错误的值类：类org.apache.hadoop.io.Text不是类org.apache.hadoop.io.IntWritable

我使用了一个mapper，一个reducer和一个combiner类，但是我得到的错误如下：

java.io.IOException: wrong value class: class org.apache.hadoop.io.Text is not class org.apache.hadoop.io.IntWritable at org.apache.hadoop.mapred.IFile$Writer.append(IFile.java:199) at org.apache.hadoop.mapred.Task$CombineOutputCollector.collect(Task.java:1307) at org.apache.hadoop.mapred.Task$NewCombinerRunner$OutputConverter.write(Task.java:1623) at org.apache.hadoop.mapreduce.task.TaskInputOutputContextImpl.write(TaskInputOutputContextImpl.java:89) at org.apache.hadoop.mapreduce.lib.reduce.WrappedReducer$Context.write(WrappedReducer.java:105) at BookPublished1$Combine.reduce(BookPublished1.java:47) at BookPublished1$Combine.reduce(BookPublished1.java:1) at org.apache.hadoop.mapreduce.Reducer.run(Reducer.java:171) at org.apache.hadoop.mapred.Task$NewCombinerRunner.combine(Task.java:1644) at org.apache.hadoop.mapred.MapTask$MapOutputBuffer.sortAndSpill(MapTask.java:1618) at org.apache.hadoop.mapred.MapTask$MapOutputBuffer.flush(MapTask.java:1467) at org.apache.hadoop.mapred.MapTask$NewOutputCollector.close(MapTask.java:699) at org.apache.hadoop.mapred.MapTask.runNewMapper(MapTask.java:769) at org.apache.hadoop.mapred.MapTask.run(MapTask.java:339) at org.apache.hadoop.mapred.YarnChild$2.run(YarnChild.java:162) at java.security.AccessController.doPrivileged(Native Method) at javax.security.auth.Subject.doAs(Subject.java:415) at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1491) at org.apache.hadoop.mapred.YarnChild.main(YarnChild.java:157) 

我的整个程序如下所示：

 import java.io.IOException; import org.apache.hadoop.io.FloatWritable; import org.apache.hadoop.io.IntWritable; import org.apache.hadoop.io.LongWritable; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapreduce.Mapper; import org.apache.hadoop.mapreduce.Reducer; import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.mapreduce.Job; import org.apache.hadoop.mapreduce.lib.input.TextInputFormat; import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat; import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; import org.apache.hadoop.fs.Path; public class BookPublished1 { public static class Map extends Mapper{ public void map(LongWritable key, Text value,Context context) throws IOException,InterruptedException { String line = value.toString(); String [] strYear = line.split(";"); context.write(new Text(strYear[3]), new IntWritable(1)); } } public static class Combine extends Reducer{ public void reduce(Text key, Iterable values,Context context) throws IOException,InterruptedException { int sum=0; // TODO Auto-generated method stub for(IntWritable x: values) { sum+=x.get(); } context.write(new Text("BookSummary"), new Text(key + "_"+ sum)); } } public static class Reduce extends Reducer{ public void reduce(Text key, Iterable values,Context context)throws IOException,InterruptedException { Long publishYear =0L, max=Long.MAX_VALUE; Text publishYear1 = null,maxYear=null; Long publishValue= 0L; String compositeString; String compositeStringArray[]; // TODO Auto-generated method stub for(Text x: values) { compositeString = x.toString(); compositeStringArray = compositeString.split("_"); publishYear1=new Text(compositeStringArray[0]); publishValue=new Long(compositeStringArray[1]); if(publishValue > max){ max=publishValue; maxYear=publishYear1; } } Text keyText= new Text("max" + " ( " + maxYear.toString() + ") : "); context.write(keyText, new FloatWritable(max)); } } public static void main(String[] args) throws Exception { Configuration conf= new Configuration(); Job job = new Job(conf,"BookPublished"); job.setJarByClass(BookPublished1.class); job.setMapperClass(Map.class); job.setReducerClass(Reduce.class); job.setCombinerClass(Combine.class); job.setMapOutputKeyClass(Text.class); job.setMapOutputValueClass(IntWritable.class); job.setOutputKeyClass(Text.class); job.setOutputValueClass(FloatWritable.class); job.setInputFormatClass(TextInputFormat.class); job.setOutputFormatClass(TextOutputFormat.class); Path outputPath = new Path(args[1]); FileInputFormat.addInputPath(job, new Path(args[0])); FileOutputFormat.setOutputPath(job, new Path(args[1])); outputPath.getFileSystem(conf).delete(outputPath); System.exit(job.waitForCompletion(true) ? 0 : 1); } } 

请帮我解决问题。

Answer 1

组合器的输出类型必须与映射器的输出类型匹配。 Hadoop不保证组合器应用的次数，或者甚至根本不应用。 这就是你的情况。

map（ ）中的值直接转到reduce，其中类型为 。