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- Waldemar Hummer
- Distributed Systems Group Vienna University of Technology Vienna Austria
説明
<jats:p>Stream processing is a computing paradigm that has emerged from the necessity of handling high volumes of data in real time. In contrast to traditional databases, stream‐processing systems perform continuous queries and handle data on‐the‐fly. Today, a wide range of application areas relies on efficient pattern detection and queries over streams. The advent of Cloud computing fosters the development of elastic stream‐processing platforms, which are able to dynamically adapt based on different cost–benefit trade‐offs. This article provides an overview of the historical evolution and the key concepts of stream processing, with special focus on adaptivity and Cloud‐based elasticity.</jats:p><jats:p>This article is categorized under: <jats:list list-type="explicit-label"> <jats:list-item><jats:p>Application Areas > Data Mining Software Tools</jats:p></jats:list-item> <jats:list-item><jats:p>Technologies > Computer Architectures for Data Mining</jats:p></jats:list-item> </jats:list></jats:p>
収録刊行物
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- WIREs Data Mining and Knowledge Discovery
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WIREs Data Mining and Knowledge Discovery 3 (5), 333-345, 2013-08-12
Wiley
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キーワード
詳細情報 詳細情報について
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- CRID
- 1360576121288787712
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- ISSN
- 19424795
- 19424787
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- データソース種別
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- Crossref