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Ganesan / Chellappan

Practical Apache Spark

Using the Scala API

Medium: Buch
ISBN: 978-1-4842-3651-2
Verlag: Apress
Erscheinungstermin: 13.12.2018
Lieferfrist: bis zu 10 Tage
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.

Produkteigenschaften


  • Artikelnummer: 9781484236512
  • Medium: Buch
  • ISBN: 978-1-4842-3651-2
  • Verlag: Apress
  • Erscheinungstermin: 13.12.2018
  • Sprache(n): Englisch
  • Auflage: 1. Auflage 2018
  • Produktform: Kartoniert, Paperback
  • Gewicht: 561 g
  • Seiten: 280
  • Format (B x H x T): 178 x 254 x 17 mm
  • Ausgabetyp: Kein, Unbekannt

Autoren/Hrsg.

Autoren

Ganesan, Dharanitharan

Chellappan, Subhashini

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.