Hadoop:Reduce并没有产生所需的输出，它和map输出是一样的

Question

这是我的Map

 public static class MapClass extends Mapper<LongWritable, Text, Text, Text> {
        public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException{
            String[] fields = value.toString().split(",", -20);
            String country = fields[4];
            String numClaims = fields[8];
            if (numClaims.length() > 0 && !numClaims.startsWith(""")) {
                context.write(new Text(country), new Text(numClaims + ",1"));
            }
        }
    }

这是我的Reduce

public void reduce(Text key, Iterator<Text> values, Context context) throws IOException, InterruptedException {
            double sum = 0.0;
            int count = 0;
            while (values.hasNext()) {
                String[] fields = values.next().toString().split(",");
                sum += Double.parseDouble(fields[0]);
                count += Integer.parseInt(fields[1]);
            }
            context.write(new Text(key), new DoubleWritable(sum/count));
        }

以下是如何配置

Job job = new Job(getConf());
            job.setJarByClass(AverageByAttributeUsingCombiner.class);
            job.setJobName("AverageByAttributeUsingCombiner");
            job.setOutputKeyClass(Text.class);
            job.setOutputValueClass(Text.class);
            job.setMapperClass(MapClass.class);
    //        job.setCombinerClass(Combinber.class);
            job.setReducerClass(Reduce.class);
            job.setInputFormatClass(TextInputFormat.class);
            job.setOutputFormatClass(TextOutputFormat.class);
            FileInputFormat.setInputPaths(job, new Path(args[0]));
            FileOutputFormat.setOutputPath(job, new Path(args[1]));
    //        job.setNumReduceTasks(0); // to not run the reducer
            boolean success = job.waitForCompletion(true);
            return success ? 0 : 1;

输入的形式为

   "PATENT","GYEAR","GDATE","APPYEAR","COUNTRY","POSTATE","ASSIGNEE","ASSCODE","CLAIMS","NCLASS","CAT","SUBCAT","CMADE","CRECEIVE","RATIOCIT","GENERAL","ORIGINAL","FWDAPLAG","BCKGTLAG","SELFCTUB","SELFCTLB","SECDUPBD│                                                                                                                                                                                                                
    ","SECDLWBD"                                                                                                                                                                                                         │                                                                                                                                                                                                                
    3070801,1963,1096,,"BE","",,1,,269,6,69,,1,,0,,,,,,,                                                                                                                                                                 │                                                                                                                                                                                                                
    3070802,1963,1096,,"US","TX",,1,,2,6,63,,0,,,,,,,,,                                                                                                                                                                  │                                                                                                                                                                                                                
    3070803,1963,1096,,"US","IL",,1,,2,6,63,,9,,0.3704,,,,,,,                                                                                                                                                            │                                                                                                                                                                                                                
    3070804,1963,1096,,"US","OH",,1,,2,6,63,,3,,0.6667,,,,,,,        

整个map reduce的输出看起来像

"AR"5,1│
"AR"9.1│
"AR"2,1│
"AR"15,1│
"AR"13,1│
"AR"1,1│
"AR"34,1│
"AR"12,1│
"AR"8,1│
"AR"7,1│
"AR"23,1│
"AR"3,1│
"AR"4,1│
"AR"4,1

如何调试和修复此问题？我正在学习hadoop

Answer 1

如前所述，问题在于您没有覆盖默认抽象Reducer类的默认reduce方法。

更具体地说，到目前为止的问题是，您的reduce方法签名是：

 public void reduce(Text key, **Iterator**<Text> values, Context context) 
             throws IOException, InterruptedException

相反，它应该是：

 public void reduce(Text key, **Iterable**<Text> values, Context context) 
             throws IOException, InterruptedException

旧的API版本是正确的，您实现了Reducer接口reduce()方法，并且它有效。

对于这种情况，一个很好的验证是使用@Override，因为它强制编译时检查签名不匹配。

Answer 2

您的减速器没有"捕获"。可能存在类型不匹配或类似情况，因此reduce函数与它从中继承的抽象接口不匹配。。。所以它不是压倒一切的。默认情况下，reduce将使用IdentityReducer，它什么也不做（这就是您正在经历的）。

为了确保您实际上正在重写，请添加@override:

@override
public void reduce(Text key, Iterator<Text> values, Context context)

这将引发一个错误，因为函数签名不匹配。这有望帮助您诊断问题。

Answer 3

• 我目前正在使用hadoop-core-1.0.3.jar，并尝试使用新的API编写Map Reduce，不确定为什么它不起作用
• 这个程序是Hadoop-in-Action代码的一部分，我正在用这本书学习Hadoop
• 当我用old API syntax运行相同的map reduce程序时，它运行得非常好
• 代码看起来像（连同包含的Combiner，我在Combiner第一次出现之前就对它进行了测试）

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.DoubleWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.*;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;
import java.io.IOException;
import java.util.Iterator;

public class AveragingWithCombiner extends Configured implements Tool {
    public static class MapClass extends MapReduceBase
            implements Mapper<LongWritable, Text, Text, Text> {
        static enum ClaimsCounters { MISSING, QUOTED };
        public void map(LongWritable key, Text value,
                        OutputCollector<Text, Text> output,
                        Reporter reporter) throws IOException {
            String fields[] = value.toString().split(",", -20);
            String country = fields[4];
            String numClaims = fields[8];
            if (numClaims.length() > 0 && !numClaims.startsWith(""")) {
                output.collect(new Text(country), new Text(numClaims + ",1"));
            }
        }
    }
    public static class Combine extends MapReduceBase
            implements Reducer<Text, Text, Text, Text> {
        public void reduce(Text key, Iterator<Text> values,
                           OutputCollector<Text, Text> output,
                           Reporter reporter) throws IOException {
            double sum = 0;
            int count = 0;
            while (values.hasNext()) {
                String fields[] = values.next().toString().split(",");
                sum += Double.parseDouble(fields[0]);
                count += Integer.parseInt(fields[1]);
            }
            output.collect(key, new Text(sum + "," + count));
        }
    }
    public static class Reduce extends MapReduceBase
            implements Reducer<Text, Text, Text, DoubleWritable> {
        public void reduce(Text key, Iterator<Text> values,
                           OutputCollector<Text, DoubleWritable> output,
                           Reporter reporter) throws IOException {
            double sum = 0;
            int count = 0;
            while (values.hasNext()) {
                String fields[] = values.next().toString().split(",");
                sum += Double.parseDouble(fields[0]);
                count += Integer.parseInt(fields[1]);
            }
            output.collect(key, new DoubleWritable(sum/count));
        }
    }
    public int run(String[] args) throws Exception {
        // Configuration processed by ToolRunner
        Configuration conf = getConf();
        // Create a JobConf using the processed conf
        JobConf job = new JobConf(conf, AveragingWithCombiner.class);
        // Process custom command-line options
        Path in = new Path(args[0]);
        Path out = new Path(args[1]);
        FileInputFormat.setInputPaths(job, in);
        FileOutputFormat.setOutputPath(job, out);
        // Specify various job-specific parameters
        job.setJobName("AveragingWithCombiner");
        job.setMapperClass(MapClass.class);
        job.setCombinerClass(Combine.class);
        job.setReducerClass(Reduce.class);
        job.setInputFormat(TextInputFormat.class);
        job.setOutputFormat(TextOutputFormat.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(Text.class);
        // Submit the job, then poll for progress until the job is complete
        JobClient.runJob(job);
        return 0;
    }
    public static void main(String[] args) throws Exception {
        // Let ToolRunner handle generic command-line options
        int res = ToolRunner.run(new Configuration(), new AveragingWithCombiner(), args);
        System.exit(res);
    }
}