Frost Optical Team

https://www.academia.edu › Parallel_Query_Processing
Parallel Query Processing This paper explores various methods of parallel query processing in SQL databases emphasizing the principles of data independence and the benefits of parallelism for

https://link.springer.com › rwe
Graefe G Encapsulation of parallelism in the volcano query processing system In Proc ACM SIGMOD Int Conf on Management of Data 1990 pp 102 111 Google Scholar Graefe G and Davison D L

https://awoc.wolski.fi › dlib › parallel-db-arch
Abstract In this paper we present a novel and complete approach on how to encapsulate parallelism for relational database query execution that strives for maximum resource utilization for both CPU and

https://ieeexplore.ieee.org › document
Volcano is a new data flow query processing system developed for database systems research and education All operators are designed and coded as if they were meant for a single

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Also some work on making join algorithms for interactive query systems that favor one input or the other based on user feedback Haas Hellerstein 97 Adaptive partitioning River Arpaci etal 99 adaptively

https://cs-people.bu.edu › mathan › reading-groups › ...
The Vol cano effort provides a rich environment for research and edu cation in database systems design heuristics for query opti mization parallel query execution and resource allocation Volcano

https://www.vldb.org › pvldb
In this paper we introduce HetExchange a parallel query execu tion framework that encapsulates the heterogeneous parallelism of modern multi CPU multi GPU servers and enables the paralleliza tion

https://cs186berkeley.net › static › notes
Parallelism through pipelining each operator processes the previous operator s output as it is being produced Parallelism through Partitioning partition data across multiple machines so that algorithms

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All other operators are programmed as for single process execution the exchange operator encapsulates all parallelism issues including the translation between demand driven dataflow within