Learning Spark : lightning-fast data analysis / Golden Karau, Andy Konwinski, Patrick Wendell & Matei Zaharia.

Contributor(s): Karau, Holden [autor.] | Konwinski, Andy [autor.] | Wendell, Patrick [autor.] | Zaharia, Matei [autor.]Material type: Text

TextLanguage: English Publisher: Sebastopol : O'Reilly Media Inc., 2015Copyright date: ©2015Edition: Primera ediciónDescription: xvi, 256 páginas : ilustraciones, gráficas ; 24 cmContent type: texto Media type: sin mediación Carrier type: volumenISBN: 9781449358624Subject(s): Análisis de datos -- Estudio y enseñanza | Almacenamiento de datos | Lenguajes de Programación (Computadores Electrónicos) | Algoritmos -- Software | Arquitectura de softwareDDC classification: 658.05

Contents:

1. Introduction to data analysis with Spark ; 2. Dowloading Spark and Getting Started ; 3. Programming with RDDs ; 4. Working with key/value pairs ; 5. Loading and saving your data ; 6. Advanced Spark programming ; 7. Running on a cluster ; 8. Tuning and debugging Spark ; 9. Spark SQL ; 10. Spark streaming ; 11. Machine learning sith MLlib.

Abstract: Data in all domains is getting bigger. How can you work with it efficiently?, this book introduces Apache Spark, the open source cluster computing system that makes data analytics fast to write and fast to run. With Spark, you can tackle big datasets quickly through simple APIs in Python, Java, and Scala. Written by the developers of Spark, this book will have data scientists and engineers up and running in no time. You'll learn how to express parallel jobs with just a few lines of code, and cover applications from simple batch jobs to stream processing and machine learning. editor.

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Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode	Item holds
Libros	Biblioteca CESA Diagonal 34 A No. 5 A - 23 Casa Incolda PBX: 339 53 00 serviciosbiblioteca@cesa.edu.co Piso 1	General	658.05 / L438 2015 (Browse shelf(Opens below))	Ej.1	Available (Sin restricciones)		7109101129

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Data in all domains is getting bigger. How can you work with it efficiently?, this book introduces Apache Spark, the open source cluster computing system that makes data analytics fast to write and fast to run. With Spark, you can tackle big datasets quickly through simple APIs in Python, Java, and Scala. Written by the developers of Spark, this book will have data scientists and engineers up and running in no time. You'll learn how to express parallel jobs with just a few lines of code, and cover applications from simple batch jobs to stream processing and machine learning. editor.

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