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實作八 Lab 8

在完全分散模式下編譯 MapReduce 程式
Compiling Hadoop MapReduce Java Program in Hadoop Cluster

以下練習，請連線至 hadoop.3du.me 操作。底下的 userXX 等於您的用戶名稱。

Practice 1 : Word Count (Basic)

• 上傳內容到 HDFS 內
  upload data to HDFS

  $ mkdir lab8_input
  $ echo "I like NCTU Cloud Course." > lab8_input/input1
  $ echo "I like nctu Cloud Course, and we enjoy this course." > lab8_input/input2
  $ hadoop fs -put lab8_input lab8_input
  $ hadoop fs -ls lab8_input
  Found 2 items
  -rw-r--r--   2 hXXXX supergroup         26 2011-04-19 10:07 /user/hXXXX/lab8_input/input1
  -rw-r--r--   2 hXXXX supergroup         52 2011-04-19 10:07 /user/hXXXX/lab8_input/input2
  

• 下載 ​WordCount.java 並存到家目錄;
  Download ​WordCount.java and save to your home directory

  ~$ wget http://www.classcloud.org/hadoop4win/WordCount.java
  

• 運作程式
  Compile WordCount.java and run it by hadoop jar command

$ mkdir MyJava
$ ln -s /opt/hadoop/hadoop-*-core.jar hadoop-core.jar
$ javac -classpath hadoop-core.jar -d MyJava WordCount.java
$ jar -cvf wordcount.jar -C MyJava .
$ hadoop jar wordcount.jar WordCount lab8_input/ lab8_out1/
$ hadoop fs -cat lab8_out1/part-00000

• lab8_out1 執行結果
  You should see results like this :

  Cloud 2
  Course, 1
  Course. 1
  I 2
  NCTU  1
  and 1
  course. 1
  enjoy 1
  like  2
  nctu  1
  this  1
  we  1
  

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