1. (4 points) Suppose we have a hash table of size 29 and we want to implement a system for looking up a friend's information given his/her name. Which of the following hash functions is the best? Justify your choice. (Assuming none of the names is empty.) (a) h(x) = x (b) h(x) = n % 13, where n is the number of characters in x (c) h(x) = (ord(x[0])+ ord(x[-1])) % 29, where x[0] is the first character in the name and x[-1] is the last. (d) h(x) = 29 (e) h(x) = 11 Σ ord(x[i]), where n is the number of characters in x, x[i] the ith character in x, i=0 and ord(c) returns the ordinal value of a character. (Instruction on the Σ summation symbol https://www.mathsisfun.com/algebra/sigma-notation.html.)

1. (4 points) Suppose we have a hash table of size 29 and we want to implement a system for looking up a friend's information given his/her name. Which of the following hash functions is the best? Justify your choice. (Assuming none of the names is empty.) (a) h(x) = x (b) h(x) = n % 13, where n is the number of characters in x (c) h(x) = (ord(x[0])+ ord(x[-1])) % 29, where x[0] is the first character in the name and x[-1] is the last. (d) h(x) = 29 (e) h(x) = 11 Σ ord(x[i]), where n is the number of characters in x, x[i] the ith character in x, i=0 and ord(c) returns the ordinal value of a character. (Instruction on the Σ summation symbol https://www.mathsisfun.com/algebra/sigma-notation.html.)

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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python In simple uniform hashing, each key is assumed to have equal probability to map to any ofthe hashes in a given table of size m. Given an open-address table of size 100 and 2random keys, what is the probability that they hash to the same value? What is theprobability that they hash to different values?
I need help with this pratice run question. In C++, Implement a Hash Table of size 8191 (= 2^13 - 1) to store integers based on quadratic probing. Design your own hash function that is, in your view, sufficiently non-trivial and efficient to compute. Compare the average number of probes for the following cases:Generate 4000 integer random numbers in the range 0 to 10^6 - 1, and insert them into the hash table. Compute and print the total number of probes.Repeat step (a) above 10 times, and find the average number of probes over these 10 trials
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