问题导读:
1.如何实现实时随机输出一字符串
2.tuple是由哪类个来发出的?
3.哪个类处理输入tuple?
本节探讨一下storm具体怎么使用,明白怎么在windows下开发storm程序。
功能描述:实时随机输出一字符串。
在开发前记得导入storm需要的jar包。
1、SimpleSpout类继承BaseRichSpout类,用来产生数据并且向topology里面发出消息:tuple。
- package com.ljq.helloword;
-
- import java.util.Map;
- import java.util.Random;
-
- 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;
-
- /**
- * Spout起到和外界沟通的作用,他可以从一个数据库中按照某种规则取数据,也可以从分布式队列中取任务
- *
- * @author Administrator
- *
- */
- @SuppressWarnings("serial")
- public class SimpleSpout extends BaseRichSpout{
- //用来发射数据的工具类
- private SpoutOutputCollector collector;
- private static String[] info = new String[]{
- "comaple\t,12424,44w46,654,12424,44w46,654,",
- "lisi\t,435435,6537,12424,44w46,654,",
- "lipeng\t,45735,6757,12424,44w46,654,",
- "hujintao\t,45735,6757,12424,44w46,654,",
- "jiangmin\t,23545,6457,2455,7576,qr44453",
- "beijing\t,435435,6537,12424,44w46,654,",
- "xiaoming\t,46654,8579,w3675,85877,077998,",
- "xiaozhang\t,9789,788,97978,656,345235,09889,",
- "ceo\t,46654,8579,w3675,85877,077998,",
- "cto\t,46654,8579,w3675,85877,077998,",
- "zhansan\t,46654,8579,w3675,85877,077998,"};
-
- Random random=new Random();
-
- /**
- * 初始化collector
- */
- public void open(Map conf, TopologyContext context, SpoutOutputCollector collector) {
- this.collector = collector;
- }
-
- /**
- * 在SpoutTracker类中被调用,每调用一次就可以向storm集群中发射一条数据(一个tuple元组),该方法会被不停的调用
- */
- @Override
- public void nextTuple() {
- try {
- String msg = info[random.nextInt(11)];
- // 调用发射方法
- collector.emit(new Values(msg));
- // 模拟等待100ms
- Thread.sleep(100);
- } catch (InterruptedException e) {
- e.printStackTrace();
- }
- }
-
- /**
- * 定义字段id,该id在简单模式下没有用处,但在按照字段分组的模式下有很大的用处。
- * 该declarer变量有很大作用,我们还可以调用declarer.declareStream();来定义stramId,该id可以用来定义更加复杂的流拓扑结构
- */
- @Override
- public void declareOutputFields(OutputFieldsDeclarer declarer) {
- declarer.declare(new Fields("source")); //collector.emit(new Values(msg));参数要对应
- }
-
- }
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2、SimpleBolt类继承BaseBasicBolt类,处理一个输入tuple。
- package com.ljq.helloword;
-
- 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;
-
- /**
- * 接收喷发节点(Spout)发送的数据进行简单的处理后,发射出去。
- *
- * @author Administrator
- *
- */
- @SuppressWarnings("serial")
- public class SimpleBolt extends BaseBasicBolt {
-
- public void execute(Tuple input, BasicOutputCollector collector) {
- try {
- String msg = input.getString(0);
- if (msg != null){
- //System.out.println("msg="+msg);
- collector.emit(new Values(msg + "msg is processed!"));
- }
-
- } catch (Exception e) {
- e.printStackTrace();
- }
- }
-
- public void declareOutputFields(OutputFieldsDeclarer declarer) {
- declarer.declare(new Fields("info"));
- }
-
- }
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3、SimpleTopology类包含一个main函数,是Storm程序执行的入口点,包括一个数据喷发节点spout和一个数据处理节点bolt。
- package com.ljq.helloword;
-
- import backtype.storm.Config;
- import backtype.storm.LocalCluster;
- import backtype.storm.StormSubmitter;
- import backtype.storm.topology.TopologyBuilder;
-
- /**
- * 定义了一个简单的topology,包括一个数据喷发节点spout和一个数据处理节点bolt。
- *
- * @author Administrator
- *
- */
- public class SimpleTopology {
- public static void main(String[] args) {
- try {
- // 实例化TopologyBuilder类。
- TopologyBuilder topologyBuilder = new TopologyBuilder();
- // 设置喷发节点并分配并发数,该并发数将会控制该对象在集群中的线程数。
- topologyBuilder.setSpout("SimpleSpout", new SimpleSpout(), 1);
- // 设置数据处理节点并分配并发数。指定该节点接收喷发节点的策略为随机方式。
- topologyBuilder.setBolt("SimpleBolt", new SimpleBolt(), 3).shuffleGrouping("SimpleSpout");
- Config config = new Config();
- config.setDebug(true);
- if (args != null && args.length > 0) {
- config.setNumWorkers(1);
- StormSubmitter.submitTopology(args[0], config, topologyBuilder.createTopology());
- } else {
- // 这里是本地模式下运行的启动代码。
- config.setMaxTaskParallelism(1);
- LocalCluster cluster = new LocalCluster();
- cluster.submitTopology("simple", config, topologyBuilder.createTopology());
- }
-
- } catch (Exception e) {
- e.printStackTrace();
- }
- }
- }
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运行结果效果如下:
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