1. In a BST, if the right sub tree is not empty, then the successor is The maximum in the left sub tree The maximum in the right sub tree The minimum in the left sub tree The minimum in the right sub tree 1. What is the hash key value of "CASE" if you assign each letter its corresponding number in the alphabet (i.e. A = 1) and if you use a hash table of size 10 in division hashing? 28 9 4

1. In a BST, if the right sub tree is not empty, then the successor is The maximum in the left sub tree The maximum in the right sub tree The minimum in the left sub tree The minimum in the right sub tree 1. What is the hash key value of "CASE" if you assign each letter its corresponding number in the alphabet (i.e. A = 1) and if you use a hash table of size 10 in division hashing? 28 9 4

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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Similar questions

A message is made of 10 numbers between 00 and 99. A hash algorithm creates a digest out of this message by adding all numbers modulo 100. The resulting digest is a number between 00 and 99. Does this algorithm meet the first criterion of a hash algorithm? Does it meet the second criterion? Does it meet the third criterion?
valsTable: o Empty-since-start 1 Empty-after-removal Occupied Hash table valsTable uses double probing with the hash functions hash1(key): key % 11 hash2(key): 5 - key % 5 and a table size of 11. 15 5 27 6. 7 HashInsert(valsTable, item 70) inserts item 70 into bucket Ex: 10 8 9 Hashlnsert(valsTable, item 62) inserts item 62 into bucket 10 Hashlnsert(valsTable, item 59) inserts item 59 into bucket 2. 3.
Java - Hash table valsTable uses linear probing and a hash function of key % 10.
5. Here are keys and their hash values, for hashing using h(k)= k mod m Where m = 13 130 108 K H(K) 9 0 4 Use double hashing to resolve the collision with h2(k)= 10 - (k mod 10) Construct the hash table 100 78 0 35 9
2. Consider the Linear Hashing index. Linear Hashing | h1 000 001 010 011 ho ठ 00 01 10 11 Mod 8 (%68) Mod 4 (%4) 16* 21* 40* 37* 14* 18* 6* Primary Page 13* A. Show the resulting index after inserting the entry 9* C. Show the resulting index after inserting entry 7* 31* 19* 11* 23* B. Show the resulting index after inserting the entry 3* 30* D. Show the resulting index after inserting the entry 22* Overflow Page
1. Using Rabin-Karp string searching algorithm, walk through the steps of finding how many times the string “aba" occurs in the string “abdabababd". Now, re-calculating the hash values, take modulus with respect to 3 and 7. For hashing with modulo 3, will any collision (the stings are different but the hash is same) occur between any sub-string of the text with the pattern? Can you come up with an efficient way to reduce the probability of this collision (check the hash values for modulo 3 and modulo 7)?
In Hash table H, collision is resolved by using chaining. There are 29 slots in H. The average number of elements stored in a chain is 130. What is the total number of elements stored in H?
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
hi! can you make a flowchart from this c++ program wherein it's easy for people without the knowledge of programming to understand. here's our code: #include<iostream>using namespace std; int main(){ int ch; string Firstname,Middlename,Surname,address,status,number,rate; int age; bool hasCough; bool breathingProblem; char input; while(1) { cout << "WELCOME TO COVID-19 TRACKER \n \n" ; cout << "Please Choose from the following \n" ; cout <<"1.Information\t2.Testing\t3.Exit\n"; cin>>ch; switch(ch) { case 1:cout<<"Enter first name:"; cin>>Firstname; cout<<"Enter middle name:"; cin>>Middlename; cout<<"Enter surname:"; cin>>Surname; cout<<"Enter your Address (NOTE: USE UNDERSCORE AS SPACES FOR EACH WORDS):";…