环境
虚拟机：VMware 10
Linux版本：CentOS-6.5-x86_64
客户端：Xshell4
FTP：Xftp4
jdk1.8
storm-0.9
一、DRPC
DRPC：Distributed remote procedure call，分布式远程过程调用，DRPC是通过一个DRPC服务端(DRPC server)来实现分布式 RPC 功能的。
Strom DRPC设计目的：
为了充分利用Storm的计算能力实现高密度的并行实时计算：Storm接收若干个数据流输入，数据在Topology当中运行完成，然后通过DRPC将结果进行输出。
DRPC Server负责接收RPC请求，并将该请求发送到Storm中运行的 Topology，等待接收 Topology 发送的处理结果，并将该结果返回给发送请求的客户端。（其实，从客户端的角度来说，DPRC 与普通的 RPC 调用并没有什么区别。）
二、strom DRPC处理流程
客户端通过向DRPC服务器发送待执行函数的名称以及该函数的参数来获取处理结果。实现该函数的拓扑使用一个DRPCSpout 从 DRPC 服务器中接收一个函数调用流。DRPC 服务器会为每个函数调用都标记了一个唯一的 id。随后拓扑会执行函数来计算结果，并在拓扑的最后使用一个名为 ReturnResults 的 bolt 连接到 DRPC 服务器，根据函数调用的 id 来将函数调用的结果返回。
三、定义DRPC拓扑
方法1：
通过LinearDRPCTopologyBuilder （该方法已过期，不建议使用）
该方法会自动为我们设定Spout、将结果返回给DRPC Server等，我们只需要将Topology实现
/**
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package com.sxt.storm.drpc; import backtype.storm.Config;
import backtype.storm.LocalCluster;
import backtype.storm.LocalDRPC;
import backtype.storm.StormSubmitter;
import backtype.storm.drpc.LinearDRPCTopologyBuilder;
import backtype.storm.topology.BasicOutputCollector;
import backtype.storm.topology.OutputFieldsDeclarer;
import backtype.storm.topology.base.BaseBasicBolt;
import backtype.storm.tuple.Fields;
import backtype.storm.tuple.Tuple;
import backtype.storm.tuple.Values; /**
* This topology is a basic example of doing distributed RPC on top of Storm. It
* implements a function that appends a "!" to any string you send the DRPC
* function.
* <p/>
* See https://github.com/nathanmarz/storm/wiki/Distributed-RPC for more
* information on doing distributed RPC on top of Storm.
*/
public class BasicDRPCTopology {
public static class ExclaimBolt extends BaseBasicBolt {
@Override
public void execute(Tuple tuple, BasicOutputCollector collector) {
String input = tuple.getString(1);
collector.emit(new Values(tuple.getValue(0), input + "!"));
} @Override
public void declareOutputFields(OutputFieldsDeclarer declarer) {
declarer.declare(new Fields("id", "result"));
} } public static void main(String[] args) throws Exception {
//线性创建拓扑 参数为函数名或drpc服务名
//LinearDRPCTopologyBuilder封装了spout和返回结果的bolt
LinearDRPCTopologyBuilder builder = new LinearDRPCTopologyBuilder("exclamation");
//按照顺序添加业务计算单元
builder.addBolt(new ExclaimBolt(), 3); Config conf = new Config();
if (args == null || args.length == 0) {
LocalDRPC drpc = new LocalDRPC();
LocalCluster cluster = new LocalCluster();
cluster.submitTopology("drpc-demo", conf, builder.createLocalTopology(drpc));
for (String word : new String[] { "hello", "goodbye" }) {
//执行函数或服务
System.err.println("Result for \"" + word + "\": " + drpc.execute("exclamation", word));
}
//关闭集群
cluster.shutdown();
//关闭drpc
drpc.shutdown();
} else {
conf.setNumWorkers(3);
StormSubmitter.submitTopologyWithProgressBar(args[0], conf, builder.createRemoteTopology());
//StormSubmitter.submitTopology(args[0], conf, builder.createTopology());
}
}
}
方法2：
直接通过普通的拓扑构造方法TopologyBuilder来创建DRPC拓扑
需要手动设定好开始的DRPCSpout以及结束的ReturnResults
/**
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package com.sxt.storm.drpc; import backtype.storm.Config;
import backtype.storm.LocalCluster;
import backtype.storm.LocalDRPC;
import backtype.storm.drpc.DRPCSpout;
import backtype.storm.drpc.ReturnResults;
import backtype.storm.topology.BasicOutputCollector;
import backtype.storm.topology.OutputFieldsDeclarer;
import backtype.storm.topology.TopologyBuilder;
import backtype.storm.topology.base.BaseBasicBolt;
import backtype.storm.tuple.Fields;
import backtype.storm.tuple.Tuple;
import backtype.storm.tuple.Values; public class ManualDRPC {
public static class ExclamationBolt extends BaseBasicBolt { @Override
public void declareOutputFields(OutputFieldsDeclarer declarer) {
declarer.declare(new Fields("result", "return-info"));
} @Override
public void execute(Tuple tuple, BasicOutputCollector collector) {
String arg = tuple.getString(0);
Object retInfo = tuple.getValue(1);
collector.emit(new Values(arg + "!!!", retInfo));
} } public static void main(String[] args) {
TopologyBuilder builder = new TopologyBuilder();
LocalDRPC drpc = new LocalDRPC();
//自己定义spout和返回结果bolt-ReturnResults
DRPCSpout spout = new DRPCSpout("exclamation", drpc);
builder.setSpout("drpc", spout);
builder.setBolt("exclaim", new ExclamationBolt(), 3).shuffleGrouping("drpc");
builder.setBolt("return", new ReturnResults(), 3).shuffleGrouping("exclaim"); LocalCluster cluster = new LocalCluster();
Config conf = new Config();
cluster.submitTopology("exclaim", conf, builder.createTopology()); System.err.println(drpc.execute("exclamation", "aaa"));
System.err.println(drpc.execute("exclamation", "bbb")); }
}
四、运行模式
1、本地模式
参考上述方法2.
2、集群模式
(1)修改配置文件conf/storm.yaml
drpc.servers:
- "node1"
(2)启动DRPC Server
bin/storm drpc &
(3)提交jar
./storm jar drpc.jar com.sxt.storm.drpc.BasicDRPCTopology drpc
(4)客户端调用DRPC
package com.sxt.storm.drpc;
import org.apache.thrift7.TException;
import backtype.storm.generated.DRPCExecutionException;
import backtype.storm.utils.DRPCClient; public class MyDRPCclient { public static void main(String[] args) {
//连接DRPC服务端端口3772通信
DRPCClient client = new DRPCClient("node1", 3772);
try {
String result = client.execute("exclamation", "11,22");
System.out.println(result);
} catch (TException e) {
e.printStackTrace();
} catch (DRPCExecutionException e) {
e.printStackTrace();
}
}
}
五、案例
Twitter 中某个URL的受众人数统计(这篇twitter到底有多少人看到过)
分析：
首先看一下这篇文章被哪些人看到
1、这篇文章的发送者；
2、发送者的粉丝；
其次，不同的发送者粉丝有重复的，需要去重
最后，累加在一起count
/**
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package com.sxt.storm.drpc; import java.util.Arrays;
import java.util.HashMap;
import java.util.HashSet;
import java.util.List;
import java.util.Map;
import java.util.Set; import backtype.storm.Config;
import backtype.storm.LocalCluster;
import backtype.storm.LocalDRPC;
import backtype.storm.StormSubmitter;
import backtype.storm.coordination.BatchOutputCollector;
import backtype.storm.drpc.LinearDRPCTopologyBuilder;
import backtype.storm.task.TopologyContext;
import backtype.storm.topology.BasicOutputCollector;
import backtype.storm.topology.OutputFieldsDeclarer;
import backtype.storm.topology.base.BaseBasicBolt;
import backtype.storm.topology.base.BaseBatchBolt;
import backtype.storm.tuple.Fields;
import backtype.storm.tuple.Tuple;
import backtype.storm.tuple.Values; /**
* This is a good example of doing complex Distributed RPC on top of Storm. This
* program creates a topology that can compute the reach for any URL on Twitter
* in realtime by parallelizing the whole computation.
* <p/>
* Reach is the number of unique people exposed to a URL on Twitter. To compute
* reach, you have to get all the people who tweeted the URL, get all the
* followers of all those people, unique that set of followers, and then count
* the unique set. It's an intense computation that can involve thousands of
* database calls and tens of millions of follower records.
* <p/>
* This Storm topology does every piece of that computation in parallel, turning
* what would be a computation that takes minutes on a single machine into one
* that takes just a couple seconds.
* <p/>
* For the purposes of demonstration, this topology replaces the use of actual
* DBs with in-memory hashmaps.
* <p/>
* See https://github.com/nathanmarz/storm/wiki/Distributed-RPC for more
* information on Distributed RPC.
*/
public class ReachTopology {
//发tweeter的信息库
public static Map<String, List<String>> TWEETERS_DB = new HashMap<String, List<String>>() {
{
put("foo.com/blog/1", Arrays.asList("sally", "bob", "tim", "george", "nathan"));
put("engineering.twitter.com/blog/5", Arrays.asList("adam", "david", "sally", "nathan"));
put("tech.backtype.com/blog/123", Arrays.asList("tim", "mike", "john"));
}
};
//粉丝信息库
public static Map<String, List<String>> FOLLOWERS_DB = new HashMap<String, List<String>>() {
{
put("sally", Arrays.asList("bob", "tim", "alice", "adam", "jim", "chris", "jai"));
put("bob", Arrays.asList("sally", "nathan", "jim", "mary", "david", "vivian"));
put("tim", Arrays.asList("alex"));
put("nathan", Arrays.asList("sally", "bob", "adam", "harry", "chris", "vivian", "emily", "jordan"));
put("adam", Arrays.asList("david", "carissa"));
put("mike", Arrays.asList("john", "bob"));
put("john", Arrays.asList("alice", "nathan", "jim", "mike", "bob"));
}
}; //获取发微博人
public static class GetTweeters extends BaseBasicBolt {
@Override
public void execute(Tuple tuple, BasicOutputCollector collector) {
//第一个参数是request-id
Object id = tuple.getValue(0);
//第二个value是客户端请求的参数 url
String url = tuple.getString(1);
//根据请求url 获取发微博的人
List<String> tweeters = TWEETERS_DB.get(url);
if (tweeters != null) {
for (String tweeter : tweeters) {
//向后推送发微博的人-博主
collector.emit(new Values(id, tweeter));
}
}
} @Override
public void declareOutputFields(OutputFieldsDeclarer declarer) {
declarer.declare(new Fields("id", "tweeter"));
}
} //获取粉丝
public static class GetFollowers extends BaseBasicBolt {
@Override
public void execute(Tuple tuple, BasicOutputCollector collector) {
//request-id
Object id = tuple.getValue(0);
//第二个参数是博主
String tweeter = tuple.getString(1);
//根据博主获取对应粉丝
List<String> followers = FOLLOWERS_DB.get(tweeter);
if (followers != null) {
for (String follower : followers) {
//将粉丝信息推送出去
collector.emit(new Values(id, follower));
}
}
} @Override
public void declareOutputFields(OutputFieldsDeclarer declarer) {
declarer.declare(new Fields("id", "follower"));
}
} public static class PartialUniquer extends BaseBatchBolt {
BatchOutputCollector _collector;
Object _id;
Set<String> _followers = new HashSet<String>(); @Override
public void prepare(Map conf, TopologyContext context, BatchOutputCollector collector, Object id) {
_collector = collector;
_id = id;
} @Override
public void execute(Tuple tuple) {
//接收粉丝信息放进Set 达到去重的目的
_followers.add(tuple.getString(1));
} @Override
public void finishBatch() {
//等到这一批数据统计完成之后将这一波统计信息发送出去
_collector.emit(new Values(_id, _followers.size()));
} @Override
public void declareOutputFields(OutputFieldsDeclarer declarer) {
declarer.declare(new Fields("id", "partial-count"));
}
} public static class CountAggregator extends BaseBatchBolt {
BatchOutputCollector _collector;
Object _id;
int _count = 0; @Override
public void prepare(Map conf, TopologyContext context, BatchOutputCollector collector, Object id) {
_collector = collector;
_id = id;
} @Override
public void execute(Tuple tuple) {
//累加
_count += tuple.getInteger(1);
} @Override
public void finishBatch() {
//将统计结果推送出去
_collector.emit(new Values(_id, _count));
} @Override
public void declareOutputFields(OutputFieldsDeclarer declarer) {
declarer.declare(new Fields("id", "reach"));
}
} public static LinearDRPCTopologyBuilder construct() {
LinearDRPCTopologyBuilder builder = new LinearDRPCTopologyBuilder("reach");
builder.addBolt(new GetTweeters(), 4);
builder.addBolt(new GetFollowers(), 12).shuffleGrouping();
builder.addBolt(new PartialUniquer(), 6).fieldsGrouping(new Fields("id", "follower"));
builder.addBolt(new CountAggregator(), 3).fieldsGrouping(new Fields("id"));
return builder;
} public static void main(String[] args) throws Exception {
LinearDRPCTopologyBuilder builder = construct(); Config conf = new Config(); if (args == null || args.length == 0) {
conf.setMaxTaskParallelism(3);
LocalDRPC drpc = new LocalDRPC();
LocalCluster cluster = new LocalCluster();
cluster.submitTopology("reach-drpc", conf, builder.createLocalTopology(drpc)); String[] urlsToTry = new String[] { "foo.com/blog/1", "engineering.twitter.com/blog/5", "notaurl.com" };
for (String url : urlsToTry) {
System.err.println("Reach of " + url + ": " + drpc.execute("reach", url));
} cluster.shutdown();
drpc.shutdown();
} else {
conf.setNumWorkers(6);
StormSubmitter.submitTopologyWithProgressBar(args[0], conf, builder.createRemoteTopology());
}
}
}
备注：在实际应用中，storm异步统计分析用的多一些，实时统计分析用spark多一些。