Learning Spark

Lightning-Fast Big Data Analysis

Data in all domains is getting bigger. How can you work with it efficiently? Recently updated for Spark 1.3, 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. This edition includes new information on Spark SQL, Spark Streaming, setup, and Maven coordinates. 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.
* Quickly dive into Spark capabilities such as distributed datasets, in-memory caching, and the interactive shell
* Leverage Spark’s powerful built-in libraries, including Spark SQL, Spark Streaming, and MLlib
* Use one programming paradigm instead of mixing and matching tools like Hive, Hadoop, Mahout, and Storm
* Learn how to deploy interactive, batch, and streaming applications
* Connect to data sources including HDFS, Hive, JSON, and S3
* Master advanced topics like data partitioning and shared variables
Portrait

Mark Hamstra has worked in cross-platform systems development for many years. Previously, that work was centered mostly on CAD software, systems and consulting. Mark now does data analytics development and consulting, with an emphasis applications of functional programming to Big Data problems. Matei Zaharia is a PhD student in the AMP Lab at UC Berkeley, working on topics in computer systems, cloud computing and big data. He is also a committer on Apache Hadoop and Apache Mesos. At Berkeley, he leads the development of the Spark cluster computing framework, and has also worked on projects including Mesos, the Hadoop Fair Scheduler, Hadoop's straggler detection algorithm, Shark, and multi-resource sharing. Matei got his undergraduate degree at the University of Waterloo in Canada.

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Einband Taschenbuch
Seitenzahl 274
Erscheinungsdatum 16.03.2015
Sprache Englisch
ISBN 978-1-4493-5862-4
Verlag O'Reilly UK Ltd.
Maße (L/B/H) 23,1/17,9/1,7 cm
Gewicht 488 g
Buch (Taschenbuch, Englisch)
31,99
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