基於Eclipse的Hadoop開發環境配置方法

（1）啓動hadoop守護進程

在Terminal中輸入如下命令：

$ bin/hadoop namenode -format

$ bin/start-all.sh

（2）在Eclipse上安裝Hadoop插件

找到hadoop的安裝路徑，我的是hadoop-0.20.2，將/home/wenqisun/hadoop-0.20.2/contrib/eclipse-plugin/下的hadoop-0.20.2- eclipse-plugin.jar拷貝到eclipse安裝目錄下的plugins裏，我的是在/home/wenqisun/eclipse /plugins/下。

然後重啓eclipse，點擊主菜單上的window-->preferences，在左邊欄中找到Hadoop Map/Reduce，點擊後在右邊對話框裏設置hadoop的安裝路徑即主目錄，我的是/home/wenqisun/hadoop-0.20.2。

（3）配置Map/Reduce Locations

在Window-->Show View中打開Map/Reduce Locations。
在Map/Reduce Locations中New一個Hadoop Location。
在打開的對話框中配置Location name（爲任意的名字）。
配置Map/Reduce Master和DFS Master，這裏的Host和Port要和已經配置的mapred-site.xml 和core-site.xml相一致。
一般情況下爲
Map/Reduce Master
Host： localhost
Port： 9001
DFS Master
Host： localhost
Port： 9000
配置完成後，點擊Finish。如配置成功，在DFS Locations中將顯示出新配置的文件夾。

（4）新建項目

創建一個MapReduce Project，點擊eclipse主菜單上的File-->New-->Project，在彈出的對話框中選擇Map/Reduce Project，之後輸入Project的名，例如Q1，確定即可。然後就可以新建Java類，比如可以創建一個WordCount 類，然後將你安裝的hadoop程序裏的WordCount源程序代碼（版本不同會有區別），我的是在/home/wenqisun/hadoop-0.20.2/src /examples/org/apache/hadoop/examples/WordCount.java，寫到此類中。以下是WordCount的源代碼：

import java.io.IOException;
import java.util.StringTokenizer;

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.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
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 class TokenizerMapper 
       extends Mapper<Object, Text, Text, IntWritable>{
    
    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);
      }
    }
  }
  
  public static class IntSumReducer 
       extends Reducer<Text,IntWritable,Text,IntWritable> {
    private IntWritable result = new IntWritable();

    public void reduce(Text key, Iterable<IntWritable> values, 
                       Context context
                       ) throws IOException, InterruptedException {
      int sum = 0;
      for (IntWritable val : values) {
        sum += val.get();
      }
      result.set(sum);
      context.write(key, result);
    }
  }

  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 <in> <out>");
      System.exit(2);
    }
    Job job = new Job(conf, "word count");
    job.setJarByClass(WordCount.class);
    job.setMapperClass(TokenizerMapper.class);
    job.setCombinerClass(IntSumReducer.class);
    job.setReducerClass(IntSumReducer.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);
  }
}

（5）配置參數

點擊Run-->Run Configurations，在彈出的對話框中左邊欄選擇Java Application，點擊右鍵New，在右邊欄中對Arguments進行配置。

在Program arguments中配置輸入輸出目錄參數

/home/wenqisun/in /home/wenqisun/out

這裏的路徑是文件存儲的路徑。

在VM arguments中配置VM arguments的參數

-Xms512m -Xmx1024m -XX:MaxPermSize=256m

注意：

in文件夾是需要在程序運行前創建的，out文件夾是不能提前創建的，要由系統自動生成，否則運行時會出現錯誤。

（6）點擊Run運行程序

程序的運行結果可在out目錄下進行查看。

在Console中可以查看到的運行過程爲：

12/04/07 06:21:00 INFO jvm.JvmMetrics: Initializing JVM Metrics with processName=JobTracker, sessionId=
12/04/07 06:21:00 WARN mapred.JobClient: No job jar file set. User classes may not be found. See JobConf(Class) or JobConf#setJar(String).
12/04/07 06:21:00 INFO input.FileInputFormat: Total input paths to process : 2
12/04/07 06:21:01 INFO mapred.JobClient: Running job: job_local_0001
12/04/07 06:21:01 INFO input.FileInputFormat: Total input paths to process : 2
12/04/07 06:21:02 INFO mapred.MapTask: io.sort.mb = 100
12/04/07 06:21:30 INFO mapred.MapTask: data buffer = 79691776/99614720
12/04/07 06:21:30 INFO mapred.MapTask: record buffer = 262144/327680
12/04/07 06:21:32 INFO mapred.JobClient: map 0% reduce 0%
12/04/07 06:21:34 INFO mapred.MapTask: Starting flush of map output
12/04/07 06:21:40 INFO mapred.LocalJobRunner:
12/04/07 06:21:40 INFO mapred.MapTask: Finished spill 0
12/04/07 06:21:40 INFO mapred.JobClient: map 100% reduce 0%
12/04/07 06:21:40 INFO mapred.TaskRunner: Task:attempt_local_0001_m_000000_0 is done. And is in the process of commiting
12/04/07 06:21:40 INFO mapred.LocalJobRunner:
12/04/07 06:21:40 INFO mapred.TaskRunner: Task 'attempt_local_0001_m_000000_0' done.
12/04/07 06:21:44 INFO mapred.MapTask: io.sort.mb = 100
12/04/07 06:22:00 INFO mapred.MapTask: data buffer = 79691776/99614720
12/04/07 06:22:00 INFO mapred.MapTask: record buffer = 262144/327680
12/04/07 06:22:03 INFO mapred.MapTask: Starting flush of map output
12/04/07 06:22:03 INFO mapred.MapTask: Finished spill 0
12/04/07 06:22:03 INFO mapred.TaskRunner: Task:attempt_local_0001_m_000001_0 is done. And is in the process of commiting
12/04/07 06:22:03 INFO mapred.LocalJobRunner:
12/04/07 06:22:03 INFO mapred.TaskRunner: Task 'attempt_local_0001_m_000001_0' done.
12/04/07 06:22:04 INFO mapred.LocalJobRunner:
12/04/07 06:22:04 INFO mapred.Merger: Merging 2 sorted segments
12/04/07 06:22:05 INFO mapred.Merger: Down to the last merge-pass, with 2 segments left of total size: 86 bytes
12/04/07 06:22:05 INFO mapred.LocalJobRunner:
12/04/07 06:22:08 INFO mapred.TaskRunner: Task:attempt_local_0001_r_000000_0 is done. And is in the process of commiting
12/04/07 06:22:08 INFO mapred.LocalJobRunner:
12/04/07 06:22:08 INFO mapred.TaskRunner: Task attempt_local_0001_r_000000_0 is allowed to commit now
12/04/07 06:22:08 INFO output.FileOutputCommitter: Saved output of task 'attempt_local_0001_r_000000_0' to /home/wenqisun/out
12/04/07 06:22:08 INFO mapred.LocalJobRunner: reduce > reduce
12/04/07 06:22:08 INFO mapred.TaskRunner: Task 'attempt_local_0001_r_000000_0' done.
12/04/07 06:22:08 INFO mapred.JobClient: map 100% reduce 100%
12/04/07 06:22:09 INFO mapred.JobClient: Job complete: job_local_0001
12/04/07 06:22:09 INFO mapred.JobClient: Counters: 12
12/04/07 06:22:09 INFO mapred.JobClient: FileSystemCounters
12/04/07 06:22:09 INFO mapred.JobClient: FILE_BYTES_READ=39840
12/04/07 06:22:09 INFO mapred.JobClient: FILE_BYTES_WRITTEN=80973
12/04/07 06:22:09 INFO mapred.JobClient: Map-Reduce Framework
12/04/07 06:22:09 INFO mapred.JobClient: Reduce input groups=5
12/04/07 06:22:09 INFO mapred.JobClient: Combine output records=7
12/04/07 06:22:09 INFO mapred.JobClient: Map input records=4
12/04/07 06:22:09 INFO mapred.JobClient: Reduce shuffle bytes=0
12/04/07 06:22:09 INFO mapred.JobClient: Reduce output records=5
12/04/07 06:22:09 INFO mapred.JobClient: Spilled Records=14
12/04/07 06:22:09 INFO mapred.JobClient: Map output bytes=78
12/04/07 06:22:10 INFO mapred.JobClient: Combine input records=8
12/04/07 06:22:10 INFO mapred.JobClient: Map output records=8
12/04/07 06:22:10 INFO mapred.JobClient: Reduce input records=7

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