Create the Sample class, which has a constructor that accepts an array p[] of double values as an input and supports the following two operations: Return an index i with a probability of p[i]/T (where T is the total of the numbers in p[]) and alter(i, v) to change the value of p[i] to v. Use a full binary tree with an inferred weight of p[i] for each node. Keep the total weight of all the nodes in its subtree in each node. Pick a random number between 0 and T to obtain a random index and use the cumulative weights to select which branch of the subtree to examine. Change the weights of all nodes on the path from the root to i when updating p[i]. Avoid explicit pointers, as we do for heaps.
Create the Sample class, which has a constructor that accepts an array p[] of double values as an input and supports the following two operations: Return an index i with a probability of p[i]/T (where T is the total of the numbers in p[]) and alter(i, v) to change the value of p[i] to v. Use a full binary tree with an inferred weight of p[i] for each node. Keep the total weight of all the nodes in its subtree in each node. Pick a random number between 0 and T to obtain a random index and use the cumulative weights to select which branch of the subtree to examine. Change the weights of all nodes on the path from the root to i when updating p[i]. Avoid explicit pointers, as we do for heaps.
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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Create the Sample class, which has a constructor that accepts an array p[] of double values as an input and supports the following two operations: Return an index i with a probability of p[i]/T (where T is the total of the numbers in p[]) and alter(i, v) to change the value of p[i] to v. Use a full binary tree with an inferred weight of p[i] for each node. Keep the total weight of all the nodes in its subtree in each node. Pick a random number between 0 and T to obtain a random index and use the cumulative weights to select which branch of the subtree to examine. Change the weights of all nodes on the path from the root to i when updating p[i]. Avoid explicit pointers, as we do for heaps.
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