Apache Spark: Tips, Tricks, & Techniques [Video]

More Information
  • Compose Spark jobs from actions and transformations
  • Create highly concurrent Spark programs by leveraging immutability
  • Ways to avoid the most expensive operation in the Spark API—Shuffle
  • How to save data for further processing by picking the proper data format saved by Spark
  • Parallelize keyed data; learn of how to use Spark's Key/Value API
  • Re-design your jobs to use reduceByKey instead of groupBy
  • Create robust processing pipelines by testing Apache Spark jobs
  • Solve repeated problems by leveraging the GraphX API

Apache Spark has been around for quite some time, but do you really know how to get the most out of Spark? This course aims at giving you new possibilities; you will explore many aspects of Spark, some you may have never heard of and some you never knew existed.

In this course you'll learn to implement some practical and proven techniques to improve particular aspects of programming and administration in Apache Spark. You will explore 7 sections that will address different aspects of Spark via 5 specific techniques with clear instructions on how to carry out different Apache Spark tasks with hands-on experience. The techniques are demonstrated using practical examples and best practices.

By the end of this course, you will have learned some exciting tips, best practices, and techniques with Apache Spark. You will be able to perform tasks and get the best data out of your databases much faster and with ease.

All the code and supporting files for this course are available on Github at https://github.com/PacktPublishing/Apache-Spark-Tips-Tricks-Techniques

Style and Approach

This step-by-step and fast-paced guide will help you learn different techniques you can use to optimize your testing time, speed, and results with a practical approach, take your skills to the next level, and get you up-and-running with Spark.

  • Speed up your Spark jobs by reducing shuffles
  • Leverage the Key/Value API in your big data processing to make your jobs work faster with lower network traffic
  • Test Spark jobs using the unit, integration, and end-to-end techniques to make your data pipeline robust and bullet proof
Course Length 2 hours 26 minutes
ISBN 9781789801125
Date Of Publication 30 Nov 2018


Tomasz Lelek

Tomasz Lelek is a software engineer, programming mostly in Java and Scala. He has been working with the Spark and ML APIs for the past 6 years, with production experience in processing petabytes of data. He is passionate about nearly everything associated with software development and believes that we should always try to consider different solutions and approaches before attempting to solve a problem. Recently, he was also a speaker at conferences in Poland—Confitura, and JDD (Java Developers Day) and at Krakow Scala User Group. He has also conducted a live coding session at the Geecon Conference.