Mastering Apache Spark 2.x

Romeo Kienzler

ISBN 10: 1786462745 / ISBN 13: 9781786462749

Editore: Packt Publishing, 2017

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Codice articolo 9781786462749

Dati bibliografici

• Titolo: Mastering Apache Spark 2.x
• Editore: Packt Publishing
• Data di pubblicazione: 2017
• Lingua: Inglese
• ISBN 10: 1786462745
• ISBN 13: 9781786462749
• Rilegatura: Taschenbuch
• Edizione: seconda edizione
• Condizione: Neu
• Dimensioni: 235 L x 191 A x 20 P (millimetri) 235 millimetri di larghezza per 191 millimetri di altezza per 20 millimetri di profondità
• Peso: 661 grammi

Descrizione articolo

Riassunto

Advanced analytics on your Big Data with latest Apache Spark 2.x

About This Book

• An advanced guide with a combination of instructions and practical examples to extend the most up-to date Spark functionalities.
• Extend your data processing capabilities to process huge chunk of data in minimum time using advanced concepts in Spark.
• Master the art of real-time processing with the help of Apache Spark 2.x

Who This Book Is For

If you are a developer with some experience with Spark and want to strengthen your knowledge of how to get around in the world of Spark, then this book is ideal for you. Basic knowledge of Linux, Hadoop and Spark is assumed. Reasonable knowledge of Scala is expected.

What You Will Learn

• Examine Advanced Machine Learning and DeepLearning with MLlib, SparkML, SystemML, H2O and DeepLearning4J
• Study highly optimised unified batch and real-time data processing using SparkSQL and Structured Streaming
• Evaluate large-scale Graph Processing and Analysis using GraphX and GraphFrames
• Apply Apache Spark in Elastic deployments using Jupyter and Zeppelin Notebooks, Docker, Kubernetes and the IBM Cloud
• Understand internal details of cost based optimizers used in Catalyst, SystemML and GraphFrames
• Learn how specific parameter settings affect overall performance of an Apache Spark cluster
• Leverage Scala, R and python for your data science projects

In Detail

Apache Spark is an in-memory cluster-based parallel processing system that provides a wide range of functionalities such as graph processing, machine learning, stream processing, and SQL. This book aims to take your knowledge of Spark

L'autore

Romeo Kienzler works as the chief data scientist in the IBM Watson IoT worldwide team, helping clients to apply advanced machine learning at scale on their IoT sensor data. He holds a Master's degree in computer science from the Swiss Federal Institute of Technology, Zurich, with a specialization in information systems, bioinformatics, and applied statistics. His current research focus is on scalable machine learning on Apache Spark. He is a contributor to various open source projects and works as an associate professor for artificial intelligence at Swiss University of Applied Sciences, Berne. He is a member of the IBM Technical Expert Council and the IBM Academy of Technology, IBM's leading brains trust.