Book Image

Frank Kane's Taming Big Data with Apache Spark and Python

By : Frank Kane
Book Image

Frank Kane's Taming Big Data with Apache Spark and Python

By: Frank Kane

Overview of this book

Frank Kane’s Taming Big Data with Apache Spark and Python is your companion to learning Apache Spark in a hands-on manner. Frank will start you off by teaching you how to set up Spark on a single system or on a cluster, and you’ll soon move on to analyzing large data sets using Spark RDD, and developing and running effective Spark jobs quickly using Python. Apache Spark has emerged as the next big thing in the Big Data domain – quickly rising from an ascending technology to an established superstar in just a matter of years. Spark allows you to quickly extract actionable insights from large amounts of data, on a real-time basis, making it an essential tool in many modern businesses. Frank has packed this book with over 15 interactive, fun-filled examples relevant to the real world, and he will empower you to understand the Spark ecosystem and implement production-grade real-time Spark projects with ease.
Table of Contents (13 chapters)
Title Page
Credits
About the Author
www.PacktPub.com
Customer Feedback
Preface
7
Where to Go From Here? – Learning More About Spark and Data Science

More troubleshooting and managing dependencies


In this section, I want to talk about a few more troubleshooting tips with Spark. There are weird things that will happen and have happened to me in the past when working with Spark. It's not always obvious what to do about them, so let me impart some of my experience to you here. Then we'll talk about managing code dependencies within Spark jobs as well.

Troubleshooting

So let's talk about troubleshooting a little bit more. I can tell you, I did need to do some troubleshooting to get that million ratings job running successfully on my Spark cluster. We'll start by talking about logs. Where are the logs? We saw some stuff scroll by from the driver script, and in practice, if you're running on EMR, that's pretty much all you'll have to go on. Now, as I showed you, if you're in standalone mode and you have access directly, on the network to your master node, all the log information is displayed in this beautiful graphical form in the web UI. However...