WordCount程序的目标是统计几个文件中每个单词出现的次数,是官方提供的示例程序,这里使用的hadoop的版本为hadoop-1.2.1。
1)、首先编写代码,将WordCount.java文件放到wordcount_classes文件夹中,代码如下:
import java.io.IOException; import java.util.*; import org.apache.hadoop.fs.Path; import org.apache.hadoop.conf.*; import org.apache.hadoop.io.*; import org.apache.hadoop.mapred.*; import org.apache.hadoop.util.*; public class WordCount { public static class Map extends MapReduceBase implements Mapper<LongWritable, Text, Text, IntWritable> { private final static IntWritable one = new IntWritable(1); private Text word = new Text(); public void map(LongWritable key, Text value,OutputCollector<Text, IntWritable> output, Reporter reporter) throws IOException { String line = value.toString(); StringTokenizer tokenizer = new StringTokenizer(line); while (tokenizer.hasMoreTokens()) { word.set(tokenizer.nextToken()); output.collect(word, one); } } } public static class Reduce extends MapReduceBase implements Reducer<Text, IntWritable, Text, 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(); } output.collect(key, new IntWritable(sum)); } } public static void main(String[] args) throws Exception { JobConf conf = new JobConf(WordCount.class); conf.setJobName("wordcount"); conf.setOutputKeyClass(Text.class); conf.setOutputValueClass(IntWritable.class); conf.setMapperClass(Map.class); conf.setCombinerClass(Reduce.class); conf.setReducerClass(Reduce.class); conf.setInputFormat(TextInputFormat.class); conf.setOutputFormat(TextOutputFormat.class); FileInputFormat.setInputPaths(conf, new Path(args[0])); FileOutputFormat.setOutputPath(conf, new Path(args[1])); JobClient.runJob(conf); } }
2)、编译代码并打成jar包,打jar包的时候别忘了后面的点号”.”,表示打包到当前文件夹:
$ javac –classpath ~/hadoop-1.2.1/hadoop-core-1.2.1.jar-dwordcount_classes ~/wordcount_classes/WordCount.java $ jar –cvf wordcount.jar -C wordcount_classes/.
成功后,将生成wordcount.jar文件
3)、在HDFS中新建输入文件的文件夹input,建好后使用-ls命令查看
$ bin/hadoop dfs –mkdir input $ bin/hadoop dfs –ls
4)、新建两个文本文件并上传至HDFS。在两个文件中分别输入一篇英文文章(随便找,或者输入几个单词即可),这里假设两个文件分别是file01和file02,使用以下命令将两个文件上传至HDFS中,file01 file02在input_files中:
$ bin/hadoop dfs -put ~/input_files/* input
5)、运行程序,查看结果,将结果输出到output中。
$ bin/hadoop jar~/wordcount_classes/wordcount.jar WordCount input output
结果如下(太长,只截取了一部分):
也可以使用下面的命令,将output文件下载下来查看
$ bin/hadoop dfs –get output output_local
output_local结构为:
示例程序结束,下面是HDFS常用的操作:
hadoop dfs -ls in 列出HDFS下某个文档中的文件
hadoop dfs -put test1.txt test 上传文件到指定目录并且重新命名,只有所有的DataNode都接收完数据才算成功
hadoop dfs -get in getin 从HDFS获取文件并且重新命名为getin,同put一样可操作文件也可操作目录
hadoop dfs -rmr out 删除指定文件从HDFS上
hadoop dfs -cat in/* 查看HDFS上in目录的内容
hadoop dfsadmin -report 查看HDFS的基本统计信息,结果如下
hadoop dfsadmin -safemode leave 退出安全模式
hadoop dfsadmin -safemode enter 进入安全模式