TY - JOUR
T1 - Catcher: A Cache Analysis System for Top-k Pub/Sub Service
AU - Mei, Baolong
AU - Li, Yafei
AU - Chen, Wei
AU - Luan, Linshen
AU - Zhu, Guanglei
AU - Jin, Yuanyuan
AU - Xu, Jianliang
N1 - This work is supported by NSFC Grants 62372416, 61972362, and 62302460, HNSF Grant 242300421215, CPSF Grant 2022TQ0297, Hong Kong RGC Grant (R1015-23), and Guangdong Basic and Applied Basic Research Foundation (2023B1515130002).
Publisher Copyright:
© 2024, VLDB Endowment. All rights reserved.
PY - 2024/8
Y1 - 2024/8
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85205310046&partnerID=8YFLogxK
U2 - 10.14778/3685800.3685882
DO - 10.14778/3685800.3685882
M3 - Conference article
AN - SCOPUS:85205310046
SN - 2150-8097
VL - 17
SP - 4389
EP - 4392
JO - Proceedings of the VLDB Endowment
JF - Proceedings of the VLDB Endowment
IS - 12
T2 - 50th International Conference on Very Large Data Bases, VLDB 2024
Y2 - 26 August 2024 through 30 August 2024
ER -