How to initialize instance variables in setup()? - hadoop

Question

This should be a simple question, but I'm struggling with it. Everything in my code is working except for initializing the parameter values for "train_rows" and "cols" read in from the Configuration file.
I set up logging to display the values of "train_rows" and "cols" within the setup() method, and the values were correct. However, when I tried the same thing within the map() method, both values showed 0. What am I doing wrong?
import java.io.File;
import java.io.IOException;
import java.io.FileNotFoundException;
import java.util.Scanner;
import org.apache.log4j.Logger;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;
public class KNNMapper extends Mapper<LongWritable, Text, IntWritable, IntWritable> {
private static final Logger sLogger = Logger.getLogger(KNNMapper.class);
private int[][] train_vals;
private int[] train_label_vals;
private int train_rows;
private int test_rows;
private int cols;
#Override
public void setup(Context context) throws IOException, InterruptedException {
Configuration conf = context.getConfiguration();
train_rows = conf.getInt("rows", -1);
cols = conf.getInt("columns", -1);
//just changed this
//int[][] train_vals = new int[train_rows][cols];
//int[] train_label_vals = new int[train_rows];
train_vals = new int[train_rows][cols];
train_label_vals = new int[train_rows];
// read train csv, parse, and store into 2d int array
Scanner myScan;
try {
File trainfile = new File("train_sample.csv");
if (!trainfile.exists()) {
throw new IllegalArgumentException("train file didn't load");
}
myScan = new Scanner(trainfile);
//Set the delimiter used in file
myScan.useDelimiter("[,\r\n]+");
//Get all tokens and store them in some data structure
//I am just printing them
for(int row = 0; row < train_rows; row++) {
for(int col = 0; col < cols; col++) {
train_vals[row][col] = Integer.parseInt(myScan.next().toString());
}
}
myScan.close();
} catch (FileNotFoundException e) {
System.out.print("Error: Train file execution did not work.");
}
// read train_labels csv, parse, and store into 2d int array
try {
File trainlabels = new File("train_labels.csv");
if (!trainlabels.exists()) {
throw new IllegalArgumentException("train labels didn't load");
}
myScan = new Scanner(trainlabels);
//Set the delimiter used in file
myScan.useDelimiter("[,\r\n]+");
//Get all tokens and store them in some data structure
//I am just printing them
for(int row = 0; row < train_rows; row++) {
train_label_vals[row] = Integer.parseInt(myScan.next().toString());
if(row < 10) {
System.out.println(train_label_vals[row]);
}
}
myScan.close();
} catch (FileNotFoundException e) {
System.out.print("Error: Train Labels file not found.");
}
}
#Override
public void map(LongWritable key, Text value, Context context)
throws IOException, InterruptedException {
// setup() gave us train_vals & train_label_vals.
// Each line in map() represents a test observation. We iterate
// through every train_val row to find nearest L2 match, then
// return a key/value pair of <observation #,
// convert from Text to String
System.out.println("I'm in the map!");
String line = value.toString();
double distance;
double best_distance = Double.POSITIVE_INFINITY;
int col_num;
int best_digit = -1;
IntWritable rowId = null;
int i;
IntWritable rowNum;
String[] pixels;
System.out.println("Number of train rows:" + train_rows);
System.out.println("Number of columns:" + cols);
// comma delimited files, split on commas
// first we find the # of rows
pixels = line.split(",");
rowId = new IntWritable(Integer.parseInt(pixels[0]));
System.out.println("working on row " + rowId);
best_distance = Double.POSITIVE_INFINITY;
for (i = 0; i < train_rows; i++) {
distance = 0.0;
col_num = 0;
for (int j = 1; j < cols; j++) {
distance += (Integer.parseInt(pixels[j]) - train_vals[i][j-1])^2;
}
if (distance < best_distance) {
best_distance = distance;
best_digit = train_label_vals[i];
}
}
System.out.println("And we're out of the loop baby yeah!");
context.write(rowId, new IntWritable(best_digit));
System.out.println("Mapper done!");
}
}

Answer 1

i doubt this , assuming you are scanning the file in hdfs.
you used:
import java.io.File; File trainfile = new File("train_sample.csv");
in hadoop this is how we check for a file in hdfs :
try {
FileSystem fs = FileSystem.get(context.getConfiguration());
if (fs.exists(new Path("/user/username/path/of/file/inhdfs"))) {
System.out.println("File exists");
}
} catch (IOException e) {
e.printStackTrace();
}