我在hadoop中遇到了WordCount程序的问题。单词计数不正确,它对所有单词显示0,但输出中存在所有不同的单词。
这是我的示例数据,加载到hdfs
# filename: file01.txt
Hello World Bye World
和
# filename: file02.txt
Hello Hadoop Bye Hadoop
这是来源:
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.mapred.*;
import java.io.IOException;
import java.util.*;
import org.apache.hadoop.io.*;
public class WordCount {
public static class Map
extends MapReduceBase
implements Mapper<LongWritable, Text, Text, IntWritable> {
private final static IntWritable one = new IntWritable();
private Text word = new Text();
public void map(LongWritable longWritable, 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 IOException {
JobConf jobConf = new JobConf(WordCount.class);
jobConf.setJobName("wordcount");
jobConf.setOutputKeyClass(Text.class);
jobConf.setOutputValueClass(IntWritable.class);
jobConf.setCombinerClass(WordCount.Reduce.class);
jobConf.setReducerClass(WordCount.Reduce.class);
jobConf.setMapperClass(WordCount.Map.class);
jobConf.setInputFormat(TextInputFormat.class);
jobConf.setOutputFormat(TextOutputFormat.class);
FileInputFormat.setInputPaths(jobConf, new Path(args[0]));
FileOutputFormat.setOutputPath(jobConf, new Path(args[1]));
JobClient.runJob(jobConf);
}
}
当我运行jar时,输出文件在输出文件夹中生成,但它显示以下内容:
$ bin/hdfs dfs -cat ./output/part-00000
17/11/09 02:50:39 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Bye 0
Hadoop 0
Hello 0
World 0
如您所见,所有计数均为零,但我无法在实施中找到错误的位置。
答案 0 :(得分:1)
是的,我已经尝试调试代码,错误发生在Map类
中 public static class Map
extends MapReduceBase
implements Mapper<LongWritable, Text, Text, IntWritable> {
private final static IntWritable one = new IntWritable();
private Text word = new Text();
public void map(LongWritable longWritable, 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);
}
}
}
由于您的Mapper类返回null(0)为Value,因此reducer无法减小值
这是代码
public static class Map extends MapReduceBase implements Mapper<LongWritable, Text, Text, IntWritable> {
private final static IntWritable one = new IntWritable();
private Text word = new Text();
public void map(LongWritable longWritable, 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());
one.set(1);
output.collect(word, one);
}
}
它会起作用....