job.setInputFormatClass(SequenceFileInputFormat.class);
Just you have to follow Hadoop API from apache web-site
Hints:
1) Create sequence file prior to the Job.(Java Algorithm )
Example POC: You have to change based on your requirement
import java.io.IOException;
import java.net.URI;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IOUtils;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.SequenceFile;
import org.apache.hadoop.io.Text;
//White, Tom (2012-05-10). Hadoop: The Definitive Guide (Kindle Locations
5375-5384). OReilly Media - A. Kindle Edition.
public class SequenceFileWriteDemo {
private static final String[] DATA = { "One, two, buckle my shoe", "Three,
four, shut the door", "Five, six, pick up sticks", "Seven, eight, lay them
straight", "Nine, ten, a big fat hen" };
public static void main( String[] args) throws IOException {
//local file path
String uri = "/home/hadoop/Desktop/Image/test_02.txt";
Configuration conf = new Configuration();
FileSystem fs = FileSystem.get(URI.create( uri), conf);
Path path = new Path( uri);
IntWritable key = new IntWritable();
Text value = new Text();
SequenceFile.Writer writer = null;
try {
writer = SequenceFile.createWriter( fs,
conf, path, key.getClass(), value.getClass());
for (int i = 0; i < 100; i ++) {
key.set( 100 - i);
value.set( DATA[ i %
DATA.length]);
// System.out.printf("[%
s]\t% s\t% s\n", writer.getLength(), key, value);
writer.append( key, value);
}
} finally
{ IOUtils.closeStream( writer);
}
}
}
Note: you have to convert all image file to one sequence file.
2) Put it into the HDFS
3) Write MAP/Reduce based on the logic what you need
From: AMARNATH, Balachandar [mailto:balachandar.amarn...@airbus.com]
Sent: 06 March 2013 11:24
To: user@hadoop.apache.org
Subject: RE: Map reduce technique
Thanks for the mail,
Can u please share few links to start with?
Regards
Bala
From: Samir Kumar Das Mohapatra [mailto:dasmo...@adobe.com]
Sent: 06 March 2013 11:21
To: user@hadoop.apache.org<mailto:user@hadoop.apache.org>
Subject: RE: Map reduce technique
I think you have to look the sequence file as input format .
Basically, the way this works is, you will have a separate Java process that
takes several image files, reads the ray bytes into memory, then stores the
data into a key-value pair in a SequenceFile. Keep going and keep writing into
HDFS. This may take a while, but you'll only have to do it once.
Regards,
Samir.
From: AMARNATH, Balachandar [mailto:balachandar.amarn...@airbus.com]
Sent: 06 March 2013 11:07
To: user@hadoop.apache.org<mailto:user@hadoop.apache.org>
Subject: Map reduce technique
Hi,
I am new to map reduce paradigm. I read in a tutorial that says that 'map'
function splits the data and into key value pairs. This means, the map-reduce
framework automatically splits the data into pieces or do we need to explicitly
provide the method to split the data into pieces. If it does automatically, how
it splits an image file (size etc)? I see, processing of an image file as a
whole will give different results than processing them in chunks.
With thanks and regards
Balachandar
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