无法将Partitoner设置为JobConf对象 [英] Unable to set partitoner to the JobConf object

问题描述

我写了一个自定义分区器，但无法将其设置为主类中的 JobConf 对象。

  import org.apache.hadoop.io.Text; 
 import org.apache.hadoop.mapreduce.Partitioner; 
 
公共类FirstCharTextPartitioner扩展了分区器<文本，文本> {
 
 @Override 
 public int getPartition（Text key，Text value，int numReduceTasks）{
 return（key.toString（）。charAt（0））％numReduceTasks; 
 
 
  

但是当我尝试将它设置为 JobConf 对象，我得到以下错误。

JobConf类型的方法setPartitionerClass（Class）不适用于参数（Class）

  public class WordCount {
 
 public static class Map扩展MapReduceBase实现Mapper< LongWritable，文字，文字，IntWritable> {
 private static static IntWritable one = new IntWritable（1）; 
私人文字=新文字（）; 
 $ b $ public void map（LongWritable key，Text value，OutputCollector< Text，IntWritable> output，Reporter reporter）throws IOException {
 String line = value.toString（）; 
 String [] tokens = line.split（\\s）; 
 for（String token：tokens）{
 word.set（token）; 
 output.collect（word，one）; 
 
 
 
 $ b 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（WordCount.class）; 
 conf.setJobName（wordcount）; 
 
 conf.setOutputKeyClass（Text.class）; 
 conf.setOutputValueClass（IntWritable.class）; 
 
 conf.setMapperClass（Map.class）; 
 conf.setCombinerClass（Reduce.class）; 
 conf.setReducerClass（Reduce.class）; 
 conf.setPartitionerClass（FirstCharTextPartitioner.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）; 
 
 
 
 
 
 
 $ b 
有人可以告诉我我做错了什么吗？ 
解决方案
您正在导入新  org.apache.hadoop.mapreduce .Partitioner 。  
 
 
您需要实现旧接口 org.apache.hadoop.mapred.Partitioner ，如下所示： p> 
 
 
  import org.apache.hadoop.io.Text; 
 import org.apache.hadoop.mapred.Partitioner; 
 
公共类FirstCharTextPartitioner实现分区程序<文本，文本> {
 
 @Override 
 public int getPartition（Text key，Text value，int numReduceTasks）{
 return（key.toString（）。charAt（0））％numReduceTasks; 
} 
} 
  
 
I wrote a custom partitioner but am unable to set it to the JobConf object in the main class.
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Partitioner;

public class FirstCharTextPartitioner extends Partitioner<Text, Text> {

    @Override
    public int getPartition(Text key, Text value, int numReduceTasks) {
        return (key.toString().charAt(0)) % numReduceTasks;
    }    
}
But when I try to set this to the JobConf object, I get the following error.

The method setPartitionerClass(Class) in the type JobConf is not applicable for the arguments (Class)
public class WordCount {

    public static class Map extends MapReduceBase implements Mapper<LongWritable, Text, Text, IntWritable> {
        private final static IntWritable one = new IntWritable(1); 
        private Text word = new Text();

        public void map(LongWritable key, Text value, OutputCollector<Text, IntWritable> output, Reporter reporter) throws IOException {
            String line = value.toString();
            String[] tokens = line.split("\\s");
            for (String token : tokens) {
                word.set(token);
                output.collect(word, one);
            }
        }
    }

    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(WordCount.class);
        conf.setJobName("wordcount");

        conf.setOutputKeyClass(Text.class);
        conf.setOutputValueClass(IntWritable.class);

        conf.setMapperClass(Map.class);
        conf.setCombinerClass(Reduce.class);
        conf.setReducerClass(Reduce.class);
        conf.setPartitionerClass(FirstCharTextPartitioner.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);
    }
}
Can someone please tell me what I am doing wrong?
解决方案
You are importing the new org.apache.hadoop.mapreduce.Partitioner. 

You need to implement the old interface org.apache.hadoop.mapred.Partitioner, like this:
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.Partitioner;

public class FirstCharTextPartitioner implements Partitioner<Text, Text> {

    @Override
    public int getPartition(Text key, Text value, int numReduceTasks) {
        return (key.toString().charAt(0)) % numReduceTasks;
    }    
}


                        
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