Hadoop:java.lang.IncompatibleClassChangeError:找到接口 org.apache.hadoop.mapreduce.JobContext，但需要类

Full text of my MarReduce Job:

package com.bigdata.hadoop;

import java.io.IOException;
import java.util.*;

import org.apache.hadoop.conf.*;
import org.apache.hadoop.io.*;
import org.apache.hadoop.mapreduce.*;
import org.apache.hadoop.util.*;
import org.apache.hcatalog.mapreduce.*;
import org.apache.hcatalog.data.*;
import org.apache.hcatalog.data.schema.*;
import org.apache.log4j.Logger;

public class FieldCounts extends Configured implements Tool {

    public static class Map extends Mapper<WritableComparable, HCatRecord, TableFieldValueKey, IntWritable> {

        static Logger logger = Logger.getLogger("com.foo.Bar");

        static boolean firstMapRun = true;
        static List<String> fieldNameList = new LinkedList<String>();
        /**
         * Return a list of field names not containing `id` field name
         * @param schema
         * @return
         */
        static List<String> getFieldNames(HCatSchema schema) {
            // Filter out `id` name just once
            if (firstMapRun) {
                firstMapRun = false;
                List<String> fieldNames = schema.getFieldNames();
                for (String fieldName : fieldNames) {
                    if (!fieldName.equals("id")) {
                        fieldNameList.add(fieldName);
                    }
                }
            } // if (firstMapRun)
            return fieldNameList;
        }

        @Override
      protected void map( WritableComparable key,
                          HCatRecord hcatRecord,
                          //org.apache.hadoop.mapreduce.Mapper
                          //<WritableComparable, HCatRecord, Text, IntWritable>.Context context)
                          Context context)
            throws IOException, InterruptedException {

            HCatSchema schema = HCatBaseInputFormat.getTableSchema(context.getConfiguration());

           //String schemaTypeStr = schema.getSchemaAsTypeString();
           //logger.info("******** schemaTypeStr ********** : "+schemaTypeStr);

           //List<String> fieldNames = schema.getFieldNames();
            List<String> fieldNames = getFieldNames(schema);
            for (String fieldName : fieldNames) {
                Object value = hcatRecord.get(fieldName, schema);
                String fieldValue = null;
                if (null == value) {
                    fieldValue = "<NULL>";
                } else {
                    fieldValue = value.toString();
                }
                //String fieldNameValue = fieldName+"."+fieldValue;
                //context.write(new Text(fieldNameValue), new IntWritable(1));
                TableFieldValueKey fieldKey = new TableFieldValueKey();
                fieldKey.fieldName = fieldName;
                fieldKey.fieldValue = fieldValue;
                context.write(fieldKey, new IntWritable(1));
            }

        }       
    }

    public static class Reduce extends Reducer<TableFieldValueKey, IntWritable,
                                       WritableComparable, HCatRecord> {

        protected void reduce( TableFieldValueKey key,
                               java.lang.Iterable<IntWritable> values,
                               Context context)
                               //org.apache.hadoop.mapreduce.Reducer<Text, IntWritable,
                               //WritableComparable, HCatRecord>.Context context)
            throws IOException, InterruptedException {
            Iterator<IntWritable> iter = values.iterator();
            int sum = 0;
            // Sum up occurrences of the given key 
            while (iter.hasNext()) {
                IntWritable iw = iter.next();
                sum = sum + iw.get();
            }

            HCatRecord record = new DefaultHCatRecord(3);
            record.set(0, key.fieldName);
            record.set(1, key.fieldValue);
            record.set(2, sum);

            context.write(null, record);
        }
    }

    public int run(String[] args) throws Exception {
        Configuration conf = getConf();
        args = new GenericOptionsParser(conf, args).getRemainingArgs();

        // To fix Hadoop "META-INFO" (http://stackoverflow.com/questions/17265002/hadoop-no-filesystem-for-scheme-file)
        conf.set("fs.hdfs.impl",
                org.apache.hadoop.hdfs.DistributedFileSystem.class.getName());
        conf.set("fs.file.impl",
                org.apache.hadoop.fs.LocalFileSystem.class.getName());

        // Get the input and output table names as arguments
        String inputTableName = args[0];
        String outputTableName = args[1];
        // Assume the default database
        String dbName = null;

        Job job = new Job(conf, "FieldCounts");

        HCatInputFormat.setInput(job,
                InputJobInfo.create(dbName, inputTableName, null));
        job.setJarByClass(FieldCounts.class);
        job.setMapperClass(Map.class);
        job.setReducerClass(Reduce.class);

        // An HCatalog record as input
        job.setInputFormatClass(HCatInputFormat.class);

        // Mapper emits TableFieldValueKey as key and an integer as value
        job.setMapOutputKeyClass(TableFieldValueKey.class);
        job.setMapOutputValueClass(IntWritable.class);

        // Ignore the key for the reducer output; emitting an HCatalog record as
        // value
        job.setOutputKeyClass(WritableComparable.class);
        job.setOutputValueClass(DefaultHCatRecord.class);
        job.setOutputFormatClass(HCatOutputFormat.class);

        HCatOutputFormat.setOutput(job,
                OutputJobInfo.create(dbName, outputTableName, null));
        HCatSchema s = HCatOutputFormat.getTableSchema(job);
        System.err.println("INFO: output schema explicitly set for writing:"
                + s);
        HCatOutputFormat.setSchema(job, s);
        return (job.waitForCompletion(true) ? 0 : 1);
    }

    public static void main(String[] args) throws Exception {
        String classpath = System.getProperty("java.class.path");
        //System.out.println("*** CLASSPATH: "+classpath);       
        int exitCode = ToolRunner.run(new FieldCounts(), args);
        System.exit(exitCode);
    }
}

复杂键的类:

package com.bigdata.hadoop;

import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;

import org.apache.hadoop.io.WritableComparable;

import com.google.common.collect.ComparisonChain;

public class TableFieldValueKey  implements WritableComparable<TableFieldValueKey> {

      public String fieldName;
      public String fieldValue;

      public TableFieldValueKey() {} //must have a default constructor
      //

      public void readFields(DataInput in) throws IOException {
        fieldName = in.readUTF();
        fieldValue = in.readUTF();
      }

      public void write(DataOutput out) throws IOException {
        out.writeUTF(fieldName);
        out.writeUTF(fieldValue);
      }

      public int compareTo(TableFieldValueKey o) {
        return ComparisonChain.start().compare(fieldName, o.fieldName)
            .compare(fieldValue, o.fieldValue).result();
      }

    }

推荐答案

Hadoop 经历了从 Hadoop 1.0 到 Hadoop 2.0 的巨大代码重构.一个副作用是针对 Hadoop 1.0 编译的代码与 Hadoop 2.0 不兼容，反之亦然.但是源代码大部分是兼容的，因此只需要使用目标重新编译代码Hadoop 发行版.