Storm starter - Overview

Storm的starter例子, 都给的很有诚意, 不光是例子, 而是可以直接使用在实际的场景里面.
并且提高一些很有用的tool, 比如SlidingWindowCounter, TimeCacheMap
所以starter可以说是提高了基于storm编程的框架, 值得认真研究一下...

 

ExclamationTopology, 基本的Topology

没有什么特别的地方, 标准的例子

/**
 * This is a basic example of a Storm topology.
 */
public class ExclamationTopology {
    
    public static class ExclamationBolt extends BaseRichBolt {
        OutputCollector _collector;

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

        @Override
        public void execute(Tuple tuple) {
            _collector.emit(tuple, new Values(tuple.getString(0) + "!!!"));
            _collector.ack(tuple);
        }

        @Override
        public void declareOutputFields(OutputFieldsDeclarer declarer) {
            declarer.declare(new Fields("word"));
        }
    }
    
    public static void main(String[] args) throws Exception {
        TopologyBuilder builder = new TopologyBuilder();
        
        builder.setSpout("word", new TestWordSpout(), 10);        
        builder.setBolt("exclaim1", new ExclamationBolt(), 3)
                .shuffleGrouping("word");
        builder.setBolt("exclaim2", new ExclamationBolt(), 2)
                .shuffleGrouping("exclaim1");
                
        Config conf = new Config();
        conf.setDebug(true);
        
        if(args!=null && args.length > 0) {
            conf.setNumWorkers(3);
            
            StormSubmitter.submitTopology(args[0], conf, builder.createTopology());
        } else {
        
            LocalCluster cluster = new LocalCluster();
            cluster.submitTopology("test", conf, builder.createTopology());
            Utils.sleep(10000);
            cluster.killTopology("test");
            cluster.shutdown();    
        }
    }
}

 

RollingTopWords

实现了TopN和滑动窗口功能
这个例子的Bolt实现的很有指导意义, Storm starter - RollingTopWords

 

SingleJoinExample

通过TimeCacheMap, 实现基于memory的join, Storm starter - SingleJoinExample

 

BasicDRPCTopology, ReachTopology

关于DRPC的例子, 参考Twitter Storm – DRPC

 

TransactionalGlobalCount, TransactionalWords

Transactional Topology, Storm - Transactional-topologies

TransactionalGlobalCount比较简单, 看看TransactionalWords
在对word计数的基础上, 加上word count分布统计信息

public static Map<String, CountValue> COUNT_DATABASE = new HashMap<String, CountValue>();
public static Map<Integer, BucketValue> BUCKET_DATABASE = new HashMap<Integer, BucketValue>();

使用Count_Database来记录word的计数
使用Bucket_Database来记录word计数的分布, 比如, 出现0~9次的word有多少, 10~20的word有多少

public static class KeyedCountUpdater extends BaseTransactionalBolt implements ICommitter

对于KeyedCountUpdater和前面的简单例子没有啥大区别, 在execute时对word进行count, 在finishBatch时, 直接commit到Count_Database
输出, new Fields("id", "key", "count", "prev-count"), 其他都好理解, 为啥需要prev-count? 因为在更新Bucket_Database, 需要知道该word的bucket是否发生迁移, 所以必须知道之前的count

 

Bucketize, 根据count/BUCKET_SIZE, 算出应该属于哪个bucket
如果新的word, 直接在某bucket +1
如果word的bucket发生变化, 在新的bucket +1, 旧的bucket –1
如果没有变化, 不需要输出

    public static class Bucketize extends BaseBasicBolt {
        @Override
        public void execute(Tuple tuple, BasicOutputCollector collector) {
            TransactionAttempt attempt = (TransactionAttempt) tuple.getValue(0);
            int curr = tuple.getInteger(2);
            Integer prev = tuple.getInteger(3);

            int currBucket = curr / BUCKET_SIZE;
            Integer prevBucket = null;
            if(prev!=null) {
                prevBucket = prev / BUCKET_SIZE;
            }
            
            if(prevBucket==null) {
                collector.emit(new Values(attempt, currBucket, 1));                
            } else if(currBucket != prevBucket) {
                collector.emit(new Values(attempt, currBucket, 1));
                collector.emit(new Values(attempt, prevBucket, -1));
            }
        }
        
        @Override
        public void declareOutputFields(OutputFieldsDeclarer declarer) {
            declarer.declare(new Fields("attempt", "bucket", "delta"));
        }
    }

BucketCountUpdater, 也就是将上面的bucket的更新, 更新到Bucket_Database

Topology定义如下,

MemoryTransactionalSpout spout = new MemoryTransactionalSpout(DATA, new Fields("word"), PARTITION_TAKE_PER_BATCH);
TransactionalTopologyBuilder builder = new TransactionalTopologyBuilder("top-n-words", "spout", spout, 2);
builder.setBolt("count", new KeyedCountUpdater(), 5)
        .fieldsGrouping("spout", new Fields("word"));
builder.setBolt("bucketize", new Bucketize())
        .noneGrouping("count");
builder.setBolt("buckets", new BucketCountUpdater(), 5)
        .fieldsGrouping("bucketize", new Fields("bucket"));

 

WordCountTopology, 多语言的支持

Storm 多语言支持

分别使用ShellBolt和BaseBasicBolt来声明使用python和Java实现的Blot

    public static class SplitSentence extends ShellBolt implements IRichBolt {
        
        public SplitSentence() {
            super("python", "splitsentence.py");
        }

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

        @Override
        public Map<String, Object> getComponentConfiguration() {
            return null;
        }
    }  
    
    public static class WordCount extends BaseBasicBolt {
        Map<String, Integer> counts = new HashMap<String, Integer>();

        @Override
        public void execute(Tuple tuple, BasicOutputCollector collector) {
            String word = tuple.getString(0);
            Integer count = counts.get(word);
            if(count==null) count = 0;
            count++;
            counts.put(word, count);
            collector.emit(new Values(word, count));
        }

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

在定义Topology的时候, 可以直接将ShellBolt和BaseBasicBolt混合使用, 非常方便

        TopologyBuilder builder = new TopologyBuilder();
        
        builder.setSpout("spout", new RandomSentenceSpout(), 5);
        
        builder.setBolt("split", new SplitSentence(), 8)
                 .shuffleGrouping("spout");
        builder.setBolt("count", new WordCount(), 12)
                 .fieldsGrouping("split", new Fields("word"));