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.
