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Efficiently Searching In-Memory Sorted Arrays: Revenge of the Interpolation Search?

Summary: Proposes SIP and TIP, in-memory search for sorted arrays with slope-based and three-point interpolation to beat Binary Search. Adds a meta-algorithm to auto-switch among SIP, TIP, and Binary Search, yielding up to 4x/2-3x speedups on varied data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5606
Venue
SIGMOD
Year
2019
Pagerank
8.2087602e-05
Overall Rank
2,732 | 81.00%
DOI
10.1145/3299869.3300075

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Showing 4 of 4 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
64 Improved Histograms for Selectivity Estimation of Range Predicates 1996 SIGMOD 0.00063612837
102 The Case for Learned Index Structures 2018 SIGMOD 0.00049545203
540 Design and Evaluation of Main Memory Hash Join Algorithms for Multi-core CPUs 2011 SIGMOD 0.0002063443
638 On B-tree Indices for Skewed Distributions 1992 VLDB 0.00018798677
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