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Abstract: The dQUOB system satisfies client need for specific information from high-volume data streams. The data streams we speak of are the flow of data existing during large-scale visualizations, video streaming to large numbers of distributed users, and high volume business transactions. We introduces the notion of conceptualizing a data stream as a set of relational database tables so that a scientist can request information with an SQL-like query. Transformation or computation that often needs to... (Update)
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.... rem PJ maybe yes any trt irt stats inter D O G S Telegraph [11] op or parl no yes any trt stats l dr intra D O L S dQUOB [21, 22] op or no no no ac statstrt stats inter D L A Table 1. Properties of existing adaptive query processing techniques (PPHJs) is proposed in [20]...
...of the query) which is in turn determined by the time bound. Data stream support: This work leverages off the dQUOB system [3], wherein an SQL query is evaluated purely over data streams instead of tables in a database. Our plan is to be able to seamlessly switch from...
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BibTeX entry: (Update)
Beth Plale and Karsten Schwan. dQUOB: Managing large data flows using dynamic embedded queries. Technical Report GIT-CC-00-07, Georgia Institute of Technology, Atlanta, Georgia, August 2000. http://citeseer.ist.psu.edu/plale00dquob.html More
@inproceedings{ plale00dquob,
author = "Beth Plale and Karsten Schwan",
title = "{dQUOB}: Managing Large Data Flows using Dynamic Embedded Queries",
booktitle = "{HPDC}",
pages = "263-270",
year = "2000",
url = "citeseer.ist.psu.edu/plale00dquob.html" }
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13 Realizing distributed computational laboratories - Plale, Elling et al. - 1999
13 The case for prediction-based best-effort real-time systems - Dinda, Lowekamp et al. - 1999
10 Development of an intelligent monitoring and control system .. - Afjeh, Homer et al. - 1995 ACM DBLP
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