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Spatial hash-joins

Authors:

Chinya V. RavishankarAuthors Info & Claims

ACM SIGMOD Record, Volume 25, Issue 2

Pages 247 - 258

https://doi.org/10.1145/235968.233337

Published: 01 June 1996 Publication History

Abstract

We examine how to apply the hash-join paradigm to spatial joins, and define a new framework for spatial hash-joins. Our spatial partition functions have two components: a set of bucket extents and an assignment function, which may map a data item into multiple buckets. Furthermore, the partition functions for the two input datasets may be different.We have designed and tested a spatial hash-join method based on this framework. The partition function for the inner dataset is initialized by sampling the dataset, and evolves as data are inserted. The partition function for the outer dataset is immutable, but may replicate a data item from the outer dataset into multiple buckets. The method mirrors relational hash-joins in other aspects. Our method needs no pre-computed indices. It is therefore applicable to a wide range of spatial joins.Our experiments show that our method outperforms current spatial join algorithms based on tree matching by a wide margin. Further, its performance is superior even when the tree-based methods have pre-computed indices. This makes the spatial hash-join method highly competitive both when the input datasets are dynamically generated and when the datasets have pre-computed indices.

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Cited By

Li TXu J(2023)Block-Join: A Partition-Based Method for Processing Spatio-Temporal JoinsWeb and Big Data10.1007/978-3-031-25201-3_30(397-411)Online publication date: 10-Feb-2023
https://doi.org/10.1007/978-3-031-25201-3_30
Glake DRitter NOcker FAhmady-Moghaddam NOsterholz DLenfers UClemen TDemartini GZuccon GCulpepper JHuang ZTong H(2021)Hierarchical Semantics Matching For Heterogeneous Spatio-temporal SourcesProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3482350(565-575)Online publication date: 26-Oct-2021
https://dl.acm.org/doi/10.1145/3459637.3482350
Kaitoua ARabl TMarkl V(2020)A distributed data exchange engine for polystoresit - Information Technology10.1515/itit-2019-003762:3-4(145-156)Online publication date: 4-Mar-2020
https://doi.org/10.1515/itit-2019-0037
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Index Terms

Spatial hash-joins
1. Information systems
  1. Data management systems
    1. Database design and models
2. Theory of computation
  1. Design and analysis of algorithms

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Published In

cover image ACM SIGMOD Record

ACM SIGMOD Record Volume 25, Issue 2

June 1996

557 pages

ISSN:0163-5808

DOI:10.1145/235968

Chairman:
T. H. Merrett
McGill Univ.
,
Editors:
H. V. Jagadish,
Inderpal Singh Mumick

Issue’s Table of Contents

SIGMOD '96: Proceedings of the 1996 ACM SIGMOD international conference on Management of data
June 1996
560 pages
ISBN:0897917944
DOI:10.1145/233269
Editor:
Jennifer Widom
Stanford Univ., Stanford, CT

Copyright © 1996 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 June 1996

Published in SIGMOD Volume 25, Issue 2

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Cited By

Li TXu J(2023)Block-Join: A Partition-Based Method for Processing Spatio-Temporal JoinsWeb and Big Data10.1007/978-3-031-25201-3_30(397-411)Online publication date: 10-Feb-2023
https://doi.org/10.1007/978-3-031-25201-3_30
Glake DRitter NOcker FAhmady-Moghaddam NOsterholz DLenfers UClemen TDemartini GZuccon GCulpepper JHuang ZTong H(2021)Hierarchical Semantics Matching For Heterogeneous Spatio-temporal SourcesProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3482350(565-575)Online publication date: 26-Oct-2021
https://dl.acm.org/doi/10.1145/3459637.3482350
Kaitoua ARabl TMarkl V(2020)A distributed data exchange engine for polystoresit - Information Technology10.1515/itit-2019-003762:3-4(145-156)Online publication date: 4-Mar-2020
https://doi.org/10.1515/itit-2019-0037
Bhattu SPotluri AKadari PR. B. V. S(2020)Generalized communication cost efficient multi-way spatial join: revisiting the curse of the last reducerGeoInformatica10.1007/s10707-019-00387-624:3(557-589)Online publication date: 14-Jan-2020
https://doi.org/10.1007/s10707-019-00387-6
Bouros PMamoulis N(2019)Spatial joinsSIGSPATIAL Special10.1145/3355491.335549411:1(13-21)Online publication date: 5-Aug-2019
https://dl.acm.org/doi/10.1145/3355491.3355494
Louri A(2019)Editorial from the Incoming Editor-in-ChiefIEEE Transactions on Computers10.1109/TC.2018.287942168:1(3-3)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.1109/TC.2018.2879421
Yoo JBoulware DKimmey D(2019)Parallel co-location mining with MapReduce and NoSQL systemsKnowledge and Information Systems10.1007/s10115-019-01381-yOnline publication date: 21-Aug-2019
https://doi.org/10.1007/s10115-019-01381-y
LE HTAKASU A(2018)G-HBase: A High Performance Geographical Database Based on HBaseIEICE Transactions on Information and Systems10.1587/transinf.2017DAP0017E101.D:4(1053-1065)Online publication date: 2018
https://doi.org/10.1587/transinf.2017DAP0017
Gulino AKaitoua ACeri S(2018)Optimal Binning for GenomicsIEEE Transactions on Computers10.1109/TC.2018.285488068:1(125-138)Online publication date: 10-Dec-2018
https://dl.acm.org/doi/10.1109/TC.2018.2854880
Luo JShi SYang GWang HLi J(2018)O2iJoin: An Efficient Index-Based Algorithm for Overlap Interval JoinJournal of Computer Science and Technology10.1007/s11390-018-1872-x33:5(1023-1038)Online publication date: 12-Sep-2018
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