1.概述
之前在《Hadoop2源码分析－RPC探索实战》一文当中介绍了Hadoop的RPC机制，今天给大家分享关于YARN的RPC的机制。下面是今天的分享目录：
- YARN的RPC介绍
- YARN的RPC示例
- 截图预览
下面开始今天的内容分享。
2.YARN的RPC介绍
我们知道在Hadoop的RPC当中，其主要由RPC，Client及Server这三个大类组成，分别实现对外提供编程接口、客户端实现及服务端实现。如下图所示：
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图中是Hadoop的RPC的一个类的关系图，大家可以到《Hadoop2源码分析－RPC探索实战》一文中，通过代码示例去理解他们之间的关系，这里就不多做赘述了。接下来，我们去看Yarn的RPC。
Yarn对外提供的是YarnRPC这个类，这是一个抽象类，通过阅读YarnRPC的源码可以知道，实际的实现由参数yarn.ipc.rpc.class设定，默认情况下，其值为：org.apache.hadoop.yarn.ipc.HadoopYarnProtoRPC，部分代码如下：
public abstract class YarnRPC {
// ......
public static YarnRPC create(Configuration conf) {
LOG.debug("Creating YarnRPC for " +
conf.get(YarnConfiguration.IPC_RPC_IMPL));
String clazzName = conf.get(YarnConfiguration.IPC_RPC_IMPL);
if (clazzName == null) {
clazzName = YarnConfiguration.DEFAULT_IPC_RPC_IMPL;
}
try {
return (YarnRPC) Class.forName(clazzName).newInstance();
} catch (Exception e) {
throw new YarnRuntimeException(e);
}
}
}
public class YarnConfiguration extends Configuration {
//Configurations
public static final String YARN_PREFIX = "yarn.";
////////////////////////////////
// IPC Configs
////////////////////////////////
public static final String IPC_PREFIX = YARN_PREFIX + "ipc.";
/** RPC class implementation*/
public static final String IPC_RPC_IMPL =
IPC_PREFIX + "rpc.class";
public static final String DEFAULT_IPC_RPC_IMPL =
"org.apache.hadoop.yarn.ipc.HadoopYarnProtoRPC";
}
而HadoopYarnProtoRPC 通过 RPC 的 RpcFactoryProvider 生成客户端工厂(由参数 yarn.ipc.client.factory.class 指定，默认值是 org.apache.hadoop.yarn.factories.impl.pb.RpcClientFactoryPBImpl)和服务器工厂 (由参数 yarn.ipc.server.factory.class 指定，默认值是 org.apache.hadoop.yarn.factories.impl.pb.RpcServerFactoryPBImpl)，以根据通信协议的 Protocol Buffers 定义生成客户端对象和服务器对象。相关类的部分代码如下：
public class HadoopYarnProtoRPC extends YarnRPC {
private static final Log LOG = LogFactory.getLog(HadoopYarnProtoRPC.class);
@Override
public Object getProxy(Class protocol, InetSocketAddress addr,
Configuration conf) {
LOG.debug("Creating a HadoopYarnProtoRpc proxy for protocol " + protocol);
return RpcFactoryProvider.getClientFactory(conf).getClient(protocol, 1,
addr, conf);
}
@Override
public void stopProxy(Object proxy, Configuration conf) {
RpcFactoryProvider.getClientFactory(conf).stopClient(proxy);
}
@Override
public Server getServer(Class protocol, Object instance,
InetSocketAddress addr, Configuration conf,
SecretManager<? extends TokenIdentifier> secretManager,
int numHandlers, String portRangeConfig) {
LOG.debug("Creating a HadoopYarnProtoRpc server for protocol " + protocol +
" with " + numHandlers + " handlers");
return RpcFactoryProvider.getServerFactory(conf).getServer(protocol,
instance, addr, conf, secretManager, numHandlers, portRangeConfig);
}
}
public class RpcFactoryProvider {
// ......
public static RpcClientFactory getClientFactory(Configuration conf) {
String clientFactoryClassName = conf.get(
YarnConfiguration.IPC_CLIENT_FACTORY_CLASS,
YarnConfiguration.DEFAULT_IPC_CLIENT_FACTORY_CLASS);
return (RpcClientFactory) getFactoryClassInstance(clientFactoryClassName);
}
//......
}
/** Factory to create client IPC classes.*/
public static final String IPC_CLIENT_FACTORY_CLASS =
IPC_PREFIX + "client.factory.class";
public static final String DEFAULT_IPC_CLIENT_FACTORY_CLASS =
"org.apache.hadoop.yarn.factories.impl.pb.RpcClientFactoryPBImpl";
在 YARN 中并未使用Hadoop自带的Writable来做序列化，而是使用 Protocol Buffers 作为默认的序列化机制，这带来的好处主要有以下几点：
- 继承Protocol Buffers的优点：Protocol Buffers已被实践证明其拥有高效性、可扩展性、紧凑性以及跨语言性等特点。
- 支持在线升级回滚：在Hadoop 2.x版本后，添加的HA方案，该方案能够进行主备切换，在不停止NNA节点服务的前提下，能够在线升级版本。
3.YARN的RPC示例
YARN 的工作流程是先定义通信协议接口ResourceTracker，它包含2个函数，具体代码如下所示：
public interface ResourceTracker {
@Idempotent
public RegisterNodeManagerResponse registerNodeManager(
RegisterNodeManagerRequest request) throws YarnException,
IOException;
@AtMostOnce
public NodeHeartbeatResponse nodeHeartbeat(NodeHeartbeatRequest request)
throws YarnException, IOException;
}
这里ResourceTracker提供了Protocol Buffers定义和Java实现，其中设计的Protocol Buffers文件有：ResourceTracker.proto、yarn_server_common_service_protos.proto和yarn_server_common_protos.proto，文件路径在Hadoop的源码包的 hadoop-2.6.0-src/hadoop-yarn-project/hadoop-yarn/hadoop-yarn-server/hadoop-yarn-server-common/src/main/proto，这里就不贴出3个文件的具体代码类，大家可以到该目录去阅读这部分代码。这里需要注意的是，若是大家要编译这些文件需要安装 ProtoBuf 的编译环境，环境安装较为简单，这里给大家简要说明下。
首先是下载ProtoBuf的安装包，然后解压，进入到解压目录，编译安装。命令如下：
./configure --prefix=/home/work /protobuf/
make && make install
最后编译 .proto 文件的命令：
protoc ./ResourceTracker.proto --java_out=./
下面，我们去收取Hadoop源码到本地工程，运行调试相关代码。
public class TestYarnServerApiClasses {
// ......
// 列举测试4个方法
@Test
public void testRegisterNodeManagerResponsePBImpl() {
RegisterNodeManagerResponsePBImpl original =
new RegisterNodeManagerResponsePBImpl();
original.setContainerTokenMasterKey(getMasterKey());
original.setNMTokenMasterKey(getMasterKey());
original.setNodeAction(NodeAction.NORMAL);
original.setDiagnosticsMessage("testDiagnosticMessage");
RegisterNodeManagerResponsePBImpl copy =
new RegisterNodeManagerResponsePBImpl(
original.getProto());
assertEquals(1, copy.getContainerTokenMasterKey().getKeyId());
assertEquals(1, copy.getNMTokenMasterKey().getKeyId());
assertEquals(NodeAction.NORMAL, copy.getNodeAction());
assertEquals("testDiagnosticMessage", copy.getDiagnosticsMessage());
}
@Test
public void testNodeHeartbeatRequestPBImpl() {
NodeHeartbeatRequestPBImpl original = new NodeHeartbeatRequestPBImpl();
original.setLastKnownContainerTokenMasterKey(getMasterKey());
original.setLastKnownNMTokenMasterKey(getMasterKey());
original.setNodeStatus(getNodeStatus());
NodeHeartbeatRequestPBImpl copy = new NodeHeartbeatRequestPBImpl(
original.getProto());
assertEquals(1, copy.getLastKnownContainerTokenMasterKey().getKeyId());
assertEquals(1, copy.getLastKnownNMTokenMasterKey().getKeyId());
assertEquals("localhost", copy.getNodeStatus().getNodeId().getHost());
}
@Test
public void testNodeHeartbeatResponsePBImpl() {
NodeHeartbeatResponsePBImpl original = new NodeHeartbeatResponsePBImpl();
original.setDiagnosticsMessage("testDiagnosticMessage");
original.setContainerTokenMasterKey(getMasterKey());
original.setNMTokenMasterKey(getMasterKey());
original.setNextHeartBeatInterval(1000);
original.setNodeAction(NodeAction.NORMAL);
original.setResponseId(100);
NodeHeartbeatResponsePBImpl copy = new NodeHeartbeatResponsePBImpl(
original.getProto());
assertEquals(100, copy.getResponseId());
assertEquals(NodeAction.NORMAL, copy.getNodeAction());
assertEquals(1000, copy.getNextHeartBeatInterval());
assertEquals(1, copy.getContainerTokenMasterKey().getKeyId());
assertEquals(1, copy.getNMTokenMasterKey().getKeyId());
assertEquals("testDiagnosticMessage", copy.getDiagnosticsMessage());
}
@Test
public void testRegisterNodeManagerRequestPBImpl() {
RegisterNodeManagerRequestPBImpl original = new RegisterNodeManagerRequestPBImpl();
original.setHttpPort(8080);
original.setNodeId(getNodeId());
Resource resource = recordFactory.newRecordInstance(Resource.class);
resource.setMemory(10000);
resource.setVirtualCores(2);
original.setResource(resource);
RegisterNodeManagerRequestPBImpl copy = new RegisterNodeManagerRequestPBImpl(
original.getProto());
assertEquals(8080, copy.getHttpPort());
assertEquals(9090, copy.getNodeId().getPort());
assertEquals(10000, copy.getResource().getMemory());
assertEquals(2, copy.getResource().getVirtualCores());
}
}
public class TestResourceTrackerPBClientImpl {
private static ResourceTracker client;
private static Server server;
private final static org.apache.hadoop.yarn.factories.RecordFactory recordFactory = RecordFactoryProvider
.getRecordFactory(null);
@BeforeClass
public static void start() {
System.out.println("Start client test");
InetSocketAddress address = new InetSocketAddress(0);
Configuration configuration = new Configuration();
ResourceTracker instance = new ResourceTrackerTestImpl();
server = RpcServerFactoryPBImpl.get().getServer(ResourceTracker.class, instance, address, configuration, null,
1);
server.start();
client = (ResourceTracker) RpcClientFactoryPBImpl.get().getClient(ResourceTracker.class, 1,
NetUtils.getConnectAddress(server), configuration);
}
@AfterClass
public static void stop() {
System.out.println("Stop client");
if (server != null) {
server.stop();
}
}
/**
* Test the method registerNodeManager. Method should return a not null
* result.
*
*/
@Test
public void testResourceTrackerPBClientImpl() throws Exception {
RegisterNodeManagerRequest request = recordFactory.newRecordInstance(RegisterNodeManagerRequest.class);
assertNotNull(client.registerNodeManager(request));
ResourceTrackerTestImpl.exception = true;
try {
client.registerNodeManager(request);
fail("there should be YarnException");
} catch (YarnException e) {
assertTrue(e.getMessage().startsWith("testMessage"));
} finally {
ResourceTrackerTestImpl.exception = false;
}
}
/**
* Test the method nodeHeartbeat. Method should return a not null result.
*
*/
@Test
public void testNodeHeartbeat() throws Exception {
NodeHeartbeatRequest request = recordFactory.newRecordInstance(NodeHeartbeatRequest.class);
assertNotNull(client.nodeHeartbeat(request));
ResourceTrackerTestImpl.exception = true;
try {
client.nodeHeartbeat(request);
fail("there should be YarnException");
} catch (YarnException e) {
assertTrue(e.getMessage().startsWith("testMessage"));
} finally {
ResourceTrackerTestImpl.exception = false;
}
}
public static class ResourceTrackerTestImpl implements ResourceTracker {
public static boolean exception = false;
public RegisterNodeManagerResponse registerNodeManager(RegisterNodeManagerRequest request)
throws YarnException, IOException {
if (exception) {
throw new YarnException("testMessage");
}
return recordFactory.newRecordInstance(RegisterNodeManagerResponse.class);
}
public NodeHeartbeatResponse nodeHeartbeat(NodeHeartbeatRequest request) throws YarnException, IOException {
if (exception) {
throw new YarnException("testMessage");
}
return recordFactory.newRecordInstance(NodeHeartbeatResponse.class);
}
}
}
4.截图预览
接下来，我们使用JUnit去测试代码，截图预览如下所示：
- 对testRegisterNodeManagerRequestPBImpl()方法的一个DEBUG调试
![]()
![]()
这里由于设置exception的状态为true，在调用registerNodeManager()时，会打印一条测试异常信息。
if (exception) {
throw new YarnException("testMessage");
}
5.总结
在学习Hadoop YARN的RPC时，可以先了解Hadoop的RPC机制，这样在接触YARN的RPC的会比较好理解，YARN的RPC只是其中的一部分，后续会给大家分享更多关于YARN的内容。
6.结束语
这篇博客就和大家分享到这里，如果大家在研究学习的过程当中有什么问题，可以加群进行讨论或发送邮件给我，我会尽我所能为您解答，与君共勉！
作者：哥不是小萝莉 ［关于我］［犒赏］
转载请注明出处，谢谢合作！
