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Elastic stream processing in the Cloud
Author(s) -
Hummer Waldemar,
Satzger Benjamin,
Dustdar Schahram
Publication year - 2013
Publication title -
wiley interdisciplinary reviews: data mining and knowledge discovery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.506
H-Index - 47
eISSN - 1942-4795
pISSN - 1942-4787
DOI - 10.1002/widm.1100
Subject(s) - stream processing , cloud computing , computer science , data stream mining , elasticity (physics) , data processing , focus (optics) , distributed computing , data stream , software , data science , database , data mining , operating system , telecommunications , materials science , physics , optics , composite material
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. This article is categorized under: Application Areas > Data Mining Software Tools Technologies > Computer Architectures for Data Mining