please send handwritten solution for Q 3 part c d e Q3SHORT ANSWER QUESTIONS. No justification needed.Consider the Hasse diagram of the following partial order relation P:ad.a) How many maximal elements does P have?b) How many greatest (or maximum) elements does P have?c) How many minimal elements does P have?d) How many least (or minimum) elements does P have?e) How many elements are incomparable to a?

Q3 SHORT ANSWER QUESTIONS. No justification needed. Consider the Hasse diagram of the following partial order relation P: a f a) How many maximal elements does P have? b) How many greatest (or maximum) elements does P have? c) How many minimal elements does P have? d) How many least (or minimum) elements does P have? e) How many elements are incomparable to a? 60

Q3 SHORT ANSWER QUESTIONS. No justification needed. Consider the Hasse diagram of the following partial order relation P: a f a) How many maximal elements does P have? b) How many greatest (or maximum) elements does P have? c) How many minimal elements does P have? d) How many least (or minimum) elements does P have? e) How many elements are incomparable to a? 60

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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Display the resulting graphs of the following set operations, and state if any of the results are isomorphically identical to any of the other results. (1.1) 4 - 1 (1.2) 2 ∩ 4 (1.3) (2 U 3) - 1
Suppose that a B+-tree index on building is available on relation departmentand that no other index is available. What would be the best way to handle thefollowing selections that involve negation?a. σ¬ (building < “Watson”)(department)Practice Exercises 791b. σ¬ (building = “Watson”)(department)c. σ¬ (building < “Watson” ∨ budget <50000)(department)
Devise a branch-and-bound algorithm for the SET COVER problem. This entails deciding: (a) What is a subproblem? (b) How do you choose a subproblem to expand? (c) How do you expand a subproblem? (d) What is an appropriate lowerbound? Do you think that your choices above will work well on typical instances of the problem? Why?
Q2: Recall the problem of finding the median of an array of an unsorted list. How fast can one complete the median? What is the recurrence relation that the algorithm follows? (Do not state the algorithm or solve the recurrence relation)
Question 17 Answer the following consolidated question a) and b) Disjoint Sets are a data structure for keeping track of associations among items in a larger system. a) In Disjoint Sets, we have the option of using two techniques: union by rank and path compression. What are the benefits of union by rank? What are the benefits of path compression? b) Assume you have a Disjoint Set instance which is logically represented as the following set of trees. Show how this set could be represented in the following sets array (table below), assuming union by rank.
Show that, with n relations, there are (2(n−1))!∕(n−1)! different join orders.Hint: A complete binary tree is one where every internal node has exactly two children. Use the fact that the number of different complete binary trees with n leaf nodes is:If you wish, you can derive the formula for the number of complete binary trees with n nodes from the formula for the number of binary trees with n nodes. The number of binary trees with n nodes is:
Imagine that you have a database that contains the x, y coordinates as well as the names of eateries. Consider the possibility that just the following categories of questions will be asked: The inquiry seeks to ascertain whether or not a restaurant can be discovered at a certain place. Indexes based on R-trees against those based on B-trees: which is superior? Why?
If index entries were placed in sorted order, what would the occupancy of each leaf node of a B+-tree be? Justify your reasoning.
Adjacency matrix. Given a relation relation (as a numpy.array, see example below) and number of nodes n, define a function adjacency to construct the adjacency matrix A (as a numpy.array).You can assume that n is a positive integer and treat relation as a list of directed edges. # Example from p112 of VMLSrelation = np.array([[1, 2], [1, 3], [2, 1], [2, 4], [3, 4], [4, 1]])n = 4 # Modify the function adjacency below with your answer for Q8def adjacency(relation, n): A = None ########################### ### YOUR CODE HERE ######## ## REMOVE THIS LINE-------- raise NotImplementedError() ## ------------------------ ########################### return A
Let M(m,n) denote the number of comparisons required to merge two sorted lists of sizes m and n. a) Derive an "information theoretic" lower bound on M(m,n). b) Find an interesting relation between M(m,n) and the analogous function S defined for sorting. Use this relation to derive a lower bound for M(m,n) in terms of S. (Hint: Start with an upper bound on S(m+n).
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