Storm- 使用Storm实现词频汇总

需求：读取指定目录的数据，并实现单词计数的功能

实现方案：

　　Spout来读取指定目录的数据，作为后续Bolt处理的input

　　使用一个Bolt把input 的数据，切割分开，我们按照逗号进分割

　　使用一个Bolt来进行最终的单词次数统计操作并输出

拓扑设计：DataSourceSpout ==>SpiltBolt ==>CountBolt

Storm编程注意，Topology，Spout，Bolt等命名不能重复，伤到集群需要注意出现重复命名，会报错的。

package com.imooc.bigdata;

import org.apache.commons.io.FileUtils;
import org.apache.storm.Config;
import org.apache.storm.LocalCluster;
import org.apache.storm.spout.SpoutOutputCollector;
import org.apache.storm.task.OutputCollector;
import org.apache.storm.task.TopologyContext;
import org.apache.storm.topology.OutputFieldsDeclarer;
import org.apache.storm.topology.TopologyBuilder;
import org.apache.storm.topology.base.BaseRichBolt;
import org.apache.storm.topology.base.BaseRichSpout;
import org.apache.storm.tuple.Fields;
import org.apache.storm.tuple.Tuple;
import org.apache.storm.tuple.Values;

import java.io.File;
import java.io.IOException;
import java.util.*;

/**
 * 使用Storm完成词频统计功能
 */
public class LocalWordCountStormTopology {
    public static class DataSourceSpout extends BaseRichSpout{
        private SpoutOutputCollector collector;

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


        /**
         * 业务逻辑
         * 1） 读取指定目录文件夹下的数据:E:isolinux
         * 2） 把每一行的数据发射出去
         */
        @Override
        public void nextTuple() {

            // 获取所有文件
            Collection<File> files = FileUtils.listFiles(new File("E:\iso\linux"), new String[]{"txt"}, true);
            for (File file: files){
                try {
                    // 获取文件中的所有内容
                    List<String> lines = FileUtils.readLines(file);

                    // 获取文件中的每行的内容
                    for (String line: lines){

                        // 发射出去
                        this.collector.emit(new Values(line));
                    }

                    // TODO... 数据处理完成之后，改名，否则一直重复执行
                    FileUtils.moveFile(file, new File(file.getAbsolutePath()+System.currentTimeMillis()));
                } catch (IOException e) {
                    e.printStackTrace();
                }
            }
        }

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

        }
    }


    /**
     * 对数据进行分割
     */
    public static class SplitBolt extends BaseRichBolt{
        private OutputCollector collector;

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

        /**
         * 业务逻辑：
         *  line： 对line进行分割，按逗号进行分割
         * @param input
         */
        @Override
        public void execute(Tuple input) {
            String line = input.getStringByField("line");
            String[] words = line.split(",");

            for (String word: words){
                this.collector.emit(new Values(word));
            }
        }

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

    /**
     * 词频汇总Bolt
     */
    public static class WordCountBlot extends BaseRichBolt{

        @Override
        public void prepare(Map stormConf, TopologyContext context, OutputCollector collector) {

        }

        Map<String, Integer> map = new HashMap<String, Integer>();
        /**
         * 业务逻辑：
         * 1）获取每个单词
         * 2）对所有单词进行汇总
         * 3）输出
         * @param input
         */
        @Override
        public void execute(Tuple input) {

            // 1）获取每个单词
            String word = input.getStringByField("word");
            Integer count = map.get(word);
            if (count == null){
                count = 0;
            }
            count ++;


            // 2）对所有单词进行汇总
            map.put(word, count);

            // 3）输出
            System.out.println("~~~~~~~~~~~~~~~~~~~~~~~~~~~");
            Set<Map.Entry<String, Integer>> entries = map.entrySet();
            for (Map.Entry<String, Integer> entry: entries) {
                System.out.println(entry);
            }
        }

        @Override
        public void declareOutputFields(OutputFieldsDeclarer declarer) {

        }
    }

    public static void main(String[] args) {

        // 通过TopologyBuilder根据Spout和Bilt构建Topology
        TopologyBuilder builder = new TopologyBuilder();
        builder.setSpout("DataSourceSpout", new DataSourceSpout());
        builder.setBolt("SplitBolt", new SplitBolt()).shuffleGrouping("DataSourceSpout");
        builder.setBolt("WordCountBlot", new WordCountBlot()).shuffleGrouping("SplitBolt");

        // 创建本地集群
        LocalCluster cluster = new LocalCluster();
        cluster.submitTopology("LocalWordCountStormTopology", new Config(), builder.createTopology());

    }
}