DangerWind-RPC-framework---七、序列化算法

        客户端与服务端的在交互过程中需要互相发送交换数据，这就需要对传输对象进行序列化与反序列化操作，此过程涉及到序列化算法的使用。本RPC框架支持多种序列化算法，通过SPI机制进行扩展。

       比如客户端在向服务端发送数据时，首先是客户端的序列化操作：

   Serializer serializer = ExtensionLoader.getExtensionLoader(Serializer.class).getExtension(codecName);bodyBytes = serializer.serialize(rpcMessage.getData());

       服务端接收到数据后要进行反序列化操作：

   Serializer serializer = ExtensionLoader.getExtensionLoader(Serializer.class).getExtension(codecName);if (messageType == RpcConstants.REQUEST_TYPE) {RpcRequest tmpValue = serializer.deserialize(bs, RpcRequest.class);rpcMessage.setData(tmpValue);} else {RpcResponse tmpValue = serializer.deserialize(bs, RpcResponse.class);rpcMessage.setData(tmpValue);}

       本次主要支持三种序列化算法，分别是Kryo、Hessian、ProtoStuff，首先是Kryo序列化算法：

    private final ThreadLocal<Kryo> kryoThreadLocal = ThreadLocal.withInitial(() -> {Kryo kryo = new Kryo();// 注册类是一种优化手段，可以提高序列化和反序列化的效率kryo.register(RpcResponse.class);kryo.register(RpcRequest.class);return kryo;});@Overridepublic byte[] serialize(Object obj) {try (ByteArrayOutputStream byteArrayOutputStream = new ByteArrayOutputStream();Output output = new Output(byteArrayOutputStream)) {Kryo kryo = kryoThreadLocal.get();// Object->byte:将对象序列化为byte数组kryo.writeObject(output, obj);kryoThreadLocal.remove();return output.toBytes();} catch (Exception e) {throw new SerializeException("Serialization failed");}}@Overridepublic <T> T deserialize(byte[] bytes, Class<T> clazz) {try (ByteArrayInputStream byteArrayInputStream = new ByteArrayInputStream(bytes);Input input = new Input(byteArrayInputStream)) {Kryo kryo = kryoThreadLocal.get();// byte->Object:从byte数组中反序列化出对对象Object o = kryo.readObject(input, clazz);kryoThreadLocal.remove();return clazz.cast(o);} catch (Exception e) {throw new SerializeException("Deserialization failed");}}

       Kryo序列化算法性能较好，但是是线程不安全的，因此需要进行线程隔离，通过ThreadLocal为每个线程维护一个Kryo对象，使用完毕后就remove掉，之后需要使用时再次在threadLocal中初始化一个Kryo对象，这也是withInitial懒加载的过程。

      接下来是Hessian序列化算法：

    @Overridepublic byte[] serialize(Object obj) {try (ByteArrayOutputStream byteArrayOutputStream = new ByteArrayOutputStream()) {HessianOutput hessianOutput = new HessianOutput(byteArrayOutputStream);hessianOutput.writeObject(obj);return byteArrayOutputStream.toByteArray();} catch (Exception e) {throw new SerializeException("Serialization failed");}}@Overridepublic <T> T deserialize(byte[] bytes, Class<T> clazz) {try (ByteArrayInputStream byteArrayInputStream = new ByteArrayInputStream(bytes)) {HessianInput hessianInput = new HessianInput(byteArrayInputStream);Object o = hessianInput.readObject();return clazz.cast(o);} catch (Exception e) {throw new SerializeException("Deserialization failed");}}

       最后是ProtoStuff序列化算法：

    private static final LinkedBuffer BUFFER = LinkedBuffer.allocate(LinkedBuffer.DEFAULT_BUFFER_SIZE);@Overridepublic byte[] serialize(Object obj) {Class<?> clazz = obj.getClass();Schema schema = RuntimeSchema.getSchema(clazz);byte[] bytes;try {bytes = ProtostuffIOUtil.toByteArray(obj, schema, BUFFER);} finally {BUFFER.clear();}return bytes;}@Overridepublic <T> T deserialize(byte[] bytes, Class<T> clazz) {Schema<T> schema = RuntimeSchema.getSchema(clazz);T obj = schema.newMessage();ProtostuffIOUtil.mergeFrom(bytes, obj, schema);return obj;}

        BUFFER可以避免每次序列化时重新申请缓冲区空间，提高序列化的效率。三种序列化算法的实现过程中，主要是需要对线程不安全的隐患进行处理，比如进行隔离等操作，以保证序列化操作的正确执行。