我编写了一个自定义分区程序,但是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;
public class FirstCharTextPartitioner extends Partitioner<Text, Text> {
@Override
public int getPartition(Text key, Text value, int numReduceTasks) {
return (key.toString().charAt(0)) % numReduceTasks;
}
}
但是,当我尝试将此设置为
JobConf
对象时,出现以下错误。JobConf类型的setPartitionerClass(Class)方法不适用于参数(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);
}
}
有人可以告诉我我在做什么错吗?
最佳答案
您正在导入新的 org.apache.hadoop.mapreduce.Partitioner
。
您需要实现旧的接口(interface)org.apache.hadoop.mapred.Partitioner
,如下所示:
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;
}
}