#!/usr/bin/env python from operator import itemgetter import sys current_word = None current_count = 0 word = None # input comes from STDIN for line in sys.stdin: # remove leading and trailing...

In this question don’t change code, just in python postgreSQL but solve the question and follow the instructions

Extracted text: #!/usr/bin/env python from operator import itemgetter import sys current_word = None current_count = 0 word = None # input comes from STDIN for line in sys.stdin: # remove leading and trailing whitespace line = line.strip() # parse the input we got from mapper.py word, count = line.split('\t', 1)' # print "DEBUG: " # convert count (currently a string) to int try: count = int(count) except ValueError: # count was not a number, normally we would drop a log error # but that is out of scope here, so continue continue word, " " count # this IF-switch only works because Hadoop sorts # by key (here: word) before it is passed to the reducer # hence the single-host example using streaming pipe must add in # an explicit sort! if current_word == word: current_count += count else: if current_word: output # write result to STDOUT print(f'{current_word}\t{current_count}') current_count = count current_word = word # do not forget to output the last word if needed! if current_word == word: print(f'{current_word}\t{current_count}') $ cat beach_day.csv I ./mapper.py | sort -k1,1 | ./reducer.py "Accessory" "Camping" "Food" "Toy" 1 2


Extracted text: Pseudo Code: 1. For each record in my data set: a. Inspect the column listed in the group by statement, and determine if we have found it previously, b. If we have not then put it into a data structure which keeps track of keys and can associate values with them, such as a "map" (also called a hash, or dictionary) and put the aggregate function target (price) value into the value spot. c. If we have seen it before, then take the value from our aggregate function target (again, price) and apply the function to it before replacing the new value with the one curently in the value spot of our map.