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 complete architecture 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 ForDevelopers and professionals who deal with batch and stream data processing.
Practical Apache Spark: Using the Scala API
Chapter 1: Scala - Functional Programming Aspects
Chapter 2: Single & Multi-node cluster setup
Chapter 3: Introduction to Apache Spark and Spark Core
Chapter 4: Spark SQL, Dataframes & Datasets
Chapter 5: Introduction to Spark Streaming
Chapter 6: Spark Structured Streaming
Chapter 7: Spark Streaming with Kafka
Chapter 8: Spark Machine Learning Library
Chapter 9: Working with SparkR
Chapter 10: Spark - Real time use case
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