一、引言:
在storm发布到0.9.x以后,配置storm将会变得简单很多,也就是只需要配置zookeeper和storm即可,而不再需要配置zeromq和jzmq,由于网上面的storm配置绝大部分都是0.9以前的storm版本,所以有很多工作是不需要进行的,下面就storm的0.9.5版本在linux环境下进行配置进行详细解析。
由于配置storm只需要两个步骤,大大简化了配置,也是storm团队做了很大的努力,让程序员们专注于程序,让storm配置进行异常简单,好了,废话说了不少,下面正式开始讲解。
二、配置zookeeper
1.打开shell,可以根据自身的习惯设置下载文件的位置信息,使用如下命令进行下载(下载3.4.6版本,此版本位稳定版):
wget http://mirrors.hust.edu.cn/apache/zookeeper/zookeeper-3.4.6/zookeeper-3.4.6.tar.gz
2.下载完成后,使用如下命令进行解压缩:
tar -zxvf zookeeper-3.4.6.tar.gz
会出现一个名为zookeeper-3.4.6的文件夹
3.进入zookeeper-3.4.6的conf文件夹,复制zoo_sample.cfg,重命名为zoo.cfg
4.修改zoo.cfg的内容,添加的内容如下:
dataDir=/home/leesf/program/zookeeper/data //(注释:放置数据信息)
dataLogDir=/home/leesf/program/zookeeper/log //(注释:放置日志信息)
server.1=127.0.0.1:2888:3888 //(注释:使用本地模式,如果有多个机器,可以进行配置(server.1=xxx.xxx.xxxx:xxxx:xxxx
//server.2=xxx.xxx.xxx:xxxx:xxxx ....))
5.在shell命令行里进入zookeeper-3.4.6/bin目录,使用如下命令可以开启、测试、停止zookeeper服务
./zkServer.sh start //(注释:开启服务)
./zkServer.sh status //(注释:查看状态)
./zkServer.sh stop //(停止服务)
截图如下:
三、配置storm
1.下载storm,使用如下命令下载storm文件
wget http://mirrors.hust.edu.cn/apache/storm/apache-storm-0.9.5/apache-storm-0.9.5.tar.gz
2.进行解压缩,使用如下命令
tar -zxvf apache-storm-0.9.5.tar.gz
解压缩后出现文件夹apache-storm-0.9.5
3.修改apache-storm-0.9.5/conf目录中的storm.yaml文件
添加的内容如下:
# storm.zookeeper.servers:
# - "127.0.0.1"
#
# nimbus.host: "127.0.0.1"
#
# storm.zookeeper.port:2181
#
# storm.local.dir: "/home/leesf/program/storm/data"
#
# supervisor.slots.ports:
# -6700
# -6701
# -6702
# -6703
4.进入到apache-storm-0.9.5/bin目录下,启动nimbus、supervisor、ui,使用如下命令进行启动:
./storm nimbus
./storm supervisor
./storm ui
截图如下:
5.在浏览器中查看storm ui信息,打开浏览器输入127.0.0.1:8080即可查看
截图如下:
至此,storm的配置就完成了。
下面使用storm的本地模式来运行一个小的Demo,方便各位园友查看storm的运行效果
四、Storm Demo示例
storm demo的目录结构如下
1.spout包,数据发射源
2.bolt包,数据处理节点
3.main包,程序执行入口
4.words.txt,程序资源文件
分为如下几个步骤:
1.添加源代码:
1.spout包中包含一个java文件,WordReader.java,具体代码如下:
package com.leesf.Spout; import java.io.BufferedReader; import java.io.FileNotFoundException; import java.io.FileReader; import java.util.Map; 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; public class WordReader extends BaseRichSpout { private SpoutOutputCollector collector; private FileReader fileReader; private boolean completed = false; public void ack(Object msgId) { System.out.println("OK:"+msgId); } public void close() {} public void fail(Object msgId) { System.out.println("FAIL:"+msgId); } /** * The only thing that the methods will do It is emit each * file line */ public void nextTuple() { /** * The nextuple it is called forever, so if we have been readed the file * we will wait and then return */ if(completed){ try { Thread.sleep(1000); } catch (InterruptedException e) { //Do nothing } return; } String str; //Open the reader BufferedReader reader = new BufferedReader(fileReader); try{ //Read all lines while((str = reader.readLine()) != null){ /** * By each line emmit a new value with the line as a their */ this.collector.emit(new Values(str),str); } }catch(Exception e){ throw new RuntimeException("Error reading tuple",e); }finally{ completed = true; } } /** * We will create the file and get the collector object */ public void open(Map conf, TopologyContext context, SpoutOutputCollector collector) { try { this.fileReader = new FileReader(conf.get("wordsFile").toString()); } catch (FileNotFoundException e) { throw new RuntimeException("Error reading file ["+conf.get("wordFile")+"]"); } this.collector = collector; } /** * Declare the output field "word" */ public void declareOutputFields(OutputFieldsDeclarer declarer) { declarer.declare(new Fields("line")); } }
2.bolt包中包含两个java文件,WordCounter.java、WordNormalizer.java,具体代码如下:
WordCounter.java代码如下:
package com.leesf.Bolt; import java.util.HashMap; import java.util.Map; import backtype.storm.task.TopologyContext; import backtype.storm.topology.BasicOutputCollector; import backtype.storm.topology.OutputFieldsDeclarer; import backtype.storm.topology.base.BaseBasicBolt; import backtype.storm.tuple.Tuple; public class WordCounter extends BaseBasicBolt { Integer id; String name; Map<String, Integer> counters; /** * At the end of the spout (when the cluster is shutdown * We will show the word counters */ @Override public void cleanup() { System.out.println("-- Word Counter ["+name+"-"+id+"] --"); for(Map.Entry<String, Integer> entry : counters.entrySet()){ System.out.println(entry.getKey()+": "+entry.getValue()); } } /** * On create */ @Override public void prepare(Map stormConf, TopologyContext context) { this.counters = new HashMap<String, Integer>(); this.name = context.getThisComponentId(); this.id = context.getThisTaskId(); } @Override public void declareOutputFields(OutputFieldsDeclarer declarer) {} @Override public void execute(Tuple input, BasicOutputCollector collector) { String str = input.getString(0); /** * If the word dosn't exist in the map we will create * this, if not We will add 1 */ if(!counters.containsKey(str)){ counters.put(str, 1); }else{ Integer c = counters.get(str) + 1; counters.put(str, c); } } }
WordNormalizer.java代码如下:
package com.leesf.Bolt; import backtype.storm.topology.BasicOutputCollector; import backtype.storm.topology.OutputFieldsDeclarer; import backtype.storm.topology.base.BaseBasicBolt; import backtype.storm.tuple.Fields; import backtype.storm.tuple.Tuple; import backtype.storm.tuple.Values; public class WordNormalizer extends BaseBasicBolt { public void cleanup() {} /** * The bolt will receive the line from the * words file and process it to Normalize this line * * The normalize will be put the words in lower case * and split the line to get all words in this */ public void execute(Tuple input, BasicOutputCollector collector) { String sentence = input.getString(0); String[] words = sentence.split(" "); for(String word : words){ word = word.trim(); if(!word.isEmpty()){ word = word.toLowerCase(); collector.emit(new Values(word)); } } } /** * The bolt will only emit the field "word" */ public void declareOutputFields(OutputFieldsDeclarer declarer) { declarer.declare(new Fields("word")); } }
3.main包中包含一个java文件,Main.java,具体代码如下:
package com.leesf.Main; import backtype.storm.Config; import backtype.storm.LocalCluster; import backtype.storm.topology.TopologyBuilder; import backtype.storm.tuple.Fields; import com.leesf.Bolt.*; import com.leesf.Spout.*; public class Main { public static void main(String[] args) throws InterruptedException { //Topology definition TopologyBuilder builder = new TopologyBuilder(); builder.setSpout("word-reader",new WordReader()); builder.setBolt("word-normalizer", new WordNormalizer()) .shuffleGrouping("word-reader"); builder.setBolt("word-counter", new WordCounter(),1) .fieldsGrouping("word-normalizer", new Fields("word")); //Configuration Config conf = new Config(); conf.put("wordsFile", "/home/leesf/code/eclipse/StormDemo/res/words.txt"); conf.setDebug(false); //Topology run conf.put(Config.TOPOLOGY_MAX_SPOUT_PENDING, 1); LocalCluster cluster = new LocalCluster(); cluster.submitTopology("Getting-Started-Toplogie", conf, builder.createTopology()); Thread.sleep(10000); cluster.shutdown(); } }
4.资源文件,words.txt,内容如下:
storm test are great is an storm simple application but very powerfull really StOrm is great
words.txt可以放在任何地方,相应的程序中的路径也要进行修改,保证路径一致。
2.添加依赖库
将storm/lib目录下的所有文件添加到本项目中,截图如下:
3.运行程序
运行程序,可以得到如下的结果:
至此,关于storm的所有配置就已经完成了,下面可以进行相应的storm的开发了。
总结:storm在发布了0.9b版本以后,其配置工作就变得很简单,不再需要配置zeromq和jzmq,现在网上面的配置信息绝大部分都是0.9版本以前的,所以配置显得很累赘,在此记录此次的配置过程,方便各位园友的同时也方便自己以后再去配置这样的信息。在配置的过程中有任何问题也欢迎交流,谢谢各位观看。