Project/Naive.py at master · data-intensive-computing-4020/Project · GitHub

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#  _   _       _                      _                  _ _   _
# | \ | |     (_)               /\   | |                (_) | | |
# |  \| | __ _ ___   _____     /  \  | | __ _  ___  _ __ _| |_| |__  _ __ ___
# | . ` |/ _` | \ \ / / _ \   / /\ \ | |/ _` |/ _ \| '__| | __| '_ \| '_ ` _ \
# | |\  | (_| | |\ V /  __/  / ____ \| | (_| | (_) | |  | | |_| | | | | | | | |
# |_| \_|\__,_|_| \_/ \___| /_/    \_\_|\__, |\___/|_|  |_|\__|_| |_|_| |_| |_|
#                                        __/ |
#                                       |___/
# The Naive algorithm that utilizes two nested for loops
# Input execution command: python Naive.py <table1FileName> <x> <table1FileName> <x> <tableoutFileName> <BenchmarkFileName>
# Please ensure that the table1, table2 and tableout file name are in JSON format
# Please specify the name of the BenchmarkFileName and ensure that it is a .txt file
# Where x and y are the column indices to join on.


import re
import os
import sys
import time
import json
from prettytable import PrettyTable

def Naive(file1_name, index_1, file2_name, index_2, output_file_name, benchmark_file_name):

    start_time = time.time()
    fileread_starttime = time.time()
    file_1 = open(file1_name, 'r')
    table_1 = file_1.read()
    file_2 = open(file2_name, 'r')
    table_2 = file_2.read()

    fileread_endtime = time.time()


    #Load the tables into JSON format
    table_1 = json.loads(table_1)
    table_2 = json.loads(table_2)
    joined_table = []

    #For each tuple of each table, check that the keys match
    join_starttime = time.time()
    for values_1 in table_1:
        for values_2 in table_2:
            if values_1[index_1] == values_2[index_2]:
                value = (values_1, values_2)
                joined_table.append(value)
    join_endtime = time.time()
    #Write the output to JSON file

    write_starttime = time.time()
    with open(output_file_name, 'w') as output_file:
        json.dump(joined_table, output_file)
    write_endtime = time.time()

    finish_time = time.time()
    total_time = finish_time - start_time
    fileread_time = fileread_endtime - fileread_starttime
    join_time = join_endtime - join_starttime
    write_time = write_endtime - write_starttime

    benchmark_table = PrettyTable()
    benchmark_table.field_names = ["Benchmark", "Time (s)"]
    benchmark_table.align["Benchmark"] = "l"
    benchmark_table.add_row(["Read both input files time: ", fileread_time])
    benchmark_table.add_row(["Join time: ", join_time])
    benchmark_table.add_row(["Write output file time: ", write_time])
    benchmark_table.add_row(["Total time: ", total_time])

    with open(benchmark_file_name, 'a+') as benchmark_file:
        benchmark_file.write('\t***Naive Benchmark Results*** \n')
        benchmark_file.write(str(benchmark_table))
        benchmark_file.write('\n \n')
    benchmark_file.close()

command_line = sys.argv
file1_name = command_line[1]
index_1 = int(command_line[2])
file2_name = command_line[3]
index_2 = int(command_line[4])
output_file_name = command_line[5]
benchmark_file_name = command_line[6]

Naive(file1_name,index_1, file2_name, index_2, output_file_name, benchmark_file_name)