if we compare a hash table performanve with a binary search of a sorted array, the number od comparisons required by a hash table vs the binary search tree is _____ A) O(1) vs O(n) B) O(n) vs O(1) c) O(n^2) vs O(log n) d) O(1) vs O(log n) e) O(n) vs O(n)

if we compare a hash table performanve with a binary search of a sorted array, the number od comparisons required by a hash table vs the binary search tree is _____ A) O(1) vs O(n) B) O(n) vs O(1) c) O(n^2) vs O(log n) d) O(1) vs O(log n) e) O(n) vs O(n)

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

See similar textbooks

Similar questions

Trace counting sort on the following list L of unordered keys which lie withinthe range [10, 18].L[1:10]: 16 11 18 13 11 12 15 15 18 16
PYTHON def _insertionsort(self, order): # Implements the insertion sort algorithm to sort a list of items in ascending or descending order n = len(self.items) for i in range(1, n): key = self.items[i] j = i - 1 if order == 'asc': while j >= 0 and key < self.items[j]: self.items[j + 1] = self.items[j] j -= 1 self.items[j + 1] = key elif order == 'desc': while j >= 0 and key > self.items[j]: self.items[j + 1] = self.items[j] j -= 1 self.items[j + 1] = key def sort(self, order = 'asc', type = 'insertion'): if type == 'insertion': # call the insertions sort method to sort atos array based on the parameter values #######################################################################
Write Algorithm procedure code to illustrates the procedure for Fibonacci search. Here n, the number of data elements is such that:i) Fk+1 > (n+1); andii) Fk + m = (n +1) for some m ≥ 0, where Fk+1 and Fk are two consecutiveFibonacci numbers.
6. Consider the following code segment. def magic(li, key): for i in range(len(li)): if li[i] == key: return i return -1 Which algorithm is depicted above? (a) Linear search (b) Binary search (c) Selection sort (d) Insertion sort
Inserting a value in an unsorted linked list has the following big-O running time a. O (1) b. O (log n) c. None of the above d. O (n) e. O (n2)
Trace counting sort on the following list L of unordered keys which lie withinthe range [10, 18].L[1:10]: 16 11 18 13 11 12 15 15 18 16
The removeMin operation for both the linked and array implementation of a Minheap is: O O(1) O O(logn) O O(n?) O O(n) O O(nlogn)
The Big O value of hashing is: O a. O(log N) O b. O(N) Oc O(N*Log N) O d. 0(1)
C++ formatting please Write a program (not a function) that reads from a file named "data.csv". This file consists of a list of countries and gold medals they have won in various Olympic events. Write to standard out, the top 5 countries with the most gold medals. You can assume there will be no ties. Expected Output: 1: United States with 1022 gold medals 2: Soviet Union with 440 gold medals 3: Germany with 275 gold medals 4: Great Britain with 263 gold medals 5: China with 227 gold medals
The best technique of hashing when memory space is not a problem is O Linear probing O Quadratic probing O Double hashing O Separate chaining
Trace counting sort on the following list L of unordered keys which lie withinthe range [10, 18].L[1:10]: 16 11 18 13 11 12 15 15 18 16
Extendible hash index:Consider the Extendible Hashing index shown in figure below: Show the state of the index after each operation:a) Insertion of entry 1b) Insertion of entry 23c) Deletion of entry 30