Searching for authors named "Vassilis Papadimos" – sorted by Relevance.
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Distributed Queries without Distributed State
- Traditionally, distributed queries have been optimized centrally and executed synchronously. We outline a framework that relaxes both of these constraints using mutant query plans: XML representations of query plans that can also include verbatim XML data, references to resource locations (URLs), or
- Cited by 5 (1 self) – Add To MetaCart
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Distributed Query Processing and Catalogs for Peer-to-Peer Systems
- Peer-to-peer (P2P) architectures are commonly used for file-sharing applications. The reasons for P2P's popularity in file sharing -- fault tolerance, scalability, and ease of deployment -- also make it a good model for distributed data management. In this paper, we introduce a scalable P2P fr
- Cited by 40 (0 self) – Add To MetaCart
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OGI at OHSU
- Stream processing is important for many applications, such as network traffic monitoring, network trace analysis and financial data processing, but the features of streams and stream applications make some traditional database query evaluation techniques inappropriate for them. Window queries are bo
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Distributed Queries without Distributed State
- Traditionally, distributed queries have been optimized centrally and executed synchronously. We outline a framework that relaxes both of these constraints using mutant query plans: XML representations of query plans that can also include verbatim XML data, references to resource locations (URLs),
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Semantics of data streams and operators
- Abstract. What does a data stream mean? Much of the extensive work on query operators and query processing for data streams has proceeded without the benefit of an answer to this question. While such imprecision may be tolerable when dealing with simple cases, such as flat data, guaranteed physical
- Cited by 1 (0 self) – Add To MetaCart
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Semantics and evaluation techniques for window aggregates in data streams
- A windowed query operator breaks a data stream into possibly overlapping subsets of data and computes results over each. Many stream systems can evaluate window aggregate queries. However, current stream systems suffer from a lack of an explicit definition of window semantics. As a result, their imp
- Cited by 17 (1 self) – Add To MetaCart
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No pane, no gain: efficient evaluation of sliding-window aggregates over data streams
- Window queries are proving essential to data-stream processing. In this paper, we present an approach for evaluating sliding-window aggregate queries that reduces both space and computation time for query execution. Our approach divides overlapping windows into disjoint panes, computes sub-aggregate
- Cited by 9 (0 self) – Add To MetaCart

