BS-tree: A gapped data-parallel B-tree

Fuente: arXiv
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Autori principali: Tsitsigkos, Dimitrios, Michalopoulos, Achilleas, Mamoulis, Nikos, Terrovitis, Manolis
Natura: Preprint
Pubblicazione: 2025
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author Tsitsigkos, Dimitrios
Michalopoulos, Achilleas
Mamoulis, Nikos
Terrovitis, Manolis
author_facet Tsitsigkos, Dimitrios
Michalopoulos, Achilleas
Mamoulis, Nikos
Terrovitis, Manolis
contents We propose BS-tree, an in-memory implementation of the B+-tree that adopts the structure of the disk-based index (i.e., a balanced, multiway tree), setting the node size to a memory block that can be processed fast and in parallel using SIMD instructions. A novel feature of the BS-tree is that it enables gaps (unused positions) within nodes by duplicating key values. This allows (i) branchless SIMD search within each node, and (ii) branchless update operations in nodes without key shifting. We implement a frame of reference (FOR) compression mechanism, which allows nodes to have varying capacities, and can greatly decrease the memory footprint of BS-tree. We compare our approach to existing main-memory indices and learned indices under different workloads of queries and updates and demonstrate its robustness and superiority compared to previous work in single- and multi-threaded processing.
format Preprint
id arxiv_https___arxiv_org_abs_2505_01180
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle BS-tree: A gapped data-parallel B-tree
Tsitsigkos, Dimitrios
Michalopoulos, Achilleas
Mamoulis, Nikos
Terrovitis, Manolis
Databases
We propose BS-tree, an in-memory implementation of the B+-tree that adopts the structure of the disk-based index (i.e., a balanced, multiway tree), setting the node size to a memory block that can be processed fast and in parallel using SIMD instructions. A novel feature of the BS-tree is that it enables gaps (unused positions) within nodes by duplicating key values. This allows (i) branchless SIMD search within each node, and (ii) branchless update operations in nodes without key shifting. We implement a frame of reference (FOR) compression mechanism, which allows nodes to have varying capacities, and can greatly decrease the memory footprint of BS-tree. We compare our approach to existing main-memory indices and learned indices under different workloads of queries and updates and demonstrate its robustness and superiority compared to previous work in single- and multi-threaded processing.
title BS-tree: A gapped data-parallel B-tree
topic Databases
url https://arxiv.org/abs/2505.01180