Encodings for Range Minimum Queries over Bounded Alphabets

Range minimum queries (RMQs) are fundamental operations with widespread applications in database management, text indexing and computational biology. While many space-efficient data structures have been designed for RMQs on arrays with arbitrary elements, there has not been any results developed for the case when the alphabet size is small, which is the case in many practical scenarios where RMQ structures are used. In this paper, we investigate the encoding complexity of RMQs on arrays over bounded alphabet. We consider both one-dimensional (1D) and two-dimensional (2D) arrays. For the 1D case, we present a near-optimal space encoding. For constant-sized alphabets, this also supports the queries in constant time. For the 2D case, we systematically analyze the 1-sided, 2-sided, 3-sided and 4-sided queries and derive lower bounds for encoding space, and also matching upper bounds that support efficient queries in most cases. Our results demonstrate that, even with the bounded alphabet restriction, the space requirements remain close to those for the general alphabet case.

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Publication Details

Journal
DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)
Published
2025-01-01
DOI
https://doi.org/10.4230/lipics.cpm.2025.25
Primary Topic
Algorithms and Data Compression
Type
article
Field-Weighted Citation Impact
0.00

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article

Encodings for Range Minimum Queries over Bounded Alphabets

DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)
Algorithms and Data Compression
article

Encodings for Range Minimum Queries over Bounded Alphabets

article en

Abstract

Range minimum queries (RMQs) are fundamental operations with widespread applications in database management, text indexing and computational biology. While many space-efficient data structures have been designed for RMQs on arrays with arbitrary elements, there has not been any results developed for the case when the alphabet size is small, which is the case in many practical scenarios where RMQ structures are used. In this paper, we investigate the encoding complexity of RMQs on arrays over bounded alphabet. We consider both one-dimensional (1D) and two-dimensional (2D) arrays. For the 1D case, we present a near-optimal space encoding. For constant-sized alphabets, this also supports the queries in constant time. For the 2D case, we systematically analyze the 1-sided, 2-sided, 3-sided and 4-sided queries and derive lower bounds for encoding space, and also matching upper bounds that support efficient queries in most cases. Our results demonstrate that, even with the bounded alphabet restriction, the space requirements remain close to those for the general alphabet case.

DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)
Chungnam National University (KR), Norwegian University of Science and Technology (NO)
Chungnam National University
Quality Education
Openalex Percentile: Top 74%
Algorithms and Data Compression
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Encodings for Range Minimum Queries over Bounded Alphabets · DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) (2025) | TGRS Research Map | TGRS