Zobrazeno 1 - 10
of 781
pro vyhledávání: '"H.2.4"'
Autor:
Zhong, Suyang, Rigger, Manuel
Database Management System (DBMS) developers have implemented extensive test suites to test their DBMSs. For example, the SQLite test suites contain over 92 million lines of code. Despite these extensive efforts, test suites are not systematically re
Externí odkaz:
http://arxiv.org/abs/2410.21731
Anomaly Detection and Inlet Pressure Prediction in Water Distribution Systems Using Machine Learning
Autor:
Khoa, Tran Dang
This study presents two models to optimize pressure management in water distribution networks. The first model forecasts pressure at distribution points and compares predictions with actual data to detect anomalies such as leaks and blockages. Early
Externí odkaz:
http://arxiv.org/abs/2410.09530
Autor:
Goldblum, Zack, Xu, Zhongchuan, Shi, Haoer, Orzechowski, Patryk, Spence, Jamaal, Davis, Kathryn A, Litt, Brian, Sinha, Nishant, Wagenaar, Joost
The exponential growth of neuroscientific data necessitates platforms that facilitate data management and multidisciplinary collaboration. In this paper, we introduce Pennsieve - an open-source, cloud-based scientific data management platform built t
Externí odkaz:
http://arxiv.org/abs/2409.10509
Autor:
Eslami, Navid, Dayan, Niv
Range filters are probabilistic data structures that answer approximate range emptiness queries. They aid in avoiding processing empty range queries and have use cases in many application domains such as key-value stores and social web analytics. How
Externí odkaz:
http://arxiv.org/abs/2408.05625
In data exploration, users need to analyze large data files quickly, aiming to minimize data-to-analysis time. While recent adaptive indexing approaches address this need, they are cases where demonstrate poor performance. Particularly, during the in
Externí odkaz:
http://arxiv.org/abs/2407.18702
Improving the performance and reducing the cost of cloud data systems is increasingly challenging. Data processing units (DPUs) are a promising solution, but utilizing them for data processing needs characterizing the new hardware and recognizing the
Externí odkaz:
http://arxiv.org/abs/2407.13658
This extended report presents DDS, a novel disaggregated storage architecture enabled by emerging networking hardware, namely DPUs (Data Processing Units). DPUs can optimize the latency and CPU consumption of disaggregated storage servers. However, u
Externí odkaz:
http://arxiv.org/abs/2407.13618
Autor:
Wang, Wenlong, Du, David Hung-Chang
In this paper, we introduce LearnedKV, a novel tiered key-value (KV) store that seamlessly integrates a Log-Structured Merge (LSM) tree with a Learned Index. This integration yields superior read and write performance compared to standalone indexing
Externí odkaz:
http://arxiv.org/abs/2406.18892
Database systems are often confronted with queries that join many tables but ultimately only output comparatively small aggregate information. Despite all advances in query optimisation, the explosion of intermediate results as opposed to a much smal
Externí odkaz:
http://arxiv.org/abs/2406.17076
We study the optimization of navigational graph queries, i.e., queries which combine recursive and pattern-matching fragments. Current approaches to their evaluation are not effective in practice. Towards addressing this, we present a number of novel
Externí odkaz:
http://arxiv.org/abs/2406.05417