On Deletions in Open Addressing Hashing Article Swipe

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Rosa María Rodríguez Jiménez , Conrado Martı́nez ·

YOU? · · 2018 · Open Access · · DOI: https://doi.org/10.1137/1.9781611975062.3

Deletions in open addressing tables have often been seen as problematic. The usual solution is to use a special mark ’deleted’ so that probe sequences continue past deleted slots, as if there was an element still sitting there. Such a solution, notwithstanding is wide applicability, may involve serious performance degradation. In the first part of this paper we review a practical implementation of the often overlooked deletion algorithm for linear probing hash tables, analyze its properties and performance, and provide several strong arguments in favor of the Robin Hood variant. In particular, we show how a small variation can yield substantial improvements for unsuccesful search. In the second part we propose an algorithm for true deletion in open addressing hashing with secondary clustering, like quadratic hashing. As far as we know, this is the first time that such an algorithm appears in the literature. Although it involves some extra memory for bookkeeping, the algorithm is comparatively easy and efficient, and might be of practical value, besides its theoretical interest.

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Theoretical Computer Science

Data Mining

Mathematics

Artificial Intelligence

Concepts

Linear hashing Computer science Hash table Dynamic perfect hashing Randomness Hash function Cluster analysis Algorithm Bookkeeping Table (database) Theoretical computer science Value (mathematics) Universal hashing Locality-sensitive hashing Double hashing Data mining Mathematics Artificial intelligence Machine learning Statistics Programming language Economics Finance

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Type: book-chapter
Language: en
Landing Page: https://doi.org/10.1137/1.9781611975062.3
PDF: https://epubs.siam.org/doi/pdf/10.1137/1.9781611975062.3
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Cited By: 5
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DOI: https://doi.org/10.1137/1.9781611975062.3

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Title: On Deletions in Open Addressing Hashing

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Type: book-chapter

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Language: en

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Publication year: 2018

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Publication date: 2018-01-01

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Authors: Rosa María Rodríguez Jiménez, Conrado Martı́nez

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Landing page: https://doi.org/10.1137/1.9781611975062.3

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Concepts: Linear hashing, Computer science, Hash table, Dynamic perfect hashing, Randomness, Hash function, Cluster analysis, Algorithm, Bookkeeping, Table (database), Theoretical computer science, Value (mathematics), Universal hashing, Locality-sensitive hashing, Double hashing, Data mining, Mathematics, Artificial intelligence, Machine learning, Statistics, Programming language, Economics, Finance

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Cited by: 5

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Citations by year (recent): 2025: 1, 2024: 1, 2022: 2, 2021: 1

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