Data-intensive text processing with MapReduce / Jimmy Lin and Chris Dyer

Von:

Lin, Jimmy, 1979- [VerfasserIn]

Mitwirkende(r):

Dyer, Chris [VerfasserIn]

Resource type: Ressourcentyp: BuchBuchSprache: Englisch Reihen: Synthesis lectures on human language technologies ; 7Verlag: [San Rafael, Calif.] : Morgan & Claypool Publishers, [2010]Copyright-Datum: ©2010Beschreibung: ix, 165 Seiten : Diagramme ; illISBN:

9781608453429

Schlagwörter:

Andere physische Formen: 9781608453436 | Erscheint auch als: Data-intensive text processing with MapReduce. Online-Ausgabe San Rafael : Morgan & Claypool, 2010. 1 Online-Ressource (IX, 163 Seiten) | Erscheint auch als: Data-intensive text processing with MapReduce. Online-Ausgabe San Rafael, Calif. : Morgan & Claypool, 2010. IX, 165 S.DDC-Klassifikation:

005.726

RVK: RVK: ST 270Zusammenfassung: Includes bibliographical referencesZusammenfassung: Our world is being revolutionized by data-driven methods: access to large amounts of data has generated new insights and opened exciting new opportunities in commerce, science, and computing applications. Processing the enormous quantities of data necessary for these advances requires large clusters, making distributed computing paradigms more crucial than ever. MapReduce is a programming model for expressing distributed computations on massive datasets and an execution framework for large-scale data processing on clusters of commodity servers. The programming model provides an easy-to-understand abstraction for designing scalable algorithms, while the execution framework transparently handles many system-level details, ranging from scheduling to synchronization to fault tolerance. This book focuses on MapReduce algorithm design, with an emphasis on text processing algorithms common in natural language processing, information retrieval, and machine learning. We introduce the notion of MapReduce design patterns, which represent general reusable solutions to commonly occurring problems across a variety of problem domains. This book not only intends to help the reader "think in MapReduce", but also discusses limitations of the programming model as wellPPN: PPN: 1608240657

Exemplare ( 1 )

Exemplare
Medientyp	Heimatbibliothek	Sammlung	Standort	Signatur	Status	Fälligkeitsdatum	Barcode
Handbibliothek	Fakultät für Informatik	D.Lin	Handbibliothek (Ausleihe und Einsicht nicht möglich)	2014 386	Ausgeliehen Ausleihe und Einsicht nicht möglich	30.09.2034	000673064090

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