Article

STHoles: a multidimensional workload-aware histogram

Authors:

Surajit Chaudhuri,

Luis GravanoAuthors Info & Claims

SIGMOD '01: Proceedings of the 2001 ACM SIGMOD international conference on Management of data

Pages 211 - 222

https://doi.org/10.1145/375663.375686

Published: 01 May 2001 Publication History

Abstract

Attributes of a relation are not typically independent. Multidimensional histograms can be an effective tool for accurate multiattribute query selectivity estimation. In this paper, we introduce STHoles, a “workload-aware” histogram that allows bucket nesting to capture data regions with reasonably uniform tuple density. STHoles histograms are built without examining the data sets, but rather by just analyzing query results. Buckets are allocated where needed the most as indicated by the workload, which leads to accurate query selectivity estimations. Our extensive experiments demonstrate that STHoles histograms consistently produce good selectivity estimates across synthetic and real-world data sets and across query workloads, and, in many cases, outperform the best multidimensional histogram techniques that require access to and processing of the full data sets during histogram construction.

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Hurst ALucani DZhang Q(2024)PairwiseHist: Fast, Accurate and Space-Efficient Approximate Query Processing with Data CompressionProceedings of the VLDB Endowment10.14778/3648160.364818117:6(1432-1445)Online publication date: 1-Feb-2024
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Belussi AMigliorini SEldawy A(2024)A Generic Machine Learning Model for Spatial Query Optimization based on Spatial EmbeddingsACM Transactions on Spatial Algorithms and Systems10.1145/365763310:4(1-33)Online publication date: 13-Apr-2024
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Index Terms

STHoles: a multidimensional workload-aware histogram
1. Information systems
  1. Data management systems
    1. Database design and models

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Published In

cover image ACM Conferences

SIGMOD '01: Proceedings of the 2001 ACM SIGMOD international conference on Management of data

May 2001

630 pages

ISBN:1581133324

DOI:10.1145/375663

ACM SIGMOD Record Volume 30, Issue 2
June 2001
625 pages
ISSN:0163-5808
DOI:10.1145/376284
Editors:
Timos Sellis
National Technical Univ. of Athens
,
Sharad Mehrotra
Univ. of California at Irvine
Issue’s Table of Contents

Copyright © 2001 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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Published: 01 May 2001

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SIGMOD/PODS01: ACM SIGMOD International Conference on Management of Data

May 21 - 24, 2001

California, Santa Barbara, USA

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SIGMOD '01 Paper Acceptance Rate 44 of 293 submissions, 15%;

Overall Acceptance Rate 785 of 4,003 submissions, 20%

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Cited By

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https://dl.acm.org/doi/10.14778/3685800.3685828
Hurst ALucani DZhang Q(2024)PairwiseHist: Fast, Accurate and Space-Efficient Approximate Query Processing with Data CompressionProceedings of the VLDB Endowment10.14778/3648160.364818117:6(1432-1445)Online publication date: 1-Feb-2024
https://dl.acm.org/doi/10.14778/3648160.3648181
Belussi AMigliorini SEldawy A(2024)A Generic Machine Learning Model for Spatial Query Optimization based on Spatial EmbeddingsACM Transactions on Spatial Algorithms and Systems10.1145/365763310:4(1-33)Online publication date: 13-Apr-2024
https://dl.acm.org/doi/10.1145/3657633
Cheng QLi HWang DZhang YPeng Z(2024)LAF: A Local Depth Autoregressive Framework for Cardinality Estimation of Multi-attribute QueriesWeb and Big Data10.1007/978-981-97-2387-4_20(296-311)Online publication date: 28-Apr-2024
https://doi.org/10.1007/978-981-97-2387-4_20
Yang JZhang YWang BYang X(2024)BoundEst: Estimating Join Cardinalities with Tight Upper BoundsWeb and Big Data10.1007/978-981-97-2303-4_29(437-451)Online publication date: 29-May-2024
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Faltín TTrigonakis VBerdai AFusco LIorgulescu CHong SChafi HHartig OYoshida Y(2023)Better Distributed Graph Query Planning With Scouting QueriesProceedings of the 6th Joint Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA)10.1145/3594778.3594884(1-9)Online publication date: 18-Jun-2023
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Sheng YCao XFang YZhao KQi JCong GZhang W(2023)WISK: A Workload-aware Learned Index for Spatial Keyword QueriesProceedings of the ACM on Management of Data10.1145/35893321:2(1-27)Online publication date: 20-Jun-2023
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Lin YXu ZZhang YLi YZhang J(2023)Cardinality estimation with smoothing autoregressive modelsWorld Wide Web10.1007/s11280-023-01195-726:5(3441-3461)Online publication date: 28-Jul-2023
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Zhu LZhang SSong XMa QMeng W(2023)Processing Reverse Nearest Neighbor Queries Based on Unbalanced Multiway Region Tree IndexWeb Information Systems Engineering – WISE 202310.1007/978-981-99-7254-8_57(733-747)Online publication date: 21-Oct-2023
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