= 用Eclipse製成可在Hadoop上運行MapReduce的jar檔 =

 ps : 需eclipse 3.3 以上 搭配 hadoop 0.17 以上版本。
 * 本篇的安裝環境是

 || 名稱 || 目錄 ||
 || Hadoop 安裝目錄 || /opt/hadoop ||
 || 來源資料夾 || /opt/hadoop/input ||
 || 輸出資料夾 || /opt/hadoop/output ||

 1. 開啟MapReduce 專案

 || 視窗操作 || 介面中設定 || 註解 || 
 || '''File''' > '''new''' > '''Map/Reduce Project'''>'''next''' || '''Project name''':''sample'' [[br]] '''Configure Hadoop install directory''': /opt/hadoop [[br]] => '''Finish''' || 完成會增加sample專案並切換成MapReduce的視野 || 

 2. 加入檔案WordCount.java檔

 || 視窗操作 || 介面中設定 || 結果 || 
 || 右鍵點選sample專案 > '''new''' > '''file'''   || sample >'''src''' [[br]] '''File Name''': WordCount.java [[br]] => '''Finish''' || 完成後就多了一個WordCount.java檔 || 

 3. 寫入WordCount.java的內容（[wiki:WordCount code]）

 4. 執行

 || 視窗操作 || 介面中設定 || 結果 || 
 || '''run''' > '''Run Configurations...''' || '''Main''' tag :[[br]] '''Name''': '''WordCount''' [[br]] '''Project''': sample [[br]] '''Main class:''': WordCount ;'''Arguments''' tag : [[br]] '''Program arguments''': /opt/hadoop/log /opt/hadoop/test2 => '''Apply''' => '''Run''' || console 介面會出現執行結果 || 

 * Eclipse是用模擬的方式模擬Hadoop的環境，執行這段程式碼，所以並沒有送上HDFS給Hadoop的job tracker作Map Reduce。http://localhost:50030 沒有工作運作的紀錄可以證明這點。
   * 既然是在本機端上運作，所以給的Program arguments參數 '''/opt/hadoop/input /opt/hadoop/output''' 是本機上的目錄。
   * 請確認 input 資料夾內有純文字資料，且output資料夾尚未存在（執行後系統會自行建立此資料夾並將結果放入）
 * 若Console 介面沒有錯誤訊息，則代表這段程式在主機端運作無誤
{{{
09/02/06 17:18:35 INFO jvm.JvmMetrics: Initializing JVM Metrics with processName=JobTracker, sessionId=
09/02/06 17:18:35 WARN mapred.JobClient: Use GenericOptionsParser for parsing the arguments. Applications should implement Tool for the same.
09/02/06 17:18:35 WARN mapred.JobClient: No job jar file set.  User classes may not be found. See JobConf(Class) or JobConf#setJar(String).
09/02/06 17:18:35 INFO mapred.FileInputFormat: Total input paths to process : 1

... 略 ...

09/02/06 17:18:36 INFO mapred.JobClient:     Map output bytes=445846
09/02/06 17:18:36 INFO mapred.JobClient:     Map input bytes=320950
09/02/06 17:18:36 INFO mapred.JobClient:     Combine input records=37943
09/02/06 17:18:36 INFO mapred.JobClient:     Map output records=37943
09/02/06 17:18:36 INFO mapred.JobClient:     Reduce input records=9284
}}}

 錯誤排除 ： 

 * input 資料夾內有純文字資料
 * output 資料夾尚未存在（執行後系統會自行建立此資料夾並將結果放入）
 * 檢查"run configuration" 內的 "Java Application" > "WordCount" 的設定是否正確

 5. 打包成JAR

 || 視窗操作 || 介面中設定 || 結果 || 
 || '''File''' > '''Export''' > Java > Runnable JAR file ||  ''' Launch configuration''' : '''WordCount - sample''' [[br]] '''Export destionation''' : /opt/hadoop/WordCount.jar => Finish => ok ||/opt/hadoop/下可以找到檔案WordCount.jar ||

 * 最後一個ok在於包入Hadoop的必要library，所以匯出的WordCount.jar 檔大約有4.3MB

 6. 運行WordCount於HDFS之上

指令：
{{{
$ cd /opt/hadoop
$ bin/hadoop jar WordCount.jar /user/waue/input /user/waue/out/
}}}

 * bin/hadoop jar 不可用 '''-jar'''，但若是單純用java執行jar， 則要用'''$ java -jar XXX.jar'''，不可只用jar
 * /user/waue/input /user/waue/out/ 為輸入和輸出的兩個參數，這兩個路徑是HDFS上得路徑，請確認hdfs內的/user/waue/input有純文字檔，且無/user/waue/out/這個資料夾。
 * 若已經成功執行過，想再執行第二次，請更換output的資料夾名稱，否則會因資料夾已存在而出現錯誤訊息。

執行畫面
{{{
09/02/06 18:13:14 WARN mapred.JobClient: Use GenericOptionsParser for parsing the arguments. Applications should implement Tool for the same.
09/02/06 18:13:14 INFO mapred.FileInputFormat: Total input paths to process : 1
09/02/06 18:13:14 INFO mapred.FileInputFormat: Total input paths to process : 1
09/02/06 18:13:15 INFO mapred.JobClient: Running job: job_200902051032_0009
09/02/06 18:13:16 INFO mapred.JobClient:  map 0% reduce 0%
09/02/06 18:13:20 INFO mapred.JobClient:  map 100% reduce 0%
09/02/06 18:13:23 INFO mapred.JobClient: Job complete: job_200902051032_0009
09/02/06 18:13:23 INFO mapred.JobClient: Counters: 16
09/02/06 18:13:23 INFO mapred.JobClient:   File Systems
09/02/06 18:13:23 INFO mapred.JobClient:     HDFS bytes read=320950
09/02/06 18:13:23 INFO mapred.JobClient:     HDFS bytes written=130568
09/02/06 18:13:23 INFO mapred.JobClient:     Local bytes read=168448
09/02/06 18:13:23 INFO mapred.JobClient:     Local bytes written=336932
09/02/06 18:13:23 INFO mapred.JobClient:   Job Counters 
09/02/06 18:13:23 INFO mapred.JobClient:     Launched reduce tasks=1
09/02/06 18:13:23 INFO mapred.JobClient:     Launched map tasks=1
09/02/06 18:13:23 INFO mapred.JobClient:     Data-local map tasks=1
09/02/06 18:13:23 INFO mapred.JobClient:   Map-Reduce Framework
09/02/06 18:13:23 INFO mapred.JobClient:     Reduce input groups=9284
09/02/06 18:13:23 INFO mapred.JobClient:     Combine output records=18568
09/02/06 18:13:23 INFO mapred.JobClient:     Map input records=7868
09/02/06 18:13:23 INFO mapred.JobClient:     Reduce output records=9284
09/02/06 18:13:23 INFO mapred.JobClient:     Map output bytes=445846
09/02/06 18:13:23 INFO mapred.JobClient:     Map input bytes=320950
09/02/06 18:13:23 INFO mapred.JobClient:     Combine input records=47227
09/02/06 18:13:23 INFO mapred.JobClient:     Map output records=37943
09/02/06 18:13:23 INFO mapred.JobClient:     Reduce input records=9284
}}}

 * http://localhost:50030 會紀錄剛剛運作的工作