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  • 大数据处理框架之Strom:DRPC

    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。

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  • 原文地址:https://www.cnblogs.com/cac2020/p/10790778.html
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