我试图使用HADOOP MadReduce来计算所有权重的总和图形中每个节点的传入边。输入采用 .tsv 格式,如下所示:
SRC TGT 重量
X 102 1
X 200 1
X 123 5
Y 245 1
Y 101 1
Z 99 2
X 145 3
Y 24 1
A 21 5
. . .
. . .
预期输出为:
源总和(重量)
X 10
Y 3
Z 2
答 5
. .
. .
我使用了来自hadoop(http://www.cloudera.com/content/cloudera/en/documentation/hadoop-tutorial/CDH5/Hadoop-Tutorial/ht_wordcount1_source.html?scroll=topic_5_1)的WordCount示例代码作为参考。我尝试操纵代码,但我所有的努力都徒劳无功。
我对JAVA和HADOOP很陌生。我已经分享了我的代码。请帮我找出代码的问题。
谢谢。
法典:
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 Task1 {
public static class Map extends MapReduceBase implements Mapper<LongWritable, Text, Text, IntWritable> {
private final static IntWritable value_parsed = new IntWritable();
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);
Text keys = new Text();
int sum;
while(tokenizer.hasMoreTokens())
{
tokenizer.nextToken();
keys.set(tokenizer.nextToken());
sum = Integer.parseInt(tokenizer.nextToken());
output.collect(keys, new IntWritable(sum));
}
}
}
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(Task1.class);
conf.setJobName("Task1");
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);
}
}
改变一下你的代码。
while (tokenizer.hasMoreTokens()) {
tokenizer.nextToken(); // this value is of first column
keys.set(tokenizer.nextToken()); // this is wrong --you have to set
// first column as key not
// second column
sum = Integer.parseInt(tokenizer.nextToken()); // here
// third column
output.collect(keys, new IntWritable(sum));
}
希望这可以帮助您