def mapper(record):
    record = record.replace('\n', '')
    data = record.split(',')
    if data[0] == 'Department':
        mapReducer.emitIntermediate(data[1], ('D', data[2]))
    elif data[0] == 'Employee':
        mapReducer.emitIntermediate(data[2], ('P', data[1]))    
    
def reducer(key, list_of_values):
    name = [ item[1] for item in list_of_values if item[0] == 'P'][0]
    
    for item in [item[1] for item in list_of_values if item[0] == 'D']:
        mapReducer.emit((key, name, item))

def mapper(record):
    #Start writing the Map code here
    words = record.rstrip().split(',')
    if words[0] == 'Department':
        mapReducer.emitIntermediate(words[1], ('D', words[2]) )
    else:
        mapReducer.emitIntermediate(words[2], ('E', words[1]) )
        
def reducer(key, list_of_values):
    #Start writing the Reduce code here
    sl = sorted(list_of_values)
    for d in [x[1] for x in sl if x[0]=='D']:
        mapReducer.emit((key, sl[-1][-1], d))

def mapper(record):
    a, b, c = record.strip().split(",")
    if c.isdigit():  # employee
        return [(c, (a, b))]
    else:            # department
        return [(b, (a, c))]

def reducer(key, list_of_values):
    return [ (key, p[1], p[0]) for p in
             itertools.product(*combiner(sorted(list_of_values))) 
						 if (len(p) >= 2)  ]

def combiner(l):
    for _, it in itertools.groupby(l, operator.itemgetter(0)):
        yield list(map(operator.itemgetter(1), it))