[[PageOutline]]
{{{
#!html
hadoop 0.20 程式開發
eclipse plugin + Makefile
}}}
= 零. 前言 =
* 開發hadoop 需要用到許多的物件導向語法，包括繼承關係、介面類別，而且需要匯入正確的classpath，否則寫hadoop程式只是打字練習...
* 用類 vim 來處理這種複雜的程式，有可能會變成一場惡夢，因此用eclipse開發，搭配mapreduce-plugin會事半功倍。
* 早在hadoop 0.19～0.16之間的版本，我就試過各個plugin，每個版本的plugin都確實有大大小小的問題，如：hadoop plugin 無法正確使用、無法run as mapreduce。hadoop0.16搭配IBM的hadoop_plugin 可以提供完整的功能，但是，老兵不死，只是凋零...
* 子曰："逝者如斯夫，不捨晝夜"，以前寫的文件也落伍了，要跟上潮流，因此此篇的重點在：'''用eclipse開發hadoop程式，並且測試撰寫的程式運作在hadoop上'''
== 0.1 環境說明 ==
* ubuntu 8.10
* sun-java-6
* eclipse 3.4.2
* hadoop 0.20.0
== 0.2 目錄說明 ==
* 使用者：waue
* 使用者家目錄： /home/waue
* 專案目錄 ： /home/waue/workspace
* hadoop目錄： /opt/hadoop
= 一、安裝 =
* 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
== 1.1. 安裝java ==
* java 基本套件
{{{
$ sudo apt-get install java-common sun-java6-bin sun-java6-jdk sun-java6-jre
}}}
== 1.1.1. 安裝sun-java6-doc ==
* 1 將javadoc下載下來
[https://cds.sun.com/is-bin/INTERSHOP.enfinity/WFS/CDS-CDS_Developer-Site/en_US/-/USD/ViewProductDetail-Start?ProductRef=jdk-6u10-docs-oth-JPR@CDS-CDS_Developer 下載點]
* 2 放在 /tmp/ 下
* 3 執行
{{{
$ sudo apt-get install sun-java6-doc
}}}
== 1.3. 安裝hadoop ==
* 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
}}}
* 編輯 /opt/hadoop/conf/hadoop-env.sh
{{{
#!sh
export JAVA_HOME=/usr/lib/jvm/java-6-sun
export HADOOP_HOME=/opt/hadoop
export PATH=$PATH:/opt/hadoop/bin
}}}
* 編輯 /opt/hadoop/conf/core-site.xml
{{{
#!sh
fs.default.name
hdfs://localhost:9000
hadoop.tmp.dir
/tmp/hadoop/hadoop-${user.name}
}}}
* 編輯 /opt/hadoop/conf/hdfs-site.xml
{{{
#!sh
dfs.replication
1
}}}
* 編輯 /opt/hadoop/conf/mapred-site.xml
{{{
#!sh
mapred.job.tracker
localhost:9001
}}}
* 啟動
{{{
$ cd /opt/hadoop
$ source /opt/hadoop/conf/hadoop-env.sh
$ hadoop namenode -format
$ start-all.sh
$ hadoop fs -put conf input
$ hadoop -ls
}}}
* 沒有錯誤訊息則代表無誤
== 1.2. 安裝eclipse ==
* 下載 [http://www.eclipse.org/downloads/download.php?file=/eclipse/downloads/drops/R-3.4.2-200902111700/eclipse-SDK-3.4.2-linux-gtk.tar.gz eclipse SDK 3.4.2 Classic]
* 放這檔案到家目錄
{{{
$ cd ~
$ tar -zxvf eclipse-SDK-3.4.2-linux-gtk.tar.gz
$ sudo mv eclipse /opt
$ sudo ln -sf /opt/eclipse/bin/eclipse /usr/local/bin/
}}}
* 建立連結 (圖形介面要重新啟動才有吧！)
{{{
$ cat >> ~/.gnome2/panel2.d/default/launchers/eclipse.desktop << EOF
[Desktop Entry]
Encoding=UTF-8
Version=1.0
Type=Application
Terminal=false
Name[zh_TW]=eclipse
Exec=/usr/bin/eclipse
Name=eclipse
Icon[zh_TW]=/opt/eclipse/plugins/org.eclipse.platform_3.3.101.v200902111700/eclipse48.png
Icon=/opt/eclipse/plugins/org.eclipse.platform_3.3.101.v200902111700/eclipse48.png
EOF
}}}
= 二、 建立專案 =
* 匯入hadoop 0.20.0 eclipse plugin
{{{
$ 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
}}}
* 可斟酌參考eclipse.ini內容（非必要）
{{{
#!sh
-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
}}}
* window -> open pers.. -> other.. -> map/reduce
* file -> new -> project -> Map/Reduce -> Map/Reduce Project -> next
{{{
#!sh
project name-> 輸入 : icas (隨意)
use default hadoop -> Configur Hadoop install... -> 輸入： "/opt/hadoop" -> ok
Finish
}}}
* Project -> properties ->
* java Build Path -> Libraries -> hadoop-0.20.0-ant.jar
* java Build Path -> Libraries -> hadoop-0.20.0-core.jar
* java Build Path -> Libraries -> hadoop-0.20.0-tools.jar
以 hadoop-0.20.0-core.jar 的設定內容如下，其他依此類推
{{{
#!sh
source ...-> 輸入：/opt/opt/hadoop-0.20.0/src/core
javadoc ...-> 輸入：file:/opt/hadoop/docs/api/
}}}
* Project -> properties
* javadoc location -> 輸入：file:/usr/lib/jvm/java-6-sun/docs/api/
* 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：
{{{
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
}}}
= 三、 撰寫範例程式 =
* 之前在eclipse上已經開了個專案icas，因此這個目錄在：
* /home/waue/workspace/icas
* 在這個目錄內有兩個資料夾：
* src ： 用來裝程式原始碼
* bin ： 用來裝編譯後的class檔
* 如此一來原始碼和編譯檔就不會混在一起，對之後產生jar檔會很有幫助
== 3.1 我的第一隻程式 ==
* File -> new -> mapper
{{{
source folder-> 輸入： icas/src
Package : Sample
Name -> : mapper
}}}
* 編輯mapper.java
{{{
#!java
package Sample;
import java.io.IOException;
import java.util.StringTokenizer;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;
public class mapper extends Mapper {
private final static IntWritable one = new IntWritable(1);
private Text word = new Text();
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);
}
}
}
}}}
* File -> new -> reducer
{{{
source folder-> 輸入： icas/src
Package : Sample
Name -> : reducer
}}}
{{{
#!java
package Sample;
import java.io.IOException;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;
public class reducer extends Reducer {
private IntWritable result = new IntWritable();
public void reduce(Text key, Iterable values, Context context)
throws IOException, InterruptedException {
int sum = 0;
for (IntWritable val : values) {
sum += val.get();
}
result.set(sum);
context.write(key, result);
}
}
}}}
* File -> new -> Map/Reduce Driver
{{{
source folder-> 輸入： icas/src
Package : Sample
Name -> : WordCount.java
}}}
* 編輯 WordCount.java 檔
{{{
#!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;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.util.GenericOptionsParser;
public class WordCount {
public static void main(String[] args) throws Exception {
Configuration conf = new Configuration();
String[] otherArgs = new GenericOptionsParser(conf, args)
.getRemainingArgs();
if (otherArgs.length != 2) {
System.err.println("Usage: wordcount ");
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, new Path(otherArgs[1]));
System.exit(job.waitForCompletion(true) ? 0 : 1);
}
}
}}}
* 三個檔都存檔後，可以看到icas專案下的src，bin都有檔案產生
{{{
$ cd workspace/icas
$ ls src/Sample/
mapper.java reducer.java WordCount.java
$ ls bin/Sample/
mapper.class reducer.class WordCount.class
}}}
= 四、編譯 =
* 由於hadoop 0.20 此版本的eclipse-plugin依舊不完整，如：1. 齒輪圖示沒有作用 2. 右鍵點選WordCount.java -> run as -> run on Hadoop ：沒有效果
* 因此編譯hadoop程式就要靠指令來編輯，然而用一行一行指令來產生太沒效率，在此介紹用Makefile來編譯
== 4.1 產生Makefile ==
{{{
$ cd /home/waue/workspace/icas/
$ gedit Makefile
}}}
{{{
#!sh
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"
}}}
== 4.2. 執行 ==
{{{
$ cd /home/waue/workspace/icas/
$ make jar; make run; make output; make clean
}}}
== 4.3 screenshot ==
* 圖一： 完成後的eclipse視窗快照
[[Image(1.png)]]
------
* 圖二： 因為有設定完整的javadoc, 因此可以得到詳細的解說與輔助
[[Image(2.png)]]