hadoop MapRunner 源码

  • 2022-10-20
  • 浏览 (129)

haddop MapRunner 代码

文件路径:/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-core/src/main/java/org/apache/hadoop/mapred/MapRunner.java

/**
 * Licensed to the Apache Software Foundation (ASF) under one
 * or more contributor license agreements.  See the NOTICE file
 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you under the Apache License, Version 2.0 (the
 * "License"); you may not use this file except in compliance
 * with the License.  You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package org.apache.hadoop.mapred;

import java.io.IOException;

import org.apache.hadoop.classification.InterfaceAudience;
import org.apache.hadoop.classification.InterfaceStability;
import org.apache.hadoop.util.ReflectionUtils;

/** Default {@link MapRunnable} implementation.*/
@InterfaceAudience.Public
@InterfaceStability.Stable
public class MapRunner<K1, V1, K2, V2>
    implements MapRunnable<K1, V1, K2, V2> {
  
  private Mapper<K1, V1, K2, V2> mapper;
  private boolean incrProcCount;

  @SuppressWarnings("unchecked")
  public void configure(JobConf job) {
    this.mapper = ReflectionUtils.newInstance(job.getMapperClass(), job);
    //increment processed counter only if skipping feature is enabled
    this.incrProcCount = SkipBadRecords.getMapperMaxSkipRecords(job)>0 && 
      SkipBadRecords.getAutoIncrMapperProcCount(job);
  }

  public void run(RecordReader<K1, V1> input, OutputCollector<K2, V2> output,
                  Reporter reporter)
    throws IOException {
    try {
      // allocate key & value instances that are re-used for all entries
      K1 key = input.createKey();
      V1 value = input.createValue();
      
      while (input.next(key, value)) {
        // map pair to output
        mapper.map(key, value, output, reporter);
        if(incrProcCount) {
          reporter.incrCounter(SkipBadRecords.COUNTER_GROUP, 
              SkipBadRecords.COUNTER_MAP_PROCESSED_RECORDS, 1);
        }
      }
    } finally {
      mapper.close();
    }
  }

  protected Mapper<K1, V1, K2, V2> getMapper() {
    return mapper;
  }
}

相关信息

hadoop 源码目录

相关文章

hadoop AMFeedback 源码

hadoop BackupStore 源码

hadoop BasicTypeSorterBase 源码

hadoop BufferSorter 源码

hadoop CleanupQueue 源码

hadoop Clock 源码

hadoop ClusterStatus 源码

hadoop Counters 源码

hadoop CumulativePeriodicStats 源码

hadoop DeprecatedQueueConfigurationParser 源码

0  赞