High Performance Spark: Best Practices for Scaling and Optimizing Apache Spark

Abstract

With this book, you'll learn how to: Accelerate your ML workflows with integrations including PyTorch. Handle key skew and take advantage of Spark's new dynamic partitioning. Make your code reliable with scalable testing and validation techniques. Make Spark high performance. Deploy Spark on Kubernetes and similar environments.Take advantage of GPU acceleration with RAPIDS and resource profiles. Get your Spark jobs to run faster. Use Spark to productionize exploratory data science projects. Handle even larger datasets with Spark. Gain faster insights by reducing pipeline running times. Become an O’Reilly member and get unlimited acces.