Storm实战之WordCount

在storm环境部署完毕，并正确启动之后，现在就可以真正进入storm开发了，按照惯例，以wordcount作为开始。
这个例子很简单，核心组件包括：一个spout，两个bolt，一个Topology。
spout从一个路径读取文件，然后readLine，向bolt发射，一个文件处理完毕后，重命名，以不再重复处理。
第一个bolt将从spout接收到的字符串按空格split，产生word，发射给下一个bolt。
第二个bolt接收到word后，统计、计数，放到HashMap容器中。

1，定义一个spout，作用是源源不断滴向bolt发射字符串。

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

import org.apache.commons.io.FileUtils;
import org.apache.commons.io.filefilter.FileFilterUtils;

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;

public class WordReader extends BaseRichSpout {
    private static final long serialVersionUID = 2197521792014017918L;
    private String inputPath;
    private SpoutOutputCollector collector;

    @Override
    @SuppressWarnings(\"rawtypes\")
    public void open(Map conf, TopologyContext context, SpoutOutputCollector collector) {
        this.collector = collector;
        inputPath = (String) conf.get(\"INPUT_PATH\");
    }

    @Override
    public void nextTuple() {
        Collection files = FileUtils.listFiles(new File(inputPath),
                FileFilterUtils.notFileFilter(FileFilterUtils.suffixFileFilter(\".bak\")), null);
        for (File f : files) {
            try {
                List lines = FileUtils.readLines(f, \"UTF-8\");
                for (String line : lines) {
                    collector.emit(new Values(line));
                }
                FileUtils.moveFile(f, new File(f.getPath() + System.currentTimeMillis() + \".bak\"));
            } catch (IOException e) {
                e.printStackTrace();
            }
        }
    }

    @Override
    public void declareOutputFields(OutputFieldsDeclarer declarer) {
        declarer.declare(new Fields(\"line\"));
    }
}

2，定义一个bolt，作用是接收spout发过来的字符串，并分割成word，发射给下一个bolt。

import org.apache.commons.lang.StringUtils;

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;

public class WordSpliter extends BaseBasicBolt {

    private static final long serialVersionUID = -5653803832498574866L;

    @Override
    public void execute(Tuple input, BasicOutputCollector collector) {
        String line = input.getString(0);
        String[] words = line.split(\" \");
        for (String word : words) {
            word = word.trim();
            if (StringUtils.isNotBlank(word)) {
                word = word.toLowerCase();
                collector.emit(new Values(word));
            }
        }
    }

    @Override
    public void declareOutputFields(OutputFieldsDeclarer declarer) {
        declarer.declare(new Fields(\"word\"));

    }
}

3，定义一个bolt，接收word，并统计。

import java.util.HashMap;
import java.util.Map;
import java.util.Map.Entry;

import backtype.storm.task.TopologyContext;
import backtype.storm.topology.BasicOutputCollector;
import backtype.storm.topology.OutputFieldsDeclarer;
import backtype.storm.topology.base.BaseBasicBolt;
import backtype.storm.tuple.Tuple;

public class WordCounter extends BaseBasicBolt {
    private static final long serialVersionUID = 5683648523524179434L;
    private HashMap counters = new HashMap();
    private volatile boolean edit = false;

    @Override
    @SuppressWarnings(\"rawtypes\")
    public void prepare(Map stormConf, TopologyContext context) {
        final long timeOffset = Long.parseLong(stormConf.get(\"TIME_OFFSET\").toString());
        new Thread(new Runnable() {
            @Override
            public void run() {
                while (true) {
                    if (edit) {
                        for (Entry entry : counters.entrySet()) {
                            System.out.println(entry.getKey() + \" : \" + entry.getValue());
                        }
                        System.out.println(\"WordCounter---------------------------------------\");
                        edit = false;
                    }
                    try {
                        Thread.sleep(timeOffset * 1000);
                    } catch (InterruptedException e) {
                        e.printStackTrace();
                    }
                }
            }
        }).start();
    }

    @Override
    public void execute(Tuple input, BasicOutputCollector collector) {
        String str = input.getString(0);
        if (!counters.containsKey(str)) {
            counters.put(str, 1);
        } else {
            Integer c = counters.get(str) + 1;
            counters.put(str, c);
        }
        edit = true;
        System.out.println(\"WordCounter+++++++++++++++++++++++++++++++++++++++++++\");
    }

    @Override
    public void declareOutputFields(OutputFieldsDeclarer declarer) {

    }
}

注意WordCounter类的prepare方法，里面定义了一个Thread，持续监控容器的变化（word个数增加或者新增word）。

4，定义一个Topology，提交作业。

public class WordCountTopo {
    public static void main(String[] args) {
        if (args.length != 2) {
            System.err.println(\"Usage: inputPaht timeOffset\");
            System.err.println(\"such as : java -jar WordCount.jar D://input/ 2\");
            System.exit(2);
        }
        TopologyBuilder builder = new TopologyBuilder();
        builder.setSpout(\"word-reader\", new WordReader());
        builder.setBolt(\"word-spilter\", new WordSpliter()).shuffleGrouping(\"word-reader\");
        builder.setBolt(\"word-counter\", new WordCounter()).shuffleGrouping(\"word-spilter\");
        String inputPaht = args[0];
        String timeOffset = args[1];
        Config conf = new Config();
        conf.put(\"INPUT_PATH\", inputPaht);
        conf.put(\"TIME_OFFSET\", timeOffset);
        conf.setDebug(false);
        LocalCluster cluster = new LocalCluster();
        cluster.submitTopology(\"WordCount\", conf, builder.createTopology());
    }
}

5，代码完成后，导出jar（导出时不要指定Main class），然后上传至storm集群，通过命令./storm jar com.x.x.WordCountTopo /data/tianzhen/input 2来提交作业。
Topo启动，spout、bolt执行过程：

图片发自App

Thread监控的统计结果：

图片发自App

源文件处理之后被重命名为*.bak。

和Hadoop不同，在任务执行完之后，Topo不会停止，spout会一直监控数据源，不停地往bolt发射数据。
所以现在如果源数据发生变化，应该能够立马体现出来。我往path下再放一个文本文件，结果：

图片发自App

可见，结果立刻更新了，storm的实时性就体现在这里。