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.
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Sharing the knowledge of experts
O'Reilly's mission is to change the world by sharing the knowledge of innovators. For over 40 years, we've inspired companies and individuals to do new things (and do them better) by providing the skills and understanding that are necessary for success.
Our customers are hungry to build the innovations that propel the world forward. And we help them do just that.
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From the Preface
Who This Book Is For
Most developers who grapple with big data are data engineers, data scientists, or machine learning engineers. This book is aimed at those professionals who are looking to use Spark to scale their applications to handle massive amounts of data.
In particular, data engineers will learn how to use Spark’s Structured APIs to perform complex data exploration and analysis on both batch and streaming data; use Spark SQL for interactive queries; use Spark’s built-in and external data sources to read, refine, and write data in different file formats as part of their extract, transform, and load (ETL) tasks; and build reliable data lakes with Spark and the open source Delta Lake table format.
For data scientists and machine learning engineers, Spark’s MLlib library offers many common algorithms to build distributed machine learning models. We will cover how to build pipelines with MLlib, best practices for distributed machine learning, how to use Spark to scale single-node models, and how to manage and deploy these models using the open source library MLflow.
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Customer reviews
Well organized and solid information
Reviewed in the United States on September 4, 2020
It was easy to follow the book. The setup of Spark shell was also clearly written. I also find the instructions online to install spark locally to be sufficient as well. The book is well organized to delineate different components of Spark, e.g. intro, structured api, streaming, optimizations, data lake, ml deployment options. While ML deployment needs for individual business use cases are highly specific, I find the overview deployment framework provided by the book to be helpful. I also liked that the book uses screenshots of Spark UI and arrows to point in the screenshots to explain the UI, since the UI can be hard to understand. The code samples and the graphics in other sections are useful as well. There’s also coverage on how to connect to different apps, like beeline (which I’ve never heard of), tableau, thrift. Overall, the book contains solid information on the inner workings of Spark. I would recommend giving this book a read!
Reviewed in the United States on September 4, 2020
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Reviewed in the United States on July 25, 2022
I used the book as an extra study resource when taking some Databricks certifications. It was a great addition to my study materials.
Covers theoretical and practical aspects of the spark ecosystem in great depth
By Arturo Amador Cruz on July 25, 2022
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.By Arturo Amador Cruz on July 25, 2022
I used the book as an extra study resource when taking some Databricks certifications. It was a great addition to my study materials.
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Reviewed in the United States on January 28, 2022
Reviewed in the United States on September 4, 2020
Well organized and solid information
By JA on September 3, 2020
It was easy to follow the book. The setup of Spark shell was also clearly written. I also find the instructions online to install spark locally to be sufficient as well. The book is well organized to delineate different components of Spark, e.g. intro, structured api, streaming, optimizations, data lake, ml deployment options. While ML deployment needs for individual business use cases are highly specific, I find the overview deployment framework provided by the book to be helpful. I also liked that the book uses screenshots of Spark UI and arrows to point in the screenshots to explain the UI, since the UI can be hard to understand. The code samples and the graphics in other sections are useful as well. There’s also coverage on how to connect to different apps, like beeline (which I’ve never heard of), tableau, thrift. Overall, the book contains solid information on the inner workings of Spark. I would recommend giving this book a read!
By JA on September 3, 2020
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Top reviews from other countries
Josh Fry
Nicely laid out and explained
Reviewed in the United Kingdom on February 9, 2022
Nicely laid out and explained
Reviewed in the United Kingdom on February 9, 2022
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.Reviewed in the United Kingdom on February 9, 2022
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.
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Neville Andrade
Really well written technical book
Reviewed in Germany on November 15, 2020
