hadoop NLineInputFormat 源码

haddop NLineInputFormat 代码

文件路径：/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-core/src/main/java/org/apache/hadoop/mapreduce/lib/input/NLineInputFormat.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.mapreduce.lib.input;

import java.io.IOException;
import java.util.ArrayList;
import java.util.List;

import org.apache.hadoop.classification.InterfaceAudience;
import org.apache.hadoop.classification.InterfaceStability;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FSDataInputStream;
import org.apache.hadoop.fs.FileStatus;
import org.apache.hadoop.fs.FutureDataInputStreamBuilder;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.InputSplit;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.JobContext;
import org.apache.hadoop.mapreduce.MRJobConfig;
import org.apache.hadoop.mapreduce.RecordReader;
import org.apache.hadoop.mapreduce.TaskAttemptContext;
import org.apache.hadoop.util.LineReader;
import org.apache.hadoop.util.functional.FutureIO;

/**
 * NLineInputFormat which splits N lines of input as one split.
 *
 * In many "pleasantly" parallel applications, each process/mapper 
 * processes the same input file (s), but with computations are 
 * controlled by different parameters.(Referred to as "parameter sweeps").
 * One way to achieve this, is to specify a set of parameters 
 * (one set per line) as input in a control file 
 * (which is the input path to the map-reduce application,
 * where as the input dataset is specified 
 * via a config variable in JobConf.).
 * 
 * The NLineInputFormat can be used in such applications, that splits 
 * the input file such that by default, one line is fed as
 * a value to one map task, and key is the offset.
 * i.e. (k,v) is (LongWritable, Text).
 * The location hints will span the whole mapred cluster.
 */
@InterfaceAudience.Public
@InterfaceStability.Stable
public class NLineInputFormat extends FileInputFormat<LongWritable, Text> { 
  public static final String LINES_PER_MAP = 
    "mapreduce.input.lineinputformat.linespermap";

  public RecordReader<LongWritable, Text> createRecordReader(
      InputSplit genericSplit, TaskAttemptContext context) 
      throws IOException {
    context.setStatus(genericSplit.toString());
    return new LineRecordReader();
  }

  /** 
   * Logically splits the set of input files for the job, splits N lines
   * of the input as one split.
   * 
   * @see FileInputFormat#getSplits(JobContext)
   */
  public List<InputSplit> getSplits(JobContext job)
  throws IOException {
    List<InputSplit> splits = new ArrayList<InputSplit>();
    int numLinesPerSplit = getNumLinesPerSplit(job);
    for (FileStatus status : listStatus(job)) {
      splits.addAll(getSplitsForFile(status,
        job.getConfiguration(), numLinesPerSplit));
    }
    return splits;
  }
  
  public static List<FileSplit> getSplitsForFile(FileStatus status,
      Configuration conf, int numLinesPerSplit) throws IOException {
    List<FileSplit> splits = new ArrayList<FileSplit> ();
    Path fileName = status.getPath();
    if (status.isDirectory()) {
      throw new IOException("Not a file: " + fileName);
    }
    LineReader lr = null;
    try {
      final FutureDataInputStreamBuilder builder =
          fileName.getFileSystem(conf).openFile(fileName);
      FutureIO.propagateOptions(builder, conf,
          MRJobConfig.INPUT_FILE_OPTION_PREFIX,
          MRJobConfig.INPUT_FILE_MANDATORY_PREFIX);
      FSDataInputStream in  = FutureIO.awaitFuture(builder.build());
      lr = new LineReader(in, conf);
      Text line = new Text();
      int numLines = 0;
      long begin = 0;
      long length = 0;
      int num = -1;
      while ((num = lr.readLine(line)) > 0) {
        numLines++;
        length += num;
        if (numLines == numLinesPerSplit) {
          splits.add(createFileSplit(fileName, begin, length));
          begin += length;
          length = 0;
          numLines = 0;
        }
      }
      if (numLines != 0) {
        splits.add(createFileSplit(fileName, begin, length));
      }
    } finally {
      if (lr != null) {
        lr.close();
      }
    }
    return splits; 
  }

  /**
   * NLineInputFormat uses LineRecordReader, which always reads
   * (and consumes) at least one character out of its upper split
   * boundary. So to make sure that each mapper gets N lines, we
   * move back the upper split limits of each split 
   * by one character here.
   * @param fileName  Path of file
   * @param begin  the position of the first byte in the file to process
   * @param length  number of bytes in InputSplit
   * @return  FileSplit
   */
  protected static FileSplit createFileSplit(Path fileName, long begin, long length) {
    return (begin == 0) 
    ? new FileSplit(fileName, begin, length - 1, new String[] {})
    : new FileSplit(fileName, begin - 1, length, new String[] {});
  }
  
  /**
   * Set the number of lines per split
   * @param job the job to modify
   * @param numLines the number of lines per split
   */
  public static void setNumLinesPerSplit(Job job, int numLines) {
    job.getConfiguration().setInt(LINES_PER_MAP, numLines);
  }

  /**
   * Get the number of lines per split
   * @param job the job
   * @return the number of lines per split
   */
  public static int getNumLinesPerSplit(JobContext job) {
    return job.getConfiguration().getInt(LINES_PER_MAP, 1);
  }
}

相关信息

hadoop 源码目录

相关文章

hadoop CombineFileInputFormat 源码

hadoop CombineFileRecordReader 源码

hadoop CombineFileRecordReaderWrapper 源码

hadoop CombineFileSplit 源码

hadoop CombineSequenceFileInputFormat 源码

hadoop CombineTextInputFormat 源码

hadoop CompressedSplitLineReader 源码

hadoop DelegatingInputFormat 源码

hadoop DelegatingMapper 源码

hadoop DelegatingRecordReader 源码