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This SpringerBrief presents the fundamental concepts of a specialized class of data stream, spatio-temporal data streams, and demonstrates their distributed processing using Big Data frameworks and platforms. It explores a consistent framework which facilitates a thorough understanding of all different facets of the technology, from basic definitions to state-of-the-art techniques. Key topics include spatio-temporal continuous queries, distributed stream processing, SQL-like language embedding, and trajectory stream clustering. Over the course of the book, the reader will become familiar with spatio-temporal data streams management and data flow processing, which enables the analysis of huge volumes of location-aware continuous data streams. Applications range from mobile object tracking and real-time intelligent transportation systems to traffic monitoring and complex event processing. Spatio-Temporal Data Streams is a valuable resource for researchers studying spatio-temporal data streams and Big Data analytics, as well as data engineers and data scientists solving data management and analytics problems associated with this class of data.
Produkteigenschaften
- Artikelnummer: 9781493965731
- Medium: Buch
- ISBN: 978-1-4939-6573-1
- Verlag: Springer
- Erscheinungstermin: 27.08.2016
- Sprache(n): Englisch
- Auflage: 2016. Auflage 2016
- Serie: SpringerBriefs in Computer Science
- Produktform: Kartoniert
- Gewicht: 220 g
- Seiten: 107
- Format (B x H x T): 159 x 233 x 10 mm
- Ausgabetyp: Kein, Unbekannt