Storm入门（七）可靠性机制代码示例

一、关联代码

使用maven，代码如下。

pom.xml  参考 http://www.cnblogs.com/hd3013779515/p/6970551.html

MessageTopology.java

package cn.ljh.storm.reliability;

import org.apache.storm.Config;
import org.apache.storm.LocalCluster;
import org.apache.storm.topology.TopologyBuilder;
import org.apache.storm.utils.Utils;

public class MessageTopology {
    public static void main(String[] args) throws Exception {
        TopologyBuilder builder = new TopologyBuilder();

        builder.setSpout("MessageSpout", new MessageSpout(), 1);
        builder.setBolt("SpilterBolt", new SpliterBolt(), 5).shuffleGrouping("MessageSpout");
        builder.setBolt("WriterBolt", new WriterBolt(), 1).shuffleGrouping("SpilterBolt");

        Config conf = new Config();
        conf.setDebug(false);

        LocalCluster cluster = new LocalCluster();
        cluster.submitTopology("messagetest", conf, builder.createTopology());
        Utils.sleep(20000);
        cluster.killTopology("messagetest");
        cluster.shutdown();
    }
}

MessageSpou.java

package cn.ljh.storm.reliability;

import org.apache.storm.topology.OutputFieldsDeclarer;

import java.util.Map;
import org.apache.storm.spout.SpoutOutputCollector;
import org.apache.storm.task.TopologyContext;
import org.apache.storm.topology.base.BaseRichSpout;
import org.apache.storm.tuple.Fields;
import org.apache.storm.tuple.Values;

import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

public class MessageSpout extends BaseRichSpout {
   public static Logger LOG = LoggerFactory.getLogger(MessageSpout.class);
   private SpoutOutputCollector _collector;

   private int index = 0;
   private String[] subjects = new String[]{
           "Java,Python",
           "Storm,Kafka",
           "Spring,Solr",
           "Zookeeper,FastDFS",
           "Dubbox,Redis"
   };

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

   public void nextTuple() {

       if(index < subjects.length){
           String sub = subjects[index];
           //使用messageid参数，使可靠性机制生效
           _collector.emit(new Values(sub), index);
           index++;
       }
   }

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

   @Override
   public void ack(Object msgId) {
       LOG.info("【消息发送成功！】(msgId = " + msgId + ")");
   }

   @Override
   public void fail(Object msgId) {
       LOG.info("【消息发送失败！】(msgId = " + msgId + ")");
       LOG.info("【重发进行中。。。】");
       _collector.emit(new Values(subjects[(Integer)msgId]), msgId);
       LOG.info("【重发成功！】");
   }

}

SpliterBolt.java

package cn.ljh.storm.reliability;

import java.util.Map;

import org.apache.storm.task.OutputCollector;
import org.apache.storm.task.TopologyContext;
import org.apache.storm.topology.OutputFieldsDeclarer;
import org.apache.storm.topology.base.BaseRichBolt;
import org.apache.storm.tuple.Fields;
import org.apache.storm.tuple.Tuple;
import org.apache.storm.tuple.Values;

public class SpliterBolt extends BaseRichBolt {
    OutputCollector _collector;
    private boolean flag = false;

    public void prepare(Map conf, TopologyContext context, OutputCollector collector) {
      _collector = collector;
    }

    public void execute(Tuple tuple) {

        try{
            String subjects = tuple.getStringByField("subjects");

//            if(!flag && subjects.equals("Spring,Solr")){
//                flag = true;
//                int a = 1/0;
//            }

            String[] words = subjects.split(",");
            for(String word : words){
                //注意：要携带tuple对象，用于处理异常时重发策略。
                _collector.emit(tuple, new Values(word));
            }

            //对tuple进行ack
            _collector.ack(tuple);
        }catch(Exception ex){
            ex.printStackTrace();
            //对tuple进行fail，使重发。
            _collector.fail(tuple);
        }
    }

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

  }

WriterBolt.java

package cn.ljh.storm.reliability;

import java.io.FileWriter;
import java.io.IOException;
import java.util.Map;

import org.apache.storm.task.OutputCollector;
import org.apache.storm.task.TopologyContext;
import org.apache.storm.topology.OutputFieldsDeclarer;
import org.apache.storm.topology.base.BaseRichBolt;
import org.apache.storm.tuple.Tuple;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

public class WriterBolt extends BaseRichBolt {
        private static Logger LOG = LoggerFactory.getLogger(WriterBolt.class);
        OutputCollector _collector;

        private FileWriter fileWriter;
        private boolean flag = false;

        public void prepare(Map conf, TopologyContext context, OutputCollector collector) {
          _collector = collector;

            if(fileWriter == null){
                try {
                    fileWriter = new FileWriter("D:\\test\\"+"words.txt");
                } catch (IOException e) {
                    e.printStackTrace();
                }
            }

        }

        public void execute(Tuple tuple) {
            try {
                  String word = tuple.getStringByField("word");

//                if(!flag && word.equals("Kafka")){
//                    flag = true;
//                    int a = 1/0;
//                }
                fileWriter.write(word + "\r\n");
                fileWriter.flush();
            } catch (Exception e) {
                e.printStackTrace();
                //对tuple进行fail，使重发。
                _collector.fail(tuple);
            }
            //对tuple进行ack
            _collector.ack(tuple);
        }

        public void declareOutputFields(OutputFieldsDeclarer declarer) {
        }
}

二、执行效果

1、代码要点说明

MessageSpout.java

（1）发射tuple时要设置messageId来使可靠性机制生效

_collector.emit(new Values(sub), index);

（2）重写ack和fail方法

@Override
   public void ack(Object msgId) {
       LOG.info("【消息发送成功！】(msgId = " + msgId + ")");
   }

   @Override
   public void fail(Object msgId) {
       LOG.info("【消息发送失败！】(msgId = " + msgId + ")");
       LOG.info("【重发进行中。。。】");
       _collector.emit(new Values(subjects[(Integer)msgId]), msgId);
       LOG.info("【重发成功！】");
   }

SpliterBolt.java

（1）发射新tuple时设置输入tuple参数，以使新tuple和输入tuple为一个整体

_collector.emit(tuple, new Values(word));

（2）完成处理后进行ack，失败时进行fail

_collector.ack(tuple);

_collector.fail(tuple);

WriterBolt.java

（1）完成处理后进行ack，失败时进行fail

_collector.ack(tuple);

_collector.fail(tuple);

2、正常处理结果

3、放开SpliterBolt 的错误代码

结果显示能够正确的重发。

4、放开SpliterBolt 的错误代码

能够正确进行重发，但是文件中storm字符串出现了两次。

5、总结

通过以上测试，如果在第一个bolt处理时出现异常，可以让整个数据进行重发，如果第二个bolt处理时出现异常，也可以让整个数据进行重发，但是同时出现了重复处理的事务性问题，需要进行特殊的处理。

（1）如果数据入库的话，可以把messageId也进行入库保存。此messageId可以用来判断是否重复处理。

（2）事务性tuple尽量不要拆分。

（3）使用storm的Trident框架。