wordcount在eclipse上的伪分布式运行过程
hadoop 0.20 程式開發http://trac.nchc.org.tw/cloud/wiki/waue/2009/0617
單位作者Mail國家高速網路中心-格網技術組Wei-Yu Chenwaue @ nchc.org.tw
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最新版本的 Eclipse 3.5 搭配 Ubuntu 9.04 + hadoop-eclipse-plugin 0.20.1 ,初步測試功能皆可正常運作
但 Ubuntu 9.10 的 各版本 Eclipse , 似乎會有 gtk 圖形介面的bug ,有此一說增加 GDK_NATIVE_WINDOWS=1 就可以解決問題,但經過初步測試似乎無用
安裝的部份沒必要都一模一樣,僅提供參考,反正只要安裝好java , hadoop , eclipse,並清楚自己的路徑就可以了
首先安裝java 基本套件
$ sudo apt-get install java-common sun-java6-bin sun-java6-jdk sun-java6-jre
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1 將javadoc (jdk-6u10-docs.zip) 下載下來?下載點


2 下載完後將檔案放在 /tmp/ 下
3 執行
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$ sudo apt-get install sun-java6-doc
$ apt-get install ssh $ ssh-keygen -t rsa -P '' -f ~/.ssh/id_rsa $ cat ~/.ssh/id_rsa.pub >> ~/.ssh/authorized_keys $ ssh localhost
執行ssh localhost 沒有出現詢問密碼的訊息則無誤
安裝hadoop0.20到/opt/並取目錄名為hadoop
$ cd ~ $ wget http://apache.ntu.edu.tw/hadoop/core/hadoop-0.20.0/hadoop-0.20.0.tar.gz $ tar zxvf hadoop-0.20.0.tar.gz $ sudo mv hadoop-0.20.0 /opt/ $ sudo chown -R waue:waue /opt/hadoop-0.20.0 $ sudo ln -sf /opt/hadoop-0.20.0 /opt/hadoop
export?JAVA_HOME=/usr/lib/jvm/java-6-sun?export?HADOOP_HOME=/opt/hadoop?exportPATH=$PATH:/opt/hadoop/bin
<configuration> <property> <name>fs.default.name</name> <value>hdfs://localhost:9000</value> </property> <property> <name>hadoop.tmp.dir</name> <value>/tmp/hadoop/hadoop-${user.name}</value> </property> </configuration><configuration> <property> <name>dfs.replication</name> <value>1</value> </property> </configuration>
<configuration> <property> <name>mapred.job.tracker</name> <value>localhost:9001</value> </property> </configuration>
$ cd /opt/hadoop $ source /opt/hadoop/conf/hadoop-env.sh $ hadoop namenode -format $ start-all.sh $ hadoop fs -put conf input $ hadoop fs -ls
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$ cd ~ $ wget http://ftp.cs.pu.edu.tw/pub/eclipse/eclipse/downloads/drops/R-3.4.2-200902111700/eclipse-SDK-3.4.2-linux-gtk.tar.gz
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$ cd ~ $ tar -zxvf eclipse-SDK-3.4.2-linux-gtk.tar.gz $ sudo mv eclipse /opt $ sudo ln -sf /opt/eclipse/eclipse /usr/local/bin/
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$ cd /opt/hadoop $ sudo cp /opt/hadoop/contrib/eclipse-plugin/hadoop-0.20.0-eclipse-plugin.jar /opt/eclipse/plugins
$ sudo vim /opt/eclipse/eclipse.ini
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-startup plugins/org.eclipse.equinox.launcher_1.0.101.R34x_v20081125.jar --launcher.library plugins/org.eclipse.equinox.launcher.gtk.linux.x86_1.0.101.R34x_v20080805 -showsplash org.eclipse.platform --launcher.XXMaxPermSize 512m -vmargs -Xms40m -Xmx512m
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$ eclipse &
一開始會出現問你要將工作目錄放在哪裡:在這我們用預設值

PS: 之後的說明則是在eclipse 上的介面操作

設定要用 Map/Reduce 的視野
使用 Map/Reduce 的視野後的介面呈現
file ->new ->project ->Map/Reduce ->Map/Reduce Project ->next

建立mapreduce專案(1)

建立mapreduce專案的(2)
project name-> 輸入 : icas?(隨意)?use default hadoop -> Configur Hadoop install... -> 輸入:"/opt/hadoop"?-> ok Finish

由於剛剛建立了icas這個專案,因此eclipse已經建立了新的專案,出現在左邊視窗,右鍵點選該資料夾,並選properties
Step1. 右鍵點選project的properties做細部設定

Step2. 進入專案的細部設定頁
hadoop的javadoc的設定(1)
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source?...-> 輸入:/opt/opt/hadoop-0.20.0/src javadoc ...-> 輸入:file:/opt/hadoop/docs/api/
Step3. hadoop的javadoc的設定完後(2)

Step4. java本身的javadoc的設定(3)
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設定完後回到eclipse 主視窗
Step1. 視窗右下角黃色大象圖示"Map/Reduce Locations tag" -> 點選齒輪右邊的藍色大象圖示:

Step2. 進行eclipse 與 hadoop 間的設定(2)

Location Name -> 輸入:hadoop?(隨意)?Map/Reduce Master -> Host-> 輸入:localhost Map/Reduce Master -> Port-> 輸入:9001 DFS Master -> Host-> 輸入:9000 Finish
設定完後,可以看到下方多了一隻藍色大象,左方展開資料夾也可以秀出在hdfs內的檔案結構
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File ->new ->mapper


source?folder-> 輸入: icas/src Package : Sample Name -> : mapper
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package?Sample;?import?java.io.IOException;?import?java.util.StringTokenizer;?importorg.apache.hadoop.io.IntWritable;?import?org.apache.hadoop.io.Text;?importorg.apache.hadoop.mapreduce.Mapper;?public?class?mapper?extends?Mapper<Object,?Text,?Text,IntWritable>?{?private?final?static?IntWritable one?=?new?IntWritable(1);?private?Text word?=?newText();?public?void?map(Object key,?Text value,?Context context)?throws?IOException,InterruptedException?{?StringTokenizer itr?=?new?StringTokenizer(value.toString());?while(itr.hasMoreTokens())?{?word.set(itr.nextToken());?context.write(word,?one);?}?}?}建立mapper.java後,貼入程式碼


source?folder-> 輸入: icas/src Package : Sample Name -> : reducer
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package?Sample;?import?java.io.IOException;?import?org.apache.hadoop.io.IntWritable;?importorg.apache.hadoop.io.Text;?import?org.apache.hadoop.mapreduce.Reducer;?public?class?reducerextends?Reducer<Text,?IntWritable,?Text,?IntWritable>?{?private?IntWritable result?=?newIntWritable();?public?void?reduce(Text key,?Iterable<IntWritable>?values,?Context context)?throwsIOException,?InterruptedException?{?int?sum?=?0;?for?(IntWritable val?:?values)?{?sum?+=val.get();?}?result.set(sum);?context.write(key,?result);?}?}
建立WordCount.java,此檔用來驅動mapper 與 reducer,因此選擇 Map/Reduce Driver
source?folder-> 輸入: icas/src Package : Sample Name -> : WordCount.java
package?Sample;?import?org.apache.hadoop.conf.Configuration;?import?org.apache.hadoop.fs.Path;import?org.apache.hadoop.io.IntWritable;?import?org.apache.hadoop.io.Text;?importorg.apache.hadoop.mapreduce.Job;?import?org.apache.hadoop.mapreduce.lib.input.FileInputFormat;import?org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;?importorg.apache.hadoop.util.GenericOptionsParser;?public?class?WordCount?{?public?static?voidmain(String[]?args)?throws?Exception?{?Configuration conf?=?new?Configuration();?String[]otherArgs?=?new?GenericOptionsParser(conf,?args)?.getRemainingArgs();?if?(otherArgs.length?!=?2)?{System.err.println("Usage: wordcount <in> <out>");?System.exit(2);?}?Job job?=?new?Job(conf,?"word count");?job.setJarByClass(WordCount.class);?job.setMapperClass(mapper.class);job.setCombinerClass(reducer.class);?job.setReducerClass(reducer.class);job.setOutputKeyClass(Text.class);?job.setOutputValueClass(IntWritable.class);FileInputFormat.addInputPath(job,?new?Path(otherArgs[0]));?FileOutputFormat.setOutputPath(job,?newPath(otherArgs[1]));?System.exit(job.waitForCompletion(true)???0?:?1);?}?}三個檔完成後並存檔後,整個程式建立完成
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$ cd workspace/icas $ ls src/Sample/ mapper.java reducer.java WordCount.java $ ls bin/Sample/ mapper.class reducer.class WordCount.class
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有一熱心的hadoop使用者提供一個能讓 run-on-hadoop 這個功能恢復的方法。
原因是hadoop 的 eclipse-plugin 也許是用eclipse europa 這個版本開發的,而eclipse 的各版本 3.2 , 3.3, 3.4 間也都有或多或少的差異性存在。
因此如果先用eclipse europa 來建立一個新專案,之後把europa的eclipse這個版本關掉,換用eclipse 3.4開啟,之後這個專案就能用run-on-mapreduce 這個功能囉!
有興趣的話可以試試!(感謝逢甲資工所謝同學)
$ cd /home/waue/workspace/icas/ $ gedit Makefile
JarFile="sample-0.1.jar"?MainFunc="Sample.WordCount"?LocalOutDir="/tmp/output"?all:help jar: jar -cvf?${JarFile}?-C bin/ . run: hadoop jar?${JarFile}?${MainFunc}?input output clean: hadoop fs -rmr output output: rm -rf?${LocalOutDir}?hadoop fs -get output?${LocalOutDir}?gedit${LocalOutDir}/part-r-00000 &?help: @echo?"Usage:"?@echo?" make jar - Build Jar File."?@echo?" make clean - Clean up Output directory on HDFS."?@echo?" make run - Run your MapReduce code on Hadoop."?@echo?" make output - Download and show output file"?@echo?" make help - Show Makefile options."?@echo?" "?@echo?"Example:"?@echo?" make jar; make run; make output; make clean"?
$ cd /home/waue/workspace/icas/ $ make Usage: make jar - Build Jar File. make clean - Clean up Output directory on HDFS. make run - Run your MapReduce code on Hadoop. make output - Download and show output file make help - Show Makefile options. Example: make jar; make run; make output; make clean
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$ make jar
$ make run


$ make output
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$ make clean