Learning Spark 2e: Lightning-Fast Data Analytics

I've just started my role as a Data Engineer where I looked at Azure's Data Factory. I needed to learn PySpark so I picked up this book and found it a super useful guide. It is explained clearly, and whilst it's clearly aimed at someone who has been in the industry longer than I, I found I could easily understand it.I haven't read the chapter on streaming or the two chapters on machine learning as it isn't applicable to me, but everything else has been just what I needed. Well done to the authors for putting together such an amazing guide.If you want to see the different chapter contents, I've added them as photos for your ease.

This is the best demystification of Spark I've found. Well worth reading. Explanation are really superb.

You should probably have some familiarity with machine learning and python before you pick this book up, but it's a decent introduction to Spark.

This book is a great resource to learn about spark. It covers in detail the concepts related to the Spark architecture, theoretical concepts about parallelization and topics related to optimizing analytical pipelines running on Spark. The book has a very nice section about the delta lake. Also covers MLflow yup a good level of detail, more like a complement to the docs. The section on machines learning includes theoretical explanations on how some ML algorithms change when running then parallely, as MLlib does.I used the book as an extra study resource when taking some Databricks certifications. It was a great addition to my study materials.

Asi como dice el titulo este libro me ayudo a pasar la certificacion de Spark y DatabricksDenle del capitulo 1 al 7

If you want to learn Spark 3.x+ this book is for you. Easy to read and with practical examples. Recommend it!

Buen libro como complemento de “Spark The Definitive Guide”, que para no es la referencia principal. Este libro da una versión resumida del que acabo de comentar con unos cuantos ejercicios adicionales que pueden ser bastante útiles para la comprensión de la teoría.