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Dynamic Prefetching of Data Tiles for Interactive Visualization

Authors:

Leilani Battle,

Michael StonebrakerAuthors Info & Claims

SIGMOD '16: Proceedings of the 2016 International Conference on Management of Data

Pages 1363 - 1375

https://doi.org/10.1145/2882903.2882919

Published: 14 June 2016 Publication History

Abstract

In this paper, we present ForeCache, a general-purpose tool for exploratory browsing of large datasets. ForeCache utilizes a client-server architecture, where the user interacts with a lightweight client-side interface to browse datasets, and the data to be browsed is retrieved from a DBMS running on a back-end server. We assume a detail-on-demand browsing paradigm, and optimize the back-end support for this paradigm by inserting a separate middleware layer in front of the DBMS. To improve response times, the middleware layer fetches data ahead of the user as she explores a dataset.

We consider two different mechanisms for prefetching: (a) learning what to fetch from the user's recent movements, and (b) using data characteristics (e.g., histograms) to find data similar to what the user has viewed in the past. We incorporate these mechanisms into a single prediction engine that adjusts its prediction strategies over time, based on changes in the user's behavior. We evaluated our prediction engine with a user study, and found that our dynamic prefetching strategy provides: (1) significant improvements in overall latency when compared with non-prefetching systems (430% improvement); and (2) substantial improvements in both prediction accuracy (25% improvement) and latency (88% improvement) relative to existing prefetching techniques.

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Cited By

Bancilhon MSiu ARossi RLipka N(2024)Toward an Optimized Human-AI Reviewing Strategy for Contract InspectionThe New Era of Business Intelligence [Working Title]10.5772/intechopen.1005255Online publication date: 1-Jul-2024
https://doi.org/10.5772/intechopen.1005255
Herbort ORaßbach PKunde W(2024)Where scrollbars are clicked, and whyCognitive Research: Principles and Implications10.1186/s41235-024-00551-z9:1Online publication date: 19-Apr-2024
https://doi.org/10.1186/s41235-024-00551-z
Yang JJoo HYerramreddy SMoritz DBattle L(2024)Optimizing Dataflow Systems for Scalable Interactive VisualizationProceedings of the ACM on Management of Data10.1145/36392762:1(1-25)Online publication date: 26-Mar-2024
https://dl.acm.org/doi/10.1145/3639276
Show More Cited By

Index Terms

Dynamic Prefetching of Data Tiles for Interactive Visualization
1. Human-centered computing
  1. Visualization
    1. Visualization application domains
      1. Visual analytics
2. Information systems
  1. Data management systems

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Published In

cover image ACM Conferences

SIGMOD '16: Proceedings of the 2016 International Conference on Management of Data

June 2016

2300 pages

ISBN:9781450335317

DOI:10.1145/2882903

General Chairs:
Fatma Özcan
IBM Research, USA
,
Georgia Koutrika
HP Labs, USA
,
Program Chair:
Sam Madden
Massachusetts Institute of Technology, USA

Copyright © 2016 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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SIGMOD: ACM Special Interest Group on Management of Data

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New York, NY, United States

Publication History

Published: 14 June 2016

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National Science Foundation

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SIGMOD/PODS'16

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SIGMOD

SIGMOD/PODS'16: International Conference on Management of Data

June 26 - July 1, 2016

California, San Francisco, USA

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

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Citations

Cited By

Bancilhon MSiu ARossi RLipka N(2024)Toward an Optimized Human-AI Reviewing Strategy for Contract InspectionThe New Era of Business Intelligence [Working Title]10.5772/intechopen.1005255Online publication date: 1-Jul-2024
https://doi.org/10.5772/intechopen.1005255
Herbort ORaßbach PKunde W(2024)Where scrollbars are clicked, and whyCognitive Research: Principles and Implications10.1186/s41235-024-00551-z9:1Online publication date: 19-Apr-2024
https://doi.org/10.1186/s41235-024-00551-z
Yang JJoo HYerramreddy SMoritz DBattle L(2024)Optimizing Dataflow Systems for Scalable Interactive VisualizationProceedings of the ACM on Management of Data10.1145/36392762:1(1-25)Online publication date: 26-Mar-2024
https://dl.acm.org/doi/10.1145/3639276
Li NLiang TJiang SWang CLi C(2024)Interactive visual query of density maps on latent space via flow‐based modelsTransactions in GIS10.1111/tgis.1316428:4(884-901)Online publication date: 11-Apr-2024
https://doi.org/10.1111/tgis.13164
Ha SMonadjemi SOttley A(2024)Guided By AI: Navigating Trust, Bias, and Data Exploration in AI‐Guided Visual AnalyticsComputer Graphics Forum10.1111/cgf.1510843:3Online publication date: 10-Jun-2024
https://doi.org/10.1111/cgf.15108
Heer JMoritz D(2024)Mosaic: An Architecture for Scalable & Interoperable Data ViewsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2023.332718930:1(436-446)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TVCG.2023.3327189
Battle LOttley A(2024)What Do We Mean When We Say “Insight”? A Formal Synthesis of Existing TheoryIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2023.332669830:9(6075-6088)Online publication date: Sep-2024
https://doi.org/10.1109/TVCG.2023.3326698
Aoyagi RTakahashi KShimomura YTakizawa H(2024)Combining Lossy Compression with Multi-Level Caching for Data Staging over Network2024 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)10.1109/IPDPSW63119.2024.00059(212-221)Online publication date: 27-May-2024
https://doi.org/10.1109/IPDPSW63119.2024.00059
Saha SAryal NBattle LTermehchy A(2024)User Learning In Interactive Data Exploration2024 IEEE 40th International Conference on Data Engineering (ICDE)10.1109/ICDE60146.2024.00460(5660-5661)Online publication date: 13-May-2024
https://doi.org/10.1109/ICDE60146.2024.00460
Mitra SYoung MBreidt JPallickara SPallickara SFox GRana OFazio MVillari M(2023)Rubiks: Rapid Explorations and Summarization over High Dimensional Spatiotemporal DatasetsProceedings of the IEEE/ACM 10th International Conference on Big Data Computing, Applications and Technologies10.1145/3632366.3632393(1-11)Online publication date: 4-Dec-2023
https://dl.acm.org/doi/10.1145/3632366.3632393
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