import numpy as np np.random.seed(1012) DATASIZE = 10000 MAX_VALUE = 1000000000 data = np.random.randint(0, MAX_VALUE, size=DATASIZE) def compareWithNext(data): for i in range(len(data)-1): if data[i] > data[i+1]: temp = data[i]; data[i] = data[i+1]; data[i+1] = temp; def mySort(data): for i in range(len(data)): compareWithNext(data) def main(): print(data[0:5]) mySort(data[0:5]) print(data[0:5]) main() The sort from the code above can be improved. If the data passed to be sorted is already sorted, it still performs all of the work, as if the array was not sorted. Make two improvements: • Change the first function (the one that does the comparisons), so that it returns a boolean that states whether the array is sorted. Make use of that boolean to stop calling the first function if the array is sorted. • Consider what happens when the first function is called. For randomly distributed data, some comparisons will lead to swaps, and others won’t. But, the largest number will certainly “float” to the end of the array. Future calls of the first function will not move that largest number, and we could therefore end the comparisons done in future calls without examining the last position in the array. • Modify the first function further. Add a parameter that specifies the index at which the comparisons & swaps should stop. Modify the second function so that one fewer element is examined each time the first function is called.

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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Question

import numpy as np
np.random.seed(1012)
DATASIZE = 10000
MAX_VALUE = 1000000000
data = np.random.randint(0, MAX_VALUE, size=DATASIZE)

def compareWithNext(data):
for i in range(len(data)-1):
if data[i] > data[i+1]:
temp = data[i];
data[i] = data[i+1];
data[i+1] = temp;

def mySort(data):
for i in range(len(data)):
compareWithNext(data)

def main():
print(data[0:5])
mySort(data[0:5])
print(data[0:5])

main()

The sort from the code above can be improved. If the data passed to be sorted is
already sorted, it still performs all of the work, as if the array was not
sorted.
Make two improvements:
• Change the first function (the one that does the comparisons), so that it returns a
boolean that states whether the array is sorted. Make use of that boolean to stop
calling the first function if the array is sorted.
• Consider what happens when the first function is called. For randomly distributed
data, some comparisons will lead to swaps, and others won’t. But, the largest
number will certainly “float” to the end of the array. Future calls of the first
function will not move that largest number, and we could therefore end the
comparisons done in future calls without examining the last position in the array.
• Modify the first function further. Add a parameter that specifies the index at
which the comparisons & swaps should stop. Modify the second function so
that one fewer element is examined each time the first function is called.

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