kafka-->storm-->mongodb

待我称王封你为后i 2022-01-09 07:47 155阅读 0赞

**目的：**

通过Spout发射kafka的数据，到bolt统计每一个单词的个数，将这些记录更新到mongodb中。

Spout的nextTuple方法会一直处于一个while循环这中，每一条数据发送给bolt后，bolt都会调用一次execute方法。

spout用于发射数据，bolt用于对数据进行处理。

**MongoUtil:mongo工具类**

package storm;

import com.mongodb.BasicDBObject;  
import com.mongodb.DB;  
import com.mongodb.DBCollection;  
import com.mongodb.DBObject;  
import com.mongodb.MongoClient;

public class MongoUtil \{  
private MongoUtil()\{\}  
private static MongoClient mongo;  
private static DB db;  
private static DBCollection collection;  
static\{  
mongo = new MongoClient("192.168.170.185",27017);  
db = mongo.getDB("mySpout");  
collection = db.getCollection("myBolt");  
\}  
public static Long getCount()\{  
return collection.count(new BasicDBObject("\_id",1L));  
\}  
public static void insert(String substring)\{  
DBObject obj = new BasicDBObject();  
obj.put("\_id", 1);  
obj.put("bolt", substring);  
collection.insert(obj);  
\}  
public static void update(String substring)\{  
DBObject obj = new BasicDBObject();  
obj.put("\_id", 1);  
DBObject obj2 = collection.findOne(obj);  
obj2.put("bolt", substring);  
collection.update(obj, obj2);  
\}  
  
\}

**SentenceSpout:发射数据的spout，从kafka读取数据。**

package storm;

import java.util.HashMap;  
import java.util.List;  
import java.util.Map;  
import java.util.Properties;

import org.apache.kafka.common.utils.Utils;  
import org.apache.storm.Constants;  
import org.apache.storm.spout.SpoutOutputCollector;  
import org.apache.storm.task.TopologyContext;  
import org.apache.storm.topology.OutputFieldsDeclarer;  
import org.apache.storm.topology.base.BaseRichSpout;  
import org.apache.storm.tuple.Fields;  
import org.apache.storm.tuple.Values;

import kafka.KafkaConsumer;  
import kafka.KafkaProducer;  
import kafka.consumer.ConsumerConfig;  
import kafka.consumer.ConsumerIterator;  
import kafka.consumer.KafkaStream;  
import kafka.javaapi.consumer.ConsumerConnector;  
import kafka.serializer.StringDecoder;  
import kafka.utils.VerifiableProperties;

public class SentenceSpout extends BaseRichSpout\{  
private SpoutOutputCollector collector;  
private int index = 0;  
private ConsumerConnector consumer;  
private Map conf;  
@Override  
public void open(Map map, TopologyContext context, SpoutOutputCollector collector) \{//尽量将初始化写在open方法中，否则可能会报错。  
this.conf = map;  
this.collector = collector;  
Properties props = new Properties();  
  
// zookeeper 配置  
props.put("zookeeper.connect", "192.168.170.185:2181");  
  
// 消费者所在组  
props.put("group.id", "testgroup");  
  
// zk连接超时  
props.put("zookeeper.session.timeout.ms", "4000");  
props.put("zookeeper.sync.time.ms", "200");  
props.put("auto.commit.interval.ms", "1000");  
props.put("auto.offset.reset", "smallest");  
  
// 序列化类  
props.put("serializer.class", "kafka.serializer.StringEncoder");  
  
ConsumerConfig config = new ConsumerConfig(props);  
  
this.consumer = kafka.consumer.Consumer.createJavaConsumerConnector(config);  
\}  
@Override  
public void nextTuple() \{

Map<String, Integer> topicCountMap = new HashMap<String, Integer>();  
topicCountMap.put("helloworld", new Integer(1));  
  
StringDecoder keyDecoder = new StringDecoder(new VerifiableProperties());  
StringDecoder valueDecoder = new StringDecoder(new VerifiableProperties());  
Map<String, List<KafkaStream<String, String>>> consumerMap =  
consumer.createMessageStreams(topicCountMap,keyDecoder,valueDecoder);  
KafkaStream<String, String> stream = consumerMap.get("helloworld").get(0);  
ConsumerIterator<String, String> it = stream.iterator();  
  
int messageCount = 0;  
while (it.hasNext())\{  
this.collector.emit(new Values(it.next().message().toString()));  
\}  
// index = (index+1>=sentences.length)?0:index+1;  
\}

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

\}  
**SplitSentenceBolt:切割单词bolt**

package storm;

import java.util.Map;

import org.apache.storm.Constants;  
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 SplitSentenceBolt extends BaseRichBolt\{  
private OutputCollector collector;  
private Map stormConf;  
@Override  
public void prepare(Map map, TopologyContext context, OutputCollector collector) \{  
this.stormConf = map;  
this.collector = collector;  
\}  
  
@Override  
public void execute(Tuple tuple) \{  
String str = tuple.getStringByField("sentence");  
String\[\] split = str.split(" ");  
for(String word : split)\{  
this.collector.emit(new Values(word));  
\}  
\}

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

**WordCountBolt：计数的bolt**

package storm;

import java.io.ByteArrayInputStream;  
import java.io.ByteArrayOutputStream;  
import java.io.IOException;  
import java.io.ObjectInputStream;  
import java.io.ObjectOutputStream;  
import java.util.HashMap;  
import java.util.Map;

import org.apache.storm.Config;  
import org.apache.storm.Constants;  
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 WordCountBolt extends BaseRichBolt\{  
private Map boltconf;  
private OutputCollector collector;  
private HashMap<String,Long> counts = null;  
@Override  
public void prepare(Map map, TopologyContext context, OutputCollector collector) \{  
this.boltconf = map;  
this.collector=collector;  
this.counts = new HashMap<String,Long>();  
\}

@Override  
public void execute(Tuple tuple) \{  
String word = tuple.getStringByField("word");  
this.counts.put(word, this.counts.containsKey(word)?this.counts.get(word)+1:1);  
this.collector.emit(new Values(word,counts.get(word)));  
\}

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

**ReportBolt:打印记录结果，并将结果插入mongodb中bolt**

package storm;

import java.util.ArrayList;  
import java.util.HashMap;  
import java.util.List;  
import java.util.Map;

import com.mongodb.BasicDBObject;  
import com.mongodb.DB;  
import com.mongodb.DBCollection;  
import com.mongodb.DBObject;  
import com.mongodb.MongoClient;

public class ReportBolt extends BaseRichBolt\{  
private HashMap<String,Long> counts = null;  
private Map boltconf;  
private StringBuffer buf = null;  
@Override  
public void prepare(Map arg0, TopologyContext arg1, OutputCollector arg2) \{  
this.boltconf = arg0;  
this.counts=new HashMap<String,Long>();  
this.buf = new StringBuffer();  
\}

@Override  
public void execute(Tuple tuple) \{  
String word = tuple.getStringByField("word");  
Long counts = tuple.getLongByField("count");  
this.counts.put(word, counts);  
System.out.println("------统计结果------");  
List<String> keys = new ArrayList<String>();  
keys.addAll(this.counts.keySet());  
  
buf.append("\{");  
for(String key : keys)\{  
  
buf.append(key+":"+this.counts.get(key)).append(",");  
System.out.println(key + " : " +this.counts.get(key));  
\}  
System.out.println("------------------");  
buf.append("\}");  
String substring = buf.delete(buf.length()-2, buf.length()-1).toString();  
  
long count = MongoUtil.getCount();  
if(count<=0)\{  
MongoUtil.insert(substring);  
\}else\{  
MongoUtil.update(substring);  
\}  
buf = buf.delete(0, buf.length());  
\}  
@Override  
public void declareOutputFields(OutputFieldsDeclarer arg0) \{  
// TODO Auto-generated method stub  
\}  
/\* @Override  
public Map<String, Object> getComponentConfiguration() \{  
HashMap<String, Object> hashMap = new HashMap<String, Object>();  
hashMap.put(Config.TOPOLOGY\_TICK\_TUPLE\_FREQ\_SECS, 10);  
return hashMap;  
\}\*/  
\}

**WordCountTopology: topology,storm零件的组装**

package storm;

import org.apache.storm.Config;  
import org.apache.storm.LocalCluster;  
import org.apache.storm.topology.TopologyBuilder;  
import org.apache.storm.tuple.Fields;

public class WordCountTopology \{  
private static final String SENTENCE\_SPOUT\_ID = "sentence-spout";  
private static final String SPLIT\_BOLT\_ID = "split-bolt";  
private static final String COUNT\_BOLT\_ID = "count-bolt";  
private static final String REPORT\_BOLT\_ID = "report-bolt";  
private static final String TOPOLOGY\_NAME = "word-count-topology";

public static void main(String\[\] args) throws Exception \{  
  
//--实例化Spout和Bolt  
SentenceSpout spout = new SentenceSpout();  
SplitSentenceBolt splitBolt = new SplitSentenceBolt();  
WordCountBolt countBolt = new WordCountBolt();  
ReportBolt reportBolt = new ReportBolt();  
//--创建TopologyBuilder类实例  
TopologyBuilder builder = new TopologyBuilder();  
  
//--注册SentenceSpout  
builder.setSpout(SENTENCE\_SPOUT\_ID, spout);  
//--注册SplitSentenceBolt，订阅SentenceSpout发送的tuple  
//此处使用了shuffleGrouping方法，此方法指定所有的tuple随机均匀的分发给SplitSentenceBolt的实例。  
builder.setBolt(SPLIT\_BOLT\_ID, splitBolt).shuffleGrouping(SENTENCE\_SPOUT\_ID);  
//--注册WordCountBolt,，订阅SplitSentenceBolt发送的tuple  
//此处使用了filedsGrouping方法，此方法可以将指定名称的tuple路由到同一个WordCountBolt实例中  
builder.setBolt(COUNT\_BOLT\_ID, countBolt).fieldsGrouping(SPLIT\_BOLT\_ID, new Fields("word"));  
//--注册ReprotBolt，订阅WordCountBolt发送的tuple  
//此处使用了globalGrouping方法，表示所有的tuple都路由到唯一的ReprotBolt实例中  
builder.setBolt(REPORT\_BOLT\_ID, reportBolt).globalGrouping(COUNT\_BOLT\_ID);  
  
//--创建配置对象  
Config conf = new Config();  
  
  
//--创建代表集群的对象，LocalCluster表示在本地开发环境来模拟一个完整的Storm集群  
//本地模式是开发和测试的简单方式，省去了在分布式集群中反复部署的开销  
//另外可以执行断点调试非常的便捷  
LocalCluster cluster = new LocalCluster();  
  
//--提交Topology给集群运行  
cluster.submitTopology(TOPOLOGY\_NAME, conf, builder.createTopology());  
  
//--运行10秒钟后杀死Topology关闭集群  
Thread.sleep(300000000);  
cluster.killTopology(TOPOLOGY\_NAME);  
cluster.shutdown();  
\}  
\}

转载于:https://www.cnblogs.com/wangjing666/p/6894015.html

kafka-->storm-->mongodb

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