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"));
本文章摘自博客园,原文发布日期:2013-05-24