环境：
Eclipse版本：MyEclipse6.5.1
Hadoop版本：hadoop-1.2.1
1.安装MyEclipse后，创建一个java项目
File->New->Java Project
输入项目名称，确定
2.导入hadoop所有包
解压hadoop-1.2.1.tar（E:softwaresharehadoop-1.2.1）
把E:softwaresharehadoop-1.2.1下
和E:softwaresharehadoop-1.2.1lib下的jar包都导入到项目里
方法如下：
点中项目根右键->Properties->JavaPath->Libraries->Add External JARs
3.确认jre为6.0以上版本
我的MyEclipse6.5.1版本开始默认使用jre5.0版本，因hadoop-1.2.1需要jre 6.0以上版本，所执行程序时报错：
Bad version number in .class file (unableto load class ***)
更改jre版本方法
Windows->Preference->Java->InstalledJREsàadd
4.修改FileUtil.java文件
这时在创建一个测试WordCount的mapreduce程序时，同样遇到了下面的问题
13/12/13 22:58:49 WARNutil.NativeCodeLoader: Unable to load native-hadoop library for yourplatform... using builtin-java classes where applicable
13/12/13 22:58:49 ERRORsecurity.UserGroupInformation:PriviledgedActionExceptionas:liczcause:java.io.IOException: Failed to set permissions of path:tmphadoop-liczmapredstaginglicz1853164772.staging to 0700
Exception in thread"main"java.io.IOException: Failed to set permissions of path:tmphadoop-liczmapredstaginglicz1853164772.staging to
......
解决办法：
修改E:softwaresharehadoop-1.2.1srccoreorgapachehadoopfsFileUtil.java文件
注释掉下面的内容
685 private static voidcheckReturnValue(boolean rv, File p,
686 FsPermission permission
687 ) throws IOException {
688 /*if (!rv) {
689 throw new IOException("Failed toset permissions of path: " p
690 " to "
691 String.format("o", permission.toShort()));
692 }*/
693 }
然后在Mapreduce1/scr新建一个org.apache.hadoop.fs包，把FileUtil.java文件拷到这个包的下面（在eclipse里直接粘贴就可以）
再次编译WordCount.java程序没有报错
import java.io.IOException; import java.util.Iterator; import java.util.StringTokenizer;
import org.apache.hadoop.fs.Path; import org.apache.hadoop.io.IntWritable; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapred.FileInputFormat; importorg.apache.hadoop.mapred.FileOutputFormat; importorg.apache.hadoop.mapred.JobClient; importorg.apache.hadoop.mapred.JobConf; import org.apache.hadoop.mapred.MapReduceBase; importorg.apache.hadoop.mapred.Mapper; importorg.apache.hadoop.mapred.OutputCollector; importorg.apache.hadoop.mapred.Reducer; importorg.apache.hadoop.mapred.Reporter; importorg.apache.hadoop.mapred.TextInputFormat; importorg.apache.hadoop.mapred.TextOutputFormat;
public class WordCount {
public static class WordCountMapper extends MapReduceBase implementsMapper<Object, Text, Text, IntWritable> { private final static IntWritable one = new IntWritable(1); private Text word = new Text();
public void map(Object key, Text value,OutputCollector<Text, IntWritable> output, Reporter reporter) throws IOException { StringTokenizer itr = newStringTokenizer(value.toString()); while (itr.hasMoreTokens()) { word.set(itr.nextToken()); output.collect(word, one); }
} }
public static class WordCountReducer extends MapReduceBase implementsReducer<Text, IntWritable, Text, IntWritable> { private IntWritable result = new IntWritable();
public void reduce(Text key, Iterator<IntWritable>values, OutputCollector<Text, IntWritable> output, Reporter reporter) throws IOException { int sum = 0; while (values.hasNext()) { sum =values.next().get(); } result.set(sum); output.collect(key, result); }
}
public static void main(String[] args) throws Exception { String input = "hdfs://192.168.2.100:9000/user/licz/hdfs/o_t_account"; String output = "hdfs://192.168.2.100:9000/user/licz/hdfs/o_t_account/result";
JobConf conf = new JobConf(WordCount.class); conf.setJobName("WordCount"); conf.addResource("classpath:/hadoop/core-site.xml"); conf.addResource("classpath:/hadoop/hdfs-site.xml"); conf.addResource("classpath:/hadoop/mapred-site.xml");
conf.setOutputKeyClass(Text.class); conf.setOutputValueClass(IntWritable.class);
conf.setMapperClass(WordCountMapper.class); conf.setCombinerClass(WordCountReducer.class); conf.setReducerClass(WordCountReducer.class);
conf.setInputFormat(TextInputFormat.class); conf.setOutputFormat(TextOutputFormat.class);
FileInputFormat.setInputPaths(conf, new Path(input)); FileOutputFormat.setOutputPath(conf,new Path(output));
JobClient.runJob(conf); System.exit(0); }
}
注意：
在windows上使用eclipse用户要与hadoop服务器上安装hadoop的用户名一致，这样才能正常运行，否则会出现没有权限创建目录的报错。
如hadoop安装在了linux服务器的licz用户下，我必需在windows的上的licz用户下使用eclipse开发程序。
这样，我们就可以在eclipse上开发mapreduce程序了。
