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我在Hadoop上实现PageRank算法，正如标题所示我想出了如下因素的错误，而试图执行该代码：从图中关键Hadoop执行错误：类型在映射键中不匹配：expected org.apache.hadoop.io.Text，收到org.apache.hadoop.io.LongWritable
类型不匹配：预计org.apache.hadoop.io.Text，收到org.apache.hadoop.io.LongWritable
在我的输入文件中，我将图形节点ID作为关键字和一些关于它们的信息存储为值。我的输入文件的格式如下：
1 \ t 3.4,2,5,6,67
4 \ t 4.2,77,2,7,83
... ..
试图了解错误说什么我尝试使用LongWritable作为我的主变量类型，如下面的代码中所示。这意味着我有：
地图< LongWritable，LongWritable，LongWritable，LongWritable>
减少< LongWritable，LongWritable，LongWritable，LongWritable>
而且，我也试过：
地图<文本，文本，文本，文本>
减少<文本，文本，文本，文本>
也：
地图< LongWritable，文本，LongWritable，文字>
减少< LongWritable，文本，LongWritable，文字>
，我总是拿出同样的错误。我想我很难理解错误中期望和接受的方式。这是否意味着我的地图函数期望从我的输入文件中获得LongWritable，并且它具有Text？我使用的输入文件格式或变量类型有问题吗？
下面是完整的代码，你能告诉我什么改变在哪里？：
import java.io.IOException;
import java.util.*;
import java.util.regex.Matcher;
import java.util.regex.Pattern;
import java.lang.Object.*;
import org.apache.commons.cli.ParseException;
import org.apache.commons.lang.StringUtils;
import org.apache.commons.configuration.Configuration;
import org.apache.hadoop.security.Credentials;
import org.apache.log4j.*;
import org.apache.commons.logging.*;
import org.apache.hadoop.mapred.*;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.DoubleWritable;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.JobContext;
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.input.SequenceFileInputFormat;
import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
import org.apache.hadoop.mapreduce.lib.output.SequenceFileOutputFormat;
import org.apache.hadoop.util.GenericOptionsParser;
public class Pagerank
{
public static class PRMap extends Mapper<LongWritable, LongWritable, LongWritable, LongWritable>
{
public void map(LongWritable lineNum, LongWritable line, OutputCollector<LongWritable, LongWritable> outputCollector, Reporter reporter) throws IOException, InterruptedException
{
if (line.toString().length() == 0) {
return;
}
Text key = new Text();
Text value = new Text();
LongWritable valuel = new LongWritable();
StringTokenizer spline = new StringTokenizer(line.toString(),"\t");
key.set(spline.nextToken());
value.set(spline.nextToken());
valuel.set(Long.parseLong(value.toString()));
outputCollector.collect(lineNum,valuel);
String info = value.toString();
String splitter[] = info.split(",");
if(splitter.length >= 3)
{
float f = Float.parseFloat(splitter[0]);
float pagerank = f/(splitter.length - 2);
for(int i=2;i<splitter.length;i++)
{
LongWritable key2 = new LongWritable();
LongWritable value2 = new LongWritable();
long l;
l = Long.parseLong(splitter[i]);
key2.set(l);
//key2.set(splitter[i]);
value2.set((long)f);
outputCollector.collect(key2, value2);
}
}
}
}
public static class PRReduce extends Reducer<LongWritable,LongWritable,LongWritable,LongWritable>
{
private Text result = new Text();
public void reduce(LongWritable key, Iterator<LongWritable> values,OutputCollector<LongWritable, LongWritable> results, Reporter reporter) throws IOException, InterruptedException
{
float pagerank = 0;
String allinone = ",";
while(values.hasNext())
{
LongWritable temp = values.next();
String converted = temp.toString();
String[] splitted = converted.split(",");
if(splitted.length > 1)
{
for(int i=1;i<splitted.length;i++)
{
allinone = allinone.concat(splitted[i]);
if(i != splitted.length - 1)
allinone = allinone.concat(",");
}
}
else
{
float f = Float.parseFloat(splitted[0]);
pagerank = pagerank + f;
}
}
String last = Float.toString(pagerank);
last = last.concat(allinone);
LongWritable value = new LongWritable();
value.set(Long.parseLong(last));
results.collect(key, value);
}
}
public static void main(String[] args) throws Exception
{
org.apache.hadoop.conf.Configuration conf = new org.apache.hadoop.conf.Configuration();
String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
if (otherArgs.length != 2) {
System.err.println("Usage: wordcount <in> <out>");
System.exit(2);
}
Job job = new Job(conf, "pagerank_itr0");
job.setJarByClass(Pagerank.class);
job.setMapperClass(Pagerank.PRMap.class);
job.setReducerClass(Pagerank.PRReduce.class);
job.setOutputKeyClass(LongWritable.class);
job.setOutputValueClass(LongWritable.class);
FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));
job.waitForCompletion(true);
}
}