WholeFileRecordReader无法强制转换为org.apache.hadoop.mapred.RecordReader

时间:2014-06-10 13:58:24

标签: hadoop map casting

我想在Hadoop中创建一个新的数据类型但是我的自定义inputformat类出现以下错误这是我的代码:

错误 - 无法将WholeFileRecordReader强制转换为org.apache.hadoop.mapred.RecordReader

代码 -

import java.io.IOException;

import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.FileInputFormat;
import org.apache.hadoop.mapred.FileSplit;
import org.apache.hadoop.mapred.InputSplit;
import org.apache.hadoop.mapred.JobConf;
import org.apache.hadoop.mapred.RecordReader;
import org.apache.hadoop.mapred.Reporter;
import org.apache.hadoop.mapred.TaskAttemptContext;



 public class wholeFileInputFormat extends FileInputFormat<Text, apriori>{

public RecordReader<Text, apriori> getRecordReader(
          InputSplit input, JobConf job, Reporter reporter)
          throws IOException {

        reporter.setStatus(input.toString());

    return (RecordReader<Text, apriori>) new WholeFileRecordReader(job,FileSplit)input);

      }

}

我的自定义记录阅读器如下

import java.io.FileInputStream;
import java.io.FileNotFoundException;
import java.io.IOException;
import java.io.InputStream;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IOUtils;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.FileSplit;
import org.apache.hadoop.mapred.JobConf;
import org.apache.hadoop.mapreduce.InputSplit;
import org.apache.hadoop.mapreduce.RecordReader;
import org.apache.hadoop.mapreduce.TaskAttemptContext;

 class WholeFileRecordReader extends RecordReader<Text, apriori> {


private FileSplit fileSplit;
private Configuration conf;
private InputStream in;
private Text key = new Text("");
private apriori value = new apriori();
private boolean processed = false;


public void initialize( JobConf job, FileSplit split)
        throws IOException {

    this.fileSplit = split;
    this.conf = job;
    final Path file = fileSplit.getPath();
    String StringPath = new String(fileSplit.getPath().toString());
    String StringPath2 = new String();
    StringPath2 = StringPath.substring(5);
    System.out.println(StringPath2);
    in = new FileInputStream(StringPath2);

    FileSystem fs = file.getFileSystem(conf);
    in = fs.open(file);
    }


public boolean nextKeyValue() throws IOException, InterruptedException {
    if (!processed) {
        byte[] contents = new byte[(int) fileSplit.getLength()];
        Path file = fileSplit.getPath();
        key.set(file.getName());

        try {
            IOUtils.readFully(in, contents, 0, contents.length);
            value.set(contents, 0, contents.length);
        } finally {
            IOUtils.closeStream(in);
        }

        processed = true;
        return true;
    }

    return false;
}

@Override
public Text getCurrentKey() throws IOException, InterruptedException {
    return key;
}

@Override
public apriori getCurrentValue() throws IOException, InterruptedException {
    return value;
}

@Override
public float getProgress() throws IOException {
    return processed ? 1.0f : 0.0f;
}

@Override
public void close() throws IOException {
    // Do nothing
}

@Override
public void initialize(InputSplit arg0, TaskAttemptContext arg1)
        throws IOException, InterruptedException {
    // TODO Auto-generated method stub

}

} 

2 个答案:

答案 0 :(得分:0)

WholeFileRecordReader类是org.apache.hadoop.mapreduce.RecordReader类的子类。此类无法强制转换为org.apache.hadoop.mapred.RecordReader类。可以尝试在两个类中使用相同的API

根据Java编程语言的规则,只能将相同类型层次结构中的类或接口(统称为Type)转换或相互转换。如果您尝试转换两个不共享相同类型层次结构的对象,即它们之间没有父子关系,则会出现编译时错误。您可以参考此link

答案 1 :(得分:0)

由于此错误即将发生包裹不匹配。

在您的代码中,您合并了MRv1和MRv2,因为您收到错误。

org.apache.hadoop.mapred是Mrv1。 (Map Reduce版本1)

org.apache.hadoop.mapreduce是Mrv2。 (Map Reduce version 2)

在您的代码中,您结合了MRv1和MRv2:

import org.apache.hadoop.mapred.FileSplit;

import org.apache.hadoop.mapred.JobConf;

import org.apache.hadoop.mapreduce.InputSplit;

import org.apache.hadoop.mapreduce.RecordReader;

import org.apache.hadoop.mapreduce.TaskAttemptContext;

将所有导入包用作org.apache.hadoop.mapred(MRv1)或org.apache.hadoop.mapreduce(MRv2)。

希望这有帮助。