research-article

ASTRO: A Datalog System for Advanced Stream Reasoning

Authors:

Sahil M. Gandhi,

Carlo ZanioloAuthors Info & Claims

CIKM '18: Proceedings of the 27th ACM International Conference on Information and Knowledge Management

Pages 1863 - 1866

https://doi.org/10.1145/3269206.3269223

Published: 17 October 2018 Publication History

Abstract

The rise of the Internet of Things (IoT) and the recent focus on a gamut of 'Smart City' initiatives world-wide have pushed for new advances in data stream systems to (1) support complex analytics and evolving graph applications as continuous queries, and (2) deliver fast and scalable processing on large data streams. Unfortunately current continuous query languages (CQL) lack the features and constructs needed to support the more advanced applications. For example recursive queries are now part of SQL, Datalog, and other query languages, but they are not supported by most CQLs, a fact that caused a significant loss of expressive power, which is further aggravated by the limitation that only non-blocking queries can be supported. To overcome these limitations we have developed an a dvanced st ream r easo ning system ASTRO that builds on recent advances in supporting aggregates in recursive queries. In this demo, we will briefly elucidate the formal Streamlog semantics, which combined with the Pre-Mappability (PreM) concept, allows the declarative specification of many complex continuous queries, which are then efficiently executed in real-time by the portable ASTRO architecture. Using different case studies, we demonstrate (i) the ease-of-use, (ii) the expressive power and (iii) the robustness of our system, as compared to other state-of-the-art declarative CQL systems.

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Cited By

Ronca AKaminski MCuenca Grau BHorrocks I(2022)The delay and window size problems in rule-based stream reasoningArtificial Intelligence10.1016/j.artint.2022.103668306(103668)Online publication date: May-2022
https://doi.org/10.1016/j.artint.2022.103668
Zaniolo CDas AGu JLi MLi YWang J(2019)Proceedings 35th International Conference on Logic Programming (Technical Communications)Electronic Proceedings in Theoretical Computer Science10.4204/EPTCS.306.29306(255-258)Online publication date: 19-Sep-2019
https://doi.org/10.4204/EPTCS.306.29
Gu JWatanabe YMazza WShkapsky AYang MDing LZaniolo CBoncz PManegold SAilamaki ADeshpande AKraska T(2019)RaSQLProceedings of the 2019 International Conference on Management of Data10.1145/3299869.3324959(467-484)Online publication date: 25-Jun-2019
https://dl.acm.org/doi/10.1145/3299869.3324959
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ASTRO: A Datalog System for Advanced Stream Reasoning

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cover image ACM Conferences

CIKM '18: Proceedings of the 27th ACM International Conference on Information and Knowledge Management

October 2018

2362 pages

ISBN:9781450360142

DOI:10.1145/3269206

General Chair:
Alfredo Cuzzocrea
University of Trieste, Italy
,
Program Chairs:
James Allan
University of Massachusetts, USA
,
Norman Paton
University of Manchester, United Kingdom
,
Divesh Srivastava
AT&T Labs Research, USA
,
Rakesh Agrawal
Data Insights Lab, USA
,
Andrei Broder
Google Research, USA
,
Mohammed Zaki
Rensselaer Polytechnic Institute, USA
,
Selcuk Candan
Arizona State University, USA
,
Alexandros Labrinidis
University of Pittsburgh, USA
,
Assaf Schuster
Technion, Israel
,
Haixun Wang
Google Research, USA

Copyright © 2018 ACM.

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Published: 17 October 2018

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October 22 - 26, 2018

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Cited By

Ronca AKaminski MCuenca Grau BHorrocks I(2022)The delay and window size problems in rule-based stream reasoningArtificial Intelligence10.1016/j.artint.2022.103668306(103668)Online publication date: May-2022
https://doi.org/10.1016/j.artint.2022.103668
Zaniolo CDas AGu JLi MLi YWang J(2019)Proceedings 35th International Conference on Logic Programming (Technical Communications)Electronic Proceedings in Theoretical Computer Science10.4204/EPTCS.306.29306(255-258)Online publication date: 19-Sep-2019
https://doi.org/10.4204/EPTCS.306.29
Gu JWatanabe YMazza WShkapsky AYang MDing LZaniolo CBoncz PManegold SAilamaki ADeshpande AKraska T(2019)RaSQLProceedings of the 2019 International Conference on Management of Data10.1145/3299869.3324959(467-484)Online publication date: 25-Jun-2019
https://dl.acm.org/doi/10.1145/3299869.3324959
DAS AZANIOLO C(2019)A Case for Stale Synchronous Distributed Model for Declarative Recursive ComputationTheory and Practice of Logic Programming10.1017/S147106841900035819:5-6(1056-1072)Online publication date: 20-Sep-2019
https://doi.org/10.1017/S1471068419000358

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