HackerRank Map Reduce Advanced - Count number of friends problem solution

In this HackerRank Map Reduce Advanced - Count number of friends problem solution Mappers and Reducers

Here's a quick but comprehensive introduction to the idea of splitting tasks into a MapReduce model. The four important functions involved are:

Map (the mapper function)  

EmitIntermediate(the intermediate key,value pairs emitted by the mapper functions)  

Reduce (the reducer function)  

Emit (the final output, after summarization from the Reduce functions)

We provide you with a single system, single thread version of a basic MapReduce implementation.

Task

Joins are

The input is a number of lines with pairs of name of friends, in the form:

[Friend1] [Friend2]

The required output is to print the number of friends of each person, in the format shown. The code for the MapReduce class, parts related to IO etc. has already been provided. However, the mapper and reducer functions are incomplete. Your task is to fill up the mapper and reducer functions appropriately, such that the program works, and outputs the list of number of friends of each person , in lexicographical order.

Also, this program outputs certain information to the error stream. This information has been logged to help beginners gain a better understanding of the the intermediate steps in a map-reduce process.

Problem solution in Python.

import sys
from collections import OrderedDict
class MapReduce:
    def __init__(self):
        self.intermediate = OrderedDict()
        self.result = []
   

    def emitIntermediate(self, key, value):
        self.intermediate.setdefault(key, [])       
        self.intermediate[key].append(value)

    def emit(self, value):
        self.result.append(value) 

    def execute(self, data, mapper, reducer):
        for record in data:
            mapper(record)

        for key in self.intermediate:
            reducer(key, self.intermediate[key])

        self.result.sort()
        for item in self.result:
            print "{\"key\":\""+item[0]+"\",\"value\":\"" + str(item[1]) + "\"}"

mapReducer = MapReduce()

def mapper(record):
    #Start writing the Map code here
    record = record.split()
    for item in record:
        mapReducer.emitIntermediate(item,1)

def reducer(key, list_of_values):
    #Start writing the Reduce code here
    total = sum(list_of_values)
    mapReducer.emit((key,total))
    
if __name__ == '__main__':
    inputData = []
    for line in sys.stdin:
        inputData.append(line)
    mapReducer.execute(inputData, mapper, reducer)