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pro vyhledávání: '"Deeds"'
Cardinality Estimation is to estimate the size of the output of a query without computing it, by using only statistics on the input relations. Existing estimators try to return an unbiased estimate of the cardinality: this is notoriously difficult. A
Externí odkaz:
http://arxiv.org/abs/2412.00642
The tensor programming abstraction has become a foundational paradigm for modern computing. This framework allows users to write high performance programs for bulk computation via a high-level imperative interface. Recent work has extended this parad
Externí odkaz:
http://arxiv.org/abs/2408.14706
Graph workloads pose a particularly challenging problem for query optimizers. They typically feature large queries made up of entirely many-to-many joins with complex correlations. This puts significant stress on traditional cardinality estimation me
Externí odkaz:
http://arxiv.org/abs/2405.06767
Autor:
Ahrens, Willow, Collin, Teodoro Fields, Patel, Radha, Deeds, Kyle, Hong, Changwan, Amarasinghe, Saman
From FORTRAN to NumPy, arrays have revolutionized how we express computation. However, arrays in these, and almost all prominent systems, can only handle dense rectilinear integer grids. Real world arrays often contain underlying structure, such as s
Externí odkaz:
http://arxiv.org/abs/2404.16730
Autor:
Barnes, Matt, Abueg, Matthew, Lange, Oliver F., Deeds, Matt, Trader, Jason, Molitor, Denali, Wulfmeier, Markus, O'Banion, Shawn
Inverse reinforcement learning (IRL) offers a powerful and general framework for learning humans' latent preferences in route recommendation, yet no approach has successfully addressed planetary-scale problems with hundreds of millions of states and
Externí odkaz:
http://arxiv.org/abs/2305.11290
Recent work has reemphasized the importance of cardinality estimates for query optimization. While new techniques have continuously improved in accuracy over time, they still generally allow for under-estimates which often lead optimizers to make ove
Externí odkaz:
http://arxiv.org/abs/2211.09864
Recent work has demonstrated the catastrophic effects of poor cardinality estimates on query processing time. In particular, underestimating query cardinality can result in overly optimistic query plans which take orders of magnitude longer to comple
Externí odkaz:
http://arxiv.org/abs/2201.04166