storm drpc学习

      storm drpc 是什么？咋一听觉得挺高大上的，其实也就是那么一回事。就是storm的topology 提供了很多函数，并且函数名唯一，函数里面封装了一些算法操作。只需要在调用的时候指定函数名和传递参数就可以得到返回值。简单的来说就是这么一回事。下面是客户端调用的例子：

public static void main(String[] args) {
   // TODO Auto-generated method stub
   try {
      DRPCClient client = new DRPCClient(null,"192.168.19.10", 3772);//drpc 服务的地址和端口
      String result = client.execute("drpcTest", "hello world ");//调用drpcTest函数，传递参数为hello world
      
      System.out.println(result);
   }  catch (Exception e) {
      // TODO Auto-generated catch block
      e.printStackTrace();
   } 

  public static void main(String[] args) throws Exception {
    LinearDRPCTopologyBuilder builder = new LinearDRPCTopologyBuilder("drpcTest");
    builder.addBolt(new DrpcTestBolt(), 3);

    Config conf = new Config();

    if (args == null || args.length == 0) {
      LocalDRPC drpc = new LocalDRPC();
      LocalCluster cluster = new LocalCluster();

      cluster.submitTopology("drpc-test", conf, builder.createLocalTopology(drpc));
      
     //客户端调用
      for (String word : new String[]{ "hello", "storm" }) {
        System.err.println("Result for \"" + word + "\": " + drpc.execute("drpcTest", word));
      }

//      cluster.shutdown();
//      drpc.shutdown();
    }
    else {
      conf.setNumWorkers(3);
      StormSubmitter.submitTopology(args[0], conf, builder.createRemoteTopology());
    }
  }

可以看到drpc的本地模式调用传递了LocalDRPC对象，而集群模式不需要传递这个参数，下面分别看看两个函数里面做了什么操作：

public StormTopology createLocalTopology(ILocalDRPC drpc) {
    return this.createTopology(new DRPCSpout(this._function, drpc));
}

public StormTopology createRemoteTopology() {
    return this.createTopology(new DRPCSpout(this._function));
}

可以看到两个函数的区别只是在于是否传递了localDrpc对象。继续查看createTopology()函数：

private StormTopology createTopology(DRPCSpout spout) {
    String SPOUT_ID = "spout";
    String PREPARE_ID = "prepare-request";
    TopologyBuilder builder = new TopologyBuilder();
    builder.setSpout("spout", spout);
    builder.setBolt("prepare-request", new PrepareRequest()).noneGrouping("spout");
    .
    .
    .
  IRichBolt var13 = ((LinearDRPCTopologyBuilder.Component)this._components.get(this._components.size() - 1)).bolt;
    OutputFieldsGetter var14 = new OutputFieldsGetter();
    var13.declareOutputFields(var14);
    Map var15 = var14.getFieldsDeclaration();
    if(var15.size() != 1) {
        throw new RuntimeException("Must declare exactly one stream from last bolt in LinearDRPCTopology");
    } else {
        String var16 = (String)var15.keySet().iterator().next();
        List var18 = ((StreamInfo)var15.get(var16)).get_output_fields();
        if(var18.size() != 2) {
            throw new RuntimeException("Output stream of last component in LinearDRPCTopology must contain exactly two fields. The first should be the request id, and the second should be the result.");
        } else {
            ((BoltDeclarer)builder.setBolt(boltId(i), new JoinResult("prepare-request")).fieldsGrouping(boltId(i - 1), var16, new Fields(new String[]{(String)var18.get(0)}))).fieldsGrouping("prepare-request", "ret", new Fields(new String[]{"request"}));
            ++i;
            builder.setBolt(boltId(i), new ReturnResults()).noneGrouping(boltId(i - 1));
            return builder.createTopology();
        }
    }
}

1）构建spout。

2）使用ReturnResults向DRPC Server返回结果。

3）为Bolt提供函数用于对tuples进行处理。

如果需要自定义DRPC的话，那么也可以参照LinearDRPCTopologyBuilder的写法：

public static void main(String[] args) {
  TopologyBuilder builder = new TopologyBuilder();
  LocalDRPC drpc = new LocalDRPC();

  DRPCSpout spout = new DRPCSpout("drpcTest2", drpc);
  builder.setSpout("drpc", spout);
  builder.setBolt("test", new TestBolt(), 3).shuffleGrouping("drpc");
  builder.setBolt("return", new ReturnResults(), 3).shuffleGrouping("test");

  LocalCluster cluster = new LocalCluster();
  Config conf = new Config();
  cluster.submitTopology("testDrpc2", conf, builder.createTopology());

  System.out.println(drpc.execute("testDrpc2", "hello"));
  System.out.println(drpc.execute("testDrpc2", "storm"));

}

  public static class TestBolt extends BaseBasicBolt {

    public void declareOutputFields(OutputFieldsDeclarer declarer) {
      declarer.declare(new Fields("result", "return-info"));
    }

    public void execute(Tuple tuple, BasicOutputCollector collector) {
      String arg = tuple.getString(0);
      Object retInfo = tuple.getValue(1);
      collector.emit(new Values(arg + "----", retInfo));
    }

  }

hello---
storm---

总结，DRPC的流程如下：

DRPC通过DRPC Server来实现，DRPC Server的工作过程分解为以下四个过程：

1.接收到一个客户端的RPC调用请求.

2.发送请求到Storm上的拓扑.

3.从Storm上接收计算结果.

4.将计算结果返回给客户端.

流程图：

Client向DRPC Server发送被调用执行的DRPC函数名称及参数；

Storm上的topology通过DRPCSpout实现这一函数，从DPRC Server接收到函数调用流；

DRPC Server会为每次函数调用生成唯一的id；

Storm上运行的topology开始计算结果，最后通过一个ReturnResults的Bolt连接到DRPC    Server，发送指定id的计算结果；

DRPC Server通过使用之前为每个函数调用生成的id，将结果关联到对应的发起调用的client，将计算结果返回给client。