Practical Apache Spark

Using the Scala API

Subhashini Chellappan, Dharanitharan Ganesan (Autoren)

Buch | Softcover

280 Seiten

2018 | 1st ed.
Apress (Verlag)
978-1-4842-3651-2 (ISBN)

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Work with Apache Spark using Scala to deploy and set up single-node, multi-node, and high-availability clusters. This book discusses various components of Spark such as Spark Core, DataFrames, Datasets and SQL, Spark Streaming, Spark MLib, and R on Spark with the help of practical code snippets for each topic. Practical Apache Spark also covers the integration of Apache Spark with Kafka with examples. You’ll follow a learn-to-do-by-yourself approach to learning – learn the concepts, practice the code snippets in Scala, and complete the assignments given to get an overall exposure.
On completion, you’ll have knowledge of the functional programming aspects of Scala, and hands-on expertise in various Spark components. You’ll also become familiar with machine learning algorithms with real-time usage.
What You Will Learn

Discover the functional programming features of Scala

Understand the completearchitecture of Spark and its components
Integrate Apache Spark with Hive and Kafka

Use Spark SQL, DataFrames, and Datasets to process data using traditional SQL queries

Work with different machine learning concepts and libraries using Spark's MLlib packages

Who This Book Is For
Developers and professionals who deal with batch and stream data processing.

Subhashini Chellappan is a technology enthusiast with expertise in the big data and cloud space. She has rich experience in both academia and the software industry. Her areas of interest and expertise are centered on business intelligence, big data analytics and cloud computing. Dharanitharan Ganesan is a senior analyst with five years of experience in IT. He has a high level of exposure and experience in big data – Apache Hadoop, Apache Spark and various Hadoop ecosystem components. He has a proven track record of improving efficiency and productivity through the automation of various routine and administrative functions in business intelligence and big data technologies. His areas of interest and expertise are centered on machine learning algorithms, statistical modelling and predictive analysis.

1. Scala - Functional Programming Aspects. - 2. Single & Multi-node cluster setup. - 3. Introduction to Apache Spark and Spark Core. - 4. Spark SQL, Dataframes & Datasets. - 5. Introduction to Spark Streaming. - 6. Spark Structured Streaming. - 7. Spark Streaming with Kafka. - 8. Spark Machine Learning Library. - 9. Working with SparkR. - 10. Spark - Real time use case.

Erscheinungsdatum	04.01.2019
Zusatzinfo	303 Illustrations, black and white; XVI, 280 p. 303 illus.
Verlagsort	Berkley
Sprache	englisch
Maße	178 x 254 mm
Themenwelt	Mathematik / Informatik ► Informatik ► Datenbanken
	Mathematik / Informatik ► Informatik ► Netzwerke
	Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge
	Informatik ► Theorie / Studium ► Compilerbau
Schlagworte	Apache Spark • Big Data • Kafka • machine learning • R • Scala
ISBN-10	1-4842-3651-3 / 1484236513
ISBN-13	978-1-4842-3651-2 / 9781484236512
Zustand	Neuware