m1_extended_main.py

# Student Id and 4 grades
import shutil
from random import choice, randrange
from time import process_time

from lstore.db import Database
from lstore.query import Query

path = './ECS165'
shutil.rmtree(path)
db = Database()
db.open(path)
grades_table = db.create_table('Grades', 5, 0)
query = Query(grades_table)
keys = []
number_of_records = 50000
insert_time_0 = process_time()
for i in range(0, number_of_records):
    query.insert(906659671 + i, 93, 0, 0, 0)
    keys.append(906659671 + i)
insert_time_1 = process_time()

print("{:.2f}".format(insert_time_1 - insert_time_0))

# Measuring update Performance
update_cols = [
    [None, None, None, None, None],
    [None, randrange(0, 100), None, None, None],
    [None, None, randrange(0, 100), None, None],
    [None, None, None, randrange(0, 100), None],
    [None, None, None, None, randrange(0, 100)],
]

update_time_0 = process_time()
for i in range(0, number_of_records):
    query.update(choice(keys), *(choice(update_cols)))
update_time_1 = process_time()
print("{:.2f}".format(update_time_1 - update_time_0))

# Measuring Select Performance
select_time_0 = process_time()
for i in range(0, number_of_records):
    query.select(choice(keys), 0, [1, 1, 1, 1, 1])
select_time_1 = process_time()
print("{:.2f}".format(select_time_1 - select_time_0))

# Measuring Aggregate Performance
agg_time_0 = process_time()
for i in range(0, number_of_records, 100):
    start_value = 906659671 + i
    end_value = start_value + 100
    result = query.sum(start_value, end_value - 1, randrange(0, 5))
agg_time_1 = process_time()
print("{:.2f}".format(agg_time_1 - agg_time_0))

# Measuring Delete Performance
delete_time_0 = process_time()
for i in range(0, number_of_records):
    query.delete(906659671 + i)
delete_time_1 = process_time()
print("{:.2f}".format(delete_time_1 - delete_time_0))
db.close()