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R Data Structures and Algorithms

R Data Structures and Algorithms

By : PKS Prakash, Sri Krishna Rao
4.5 (2)
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R Data Structures and Algorithms

R Data Structures and Algorithms

4.5 (2)
By: PKS Prakash, Sri Krishna Rao

Overview of this book

In this book, we cover not only classical data structures, but also functional data structures. We begin by answering the fundamental question: why data structures? We then move on to cover the relationship between data structures and algorithms, followed by an analysis and evaluation of algorithms. We introduce the fundamentals of data structures, such as lists, stacks, queues, and dictionaries, using real-world examples. We also cover topics such as indexing, sorting, and searching in depth. Later on, you will be exposed to advanced topics such as graph data structures, dynamic programming, and randomized algorithms. You will come to appreciate the intricacies of high performance and scalable programming using R. We also cover special R data structures such as vectors, data frames, and atomic vectors. With this easy-to-read book, you will be able to understand the power of linked lists, double linked lists, and circular linked lists. We will also explore the application of binary search and will go in depth into sorting algorithms such as bubble sort, selection sort, insertion sort, and merge sort.
Table of Contents (11 chapters)
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Tree-based indexing


Linear indexing is efficient on static databases, that is, records from the database are rarely inserted or deleted. ISAM improves the performance of linear indexing, and can be used for limited updates of the database. As ISAM uses a two-level linear indexing schema, it would break down for a database where the top-level index is already too big to fit into the memory. Thus, as databases become large, we require better organization methods. One approach proposed in Chapter 6, Exploring Search Options, is that a binary search tree could potentially be utilized for indexing to store the primary and secondary keys. The binary search tree provides an efficient structure to store duplicates, and to perform operations such as deletion and insertion given that sufficient memory is available. However, the only disadvantage with a binary search tree is that it could become unbalanced.

Unbalancing becomes an issue, especially in a scenario when the tree is stored in the disk, as...

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