001 /** 002 * Licensed to the Apache Software Foundation (ASF) under one 003 * or more contributor license agreements. See the NOTICE file 004 * distributed with this work for additional information 005 * regarding copyright ownership. The ASF licenses this file 006 * to you under the Apache License, Version 2.0 (the 007 * "License"); you may not use this file except in compliance 008 * with the License. You may obtain a copy of the License at 009 * 010 * http://www.apache.org/licenses/LICENSE-2.0 011 * 012 * Unless required by applicable law or agreed to in writing, software 013 * distributed under the License is distributed on an "AS IS" BASIS, 014 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 015 * See the License for the specific language governing permissions and 016 * limitations under the License. 017 */ 018 019 package org.apache.hadoop.mapreduce.lib.input; 020 021 import java.io.IOException; 022 import java.util.ArrayList; 023 import java.util.List; 024 025 import org.apache.hadoop.classification.InterfaceAudience; 026 import org.apache.hadoop.classification.InterfaceStability; 027 import org.apache.hadoop.conf.Configuration; 028 import org.apache.hadoop.fs.FSDataInputStream; 029 import org.apache.hadoop.fs.FileStatus; 030 import org.apache.hadoop.fs.FileSystem; 031 import org.apache.hadoop.fs.Path; 032 import org.apache.hadoop.io.LongWritable; 033 import org.apache.hadoop.io.Text; 034 import org.apache.hadoop.mapreduce.InputSplit; 035 import org.apache.hadoop.mapreduce.Job; 036 import org.apache.hadoop.mapreduce.JobContext; 037 import org.apache.hadoop.mapreduce.RecordReader; 038 import org.apache.hadoop.mapreduce.TaskAttemptContext; 039 import org.apache.hadoop.util.LineReader; 040 041 /** 042 * NLineInputFormat which splits N lines of input as one split. 043 * 044 * In many "pleasantly" parallel applications, each process/mapper 045 * processes the same input file (s), but with computations are 046 * controlled by different parameters.(Referred to as "parameter sweeps"). 047 * One way to achieve this, is to specify a set of parameters 048 * (one set per line) as input in a control file 049 * (which is the input path to the map-reduce application, 050 * where as the input dataset is specified 051 * via a config variable in JobConf.). 052 * 053 * The NLineInputFormat can be used in such applications, that splits 054 * the input file such that by default, one line is fed as 055 * a value to one map task, and key is the offset. 056 * i.e. (k,v) is (LongWritable, Text). 057 * The location hints will span the whole mapred cluster. 058 */ 059 @InterfaceAudience.Public 060 @InterfaceStability.Stable 061 public class NLineInputFormat extends FileInputFormat<LongWritable, Text> { 062 public static final String LINES_PER_MAP = 063 "mapreduce.input.lineinputformat.linespermap"; 064 065 public RecordReader<LongWritable, Text> createRecordReader( 066 InputSplit genericSplit, TaskAttemptContext context) 067 throws IOException { 068 context.setStatus(genericSplit.toString()); 069 return new LineRecordReader(); 070 } 071 072 /** 073 * Logically splits the set of input files for the job, splits N lines 074 * of the input as one split. 075 * 076 * @see FileInputFormat#getSplits(JobContext) 077 */ 078 public List<InputSplit> getSplits(JobContext job) 079 throws IOException { 080 List<InputSplit> splits = new ArrayList<InputSplit>(); 081 int numLinesPerSplit = getNumLinesPerSplit(job); 082 for (FileStatus status : listStatus(job)) { 083 splits.addAll(getSplitsForFile(status, 084 job.getConfiguration(), numLinesPerSplit)); 085 } 086 return splits; 087 } 088 089 public static List<FileSplit> getSplitsForFile(FileStatus status, 090 Configuration conf, int numLinesPerSplit) throws IOException { 091 List<FileSplit> splits = new ArrayList<FileSplit> (); 092 Path fileName = status.getPath(); 093 if (status.isDirectory()) { 094 throw new IOException("Not a file: " + fileName); 095 } 096 FileSystem fs = fileName.getFileSystem(conf); 097 LineReader lr = null; 098 try { 099 FSDataInputStream in = fs.open(fileName); 100 lr = new LineReader(in, conf); 101 Text line = new Text(); 102 int numLines = 0; 103 long begin = 0; 104 long length = 0; 105 int num = -1; 106 while ((num = lr.readLine(line)) > 0) { 107 numLines++; 108 length += num; 109 if (numLines == numLinesPerSplit) { 110 // NLineInputFormat uses LineRecordReader, which always reads 111 // (and consumes) at least one character out of its upper split 112 // boundary. So to make sure that each mapper gets N lines, we 113 // move back the upper split limits of each split 114 // by one character here. 115 if (begin == 0) { 116 splits.add(new FileSplit(fileName, begin, length - 1, 117 new String[] {})); 118 } else { 119 splits.add(new FileSplit(fileName, begin - 1, length, 120 new String[] {})); 121 } 122 begin += length; 123 length = 0; 124 numLines = 0; 125 } 126 } 127 if (numLines != 0) { 128 splits.add(new FileSplit(fileName, begin, length, new String[]{})); 129 } 130 } finally { 131 if (lr != null) { 132 lr.close(); 133 } 134 } 135 return splits; 136 } 137 138 /** 139 * Set the number of lines per split 140 * @param job the job to modify 141 * @param numLines the number of lines per split 142 */ 143 public static void setNumLinesPerSplit(Job job, int numLines) { 144 job.getConfiguration().setInt(LINES_PER_MAP, numLines); 145 } 146 147 /** 148 * Get the number of lines per split 149 * @param job the job 150 * @return the number of lines per split 151 */ 152 public static int getNumLinesPerSplit(JobContext job) { 153 return job.getConfiguration().getInt(LINES_PER_MAP, 1); 154 } 155 }