Grouping data in mapReduce - hadoop

Question

I have a csv file which I have loaded into hadoop. Data sample is below.
name | shop | balance
tom | shop a | -500
john | shop b | 200
jane | shop c | 5000
Results:
bad 1
normal 1
wealthy 1
I have to get the balance for each person and then put them into groups(bad(<0), normal(1 to 500), good(>500)
I'm not 100% sure how to put the groups into mapReduce. Do I put it in the reducer? or mapper?
Splitting the csv file(mapper):
String[] tokens = value.toString().split(",");
Sting balance = tokens[3];
Creating groups:
String[] category = new String[3];
category[0] = "Bad"
category[1] = "Normal"
category[2] = "Good"
I also have this if/else statement:
if (bal =< 500){
//put into cat 0
} else if ( bal >= 501 && bal <=1500){
// put into cat 1
} else {
//put into cat 2
}
Thanks in advance.

Answer 1

A simple way to implement this would be:
Map:
map() {
if (bal <= 0) { //or 500, or whatever
emit (bad, 1);
} else if (bal <= 500) { // or 1500, or whatever
emit (normal, 1);
} else {
emit (good, 1);
}
}
Reduce (and combiner, as well):
reduce(key, values) {
int count = 0;
while (values.hasNext()) {
count += values.next();
}
emit (key, count);
}
It's exactly the same as the word count example, where, in your case, you have three words (categories): bad, normal, good.