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 splits.add(createFileSplit(fileName, begin, length));
111 begin += length;
112 length = 0;
113 numLines = 0;
114 }
115 }
116 if (numLines != 0) {
117 splits.add(createFileSplit(fileName, begin, length));
118 }
119 } finally {
120 if (lr != null) {
121 lr.close();
122 }
123 }
124 return splits;
125 }
126
127 /**
128 * NLineInputFormat uses LineRecordReader, which always reads
129 * (and consumes) at least one character out of its upper split
130 * boundary. So to make sure that each mapper gets N lines, we
131 * move back the upper split limits of each split
132 * by one character here.
133 * @param fileName Path of file
134 * @param begin the position of the first byte in the file to process
135 * @param length number of bytes in InputSplit
136 * @return FileSplit
137 */
138 protected static FileSplit createFileSplit(Path fileName, long begin, long length) {
139 return (begin == 0)
140 ? new FileSplit(fileName, begin, length - 1, new String[] {})
141 : new FileSplit(fileName, begin - 1, length, new String[] {});
142 }
143
144 /**
145 * Set the number of lines per split
146 * @param job the job to modify
147 * @param numLines the number of lines per split
148 */
149 public static void setNumLinesPerSplit(Job job, int numLines) {
150 job.getConfiguration().setInt(LINES_PER_MAP, numLines);
151 }
152
153 /**
154 * Get the number of lines per split
155 * @param job the job
156 * @return the number of lines per split
157 */
158 public static int getNumLinesPerSplit(JobContext job) {
159 return job.getConfiguration().getInt(LINES_PER_MAP, 1);
160 }
161 }