Hadoop入门之Hadoop中的HelloWorld程序

在linux平台上执行wordcount，有官方示例，相应的jar包放在hadoop-2.0.0-cdh4.5.0\share\hadoop\mapreduce1下的hadoop-examples-2.0.0-mr1-cdh4.5.0.jar（注：本人用的是CDH4.5.0版本），我们首先需要准备好数据：

echo "Hello World Hello Hadoop" > 1.txtecho "Hello Hadoop Bye  " >2.txt

然后把数据put到HDFS里：

hadoop fs -mkdir /inputhadoop fs -put /root/1.txt /inputhadoop fs -put /root/2.txt /input

再然后进入到jar所在的目录里“

cd hadoop-2.0.0-cdh4.5.0\share\hadoop\mapreduce1

执行命令：

hadoop jar hadoop-mapreduce-examples-2.0.0-cdh4.5.0.jar WordCount /input /output

其中，/output是执行结果输出目录。

到此，HelloWorld就顺利执行了，你可以用hadoop fs -cat  /output/part 命令来查看结果.

接下来，我们在看看在window上的eclipse如何执行。

首先贴出代码：

public class WordCount {    // mapper    public static class Map extends Mapper<LongWritable, Text, Text, IntWritable> {        private static IntWritable one = new IntWritable(1);        private Text word = new Text();        @Override        public void map(LongWritable key, Text value, Context context) throws IOException,                InterruptedException {            String line = value.toString();            StringTokenizer token = new StringTokenizer(line);            while (token.hasMoreElements()) {                word.set(token.nextToken());                context.write(word, one);            }        };    }    // reduce    public static class Reduce extends Reducer<Text, IntWritable, Text, IntWritable> {        protected void reduce(Text key, Iterable<IntWritable> values, Context context)                throws IOException, InterruptedException {            int sum = 0;            for (IntWritable value : values) {                sum += value.get();            }            context.write(key, new IntWritable(sum));        };    }    public static void main(String[] args) throws Exception {        Configuration conf = new Configuration();        System.setProperty("HADOOP_USER_NAME", "root");//这句话很重要，要不然会告你没有权限执行        Job job = new Job(conf);                String[] ioArgs = new String[] { "hdfs://192.168.1.101:7001/input",                "hdfs://192.168.1.101:7001/output" };        String[] otherArgs = new GenericOptionsParser(conf, ioArgs).getRemainingArgs();        job.setJarByClass(WordCount.class);        FileInputFormat.addInputPath(job, new Path(otherArgs[0]));        FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));        job.setMapperClass(Map.class);        job.setReducerClass(Reduce.class);        job.setOutputKeyClass(Text.class);        job.setOutputValueClass(IntWritable.class);        System.exit(job.waitForCompletion(true) ? 0 : 1);    }}

然后在eclipse上点执行即可，在执行时可能发现jvm内存不够，添加-Xmx1024M参数执行即可。