research-article

Massive streaming data analytics: a graph-based approach

Authors:

Jason Riedy,

David A. BaderAuthors Info & Claims

XRDS: Crossroads, The ACM Magazine for Students, Volume 19, Issue 3

Pages 37 - 43

https://doi.org/10.1145/2425676.2425689

Published: 01 March 2013 Publication History

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Abstract

Analyzing massive streaming graphs efficiently requires new algorithms, data structures, and computing platforms.

References

[1]

Rios, M. Euro 2012 Recap. 2012. http://blog.twitter.com/2012/07/euro-2012-recap.html

Google Scholar

[2]

Ball, P., Klingner, J., and Lum, K. Crowdsourced data is not a substitute for real statistics. 2011. http://benetech.blogspot.com/2011/03/crowdsourced-data-is-not-substitute-for.html

Google Scholar

[3]

James, J. How Much Data is Created Every Minute? 2012. http://www.domo.com/blog/2012/06/how-much-data-is-created-every-minute

Google Scholar

[4]

Georgia Tech team uses Twitter, blogs to monitor elections in developing nations. Georgia Institute of Technology. 2011. http://www.gatech.edu/newsroom/release.html?nid=71154

Google Scholar

[5]

Frias-Martinez, E. and Frias-Martinez, V. Enhancing Public Policy Decision Making using Large-Scale Cell Phone Data. 2012. http://www.unglobalpulse.org/publicpolicyandcellphonedata

Google Scholar

[6]

Overview; Visualization to Connect the Dots. Knight Foundation. http://overview.ap.org

Google Scholar

[7]

Consolidated volume in NYSE listed issues, 2010 -- current. 2011. NYSE Euronext. http://www.nyxdata.com/nysedata/asp/factbook/viewer_edition.asp?mode=table&key=3139&category=3

Google Scholar

[8]

Findings Regarding the Market Events of May 6, 2010; Report of The Staffs of the CFTC and SEC to the Joint Advisory Committee on Emerging Regulatory Issues. 2010. U.S. Commodity Futures Trading Commission. http://www.sec.gov/news/studies/2010/marketevents-report.pdf

Google Scholar

[9]

Bader, D. and Riedy, J., et al. STINGER: Spatio-Temporal Interaction Networks and Graphs (STING) Extensible Representation. 2012. http://www.cc.gatech.edu/stinger.

Google Scholar

[10]

Chakrabarti, D., Zhan, Y., and Faloutsos, C. R-MAT: A recursive model for graph mining. In the Proceedings of the 2004 SIAM International Conference on Data Mining (Nashville, TN, June 13--16). SIAM, Philadelphia, 2004.

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Patwary MGarg SBattula SKang B(2021)SDP: Scalable Real-time Dynamic Graph PartitionerIEEE Transactions on Services Computing10.1109/TSC.2021.3137932(1-1)Online publication date: 2021
https://doi.org/10.1109/TSC.2021.3137932
Patwary MGarg SKang B(2019)Window-based Streaming Graph Partitioning AlgorithmProceedings of the Australasian Computer Science Week Multiconference10.1145/3290688.3290711(1-10)Online publication date: 29-Jan-2019
https://dl.acm.org/doi/10.1145/3290688.3290711
Srinivasan SPollard SDas SNorris BBhowmick S(2019)A Shared-Memory Algorithm for Updating Tree-Based Properties of Large Dynamic NetworksIEEE Transactions on Big Data10.1109/TBDATA.2018.2870136(1-1)Online publication date: 2019
https://doi.org/10.1109/TBDATA.2018.2870136
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Index Terms

Massive streaming data analytics: a graph-based approach
1. Mathematics of computing
  1. Discrete mathematics
    1. Graph theory

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cover image XRDS: Crossroads, The ACM Magazine for Students

XRDS: Crossroads, The ACM Magazine for Students Volume 19, Issue 3

Scientific Computing

Spring 2013

64 pages

ISSN:1528-4972

EISSN:1528-4980

DOI:10.1145/2425676

Issue’s Table of Contents

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 March 2013

Published in XRDS Volume 19, Issue 3

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Patwary MGarg SBattula SKang B(2021)SDP: Scalable Real-time Dynamic Graph PartitionerIEEE Transactions on Services Computing10.1109/TSC.2021.3137932(1-1)Online publication date: 2021
https://doi.org/10.1109/TSC.2021.3137932
Patwary MGarg SKang B(2019)Window-based Streaming Graph Partitioning AlgorithmProceedings of the Australasian Computer Science Week Multiconference10.1145/3290688.3290711(1-10)Online publication date: 29-Jan-2019
https://dl.acm.org/doi/10.1145/3290688.3290711
Srinivasan SPollard SDas SNorris BBhowmick S(2019)A Shared-Memory Algorithm for Updating Tree-Based Properties of Large Dynamic NetworksIEEE Transactions on Big Data10.1109/TBDATA.2018.2870136(1-1)Online publication date: 2019
https://doi.org/10.1109/TBDATA.2018.2870136
Srinivasan SRiazi SNorris BDas SBhowmick S(2018)A Shared-Memory Parallel Algorithm for Updating Single-Source Shortest Paths in Large Dynamic Networks2018 IEEE 25th International Conference on High Performance Computing (HiPC)10.1109/HiPC.2018.00035(245-254)Online publication date: Dec-2018
https://doi.org/10.1109/HiPC.2018.00035
Srinivasan SBhowmick SDas S(2016)Application of Graph Sparsification in Developing Parallel Algorithms for Updating Connected Components2016 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)10.1109/IPDPSW.2016.180(885-891)Online publication date: May-2016
https://doi.org/10.1109/IPDPSW.2016.180
Jain NLiao GWillke TBoncz PNeumann T(2013)GraphBuilderFirst International Workshop on Graph Data Management Experiences and Systems10.1145/2484425.2484429(1-6)Online publication date: 23-Jun-2013
https://dl.acm.org/doi/10.1145/2484425.2484429

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Large-scale multilevel streaming data analytics

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