Results 1 to 10 of about 4,566,242 (371)
Query Rewriting and Optimization for Ontological Databases [PDF]
arXiv, 2014 Ontological queries are evaluated against a knowledge base consisting of an extensional database and an ontology (i.e., a set of logical assertions and constraints which derive new intensional knowledge from the extensional database), rather than directly on the extensional database.
Gottlob, Georg +2 more
arxiv +5 more sources
Neo: A Learned Query Optimizer [PDF]
Proceedings of the VLDB Endowment, 2019 Query optimization is one of the most challenging problems in database systems. Despite the progress made over the past decades, query optimizers remain extremely complex components that require a great deal of hand-tuning for specific workloads and ...
Alizadeh, Mohammad +7 more
core +7 more sources
A technique for parallel query optimization using MapReduce framework and a semantic-based clustering method [PDF]
PeerJ Computer Science, 2021 Query optimization is the process of identifying the best Query Execution Plan (QEP). The query optimizer produces a close to optimal QEP for the given queries based on the minimum resource usage.
Elham Azhir +4 more
doaj +3 more sources
Query Optimization for Distributed Spatio-Temporal Sensing Data Processing [PDF]
Sensors, 2022 The unprecedented development of Internet of Things (IoT) technology produces humongous amounts of spatio-temporal sensing data with various geometry types.
Xin Li +3 more
doaj +2 more sources
Evolutionary Algorithms for Query Op-timization in Distributed Database Sys-tems: A review [PDF]
Advances in Distributed Computing and Artificial Intelligence Journal, 2018 Evolutionary Algorithms are bio-inspired optimization problem-solving approaches that exploit principles of biological evolution. , such as natural selection and genetic inheritance.
Zulfiqar ALI +2 more
doaj +4 more sources
Sampling-Based Query Re-Optimization [PDF]
SIGMOD Conference, 2016 Despite of decades of work, query optimizers still make mistakes on "difficult" queries because of bad cardinality estimates, often due to the interaction of multiple predicates and correlations in the data.
Bruno N. +5 more
core +2 more sources
Roq: Robust Query Optimization Based on a Risk-aware Learned Cost Model [PDF]
arXivQuery optimizers in relational database management systems (RDBMSs) search for execution plans expected to be optimal for a given queries. They use parameter estimates, often inaccurate, and make assumptions that may not hold in practice. Consequently, they may select execution plans that are suboptimal at runtime, when these estimates and assumptions ...
Corvinelli, Vincent +3 more
arxiv +2 more sources
IRBEVF-Q: Optimization of Image–Radar Fusion Algorithm Based on Bird’s Eye View Features [PDF]
SensorsIn autonomous driving, the fusion of multiple sensors is considered essential to improve the accuracy and safety of 3D object detection. Currently, a fusion scheme combining low-cost cameras with highly robust radars can counteract the performance ...
Ganlin Cai, Feng Chen, Ente Guo
doaj +2 more sources
Bao: Making Learned Query Optimization Practical [PDF]
SIGMOD Conference, 2020 Recent efforts applying machine learning techniques to query optimization have shown few practical gains due to substantive training overhead, inability to adapt to changes, and poor tail performance.
Ryan Marcus +5 more
semanticscholar +1 more source
COMPASS: Online Sketch-based Query Optimization for In-Memory Databases
SIGMOD Conference, 2021 Cost-based query optimization remains a critical task in relational databases even after decades of research and industrial development. Query optimizers rely on a large range of statistical synopses for accurate cardinality estimation. As the complexity
Yesdaulet Izenov +3 more
semanticscholar +1 more source