错误：java.lang.RuntimeException:Hadoop/Hbase上的java.lang.ClassNotFoundException

我尝试在hadoop/mapreduce上执行以下代码（此代码将数据添加到hbase表中）：

要执行它，我使用：

当我编译我的代码时，我没有得到任何错误，但是当我尝试使用上面的行执行代码时，我得到以下错误：

---

java-cp$（hbase类路径）：$（hadoop类路径）：。uploaderbase/tmp/input/input.csv测试表

感谢您的回答！我尝试了你的解决方案，但我总是犯同样的错误。关于如何修复它，你还有其他想法吗？Ps：除了我发布的错误之外！我也知道：容器被应用程序管理员杀死了。集装箱在要求时被杀死。退出代码为143，容器退出时的退出代码为非零143

//package org.apache.hadoop.hbase.mapreduce;

import java.io.IOException;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.hbase.HBaseConfiguration;
import org.apache.hadoop.hbase.client.Put;
import org.apache.hadoop.hbase.io.ImmutableBytesWritable;
import org.apache.hadoop.hbase.mapreduce.TableMapReduceUtil;
import org.apache.hadoop.hbase.util.Bytes;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.input.SequenceFileInputFormat;
import org.apache.hadoop.util.GenericOptionsParser;
/**
 * Sample Uploader MapReduce
 * <p>
 * This is EXAMPLE code.  You will need to change it to work for your context.
 * <p>
 * Uses {@link TableReducer} to put the data into HBase. Change the InputFormat
 * to suit your data.  In this example, we are importing a CSV file.
 * <p>
 * <pre>row,family,qualifier,value</pre>
 * <p>
 * The table and columnfamily we're to insert into must preexist.
 * <p>
 * There is no reducer in this example as it is not necessary and adds
 * significant overhead.  If you need to do any massaging of data before
 * inserting into HBase, you can do this in the map as well.
 * <p>Do the following to start the MR job:
 * <pre>
 * ./bin/hadoop org.apache.hadoop.hbase.mapreduce.SampleUploader /tmp/input.csv TABLE_NAME
 * </pre>
 * <p>
 * This code was written against HBase 0.21 trunk.
 */
public class UploaderHbase {

  private static final String NAME = "UploaderHbase";

  public static class Uploader
  extends Mapper<LongWritable, Text, ImmutableBytesWritable, Put> {

    private long checkpoint = 100;
    private long count = 0;

    @Override
    public void map(LongWritable key, Text line, Context context)
    throws IOException {

      // Input is a CSV file
      // Each map() is a single line, where the key is the line number
      // Each line is comma-delimited; row,family,qualifier,value

      // Split CSV line
      String [] values = line.toString().split(",");
      if(values.length != 4) {
        return;
      }

      // Extract each value
      byte [] row = Bytes.toBytes(values[0]);
      byte [] family = Bytes.toBytes(values[1]);
      byte [] qualifier = Bytes.toBytes(values[2]);
      byte [] value = Bytes.toBytes(values[3]);

      // Create Put
      Put put = new Put(row);
      put.add(family, qualifier, value);

      // Uncomment below to disable WAL. This will improve performance but means
      // you will experience data loss in the case of a RegionServer crash.
      // put.setWriteToWAL(false);

      try {
        context.write(new ImmutableBytesWritable(row), put);
      } catch (InterruptedException e) {
        e.printStackTrace();
      }

      // Set status every checkpoint lines
      if(++count % checkpoint == 0) {
        context.setStatus("Emitting Put " + count);
      }
    }
  }
 /**
   * Job configuration.
   */
  public static Job configureJob(Configuration conf, String [] args)
  throws IOException {
    Path inputPath = new Path(args[0]);
    String tableName = args[1];
    Job job = new Job(conf, NAME + "_" + tableName);
    job.setJarByClass(UploaderHbase.class);
    FileInputFormat.setInputPaths(job, inputPath);
    job.setInputFormatClass(SequenceFileInputFormat.class);
    job.setMapperClass(Uploader.class);
    // No reducers.  Just write straight to table.  Call initTableReducerJob
    // because it sets up the TableOutputFormat.
    TableMapReduceUtil.initTableReducerJob(tableName, null, job);
    job.setNumReduceTasks(0);
    return job;
  }

  /**
   * Main entry point.
   *
   * @param args  The command line parameters.
   * @throws Exception When running the job fails.
   */
  public static void main(String[] args) throws Exception {
    Configuration conf = HBaseConfiguration.create();
    String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
    if(otherArgs.length != 2) {
      System.err.println("Wrong number of arguments: " + otherArgs.length);
      System.err.println("Usage: " + NAME + " <input> <tablename>");
      System.exit(-1);
    }
    Job job = configureJob(conf, otherArgs);
    System.exit(job.waitForCompletion(true) ? 0 : 1);
  }

}

javac -cp $(hbase classpath):$(hadoop classpath) UploaderHbase.java

java -cp $(hbase classpath):$(hadoop classpath) UploaderHbase /tmp/input/input.csv TestTable

2017-05-03 12:43:45,216 INFO  [main] mapreduce.Job: Task Id : attempt_1493803829363_0004_m_000000_2, Status : FAILED
Error: java.lang.RuntimeException: java.lang.ClassNotFoundException: Class UploaderHbase$Uploader not found
    at org.apache.hadoop.conf.Configuration.getClass(Configuration.java:2195)
    at org.apache.hadoop.mapreduce.task.JobContextImpl.getMapperClass(JobContextImpl.java:186)
    at org.apache.hadoop.mapred.MapTask.runNewMapper(MapTask.java:745)
    at org.apache.hadoop.mapred.MapTask.run(MapTask.java:341)
    at org.apache.hadoop.mapred.YarnChild$2.run(YarnChild.java:164)
    at java.security.AccessController.doPrivileged(Native Method)
    at javax.security.auth.Subject.doAs(Subject.java:422)
    at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1698)
    at org.apache.hadoop.mapred.YarnChild.main(YarnChild.java:158)
Caused by: java.lang.ClassNotFoundException: Class UploaderHbase$Uploader not found
    at org.apache.hadoop.conf.Configuration.getClassByName(Configuration.java:2101)
    at org.apache.hadoop.conf.Configuration.getClass(Configuration.java:2193)
    ... 8 more

            at java.lang.Class.forName(Class.java:348)
            at org.apache.hadoop.util.RunJar.run(RunJar.java:214)
            at org.apache.hadoop.util.RunJar.main(RunJar.java:136)