7. Insert the contents of the hash table in the boxes below given the following conditions: The size of the hash table is 12. Double hashing is used to resolve collisions. The hash function used is H(k) = k mod 12 The second hash function is: H2(k) = 7 – (k % 7) What values will be in the hash table after the following sequence of insertions? Insert the values in the boxes below, and show your work for partial credit. 33, 10, 9, 13, 12, 45, 26,

7. Insert the contents of the hash table in the boxes below given the following conditions: The size of the hash table is 12. Double hashing is used to resolve collisions. The hash function used is H(k) = k mod 12 The second hash function is: H2(k) = 7 – (k % 7) What values will be in the hash table after the following sequence of insertions? Insert the values in the boxes below, and show your work for partial credit. 33, 10, 9, 13, 12, 45, 26,

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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1. Given the following hash function for storing records on courses:f(title) = ASCII value of first character in the title - 64Example: f(Biology I) = 66 – 65 = 1 (ASCII value of B is 66) a. Explain why this is or is not a good hash function.b. What improvement(s) could be made? 2. Assume that the hash function is: f(key) = key % Ba. What is the problem if B is too small?b. What is the problem if B is too large?c. What is the big-0 run-time if there are n records?d. What does the run-time for a find, insert, and delete each approach as B gets verylarge?
Use the following values to answer the questions bellow 66 47 87 900 126 140 145 500 177 285 393 395 467 566 620 735Store the values into a hash table that uses the hash function key % 10 to determine into which of ten chains (separate chaining) to put the value.
Use the following values to answer the questions bellow: 66 47 87 900 126 140 145 500 177 285 393 395 467 566 620 735 Store the values into a hash table with 25 positions, using double hashing as the method of collision resolution. Use key % table size as a hash function, and (key + 3) % table size as the rehash function.
Create a hash table of size 8 using modular division method. Use hash function h(k) = 2k + 3 where k is the key value. Apply quadratic probing method in resolving collision. Insert the following keys in the hash table: 3, 2, 9, 6, 11, 13. Show the final hash table.
Assume we wish to resize an existing hash table because the current hash table is becoming too small for the application. Without writing code briefly describe the process of resizing a hash table by "copying" the old data to the new hash table. What is the expected complexity of your process using Big-O notation. Justify your complexity measure. An example of a hash table before resizing is given.
2. Give the contents of the resulting hash table when you insert items with the keys L A G U N I V E R S in that order into an initially empty table of M = 5 lists, using separate chaining with unordered lists. Use the hash function 11k mod M to transform the kth letter of the alphabet into a table index. Example: hash(J) hash(10) = 110 % 5 = 0
Use the following values to answer the questions bellow 66 47 87 900 126 140 145 500 177 285 393 395 467 566 620 735Store the values into a hash table with ten buckets, each containing three slots. If a bucket is full, use the next (sequential) bucket that contains a free slot.
A hash table is a very important data structure in computer science. It is used for fast information retrieval. Itstores data as a < key, value > pair, where the value is indexed by the key. Note that keys must ne unique.Consider the example of storing persons name using the social security number (ssn) as the key. For eachssn x, a hash function h is used, where h(x) is the location to store the name of x. Once we have created atable, to look up the name for ssn x, we can recomputes h(x) and then look up what is stored in that location.In Python, dictionaries are based on hash tables. Typically, the hash function h is deterministic; we do notwant to get different results every time we compute h(x). But h is often chosen to be pseudo-random. Forthis problem, we will assume that h is truly random. Suppose there are k people, with each person’s namestored in a random location (independently), represented by an integer between 1 and n, k < n. It mayhappen that one location has…
1. Use the following values to answer the question below: 66 47 87 900 126 140 145 500 177 285 393 395 467 566 620 7351. Store the values into a hash table with 25 positions, using key % table size as the hash function and the linear probing method of resolving collisions.
T is an empty hash table. The size of T is 4 and the hash function is h(key) = key mod 4. Draw the hash table T after inserting the following item one by one: 24, 30, 29, 39, 30, 15, 14, 33.
Research perfect hash functions. Using a list of names (classmates, family members, etc.), generate the hash values using the perfect hash algorithm?
20 a) Given a hashing function hash(x) = ((x * x) + x) % 11, Insert the value 17 into each hash table using the rules specified below. Note that some of the boxes in each hash table are already full. If there’s a collision, start the probing at i = 0 and increment from there if you collide. b) After we insert our new data (that 17) into these hash tables, should we resize and rehash the values? Why or Why not? c) If this was a hash table using separate chaining instead of linear probing, would it be time to rehash after we insert 17?