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Simba: spatial in-memory big data analysis

Authors:

Minyi GuoAuthors Info & Claims

SIGSPACIAL '16: Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

Article No.: 86, Pages 1 - 4

https://doi.org/10.1145/2996913.2996935

Published: 31 October 2016 Publication History

Abstract

We present the Simba (<u>S</u>patial <u>I</u>n-Memory <u>B</u>ig data <u>A</u>nalytics) system, which offers scalable and efficient in-memory spatial query processing and analytics for big spatial data. Simba natively extends the Spark SQL engine to support rich spatial queries and analytics through both SQL and DataFrame API. It enables the construction of indexes over RDDs inside the engine in order to work with big spatial data and complex spatial operations. Simba also comes with an effective query optimizer, which leverages its indexes and novel spatial-aware optimizations, to achieve both low latency and high throughput in big spatial data analysis. This demonstration proposal describes key ideas in the design of Simba, and presents a demonstration plan.

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Cited By

Yang XGuan XPang ZKui XWu H(2024)GridMesaFuture Generation Computer Systems10.1016/j.future.2024.02.010155:C(324-339)Online publication date: 1-Jun-2024
https://dl.acm.org/doi/10.1016/j.future.2024.02.010
Ma MChen LOuyang XLiu XLi JJing N(2022)Efficient Interactive Global Cellular Signal Strength VisualizationIEEE Transactions on Big Data10.1109/TBDATA.2020.30295598:5(1209-1219)Online publication date: 1-Oct-2022
https://doi.org/10.1109/TBDATA.2020.3029559
Doulkeridis CVlachou APelekis NTheodoridis Y(2021)A Survey on Big Data Processing Frameworks for Mobility AnalyticsACM SIGMOD Record10.1145/3484622.348462650:2(18-29)Online publication date: 31-Aug-2021
https://dl.acm.org/doi/10.1145/3484622.3484626
Show More Cited By

Index Terms

Simba: spatial in-memory big data analysis
1. Information systems
  1. Data management systems
    1. Database management system engines

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Information & Contributors

Information

Published In

cover image ACM Other conferences

SIGSPACIAL '16: Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

October 2016

649 pages

ISBN:9781450345897

DOI:10.1145/2996913

General Chairs:
Mohamed Ali
University of Washington, Tacoma
,
Shawn Newsam
University of California, Merced
,
Program Chairs:
Matthias Renz
George Mason University, USA
,
Goce Trajcevski
Northwestern University, USA
,
Siva Ravada
Oracle Corporation, USA

Copyright © 2016 Owner/Author.

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 31 October 2016

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Author Tags

Qualifiers

Demonstration

Funding Sources

National Science Foundation
National Basic Research Program (973 Program)
National Natural Science Foundation of China
Science and Technology Commission of Shanghai Municipality

Conference

SIGSPATIAL'16

SIGSPATIAL'16: 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

October 31 - November 3, 2016

California, Burlingame

Acceptance Rates

SIGSPACIAL '16 Paper Acceptance Rate 40 of 216 submissions, 19%;

Overall Acceptance Rate 257 of 1,238 submissions, 21%

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Citations

Cited By

Yang XGuan XPang ZKui XWu H(2024)GridMesaFuture Generation Computer Systems10.1016/j.future.2024.02.010155:C(324-339)Online publication date: 1-Jun-2024
https://dl.acm.org/doi/10.1016/j.future.2024.02.010
Ma MChen LOuyang XLiu XLi JJing N(2022)Efficient Interactive Global Cellular Signal Strength VisualizationIEEE Transactions on Big Data10.1109/TBDATA.2020.30295598:5(1209-1219)Online publication date: 1-Oct-2022
https://doi.org/10.1109/TBDATA.2020.3029559
Doulkeridis CVlachou APelekis NTheodoridis Y(2021)A Survey on Big Data Processing Frameworks for Mobility AnalyticsACM SIGMOD Record10.1145/3484622.348462650:2(18-29)Online publication date: 31-Aug-2021
https://dl.acm.org/doi/10.1145/3484622.3484626
Ma MYang AWu YChen LLi JJing N(2020)DiSAProceedings of the 28th International Conference on Advances in Geographic Information Systems10.1145/3397536.3422333(147-150)Online publication date: 3-Nov-2020
https://dl.acm.org/doi/10.1145/3397536.3422333
Liu QZheng LChen L(2020)RIDE: A System for Generalized Region of Interest Discovery and Exploration2020 IEEE 36th International Conference on Data Engineering (ICDE)10.1109/ICDE48307.2020.00158(1738-1741)Online publication date: Apr-2020
https://doi.org/10.1109/ICDE48307.2020.00158
Belussi AMigliorini SEldawy A(2020)Cost estimation of spatial join in spatialhadoopGeoInformatica10.1007/s10707-020-00414-xOnline publication date: 5-Jul-2020
https://doi.org/10.1007/s10707-020-00414-x
Belussi ACarra DMigliorini SNegri M(2019)Efficient MapReduce computation of topological relations for big geometriesProceedings of the 8th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data10.1145/3356999.3365466(1-8)Online publication date: 5-Nov-2019
https://dl.acm.org/doi/10.1145/3356999.3365466
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
Xiong WLi RPeng JWu YGuo NJing N(2019)Geo-Gap Tree: A Progressive Query and Visualization Method for Massive Spatial DataIEEE Access10.1109/ACCESS.2019.29295317(99428-99440)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2929531
Mamoulis N(2019)Query Processing: JoinsEncyclopedia of Big Data Technologies10.1007/978-3-319-77525-8_219(1345-1351)Online publication date: 20-Feb-2019
https://doi.org/10.1007/978-3-319-77525-8_219
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