Fast Preprocessing for Optimal Orthogonal Range Reporting and Range Successor with Applications to Text Indexing
Younan Gao, Meng He, Yakov Nekrich

TL;DR
This paper introduces new data structures for orthogonal range queries that are constructed efficiently in $O(n\sqrt{ ext{log} ext{n}})$ time, matching optimal query times and improving preprocessing times for range reporting and successor problems.
Contribution
It presents the first data structures supporting optimal orthogonal range reporting and successor queries with $O(n\sqrt{ ext{log} ext{n}})$ preprocessing time.
Findings
Supports orthogonal range reporting in $O( ext{log} ext{log} ext{n}+k)$ time.
Supports orthogonal range successor in $O( ext{log} ext{log} ext{n})$ time.
Supports sorted range reporting in $O( ext{log} ext{log} ext{n}+k)$ time.
Abstract
Under the word RAM model, we design three data structures that can be constructed in time over points in an grid. The first data structure is an -word structure supporting orthogonal range reporting in time, where denotes output size and is an arbitrarily small constant. The second is an -word structure supporting orthogonal range successor in time, while the third is an -word structure supporting sorted range reporting in time. The query times of these data structures are optimal when the space costs must be within words. Their exact space bounds match those of the best known results achieving the same query times, and the construction time beats the previous bounds on preprocessing. Previously,…
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