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Hands-On Data Structures and Algorithms with Rust

You're reading from   Hands-On Data Structures and Algorithms with Rust Learn programming techniques to build effective, maintainable, and readable code in Rust 2018

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Product type Paperback
Published in Jan 2019
Publisher Packt
ISBN-13 9781788995528
Length 316 pages
Edition 1st Edition
Languages
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Author (1):
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Claus Matzinger Claus Matzinger
Author Profile Icon Claus Matzinger
Claus Matzinger
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Toc

Table of Contents (15) Chapters Close

Preface 1. Hello Rust! FREE CHAPTER 2. Cargo and Crates 3. Storing Efficiently 4. Lists, Lists, and More Lists 5. Robust Trees 6. Exploring Maps and Sets 7. Collections in Rust 8. Algorithm Evaluation 9. Ordering Things 10. Finding Stuff 11. Random and Combinatorial 12. Algorithms of the Standard Library 13. Assessments 14. Other Books You May Enjoy

Jump search

Going linearly over a collection one-by-one is only efficient if you are already close to a potential match, but it is very hard to determine—what does close to a match mean? In unordered collections, this is indeed impossible to know this since any item can follow. Consequently, what about sorting the collection first? As discussed in Chapter 9, Ordering Things, sorting at quasi-linear runtime complexity can be significantly faster than going over each item of a long collection past a certain size.

A jump search makes use of knowing about the range it jumps over, not unlike a skip list:

After sorting, a search can be significantly faster and a number of elements can be skipped in order to search in a linear fashion once the algorithm is close to a match. How many elements can be skipped at each jump? This is something to be tested, but first here is the code that does the work:

pub fn jump_search<T: Eq + PartialOrd + Clone>(
haystack: &[T],
needle...
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