nodejs+kafka+storm+hbase 开发
1.环境介绍如图所示，NODEJS做为数据源的的产生者产生消息，发到Kafka队列，然后参见红线，表示本地开发的环境下数据的流向（本地开发时，storm topology运行在本地模式）
2.搭建环境,我采用的是eclipse+maven
1.建立一个maven工程， 然后将pom文件修改如下：
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/maven-v4_0_0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>com.h3c.storm</groupId>
<artifactId>storm-samples</artifactId>
<packaging>jar</packaging>
<version>1.0-SNAPSHOT</version>
<name>storm-kafka-test</name>
<url>http://maven.apache.org</url>
<dependencies>
<dependency>
<groupId>junit</groupId>
<artifactId>junit</artifactId>
<version>3.8.1</version>
<scope>test</scope>
</dependency>
<dependency>
<groupId>jdk.tools</groupId>
<artifactId>jdk.tools</artifactId>
<version>1.7</version>
<scope>system</scope>
<systemPath>${JAVA_HOME}/lib/tools.jar</systemPath>
</dependency>
<dependency>
<groupId>org.apache.storm</groupId>
<artifactId>storm-core</artifactId>
<version>0.10.0</version>
<!-- keep storm out of the jar-with-dependencies -->
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.kafka</groupId>
<artifactId>kafka_2.9.2</artifactId>
<version>0.8.1.1</version>
<exclusions>
<exclusion>
<groupId>org.apache.zookeeper</groupId>
<artifactId>zookeeper</artifactId>
</exclusion>
<exclusion>
<groupId>log4j</groupId>
<artifactId>log4j</artifactId>
</exclusion>
</exclusions>
</dependency>
<dependency>
<groupId>org.apache.storm</groupId>
<artifactId>storm-kafka</artifactId>
<version>0.9.2-incubating</version>
</dependency>
<dependency>
<groupId>org.apache.storm</groupId>
<artifactId>storm-hbase</artifactId>
<version>0.10.0</version>
</dependency>
</dependencies>
</project>
View Code 2.nodeJS发消息的示例代码，当然，首先要手动在kafka里新建一个topic对应代码里的topic，我这里创建的topic是"historyclients"
var kafka = require('kafka-node');
var Producer = kafka.Producer;
var KeyedMessage = kafka.KeyedMessage;
var conf = '172.27.8.111:2181,172.27.8.112:2181,172.27.8.119:2181';
var client = new kafka.Client(conf);
var producer = new Producer(client);
var clientOnlineInfo ={"clientMAC":"0000-0000-0002",
"acSN":"210235A1AMB159000008",
"onLineTime":"2016-06-27 10:00:00"};
var clientOnlineInfoStr = JSON.stringify(clientOnlineInfo);
var msg = [
{ topic: 'historyclients', messages: clientOnlineInfoStr, partition: 0 }
];
producer.on('ready', function () {
producer.send(msg, function (err, data) {
console.log("done!")
console.log(data);
});
});
producer.on('error', function (err) {
console.error(err);
});
View Code 3.spout代码
package com.h3c.storm;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Properties;
import backtype.storm.spout.SpoutOutputCollector;
import backtype.storm.task.TopologyContext;
import backtype.storm.topology.OutputFieldsDeclarer;
import backtype.storm.topology.base.BaseRichSpout;
import backtype.storm.tuple.Fields;
import backtype.storm.tuple.Values;
import kafka.consumer.ConsumerConfig;
import kafka.consumer.ConsumerIterator;
import kafka.consumer.KafkaStream;
import kafka.javaapi.consumer.ConsumerConnector;
public class KafkaSpout extends BaseRichSpout{
private SpoutOutputCollector collector;
privateConsumerConnector consumer;
privateString topic;
Map<String, List<KafkaStream<byte[], byte[]>>> consumerMap;
private static ConsumerConfig createConsumerConfig()
{
Properties props = new Properties();
props.put("zookeeper.connect", "172.27.8.111:2181,172.27.8.112:2181,172.27.8.119:2181");
props.put("group.id", "group1");
props.put("zookeeper.session.timeout.ms", "40000");
props.put("zookeeper.sync.time.ms", "200");
props.put("auto.commit.interval.ms", "1000");
return new ConsumerConfig(props);
}
@Override
public void open(Map conf, TopologyContext context,SpoutOutputCollector collector) {
System.err.println("open!!!!!!!!!!!!!!!");
this.collector = collector;
/* create consumer */
this.topic = "historyclients";
this.consumer = kafka.consumer.Consumer.createJavaConsumerConnector(createConsumerConfig());
/* topic HashMap,which means the map can include multiple topics */
Map<String, Integer> topicCountMap = new HashMap<String, Integer>();
topicCountMap.put(topic, new Integer(1));
this.consumerMap = consumer.createMessageStreams(topicCountMap);
}
@Override
public void nextTuple() {
KafkaStream<byte[], byte[]> stream = consumerMap.get(topic).get(0);
ConsumerIterator<byte[], byte[]> it = stream.iterator();
String toSay = "";
while (it.hasNext()) {
toSay = new String(it.next().message());
System.err.println("receive：" + toSay);
this.collector.emit(new Values(toSay));
}
}
@Override
public void declareOutputFields(OutputFieldsDeclarer declarer) {
declarer.declare(new Fields("clientInfo"));
}
}
View Code 4.storm-hbase API 中要求实现的mapper代码
package com.h3c.storm;
import org.apache.storm.hbase.bolt.mapper.HBaseMapper;
import org.apache.storm.hbase.common.ColumnList;
import backtype.storm.tuple.Tuple;
public class MyHBaseMapper implements HBaseMapper {
public ColumnList columns(Tuple tuple) {
ColumnList cols = new ColumnList();
//参数依次是列族名，列名，值
cols.addColumn("f1".getBytes(), "colMAC".getBytes(), tuple.getStringByField("clientInfo").getBytes());
//System.err.println("BOLT + " + tuple.getStringByField("clientInfo"));
//cols.addColumn("f1".getBytes(), "hhhhhhh".getBytes(), "0000-0000-0001".getBytes());
//System.err.println("BOLT + " + tuple.getStringByField("clientInfo"));
return cols;
}
public byte[] rowKey(Tuple tuple) {
//return tuple.getStringByField("clientInfo").getBytes();
return "newRowKey".getBytes();
}
}
Mapper 5.topology代码
package com.h3c.storm;
import java.util.Map;
import java.util.Random;
import org.apache.storm.hbase.bolt.HBaseBolt;
import org.apache.storm.hbase.bolt.mapper.HBaseMapper;
import java.util.HashMap;
import java.util.List;
import java.util.Properties;
import backtype.storm.Config;
import backtype.storm.LocalCluster;
import backtype.storm.StormSubmitter;
import backtype.storm.spout.SpoutOutputCollector;
import backtype.storm.task.TopologyContext;
import backtype.storm.topology.BasicOutputCollector;
import backtype.storm.topology.OutputFieldsDeclarer;
import backtype.storm.topology.TopologyBuilder;
import backtype.storm.topology.base.*;
import backtype.storm.tuple.Fields;
import backtype.storm.tuple.Tuple;
import backtype.storm.tuple.Values;
import backtype.storm.utils.Utils;
import kafka.consumer.Consumer;
import kafka.consumer.ConsumerConfig;
import kafka.consumer.ConsumerIterator;
import kafka.consumer.ConsumerTimeoutException;
import kafka.consumer.KafkaStream;
import kafka.javaapi.consumer.ConsumerConnector;
import kafka.message.MessageAndMetadata;
public class PersistTopology {
private static final String KAFKA_SPOUT = "KAFKA_SPOUT";
private static final String HBASE_BOLT = "HBASE_BOLT";
public static void main(String[] args) throws Exception {
/* define spout */
KafkaSpout kafkaSpout = new KafkaSpout();
System.setProperty("hadoop.home.dir", "E:\\eclipse\\");
/* define HBASE Bolt */
HBaseMapper mapper = new MyHBaseMapper();
HBaseBolt hbaseBolt = new HBaseBolt("historyclients", mapper).withConfigKey("hbase.conf");
/* define topology*/
TopologyBuilder builder = new TopologyBuilder();
builder.setSpout(KAFKA_SPOUT, kafkaSpout);
builder.setBolt(HBASE_BOLT, hbaseBolt).shuffleGrouping(KAFKA_SPOUT);
Config conf = new Config();
conf.setDebug(true);
Map<String, Object> hbConf = new HashMap<String, Object>();
// if(args.length > 0){
// hbConf.put("hbase.rootdir", args);
// }
//hbConf.put("hbase.rootdir", "hdfs://172.27.8.111:8020/apps/hbase/data");
conf.put("hbase.conf", hbConf);
if (args != null && args.length > 0) {
conf.setNumWorkers(3);
StormSubmitter.submitTopology(args, conf, builder.createTopology());
} else {
LocalCluster cluster = new LocalCluster();
cluster.submitTopology("test", conf, builder.createTopology());
Utils.sleep(600000);
cluster.killTopology("test");
cluster.shutdown();
}
}
}
View Code 6.需要从集群中取中hbase-site.xml这个文件，加到项目里，在buildpath中可设置
7.在C:\Windows\System32\drivers\etc下把hosts文件加上到集群的IP与域名的映射
172.27.8.111 node1.hde.h3c.com node1
172.27.8.112node2.hde.h3c.com node2
172.27.8.119node3.hde.h3c.com node3
8. 出现java.io.IOException: Could not locate executable null\bin\winutils.exe in the Hadoop binaries.的解决办法
网上下载winutils.exe这个文件，找一个地方放好，比如我放在E:\eclipse\bin 下面，前面一定要有个“bin”
然后在代码里加上这句即可
System.setProperty("hadoop.home.dir", "E:\\eclipse\\");
参考文章
http://www.tuicool.com/articles/r6ZZBjU
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