Appendix . Theres More with Spark
We've covered some of the hottest areas in Spark from the new Catalyst optimizer to RDDs and DataFrames. We have covered the MLLib and GraphX library before looking at some use cases to see how an application can be built on Spark. However, as this book is just an introduction, we have skipped various important topics along the way. This was intentional as we wanted to keep the book at a readable level to help you get started, but with pointed references along the way that can help you master a particular topic. However, there are certain key areas which we would like to cover as a part of an Appendix, which we believe are important for you to develop and deploy your Spark applications.
In this Appendix, we would like to cover
- Performance tuning Spark
- Data serialization
- Memory management
- Sizing up your executors
- Handling skew
- Security
- Key configuration properties
- Configuring Jupyter with Spark
- Shared variables: advanced
Let's get started.
