Spark in Action

  • 15h 34m 14s
  • Marko Bonaci, Petar Zecevic
  • Manning Publications
  • 2018

Spark in Action teaches you the theory and skills you need to effectively handle batch and streaming data using Spark. You'll get comfortable with the Spark CLI as you work through a few introductory examples. Then, you'll start programming Spark using its core APIs. Along the way, you'll work with structured data using Spark SQL, process near-real-time streaming data, apply machine learning algorithms, and munge graph data using Spark GraphX. For a zero-effort startup, you can download the preconfigured virtual machine ready for you to try the book's code. Fully updated for Spark 2.0.

Big data systems distribute datasets across clusters of machines, making it a challenge to efficiently query, stream, and interpret them. Spark can help. It is a processing system designed specifically for distributed data. It provides easy-to-use interfaces, along with the performance you need for production-quality analytics and machine learning. Spark 2 also adds improved programming APIs, better performance, and countless other upgrades.

In this Audiobook

  • Chapter 1 - Introduction to Apache Spark
  • Chapter 2 - Spark Fundamentals
  • Chapter 3 - Writing Spark Applications
  • Chapter 4 - The Spark API in Depth
  • Chapter 5 - Sparkling Queries with Spark SQL
  • Chapter 6 - Ingesting Data with Spark Streaming
  • Chapter 7 - Getting Smart with MLlib
  • Chapter 8 - ML: Classification and Clustering
  • Chapter 9 - Connecting the Dots with GraphX
  • Chapter 10 - Running Spark
  • Chapter 11 - Running on a Spark Standalone Cluster
  • Chapter 12 - Running on YARN and Mesos
  • Chapter 13 - Case Study: Real-Time Dashboard
  • Chapter 14 - Deep Learning on Spark with H2O