all AI news
Hydro: Adaptive Query Processing of ML Queries
March 25, 2024, 4:42 a.m. | Gaurav Tarlok Kakkar, Jiashen Cao, Aubhro Sengupta, Joy Arulraj, Hyesoon Kim
cs.LG updates on arXiv.org arxiv.org
Abstract: Query optimization in relational database management systems (DBMSs) is critical for fast query processing. The query optimizer relies on precise selectivity and cost estimates to effectively optimize queries prior to execution. While this strategy is effective for relational DBMSs, it is not sufficient for DBMSs tailored for processing machine learning (ML) queries. In ML-centric DBMSs, query optimization is challenging for two reasons. First, the performance bottleneck of the queries shifts to user-defined functions (UDFs) that …
abstract arxiv cost cs.db cs.lg database database management management optimization prior processing queries query query processing relational relational database strategy systems type
More from arxiv.org / cs.LG updates on arXiv.org
Jobs in AI, ML, Big Data
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Software Engineering Manager, Generative AI - Characters
@ Meta | Bellevue, WA | Menlo Park, CA | Seattle, WA | New York City | San Francisco, CA
Senior Operations Research Analyst / Predictive Modeler
@ LinQuest | Colorado Springs, Colorado, United States