Jump to level 1 valsTable: o 10 1 2 32 3 4 5 6 Check 98 7 9 1 Next Empty-since-start Empty-after-removal Occupied Hash table vals Table uses quadratic probing, a hash function of key % 10, c1 = 1, and c2 = 1. Hashinsert(valsTable, item 29) inserts item 29 into bucket Ex: 10 Hashinsert(valsTable, item 50) inserts item 50 into bucket Hashinsert(valsTable, item 42) inserts item 42 into bucket

Jump to level 1 valsTable: o 10 1 2 32 3 4 5 6 Check 98 7 9 1 Next Empty-since-start Empty-after-removal Occupied Hash table vals Table uses quadratic probing, a hash function of key % 10, c1 = 1, and c2 = 1. Hashinsert(valsTable, item 29) inserts item 29 into bucket Ex: 10 Hashinsert(valsTable, item 50) inserts item 50 into bucket Hashinsert(valsTable, item 42) inserts item 42 into bucket

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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The 9-entry hash table that results from using the hash function, h(i) = (2i+7) mod 9, to hash the keys 12, 5, 13, 4, 10, 19, 8, 3, and 28, assuming collisions are handled by linear probing as follows: 0 1 2 3 4 5 6 7 8 10 19 3 28 12 8 13 4 5 group answer choice a) True b) False
Suppose there are seven students with IDs 5701, 9302, 4210, 9015, 1553, 9902, and 2104. Suppose hash table, HT, is of the size 19, indexed 0,1,2, . . ., 18. Show how these students’ IDs, in the order given, are inserted in HT using the hashing function h(k) = k % 19. Use double hashing to resolve collision, where the second hash function is given by g(k) = (k+1) % 17.
Consider a CBHT (closed bucket hash table) in which the keys are student identifiers. Assume that the number of buckets m = 100 and hash function hash (id) = first two digits of id. #Starting with an empty hash table, show the effect of successively adding the following student identifiers: 000014, 990021, 990019, 970036, 000015, 970012, and 970023. Show the effect of deleting 000014 from the hash table.
Using quadratic probing, create a hash table HT[0..8, 0..2] for the collection of keys 17, 9, 34, 56, 11, 4, 71, 86, 55, 10, 39, 49, 52, 82, 31, 13, 22, 35, 44, 20, 60, and 28.Use the hashing formula H(X) = X mod 9. What conclusions have you drawn?
For the set of keys {17, 9, 34, 56, 11, 4, 71, 86, 55, 10, 39, 49, 52, 82, 31, 13, 22,35, 44, 20, 60, 28} obtain a hash table HT[0..8, 0..2] following quadratic probing.Make use of the hash function H(X) = X mod 9. What are your observations?
in a linear probing hash table, is it at all possible, a lookup for an item hash code is 5 end up finding that element in slot 3? explain please. C++ coding
Give the contents of a linear-probing hash table that results when you insert thekeys E A S Y Q U T I O N in that order into an initially empty table of initial size M= 4 that is expanded with doubling whenever half full. Use the hash function 11 k % Mto transform the kth letter of the alphabet into a table index.
Insert the keys <13, 19, 35, 71, 31, 6, 23, 4> into hash table of size m=11 using linear probing hashing. Here, h(k, i) =((k mod m) + i) mod m, i=0,1,2,…. How many times you have to increment i to resolve collisions?
Suppose there are six workers, in a workshop, with IDs 147, 169, 580, 216, 974, 567, 495, 555, and 124. Suppose hash table, HT, is of the size 13, indexed 0, 1, 2, . . ., 12. Show how these workers’ IDs, in the order given, are inserted in HT using the hashing function h(k) = k % 13. Draw two hash tables (one for a, and another for b) with integer keys in each slot. Use linear probing to resolve collision. Use quadratic probing to resolve the collision.
Let's say the length of a hash table is 14, and the hash algorithm is h(key)=key%11. What would happen? Only four nodes are present in the table: H(15)=4, H(38)=5, H(61)=6, and H(84)=7; the other locations are blank. In the scenario when the linear detection approach is used to resolve the dispute, what is the address of node 49? 0 8 3 Nothing Mentioned Herein
Consider a hash table of size 11 with hash function h(x) = x mod 11. Draw the tablethat results after inserting, in the given order, the following values: 26, 57, 40, 50,13, 33, and 72 for each of the three scenarios below: i. When collisions are handled by separate chaining. ii. When collisions are handled by double hashing using a second hash function ℎ’(?) = (? ??? 7) + 1. Hint, the overall (combined) hash function is ?(?) = ( ℎ(?) + ? × ℎ′(?) ) ??? 11, where i = 0, 1, 2, 3, … iii. When collisions are handled by quadratic probing with a quadratic probe function ℎ′(?,?) = (ℎ(?) + 0.5 ? + 0.5 ?2) ??? 11 where ? = 1, 2, 3,….
What should the loading factor be (on ANY HASH TABLE) if you want to have an average of 1.4 comparisons per successful search if LINEAR PROBING?