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TurboFlux: A Fast Continuous Subgraph Matching System for Streaming Graph Data

Title
TurboFlux: A Fast Continuous Subgraph Matching System for Streaming Graph Data
Authors
HAN, WOOK SHINKyoungmin KimIn SeoJeong-Hoon LeeSungpack HongHassan ChafiHyungyu ShinGeonhwa Jeong
POSTECH Authors
HAN, WOOK SHIN
Date Issued
Jun-2018
Publisher
ACM
Abstract
A dynamic graph is defined by an initial graph and a graph update stream consisting of edge insertions and deletions. Identifying and monitoring critical patterns in the dynamic graph is important in various application domains such as fraud detection, cyber security, and emergency response. Given a dynamic data graph and a query graph, a continuous subgraph matching system reports positive matches for an edge insertion and reports negative matches for an edge deletion. Previous systems show significantly low throughput due to either repeated subgraph matching for each edge update or expensive overheads in maintaining enormous intermediate results. We present a fast continuous subgraph matching system called TurboFlux which provides high throughput over a fast graph update stream. TurboFlux employs a concise representation of intermediate results, and its execution model allows fast incremental maintenance. Our empirical evaluation shows that TurboFlux significantly outperforms existing competitors by up to six orders of magnitude. © 2018 Association for Computing Machinery.
URI
http://oasis.postech.ac.kr/handle/2014.oak/92217
DOI
10.1145/3183713.3196917
ISSN
0730-8078
Article Type
Article
Citation
Proceedings of the ACM SIGMOD International Conference on Management of Data, page. 411 - 426, 2018-06
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 HAN, WOOK SHIN
Dept. of Creative IT Engin.
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