Distributed Cache - Pig

I had been trying to use Distributed-Cache in Pig.
After a lot of trial and errors behold SUCCESS!
Lets get to the meat.

	package UDF;
	import java.io.BufferedReader;
	import java.io.FileReader;
	import java.io.IOException;
	import java.util.ArrayList;
	import java.util.HashMap;
	import java.util.List;
	import java.util.Map.Entry;
	import java.util.regex.Matcher;
	import java.util.regex.Pattern;
	import org.apache.hadoop.fs.Path;
	import org.apache.pig.EvalFunc;
	import org.apache.pig.backend.executionengine.ExecException;
	import org.apache.pig.data.Tuple;
	import org.apache.pig.impl.util.WrappedIOException;
	public class Regex extends EvalFunc<String> {
	static HashMap<String, String> map = new HashMap<String, String>();
	public List<String> getCacheFiles() {
	Path lookup_file = new Path(
	"hdfs://localhost.localdomain:8020/user/cloudera/top");
	List<String> list = new ArrayList<String>(1);
	list.add(lookup_file + "#id_lookup");
	return list;
	}
	public void VectorizeData() throws IOException {
	FileReader fr = new FileReader("./id_lookup");
	BufferedReader brd = new BufferedReader(fr);
	String line;
	while ((line = brd.readLine()) != null) {
	String str[] = line.split("#");
	map.put(str[0], str[1]);
	}
	fr.close();
	}
	private String Regex(String tweet) throws ExecException {
	// TODO Auto-generated method stub
	for (Entry<String, String> entry : map.entrySet()) {
	Pattern r = Pattern.compile(map.get(entry.getKey()));
	Matcher m = r.matcher(tweet);
	if (m.find() == true) {
	return entry.getValue();
	}
	}
	return null;
	}
	public String exec(Tuple input) throws IOException {
	if (input == null || input.size() < 1 || input.get(0) == null)
	return null;
	try {
	VectorizeData();
	String str = (String) input.get(0);
	return Regex(str);
	} catch (Exception e) {
	throw WrappedIOException.wrap(
	"Caught exception processing input row ", e);
	}
	}
	}

view raw gistfile1.txt hosted with ❤ by GitHub

Lets go through the steps.
a)Create an Eval UDF
b)Initialize Distributed Cache using getCachedFiles()
c)Initialize the Data Structure using step b.
d)Finally apply your logic on the data.