

准备 准备一些输入文件,可以用hdfs dfs -put xxx/*?/user/fatkun/input上传文件 代码 package com.fatkun;?import java.io.IOException;import java.util.ArrayList;import java.util.List;import java.util.StringTokenizer;?import org.apache.commons.lo
准备一些输入文件,可以用hdfs dfs -put xxx/*?/user/fatkun/input上传文件
package com.fatkun;
?
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;
import java.util.StringTokenizer;
?
import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
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.Tool;
import org.apache.hadoop.util.ToolRunner;
?
public class WordCount extends Configured implements Tool {
static enum Counters {
INPUT_WORDS // 计数器
}
?
static Log logger = LogFactory.getLog(WordCount.class);
?
public static class CountMapper extends
Mapper {
private final IntWritable one = new IntWritable(1);
private Text word = new Text();
private boolean caseSensitive = true;
?
@Override
protected void setup(Context context) throws IOException,
InterruptedException {
// 读取配置
Configuration conf = context.getConfiguration();
caseSensitive = conf.getBoolean("wordcount.case.sensitive", true);
super.setup(context);
}
?
@Override
protected void map(LongWritable key, Text value, Context context)
throws IOException, InterruptedException {
StringTokenizer itr = new StringTokenizer(value.toString());
while (itr.hasMoreTokens()) {
if (caseSensitive) { // 是否大小写敏感
word.set(itr.nextToken());
} else {
word.set(itr.nextToken().toLowerCase());
}
context.write(word, one);
context.getCounter(Counters.INPUT_WORDS).increment(1);
}
}
}
?
public static class CountReducer extends
Reducer {
?
@Override
protected void reduce(Text text, Iterable values,
Context context) throws IOException, InterruptedException {
int sum = 0;
for (IntWritable value : values) {
sum += value.get();
}
context.write(text, new IntWritable(sum));
}
?
}
?
@Override
public int run(String[] args) throws Exception {
Configuration conf = new Configuration(getConf());
Job job = Job.getInstance(conf, "Example Hadoop WordCount");
job.setJarByClass(WordCount.class);
job.setMapperClass(CountMapper.class);
job.setCombinerClass(CountReducer.class);
job.setReducerClass(CountReducer.class);
?
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
?
List other_args = new ArrayList();
for (int i = 0; i < args.length; ++i) {
other_args.add(args[i]);
}
?
FileInputFormat.addInputPath(job, new Path(other_args.get(0)));
FileOutputFormat.setOutputPath(job, new Path(other_args.get(1)));
int ret = job.waitForCompletion(true) ? 0 : 1;
?
long inputWord = job.getCounters().findCounter(Counters.INPUT_WORDS)
.getValue();
System.out.println("INPUT_WORDS:" + inputWord);
logger.info("test log: " + inputWord);
return ret;
}
?
public static void main(String[] args) throws Exception {
int res = ToolRunner.run(new Configuration(), new WordCount(), args);
?
System.exit(res);
}
?
}在eclipse导出jar包,执行以下命令
hadoop jar wordcount.jar com.fatkun.WordCount -Dwordcount.case.sensitive=false /user/fatkun/input /user/fatkun/output
http://cxwangyi.blogspot.com/2009/12/wordcount-tutorial-for-hadoop-0201.html
http://hadoop.apache.org/docs/r1.2.1/mapred_tutorial.html#Example%3A+WordCount+v2.0
原文地址:hadoop wordcount新API例子, 感谢原作者分享。
