Catcher: A Cache Analysis System for Top-k Pub/Sub Service
Authors: 
Baolong Mei, Yafei Li, Wei Chen, Linshen Luan, Guanglei Zhu, Yuanyuan Jin, Jianliang XuAuthors Info & Claims
Baolong Mei, Yafei Li, Wei Chen, Linshen Luan, Guanglei Zhu, Yuanyuan Jin, Jianliang XuAuthors Info & ClaimsPages 4389 - 4392
Abstract
Top-k Publish/Subscribe (TkPS) service is widely studied in spatial database, with various cache-based methods proposed to address its efficiency challenge in top-k result maintenance. These methods require in-depth exploration of relationships between cache updates and different factors (e.g., data distribution) to optimize cache performance. However, there is currently no system available that assists developers in conducting comprehensive cache analyses within TkPS services. We therefore introduce Catcher, a multi-functional cache analysis system designed for TkPS services. It not only enables users to intuitively analyze the entire maintenance process of top-k results but also aids in identifying bottlenecks and potential optimization spaces of caches. Catcher provides two user-friendly interfaces that allow users to employ simple and easy-to-use consoles to perform statistical analysis. Furthermore, Catcher offers the real-time evaluation of cache-based methods, providing users with instant analysis. We have demonstrated the usability of Catcher on real-world datasets. A short video of our demonstration can be found at https://youtu.be/qI81HoypB0w.
References
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- Catcher: A Cache Analysis System for Top-k Pub/Sub Service
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Published: 01 August 2024
Published in PVLDB Volume 17, Issue 12
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