Hadoop版Helloworld之wordcount运行示例
1.编写一个统计单词数量的java程序，并命名为wordcount.java，代码如下：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;
public>
public static>
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>
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();
Job job
= Job.getInstance(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(args));
FileOutputFormat.setOutputPath(job,
new Path(args));
System.exit(job.waitForCompletion(
true) ? 0 : 1);
}
}
2.声明java环境变量：
export JAVA_HOME=/usr/java/default
export PATH
=${JAVA_HOME}/bin:${PATH}
export HADOOP_CLASSPATH
=${JAVA_HOME}/lib/tools.jar
其中JAVA_HOME根据自己安装java的实际路径进行配置。
注意：如果不声明以上环境变量，那么在以后运行时，将会收到错误提示：
3.编译并创建jar包。
bin/hadoop com.sun.tools.javac.Main WordCount.java
jar cf wc.jar WordCount
*.class
4.运行第三步骤生成的wc.jar包。此时要注意，output文件夹不要手工创建，系统运行后会自动创建。
bin/hadoop jar wc.jar WordCount /user/root/wordcount/input /user/root/wordcount/output
正常运行结束后，会在outPut文件夹下生成part-r-00000及__SUCCESS两个文件，其中part-r-00000存储分析结果。运行命令：
bin/hadoop fs -cat /user/root/wordcount/output/part-r-00000
即可查看分析结果，如下图所示：
至此，本示例完成。
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