Notes

package stubs;

import java.io.BufferedReader;
import java.io.FileNotFoundException;
import java.io.FileReader;
import java.io.IOException;
import java.util.HashSet;
import java.util.Set;

import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.conf.Configurable;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.mapreduce.Partitioner;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;

public class SentimentPartitioner extends Partitioner<Text, IntWritable> implements
Configurable {

private Configuration configuration;
Set<String> positive = new HashSet<String>();
Set<String> negative = new HashSet<String>();

/**
* Set up the positive and negative hash set in the setConf method.
*/
@Override
public void setConf(Configuration configuration) {
/*
* Add the positive and negative words to the respective sets using the files
* positive-words.txt and negative-words.txt.
*/
/*
* TODO implement
*/

BufferedReader br = null;
try {
br = new BufferedReader(new FileReader("/home/training/workspace/partitioner/src/stubs/positive-words.txt"));
} catch (FileNotFoundException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
String line;
try {
while((line = br.readLine()) != null) {
// do something with line.
if(line.charAt(0) == ';')
continue;
positive.add(line);
}
} catch (IOException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}



try {
br = new BufferedReader(new FileReader("/home/training/workspace/partitioner/src/stubs/negative-words.txt"));
} catch (FileNotFoundException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}

try {
while((line = br.readLine()) != null) {
// do something with line.
if(line.charAt(0) == ';')
continue;
negative.add(line);
}
} catch (IOException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}


}

/**
* Implement the getConf method for the Configurable interface.
*/
@Override
public Configuration getConf() {
return configuration;
}

/**
* You must implement the getPartition method for a partitioner class.
* This method receives the words as keys (i.e., the output key from the mapper.)
* It should return an integer representation of the sentiment category
* (positive, negative, neutral).
*
* For this partitioner to work, the job configuration must have been
* set so that there are exactly 3 reducers.
*/
public int getPartition(Text key, IntWritable value, int numReduceTasks) {
/*
* TODO implement
* Change the return 0 statement below to return the number of the sentiment
* category; use 0 for positive words, 1 for negative words, and 2 for neutral words.
* Use the sets of positive and negative words to find out the sentiment.
*
* Hint: use positive.contains(key.toString()) and negative.contains(key.toString())
* If a word appears in both lists assume it is positive. That is, once you found
* that a word is in the positive list you do not need to check if it is in the
* negative list.
*/

if(positive.contains(key.toString()))
{
return 0;
}
else if(negative.contains(key.toString()))
{
return 1;
}
else
{
return 2;
}

}
}