storm两个案例(1单词计数本地执行 2累加集群执行 3集群关闭storm任务写法)-优快云博客

本文链接：https://blog.youkuaiyun.com/iteye_3893/article/details/82611851

1 如何监听到文件夹内新增了文件

2 如何监听到原文件内容数据做了变更

3 为了有两个bolt 一个用于切分一个用于统计单词个数为何不写在一起呢？？

每一个组件完成单独功能执行速度非常快并且提高每个组件的并行度已达到单位时间内处理数据更大

4 参考flume ng 对处理过的文件做修改，这里是将处理过的文件后缀更改达到目的

操作图如下：

2 单词计数代码：

package changping.houzhihoujue.storm;

import java.io.File;
import java.io.IOException;
import java.util.Collection;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Map.Entry;

import org.apache.commons.io.FileUtils;

import backtype.storm.Config;
import backtype.storm.LocalCluster;
import backtype.storm.spout.SpoutOutputCollector;
import backtype.storm.task.OutputCollector;
import backtype.storm.task.TopologyContext;
import backtype.storm.topology.OutputFieldsDeclarer;
import backtype.storm.topology.TopologyBuilder;
import backtype.storm.topology.base.BaseRichBolt;
import backtype.storm.topology.base.BaseRichSpout;
import backtype.storm.tuple.Fields;
import backtype.storm.tuple.Tuple;
import backtype.storm.tuple.Values;
import backtype.storm.utils.Utils;

/**
 * 作业：实现单词计数。
 *     (1)要求从一个文件夹中把所有文件都读取，计算所有文件中的单词出现次数。
 *     (2)当文件夹中的文件数量增加是，实时计算所有文件中的单词出现次数。
 */
public class MyWordCountTopology {

	 // 祖品火车 创建轨道 发车流程
	 public static void main( String[] args ) {
		 	String DATASOURCE_SPOUT = DataSourceSpout.class.getSimpleName();
	    	String SPLIT_BOLD = SplitBolt.class.getSimpleName();
	    	String COUNT_BOLT = CountBolt.class.getSimpleName();
	    	
	        final TopologyBuilder builder = new TopologyBuilder();
	        builder.setSpout(DATASOURCE_SPOUT, new DataSourceSpout());
	        builder.setBolt(SPLIT_BOLD, new SplitBolt()).shuffleGrouping(DATASOURCE_SPOUT);
	        builder.setBolt(COUNT_BOLT, new CountBolt()).shuffleGrouping(SPLIT_BOLD);
	        
	        final LocalCluster localCluster = new LocalCluster();
	        final Config config = new Config();
			localCluster.submitTopology(MyWordCountTopology.class.getSimpleName(), config, builder.createTopology());
			Utils.sleep(9999999);
			localCluster.shutdown();
	 }
	
}
// 数据源
class DataSourceSpout extends BaseRichSpout{

	private Map conf;
	private TopologyContext context;
	private SpoutOutputCollector collector;
	
	public void open(Map conf, TopologyContext context,SpoutOutputCollector collector) {
		this.conf = conf;
		this.context = context;
		this.collector = collector;
	}

	public void nextTuple() {
		// 过滤文件夹D:/father 得到以txt结尾的文件
		Collection<File> files = FileUtils.listFiles(new File("D:/father"), new String[]{"txt"}, true);
		if(files != null && files.size() > 0){
			for(File file : files){
				try {// 将文件每一行都发射到 bolt内
					List<String> lines = FileUtils.readLines(file);
					for(String line : lines){
						collector.emit(new Values(line));
					}
					//修改操作完的文件（这里是修改后缀） 这样nextTuple方法就不会再重新处理该文件
					FileUtils.moveFile(file, new File(file.getAbsolutePath() + "." + System.currentTimeMillis()));
				} catch (IOException e) {
					e.printStackTrace();
				}
			}
			
		}
	}

	public void declareOutputFields(OutputFieldsDeclarer declarer) {
		declarer.declare(new Fields("line"));
	}
	
}
// 切分单词逻辑
class SplitBolt extends BaseRichBolt{

	private Map conf;
	private TopologyContext context;
	private OutputCollector collector;
	
	public void prepare(Map stormConf, TopologyContext context, OutputCollector collector) {
		this.conf = stormConf;
		this.context = context;
		this.collector = collector;
	}

	public void execute(Tuple input) {
		String line = input.getStringByField("line");
		String[] words = line.split("\\s");
		for(String word : words){ // 发送每一个单词
			System.err.println(word);
			collector.emit(new Values(word));
		}
	}

	public void declareOutputFields(OutputFieldsDeclarer declarer) {
		declarer.declare(new Fields("word"));
	}
	
}

//统计单词逻辑
class CountBolt extends BaseRichBolt{

	private Map stormConf;
	private TopologyContext context;
	private OutputCollector collector;
	public void prepare(Map stormConf, TopologyContext context,OutputCollector collector) {
		this.stormConf = stormConf;
		this.context = context;
		this.collector = collector;
	}

	private HashMap<String, Integer> map = new  HashMap<String, Integer>();
	public void execute(Tuple input) {
		String word = input.getStringByField("word");
		System.err.println(word);
		Integer value = map.get(word);
		if(value==null){
			value = 0;
		}
		value++;
		map.put(word, value);
		//把结果写出去
		System.err.println("============================================");
		Utils.sleep(2000);
		for (Entry<String, Integer> entry : map.entrySet()) {
			System.out.println(entry);
		}
	}

	public void declareOutputFields(OutputFieldsDeclarer declarer) {
		
	}
	
}
/*class CountBolt extends BaseRichBolt{
	private Map conf;
	private TopologyContext context;
	private OutputCollector collector;
	
	public void prepare(Map conf, TopologyContext context, OutputCollector collector) {
		this.conf = conf;
		this.context = context;
		this.collector = collector;
	}
	
	*//**
	 * 对单词进行计数
	 *//*
	
	Map<String, Integer> countMap = new HashMap<String, Integer>();
	public void execute(Tuple tuple) {
		//读取tuple
		String word = tuple.getStringByField("word");
		//保存每个单词
		Integer value = countMap.get(word);
		if(value==null){
			value = 0;
		}
		value++;
		countMap.put(word, value);
		//把结果写出去
		System.err.println("============================================");
		Utils.sleep(2000);
		for (Entry<String, Integer> entry : countMap.entrySet()) {
			System.out.println(entry);
		}
	}

	public void declareOutputFields(OutputFieldsDeclarer arg0) {
		
	}

}*/

3 集群运行累加写法：

package changping.houzhihoujue.storm;

import java.io.File;
import java.io.IOException;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.concurrent.TimeUnit;

import org.apache.commons.io.FileUtils;

import ch.qos.logback.core.util.TimeUtil;

import backtype.storm.Config;
import backtype.storm.LocalCluster;
import backtype.storm.StormSubmitter;
import backtype.storm.spout.SpoutOutputCollector;
import backtype.storm.task.OutputCollector;
import backtype.storm.task.TopologyContext;
import backtype.storm.topology.OutputFieldsDeclarer;
import backtype.storm.topology.TopologyBuilder;
import backtype.storm.topology.base.BaseRichBolt;
import backtype.storm.topology.base.BaseRichSpout;
import backtype.storm.tuple.Fields;
import backtype.storm.tuple.Tuple;
import backtype.storm.tuple.Values;

/**
 * 本地运行:
 *   实现累加
 * @author zm
 *
 */
public class MyLocalStormTopology {

	/**
	 * 组装火车 轨道  并让火车在轨道上行驶
	 * @throws InterruptedException 
	 */
	public static void main(String[] args) throws Exception {

		// 祖品列车
		TopologyBuilder topologyBuilder = new TopologyBuilder();
		topologyBuilder.setSpout("1", new MySpout2()); // 定义1号车厢
		topologyBuilder.setBolt("2", new MyBolt1()).shuffleGrouping("1");// 定义2号车厢 并和1号车厢连接起来   
		// 造出轨道
		/*LocalCluster localCluster = new LocalCluster();// 造出轨道 在本地运行
		Config config = new Config();   
		// 轨道上运行列车， 三个参数分别为：定义的列车名，列车服务人员，轨道上跑的列车本身
		localCluster.submitTopology(MyLocalStormTopology.class.getSimpleName(), config, topologyBuilder.createTopology());
		
		TimeUnit.SECONDS.sleep(99999);// 设置列车运行时间
		localCluster.shutdown();// 跑完后就停止下来， 否则storm是永不停止
*/		
		// 造出轨道 在集群中运行
		StormSubmitter stormSubmitter = new StormSubmitter();// storm集群执行
		HashMap conf = new HashMap();
		stormSubmitter.submitTopology(MyLocalStormTopology.class.getSimpleName(), conf, topologyBuilder.createTopology());
		
	}

}

//创建火车头
class MySpout2 extends BaseRichSpout {

	private Map conf;
	private TopologyContext context;
	private SpoutOutputCollector collector;
	
	// 此方法首先被调用  打开storm系统外的数据源
	public void open(Map conf, TopologyContext context, SpoutOutputCollector collector) {
		this.conf = conf;
		this.context = context;
		this.collector = collector;
	}

	private int i = 0;
	// 认为是NameNode的heartbeat，永无休息的死循环的调用 并是线程安全的操作, 这里每一次调用此方法 将i++发送到bolt
	public void nextTuple() {
		System.err.println(i);
		// 将数据(i++)放在弹壳(Values)中，并发送给bolt
		this.collector.emit(new Values(i++));
		try {
			List linesNum = FileUtils.readLines(new File("D:/father"));
			System.err.println("文件行数为: " + linesNum.size());
		} catch (IOException e1) {
			System.err.println("文件行数为: 0 读取失败" );
			// TODO Auto-generated catch block
			e1.printStackTrace();
		}
		try {
			TimeUnit.SECONDS.sleep(1);
		} catch (InterruptedException e) {
			e.printStackTrace();
		}
	}

	//声明输出的字段的名称为 v1   只有在输出给别人时才会重写此方法
	public void declareOutputFields(OutputFieldsDeclarer declarer) {
		declarer.declare(new Fields("v1"));
	}
	
}

// 创建车厢
class MyBolt1 extends BaseRichBolt{

	private Map stormConf;
	private TopologyContext context;
	private OutputCollector collector;
	
	// 准备下要对接收storm spout发送来的数据
	public void prepare(Map stormConf, TopologyContext context,OutputCollector collector) {
		this.stormConf = stormConf;
		this.context = context;
		this.collector = collector;
	}

	private int sum = 0;
	// 死循环，用于接收bolt送来的数据   这里storm每调用一次此方法 则获取发送来的tuple数据
	public void execute(Tuple input) {
		int i = input.getIntegerByField("v1");
		sum += i;
		System.err.println(sum);
	}

	// 只有向外发送数据时 此方法才会被调用 否则 不要实现此方法 
	public void declareOutputFields(OutputFieldsDeclarer declarer) {
		
	}
	
}

3.1）将代码通过eclipse export 导出包为： stormApp.jar，上传到storm集群中，执行命令如下：

[root@h2master local]# storm/bin/storm jar stormApp.jar changping.houzhihoujue.storm.MyLocalStormTopology

可以看到提交成功：
Successfully uploaded topology jar to assigned location: /usr/local/storm/tmp/nimbus/inbox/stormjar-ffe04877-a31b-426e-bc21-02f201e8cdc2.jar

4 在UI上可以看到提交的累加Topology summary 任务如下：

停止此任务命令写法为： kill 后面的名称为上面截图中红圈的名称

这样就关闭了累加的storm任务

# storm/bin/storm kill MyLocalStormTopology