Apache Storm在Twitter上的应用

在本章中，我们将讨论Apache Storm的实时应用程序。我们将看到Storm如何在Twitter中使用。

Twitter

Twitter是一种在线社交网络服务，提供发送和接收用户推文的平台。注册用户可以阅读和发布tweet，但未注册的用户只能阅读tweets。 Hashtag用于按关键字在相关关键字之前附加＃来对tweet进行分类。现在让我们来看一个实时场景，找到每个主题使用最多的hashtag。

Spout创建

spout的目的是尽快收到人们提交的tweets。Twitter提供了“Twitter Streaming API”，一个基于Web服务的工具，用于实时检索人们提交的tweets。Twitter Streaming API可以使用任何编程语言访问。

twitter4j是一个开源的非官方Java库，它提供了一个基于Java的模块，可以轻松访问Twitter Streaming API。twitter4j提供了一个基于监听器的框架来访问tweet。要访问Twitter Streaming API，我们需要登录Twitter开发人员帐户，并获取以下OAuth身份验证详细信息。

• Customerkey
• CustomerSecret
• 的accessToken
• AccessTookenSecret

Storm在其入门套件中提供了一个twitter spout，TwitterSampleSpout。我们将使用它来检索tweet。该邮件需要OAuth身份验证详细信息和至少一个关键字。该spout将发出基于关键字的实时tweet。完整的程序代码如下。

编码：TwitterSampleSpout.java

import java.util.Map; import java.util.concurrent.LinkedBlockingQueue; import twitter4j.FilterQuery; import twitter4j.StallWarning; import twitter4j.Status; import twitter4j.StatusDeletionNotice; import twitter4j.StatusListener; import twitter4j.TwitterStream; import twitter4j.TwitterStreamFactory; import twitter4j.auth.AccessToken; import twitter4j.conf.ConfigurationBuilder; import backtype.storm.Config; import backtype.storm.spout.SpoutOutputCollector; import backtype.storm.task.TopologyContext; import backtype.storm.topology.OutputFieldsDeclarer; import backtype.storm.topology.base.BaseRichSpout; import backtype.storm.tuple.Fields; import backtype.storm.tuple.Values; import backtype.storm.utils.Utils; @SuppressWarnings("serial") public class TwitterSampleSpout extends BaseRichSpout { SpoutOutputCollector _collector; LinkedBlockingQueue queue = null; TwitterStream _twitterStream; String consumerKey; String consumerSecret; String accessToken; String accessTokenSecret; String[] keyWords; public TwitterSampleSpout(String consumerKey, String consumerSecret, String accessToken, String accessTokenSecret, String[] keyWords) { this.consumerKey = consumerKey; this.consumerSecret = consumerSecret; this.accessToken = accessToken; this.accessTokenSecret = accessTokenSecret; this.keyWords = keyWords; } public TwitterSampleSpout() { // TODO Auto-generated constructor stub } @Override public void open(Map conf, TopologyContext context, SpoutOutputCollector collector) { queue = new LinkedBlockingQueue(1000); _collector = collector; StatusListener listener = new StatusListener() { @Override public void onStatus(Status status) { queue.offer(status); } @Override public void onDeletionNotice(StatusDeletionNotice sdn) {} @Override public void onTrackLimitationNotice(int i) {} @Override public void onScrubGeo(long l, long l1) {} @Override public void onException(Exception ex) {} @Override public void onStallWarning(StallWarning arg0) { // TODO Auto-generated method stub } }; ConfigurationBuilder cb = new ConfigurationBuilder(); cb.setDebugEnabled(true) .setOAuthConsumerKey(consumerKey) .setOAuthConsumerSecret(consumerSecret) .setOAuthAccessToken(accessToken) .setOAuthAccessTokenSecret(accessTokenSecret); _twitterStream = new TwitterStreamFactory(cb.build()).getInstance(); _twitterStream.addListener(listener); if (keyWords.length == 0) { _twitterStream.sample(); }else { FilterQuery query = new FilterQuery().track(keyWords); _twitterStream.filter(query); } } @Override public void nextTuple() { Status ret = queue.poll(); if (ret == null) { Utils.sleep(50); } else { _collector.emit(new Values(ret)); } } @Override public void close() { _twitterStream.shutdown(); } @Override public Map getComponentConfiguration() { Config ret = new Config(); ret.setMaxTaskParallelism(1); return ret; } @Override public void ack(Object id) {} @Override public void fail(Object id) {} @Override public void declareOutputFields(OutputFieldsDeclarer declarer) { declarer.declare(new Fields("tweet")); } }

Hashtag阅读器spout

由spout发出的tweet将被转发到HashtagReaderBolt，它将处理该tweet并发出所有可用的hashtag。HashtagReaderBolt使用twitter4j提供的getHashTagEntities方法。getHashTagEntities读取tweet并返回hashtag的列表。完整的程序代码如下 -

编码：HashtagReaderBolt.java

import java.util.HashMap; import java.util.Map; import twitter4j.*; import twitter4j.conf.*; import backtype.storm.tuple.Fields; import backtype.storm.tuple.Values; import backtype.storm.task.OutputCollector; import backtype.storm.task.TopologyContext; import backtype.storm.topology.IRichBolt; import backtype.storm.topology.OutputFieldsDeclarer; import backtype.storm.tuple.Tuple; public class HashtagReaderBolt implements IRichBolt { private OutputCollector collector; @Override public void prepare(Map conf, TopologyContext context, OutputCollector collector) { this.collector = collector; } @Override public void execute(Tuple tuple) { Status tweet = (Status) tuple.getValueByField("tweet"); for(HashtagEntity hashtage : tweet.getHashtagEntities()) { System.out.println("Hashtag: " + hashtage.getText()); this.collector.emit(new Values(hashtage.getText())); } } @Override public void cleanup() {} @Override public void declareOutputFields(OutputFieldsDeclarer declarer) { declarer.declare(new Fields("hashtag")); } @Override public Map getComponentConfiguration() { return null; } }

Hashtag计数器spout

发出的hashtag将被转发到HashtagCounterBolt。这个bolt将处理所有的hashtags，并使用Java Map对象将每个hashtags及其计数保存在内存中。完整的程序代码如下。

编码：HashtagCounterBolt.java

import java.util.HashMap; import java.util.Map; import backtype.storm.tuple.Fields; import backtype.storm.tuple.Values; import backtype.storm.task.OutputCollector; import backtype.storm.task.TopologyContext; import backtype.storm.topology.IRichBolt; import backtype.storm.topology.OutputFieldsDeclarer; import backtype.storm.tuple.Tuple; public class HashtagCounterBolt implements IRichBolt { Map counterMap; private OutputCollector collector; @Override public void prepare(Map conf, TopologyContext context, OutputCollector collector) { this.counterMap = new HashMap(); this.collector = collector; } @Override public void execute(Tuple tuple) { String key = tuple.getString(0); if(!counterMap.containsKey(key)){ counterMap.put(key, 1); }else{ Integer c = counterMap.get(key) + 1; counterMap.put(key, c); } collector.ack(tuple); } @Override public void cleanup() { for(Map.Entry entry:counterMap.entrySet()){ System.out.println("Result: " + entry.getKey()+" : " + entry.getValue()); } } @Override public void declareOutputFields(OutputFieldsDeclarer declarer) { declarer.declare(new Fields("hashtag")); } @Override public Map getComponentConfiguration() { return null; } }

提交拓扑

提交拓扑是主要应用程序。Twitter拓扑由TwitterSampleSpout，HashtagReaderBolt和HashtagCounterBolt组成。以下程序代码显示如何提交拓扑。

编码：TwitterHashtagStorm.java

import java.util.*; import backtype.storm.tuple.Fields; import backtype.storm.tuple.Values; import backtype.storm.Config; import backtype.storm.LocalCluster; import backtype.storm.topology.TopologyBuilder; public class TwitterHashtagStorm { public static void main(String[] args) throws Exception{ String consumerKey = args[0]; String consumerSecret = args[1]; String accessToken = args[2]; String accessTokenSecret = args[3]; String[] arguments = args.clone(); String[] keyWords = Arrays.copyOfRange(arguments, 4, arguments.length); Config config = new Config(); config.setDebug(true); TopologyBuilder builder = new TopologyBuilder(); builder.setSpout("twitter-spout", new TwitterSampleSpout(consumerKey, consumerSecret, accessToken, accessTokenSecret, keyWords)); builder.setBolt("twitter-hashtag-reader-bolt", new HashtagReaderBolt()) .shuffleGrouping("twitter-spout"); builder.setBolt("twitter-hashtag-counter-bolt", new HashtagCounterBolt()) .fieldsGrouping("twitter-hashtag-reader-bolt", new Fields("hashtag")); LocalCluster cluster = new LocalCluster(); cluster.submitTopology("TwitterHashtagStorm", config, builder.createTopology()); Thread.sleep(10000); cluster.shutdown(); } }

构建和运行应用程序

完整的应用程序有四个Java代码。他们如下 -

• TwitterSampleSpout.java
• HashtagReaderBolt.java
• HashtagCounterBolt.java
• TwitterHashtagStorm.java

您可以使用以下命令编译应用程序 -

javac -cp “/path/to/storm/apache-storm-0.9.5/lib/*”:”/path/to/twitter4j/lib/*” *.java

使用以下命令执行应用程序 -

javac -cp “/path/to/storm/apache-storm-0.9.5/lib/*”:”/path/to/twitter4j/lib/*”:. TwitterHashtagStorm       … 

输出

应用程序将打印当前可用的主题标签及其计数。输出应类似于以下内容 -

Result: jazztastic : 1 Result: foodie : 1 Result: Redskins : 1 Result: Recipe : 1 Result: cook : 1 Result: android : 1 Result: food : 2 Result: NoToxicHorseMeat : 1 Result: Purrs4Peace : 1 Result: livemusic : 1 Result: VIPremium : 1 Result: Frome : 1 Result: SundayRoast : 1 Result: Millennials : 1 Result: HealthWithKier : 1 Result: LPs30DaysofGratitude : 1 Result: cooking : 1 Result: gameinsight : 1 Result: Countryfile : 1 Result: androidgames : 1