
 * @filename:MessageSendExecutor.java
 *
 * Newland Co. Ltd. All rights reserved.
 *
 * @Description:Rpc客户端执行模块
 * @author tangjie
 * @version 1.0
 *
 */
package newlandframework.netty.rpc.core;

import com.google.common.reflect.Reflection;
import newlandframework.netty.rpc.serialize.support.RpcSerializeProtocol;

public class MessageSendExecutor {

    private RpcServerLoader loader = RpcServerLoader.getInstance();

    public MessageSendExecutor() {
    }

    public MessageSendExecutor(String serverAddress, RpcSerializeProtocol serializeProtocol) {
        loader.load(serverAddress, serializeProtocol);
    }

    public void setRpcServerLoader(String serverAddress, RpcSerializeProtocol serializeProtocol) {
        loader.load(serverAddress, serializeProtocol);
    }

    public void stop() {
        loader.unLoad();
    }

    public static <T> T execute(Class<T> rpcInterface) {
        return (T) Reflection.newProxy(rpcInterface, new MessageSendProxy<T>());
    }
}

　　Rpc客户端线程任务处理（MessageSendInitializeTask），其中参数增加了协议类型（RpcSerializeProtocol），具体代码如下：

/**
 * @filename:MessageSendInitializeTask.java
 *
 * Newland Co. Ltd. All rights reserved.
 *
 * @Description:Rpc客户端线程任务处理
 * @author tangjie
 * @version 1.0
 *
 */
package newlandframework.netty.rpc.core;

import io.netty.bootstrap.Bootstrap;
import io.netty.channel.ChannelFuture;
import io.netty.channel.ChannelFutureListener;
import io.netty.channel.ChannelOption;
import io.netty.channel.EventLoopGroup;
import io.netty.channel.socket.nio.NioSocketChannel;
import java.net.InetSocketAddress;
import java.util.concurrent.Callable;
import newlandframework.netty.rpc.serialize.support.RpcSerializeProtocol;

public class MessageSendInitializeTask implements Callable<Boolean> {

    private EventLoopGroup eventLoopGroup = null;
    private InetSocketAddress serverAddress = null;
    private RpcSerializeProtocol protocol;

    MessageSendInitializeTask(EventLoopGroup eventLoopGroup, InetSocketAddress serverAddress, RpcSerializeProtocol protocol) {
        this.eventLoopGroup = eventLoopGroup;
        this.serverAddress = serverAddress;
        this.protocol = protocol;
    }

    public Boolean call() {
        Bootstrap b = new Bootstrap();
        b.group(eventLoopGroup)
                .channel(NioSocketChannel.class).option(ChannelOption.SO_KEEPALIVE, true);
        b.handler(new MessageSendChannelInitializer().buildRpcSerializeProtocol(protocol));

        ChannelFuture channelFuture = b.connect(serverAddress);
        channelFuture.addListener(new ChannelFutureListener() {
            public void operationComplete(final ChannelFuture channelFuture) throws Exception {
                if (channelFuture.isSuccess()) {
                    MessageSendHandler handler = channelFuture.channel().pipeline().get(MessageSendHandler.class);
                    RpcServerLoader.getInstance().setMessageSendHandler(handler);
                }
            }
        });
        return Boolean.TRUE;
    }
}

　　Rpc客户端消息处理（MessageSendProxy）的实现方式调整重构之后，如下所示：

/**
 * @filename:MessageSendProxy.java
 *
 * Newland Co. Ltd. All rights reserved.
 *
 * @Description:Rpc客户端消息处理
 * @author tangjie
 * @version 1.0
 *
 */
package newlandframework.netty.rpc.core;

import java.lang.reflect.Method;
import java.util.UUID;
import newlandframework.netty.rpc.model.MessageRequest;
import com.google.common.reflect.AbstractInvocationHandler;

public class MessageSendProxy<T> extends AbstractInvocationHandler {

    public Object handleInvocation(Object proxy, Method method, Object[] args) throws Throwable {
        MessageRequest request = new MessageRequest();
        request.setMessageId(UUID.randomUUID().toString());
        request.setClassName(method.getDeclaringClass().getName());
        request.setMethodName(method.getName());
        request.setTypeParameters(method.getParameterTypes());
        request.setParameters(args);

        MessageSendHandler handler = RpcServerLoader.getInstance().getMessageSendHandler();
        MessageCallBack callBack = handler.sendRequest(request);
        return callBack.start();
    }
}

　　同样，NettyRPC的客户端也是可以选择协议类型的，必须注意的是，NettyRPC的客户端和服务端的协议类型必须一致，才能互相通信。NettyRPC的客户端消息序列化协议框架代码实现方式如下：

/**
 * @filename:RpcSendSerializeFrame.java
 *
 * Newland Co. Ltd. All rights reserved.
 *
 * @Description:RPC客户端消息序列化协议框架
 * @author tangjie
 * @version 1.0
 *
 */
package newlandframework.netty.rpc.core;

import io.netty.channel.ChannelPipeline;
import io.netty.handler.codec.LengthFieldBasedFrameDecoder;
import io.netty.handler.codec.LengthFieldPrepender;
import io.netty.handler.codec.serialization.ClassResolvers;
import io.netty.handler.codec.serialization.ObjectDecoder;
import io.netty.handler.codec.serialization.ObjectEncoder;
import newlandframework.netty.rpc.serialize.support.MessageCodecUtil;
import newlandframework.netty.rpc.serialize.support.hessian.HessianCodecUtil;
import newlandframework.netty.rpc.serialize.support.hessian.HessianDecoder;
import newlandframework.netty.rpc.serialize.support.hessian.HessianEncoder;
import newlandframework.netty.rpc.serialize.support.kryo.KryoCodecUtil;
import newlandframework.netty.rpc.serialize.support.kryo.KryoDecoder;
import newlandframework.netty.rpc.serialize.support.kryo.KryoEncoder;
import newlandframework.netty.rpc.serialize.support.kryo.KryoPoolFactory;
import newlandframework.netty.rpc.serialize.support.RpcSerializeFrame;
import newlandframework.netty.rpc.serialize.support.RpcSerializeProtocol;

public class RpcSendSerializeFrame implements RpcSerializeFrame {

    //后续可以优化成通过spring ioc方式注入
    public void select(RpcSerializeProtocol protocol, ChannelPipeline pipeline) {
        switch (protocol) {
            case JDKSERIALIZE: {
                pipeline.addLast(new LengthFieldBasedFrameDecoder(Integer.MAX_VALUE, 0, MessageCodecUtil.MESSAGE_LENGTH, 0, MessageCodecUtil.MESSAGE_LENGTH));
                pipeline.addLast(new LengthFieldPrepender(MessageCodecUtil.MESSAGE_LENGTH));
                pipeline.addLast(new ObjectEncoder());
                pipeline.addLast(new ObjectDecoder(Integer.MAX_VALUE, ClassResolvers.weakCachingConcurrentResolver(this.getClass().getClassLoader())));
                pipeline.addLast(new MessageSendHandler());
                break;
            }
            case KRYOSERIALIZE: {
                KryoCodecUtil util = new KryoCodecUtil(KryoPoolFactory.getKryoPoolInstance());
                pipeline.addLast(new KryoEncoder(util));
                pipeline.addLast(new KryoDecoder(util));
                pipeline.addLast(new MessageSendHandler());
                break;
            }
            case HESSIANSERIALIZE: {
                HessianCodecUtil util = new HessianCodecUtil();
                pipeline.addLast(new HessianEncoder(util));
                pipeline.addLast(new HessianDecoder(util));
                pipeline.addLast(new MessageSendHandler());
                break;
            }
        }
    }
}

　　最后，NettyRPC客户端，要加载NettyRPC服务端的一些上下文（Context）信息。因此，RPC服务器配置加载（RpcServerLoader）的代码重构调整如下：

/**
 * @filename:RpcServerLoader.java
 *
 * Newland Co. Ltd. All rights reserved.
 *
 * @Description:rpc服务器配置加载
 * @author tangjie
 * @version 1.0
 *
 */
package newlandframework.netty.rpc.core;

import com.google.common.util.concurrent.FutureCallback;
import com.google.common.util.concurrent.Futures;
import com.google.common.util.concurrent.ListenableFuture;
import com.google.common.util.concurrent.ListeningExecutorService;
import com.google.common.util.concurrent.MoreExecutors;
import io.netty.channel.EventLoopGroup;
import io.netty.channel.nio.NioEventLoopGroup;
import java.net.InetSocketAddress;
import java.util.concurrent.ThreadPoolExecutor;
import java.util.concurrent.locks.Condition;
import java.util.concurrent.locks.Lock;
import java.util.concurrent.locks.ReentrantLock;
import java.util.logging.Level;
import java.util.logging.Logger;
import newlandframework.netty.rpc.serialize.support.RpcSerializeProtocol;

public class RpcServerLoader {

    private volatile static RpcServerLoader rpcServerLoader;
    private final static String DELIMITER = ":";
    //默认采用Java原生序列化协议方式传输RPC消息
    private RpcSerializeProtocol serializeProtocol = RpcSerializeProtocol.JDKSERIALIZE;

    //方法返回到Java虚拟机的可用的处理器数量
    private final static int parallel = Runtime.getRuntime().availableProcessors() * 2;
    //netty nio线程池
    private EventLoopGroup eventLoopGroup = new NioEventLoopGroup(parallel);
    private static ListeningExecutorService threadPoolExecutor = MoreExecutors.listeningDecorator((ThreadPoolExecutor) RpcThreadPool.getExecutor(16, -1));
    private MessageSendHandler messageSendHandler = null;

    //等待Netty服务端链路建立通知信号
    private Lock lock = new ReentrantLock();
    private Condition connectStatus = lock.newCondition();
    private Condition handlerStatus = lock.newCondition();

    private RpcServerLoader() {
    }

    //并发双重锁定
    public static RpcServerLoader getInstance() {
        if (rpcServerLoader == null) {
            synchronized (RpcServerLoader.class) {
                if (rpcServerLoader == null) {
                    rpcServerLoader = new RpcServerLoader();
                }
            }
        }
        return rpcServerLoader;
    }

    public void load(String serverAddress, RpcSerializeProtocol serializeProtocol) {
        String[] ipAddr = serverAddress.split(RpcServerLoader.DELIMITER);
        if (ipAddr.length == 2) {
            String host = ipAddr[0];
            int port = Integer.parseInt(ipAddr[1]);
            final InetSocketAddress remoteAddr = new InetSocketAddress(host, port);

            ListenableFuture<Boolean> listenableFuture = threadPoolExecutor.submit(new MessageSendInitializeTask(eventLoopGroup, remoteAddr, serializeProtocol));

            //监听线程池异步的执行结果成功与否再决定是否唤醒全部的客户端RPC线程
            Futures.addCallback(listenableFuture, new FutureCallback<Boolean>() {
                public void onSuccess(Boolean result) {
                    try {
                        lock.lock();

                        if (messageSendHandler == null) {
                            handlerStatus.await();
                        }

                        //Futures异步回调，唤醒所有rpc等待线程
                        if (result == Boolean.TRUE && messageSendHandler != null) {
                            connectStatus.signalAll();
                        }
                    } catch (InterruptedException ex) {
                        Logger.getLogger(RpcServerLoader.class.getName()).log(Level.SEVERE, null, ex);
                    } finally {
                        lock.unlock();
                    }
                }

                public void onFailure(Throwable t) {
                    t.printStackTrace();
                }
            }, threadPoolExecutor);
        }
    }

    public void setMessageSendHandler(MessageSendHandler messageInHandler) {
        try {
            lock.lock();
            this.messageSendHandler = messageInHandler;
            handlerStatus.signal();
        } finally {
            lock.unlock();
        }
    }

    public MessageSendHandler getMessageSendHandler() throws InterruptedException {
        try {
            lock.lock();
            //Netty服务端链路没有建立完毕之前，先挂起等待
            if (messageSendHandler == null) {
                connectStatus.await();
            }
            return messageSendHandler;
        } finally {
            lock.unlock();
        }
    }

    public void unLoad() {
        messageSendHandler.close();
        threadPoolExecutor.shutdown();
        eventLoopGroup.shutdownGracefully();
    }

    public void setSerializeProtocol(RpcSerializeProtocol serializeProtocol) {
        this.serializeProtocol = serializeProtocol;
    }
}

到目前为止，NettyRPC的主要核心模块的代码，全部呈现出来了。到底经过改良重构之后，NettyRPC服务器的性能如何？还是那句话，实践是检验真理的唯一标准。现在，我们就来启动三台NettyRPC服务器进行验证。具体服务端的配置参数，参考如下：

1、Java原生本地序列化NettyRPC服务器，对应IP为：127.0.0.1:18887。

2、Kryo序列化NettyRPC服务器，对应IP为：127.0.0.1:18888。

3、Hessian序列化NettyRPC服务器，对应IP为：127.0.0.1:18889。

具体的Spring配置文件结构如下所示：

 

参数配置的内容如下：

rpc-server-jdknative.properties

#rpc server's ip address config
rpc.server.addr=127.0.0.1:18887

rpc-server-kryo.properties

#rpc server's ip address config
rpc.server.addr=127.0.0.1:18888

rpc-server-hessian.properties

#rpc server's ip address config
rpc.server.addr=127.0.0.1:18889

rpc-invoke-config-jdknative.xml

<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
       xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
       xmlns:context="http://www.springframework.org/schema/context"
       xsi:schemaLocation="http://www.springframework.org/schema/beans
       http://www.springframework.org/schema/beans/spring-beans.xsd
       http://www.springframework.org/schema/context
       http://www.springframework.org/schema/context/spring-context.xsd">
  <context:component-scan base-package="newlandframework.netty.rpc.core"/>
  <context:property-placeholder location="classpath:newlandframework/netty/rpc/config/rpc-server-jdknative.properties"/>
  <bean id="rpcbean" class="newlandframework.netty.rpc.model.MessageKeyVal">
    <property name="messageKeyVal">
      <map>
        <entry key="newlandframework.netty.rpc.servicebean.Calculate">
          <ref bean="calc"/>
        </entry>
      </map>
    </property>
  </bean>
  <bean id="calc" class="newlandframework.netty.rpc.servicebean.CalculateImpl"/>
  <bean id="rpcServer" class="newlandframework.netty.rpc.core.MessageRecvExecutor">
    <constructor-arg name="serverAddress" value="${rpc.server.addr}"/>
    <constructor-arg name="serializeProtocol" value="JDKSERIALIZE"/>
  </bean>
</beans>

rpc-invoke-config-kryo.xml

<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
       xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
       xmlns:context="http://www.springframework.org/schema/context"
       xsi:schemaLocation="http://www.springframework.org/schema/beans
       http://www.springframework.org/schema/beans/spring-beans.xsd
       http://www.springframework.org/schema/context
       http://www.springframework.org/schema/context/spring-context.xsd">
  <context:component-scan base-package="newlandframework.netty.rpc.core"/>
  <context:property-placeholder location="classpath:newlandframework/netty/rpc/config/rpc-server-kryo.properties"/>
  <bean id="rpcbean" class="newlandframework.netty.rpc.model.MessageKeyVal">
    <property name="messageKeyVal">
      <map>
        <entry key="newlandframework.netty.rpc.servicebean.Calculate">
          <ref bean="calc"/>
        </entry>
      </map>
    </property>
  </bean>
  <bean id="calc" class="newlandframework.netty.rpc.servicebean.CalculateImpl"/>
  <bean id="rpcServer" class="newlandframework.netty.rpc.core.MessageRecvExecutor">
    <constructor-arg name="serverAddress" value="${rpc.server.addr}"/>
    <constructor-arg name="serializeProtocol" value="KRYOSERIALIZE"/>
  </bean>
</beans>

rpc-invoke-config-hessian.xml

<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
       xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
       xmlns:context="http://www.springframework.org/schema/context"
       xsi:schemaLocation="http://www.springframework.org/schema/beans
       http://www.springframework.org/schema/beans/spring-beans.xsd
       http://www.springframework.org/schema/context
       http://www.springframework.org/schema/context/spring-context.xsd">
  <context:component-scan base-package="newlandframework.netty.rpc.core"/>
  <context:property-placeholder location="classpath:newlandframework/netty/rpc/config/rpc-server-hessian.properties"/>
  <bean id="rpcbean" class="newlandframework.netty.rpc.model.MessageKeyVal">
    <property name="messageKeyVal">
      <map>
        <entry key="newlandframework.netty.rpc.servicebean.Calculate">
          <ref bean="calc"/>
        </entry>
      </map>
    </property>
  </bean>
  <bean id="calc" class="newlandframework.netty.rpc.servicebean.CalculateImpl"/>
  <bean id="rpcServer" class="newlandframework.netty.rpc.core.MessageRecvExecutor">
    <constructor-arg name="serverAddress" value="${rpc.server.addr}"/>
    <constructor-arg name="serializeProtocol" value="HESSIANSERIALIZE"/>
  </bean>
</beans>

　　然后，对应的NettRPC服务器启动方式参考如下：

new ClassPathXmlApplicationContext("newlandframework/netty/rpc/config/rpc-invoke-config-jdknative.xml");
new ClassPathXmlApplicationContext("newlandframework/netty/rpc/config/rpc-invoke-config-kryo.xml");
new ClassPathXmlApplicationContext("newlandframework/netty/rpc/config/rpc-invoke-config-hessian.xml");

　　如果一切顺利的话，在控制台上，会打印出支持Java原生序列化、Kryo序列化、Hessian序列化的NettyRPC服务器的启动信息，具体截图如下：

　　首先是Java原生序列化NettyRPC启动成功截图：

     

　　然后是Kryo序列化NettyRPC启动成功截图:

     

　　最后是Hessian序列化NettyRPC启动成功截图：

     

　　现在，还是跟我上一篇文章用到的并发测试用例一样，设计构造一个，瞬时值并行度1W的求和计算RPC请求，总共请求10笔，然后观察每一笔具体协议（Java原生序列化、Kryo、Hessian）的RPC消息编码、解码消耗时长（毫秒）。

　　测试代码如下所示：

/**
 * @filename:RpcParallelTest.java
 *
 * Newland Co. Ltd. All rights reserved.
 *
 * @Description:rpc并发测试代码
 * @author tangjie
 * @version 1.0
 *
 */
package newlandframework.netty.rpc.servicebean;

import java.util.concurrent.CountDownLatch;
import java.util.concurrent.TimeUnit;
import newlandframework.netty.rpc.core.MessageSendExecutor;
import newlandframework.netty.rpc.serialize.support.RpcSerializeProtocol;
import org.apache.commons.lang.time.StopWatch;

public class RpcParallelTest {

    public static void parallelTask(MessageSendExecutor executor, int parallel, String serverAddress, RpcSerializeProtocol protocol) throws InterruptedException {
        //开始计时
        StopWatch sw = new StopWatch();
        sw.start();

        CountDownLatch signal = new CountDownLatch(1);
        CountDownLatch finish = new CountDownLatch(parallel);

        for (int index = 0; index < parallel; index++) {
            CalcParallelRequestThread client = new CalcParallelRequestThread(executor, signal, finish, index);
            new Thread(client).start();
        }

        //10000个并发线程瞬间发起请求操作
        signal.countDown();
        finish.await();
        sw.stop();

        String tip = String.format("[%s] RPC调用总共耗时: [%s] 毫秒", protocol, sw.getTime());
        System.out.println(tip);

    }

    //JDK本地序列化协议
    public static void JdkNativeParallelTask(MessageSendExecutor executor, int parallel) throws InterruptedException {
        String serverAddress = "127.0.0.1:18887";
        RpcSerializeProtocol protocol = RpcSerializeProtocol.JDKSERIALIZE;
        executor.setRpcServerLoader(serverAddress, protocol);
        RpcParallelTest.parallelTask(executor, parallel, serverAddress, protocol);
        TimeUnit.SECONDS.sleep(3);
    }

    //Kryo序列化协议
    public static void KryoParallelTask(MessageSendExecutor executor, int parallel) throws InterruptedException {
        String serverAddress = "127.0.0.1:18888";
        RpcSerializeProtocol protocol = RpcSerializeProtocol.KRYOSERIALIZE;
        executor.setRpcServerLoader(serverAddress, protocol);
        RpcParallelTest.parallelTask(executor, parallel, serverAddress, protocol);
        TimeUnit.SECONDS.sleep(3);
    }

    //Hessian序列化协议
    public static void HessianParallelTask(MessageSendExecutor executor, int parallel) throws InterruptedException {
        String serverAddress = "127.0.0.1:18889";
        RpcSerializeProtocol protocol = RpcSerializeProtocol.HESSIANSERIALIZE;
        executor.setRpcServerLoader(serverAddress, protocol);
        RpcParallelTest.parallelTask(executor, parallel, serverAddress, protocol);
        TimeUnit.SECONDS.sleep(3);
    }

    public static void main(String[] args) throws Exception {
        //并行度10000
        int parallel = 10000;
        MessageSendExecutor executor = new MessageSendExecutor();

        for (int i = 0; i < 10; i++) {
            JdkNativeParallelTask(executor, parallel);
            KryoParallelTask(executor, parallel);
            HessianParallelTask(executor, parallel);
            System.out.printf("[author tangjie] Netty RPC Server 消息协议序列化第[%d]轮并发验证结束!\n\n", i);
        }

        executor.stop();
    }
}

　　运行截图如下：

　　现在，我就收集汇总一下测试数据，分析对比一下，每一种协议对RPC消息序列化/反序列化的性能（注意：由于每台计算机的配置差异，下面的测试结论可能存在出入，本次测试结果仅仅是学习交流之用！）。

　　经过10轮的压力测试，具体的数据如下所示：

 

　　可以很明显的发现，经过上述代码框架优化调整之后，Java原生本地序列化的处理性能，跟之前博客文章中设计实现处理性能上对比，运行效率有较大的提升（RPC消息序列化/反序列耗时更少）。Java本地序列化、Kryo序列化、Hessian序列化在10次的压力测试中，分别有1次耗时大于10S（秒）的操作。经过统计分析之后，结果如下图：

     

　　Kryo序列化、Hessian序列化的性能不分伯仲，并且总体优于Java本地序列化的性能水平。

　　再来看下，10轮压力测试中，Java本地序列化、Kryo序列化、Hessian序列化的耗时波动情况，如下图所示：

    

　　可以很清楚的发现，三种序列化方式分别有个“拐点”，除开这个“拐点”，三种序列化方式耗时相对来说比较平稳。但是总体而言，Kryo、Hessian序列化耗时有适当的波动，震荡相对比较明显；而Java原生序列化耗时相对来说比较平稳，没有出现频繁的震荡，但是耗时较长。

　　写在最后：本文是前一篇文章“谈谈如何使用Netty开发实现高性能的RPC服务器”的性能优化篇，主要从RPC消息序列化机制、对象池（Object Pooling）、多线程优化等角度，对之前设计实现的基于Netty的RPC服务器框架进行优化重构。当然目前的RPC服务器，还仅仅处于“各自为政”的状态，能不能把集群中的若干台RPC服务器，通过某种机制进行统一的分布式协调管理、以及服务调度呢？答案是肯定的，一种可行的方案就是引入Zookeeper，进行服务治理。后续有时间，我会继续加以优化改良，到时再以博客的形式，呈现给大家！由于本人的认知水平、技术能力的限制，本文中涉及的技术观点、测试数据、测试结论等等，仅限于博客园中园友们的学习交流之用。如果本人有说得不对的地方，欢迎各位园友批评指正！

　　洋洋洒洒地写了这么多，感谢您的耐心阅读。相信读完本篇文章，面前的您，对于利用Java开发高性能的服务端应用，又多了一份了解和自信。路漫漫其修远兮，吾将上下而求索。对于软件知识的求学探索之路没有止境，谨以此话和大家共勉之！

 

http://www.cnblogs.com/Leo_wl/p/5679591.html

 

时间： 2024-09-23 04:46:25

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