MayBMS: A Probabilistic Database System User Manual
نویسندگان
چکیده
منابع مشابه
MayBMS: A System for Managing Large Uncertain and Probabilistic Databases
MayBMS is a state-of-the-art probabilistic database management system that has been built as an extension of Postgres, an open-source relational database management system. MayBMS follows a principled approach to leveraging the strengths of previous database research for achieving scalability. This article describes the main goals of this project, the design of query and update language, effici...
متن کاملManaging Probabilistic Data with MystiQ: The Can-Do, the Could-Do, and the Can't-Do
MystiQ is a system that allows users to define a probabilistic database, then to evaluate SQL queries over this database. MystiQ is a middleware: the data itself is stored in a standard relational database system, and MystiQ is providing the probabilistic semantics. The advantage of a middleware over a reimplementation from scratch is that it can leverage the infrastructure of an existing datab...
متن کاملMaking massive probabilistic databases practical
Existence of incomplete and imprecise data has moved the database paradigm from deterministic to probabilistic information. Probabilistic databases contain tuples that may or may not exist with some probability. As a result, the number of possible deterministic databases that can be instances of a probabilistic database grows exponentially with the number of probabilistic tuples. In this paper,...
متن کاملHighlights on published work ( with a bit of vision )
This paper overviews ENFrame, a framework for processing probabilistic data. In addition to relational query processing supported by existing probabilistic database management systems, ENFrame allows programming with loops, assignments, list comprehension, and aggregates to encode complex tasks such as clustering and classification of data retrieved via queries from probabilistic databases. We ...
متن کاملProbabilistic Data Programming with ENFrame
This paper overviews ENFrame, a programming framework for probabilistic data. In addition to relational query processing supported via an existing probabilistic database management system, ENFrame allows programming with loops, assignments, conditionals, list comprehension, and aggregates to encode complex tasks such as clustering and classification of probabilistic data. We explain the design ...
متن کامل