使用mapreduce的第二大薪水-输出与预期不符

时间:2018-06-24 04:32:07

标签: java hadoop mapreduce hadoop2

我写了一个小的mapreduce作业来查找数据集中第二高的薪水。我相信第二个最高薪水逻辑是正确的。但是我得到了多个不正确的输出,应该只有一个名称为John的输出,例如9000。而且输出也不正确,这里我给出了数据集和代码

hh,0,Jeet,3000
hk,1,Mayukh,4000
nn,2,Antara,3500
mm,3,Shubu,6000
ii,4,Parsi,8000  

输出应该是Shubu,6000,但是我得到的是下面的输出

  Antara    -2147483648
  Mayukh    -2147483648
  Parsi      3500
  Shubu      4000

我正在使用的代码是

 public class SecondHigestMapper extends Mapper<LongWritable,Text,Text,Text>{

private Text salary = new Text();
private Text name = new Text();
public void map(LongWritable key,Text value,Context context) throws IOException, InterruptedException{

    if(key.get()!=0){
        String split[]= value.toString().split(",");
        salary.set(split[2]+";"+split[3]);
        name.set("ignore");
        context.write(name,salary);
    }
}
}


 public class SecondHigestReducer extends Reducer<Text,Text,Text,IntWritable>{

public void reduce(Text key,Iterable<Text> values,Context context) throws IOException, InterruptedException{
    int highest = 0;
    int second_highest = 0;
    int salary;

    for(Text val:values){
        String[] fn = val.toString().split("\\;");
        salary = Integer.parseInt(fn[3]);

        if(highest < salary){
              second_highest = highest;
              highest =salary;
         } else if(second_highest < salary){
              second_highest = salary;
        }
    }
    String seconHigest = String.valueOf(second_highest);
    context.write(new Text(key),new Text(seconHigest));

}

 }

public class SecondHigestDriver {

public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
    Configuration conf = new Configuration();
    Job job = new Job(conf,"Second Higest Sal");
    job.setJarByClass(SecondHigestDriver.class);
    job.setMapperClass(SecondHigestMapper.class);
    job.setCombinerClass(SecondHigestReducer.class);
    job.setReducerClass(SecondHigestReducer.class);
    job.setOutputKeyClass(Text.class);
    job.setMapOutputValueClass(Text.class);
    FileInputFormat.addInputPath(job, new Path(args[0]));
    FileOutputFormat.setOutputPath(job, new Path(args[1]));
    System.exit(job.waitForCompletion(true) ? 0 : 1);

}
   }

我低于例外

  Error: java.io.IOException: Type mismatch in value from map: expected org.apache.hadoop.io.IntWritable, received org.apache.hadoop.io.Text
at org.apache.hadoop.mapred.MapTask$MapOutputBuffer.collect(MapTask.java:1074)
at org.apache.hadoop.mapred.MapTask$NewOutputCollector.write(MapTask.java:712)
at org.apache.hadoop.mapreduce.task.TaskInputOutputContextImpl.write(TaskInputOutputContextImpl.java:89)
at org.apache.hadoop.mapreduce.lib.map.WrappedMapper$Context.write(WrappedMapper.java:112)
at com.jeet.secondhigest.SecondHigestMapper.map(SecondHigestMapper.java:20)
at com.jeet.secondhigest.SecondHigestMapper.map(SecondHigestMapper.java:1)
at org.apache.hadoop.mapreduce.Mapper.run(Mapper.java:145)
at org.apache.hadoop.mapred.MapTask.runNewMapper(MapTask.java:784)
at org.apache.hadoop.mapred.MapTask.run(MapTask.java:341)
at org.apache.hadoop.mapred.YarnChild$2.run(YarnChild.java:168)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1642)
at org.apache.hadoop.mapred.YarnChild.main(YarnChild.java:163)

请帮助我解决这个问题

1 个答案:

答案 0 :(得分:1)

使用单个键将所有薪水强制到一个简化器中

name.set("ignore");  // Could use a NullWritable 
salary.set(split[2]+";"+split[3])); // change to TextWritable 
context.write(name,salary);  // need to change the signature of the mapper class 

然后在化简器中,更改方法以接受文本值,然后将其拆分,转换薪水,然后进行比较