this is not a beginner's guide, so you need some working knowledge of Scala and spark beforehand. <Learning Spark> and <Spark in Action> will lay a good foundation for this book. The target reader is spark programmer, all the content focuses on how to write high performance spark code, especially how to use the spark core and spark SQL API. there is nothing about how to admin or configure a spark cluster. In this latter area, one can try <expert Hadoop administration> . Having that said, this book have done a great job in explaining the nuances of writing spark code. highly recommended.

If you're a real hacker, you'll love this book. If you're not, and you would like to be, you'll find it frustrating, but if you stick with it, you will grow as a professional. If you're not, and you know you never will be, I suggest you start working on a nursing, phlebotomy or massage therapy certifation before people in the first two groups figure out how to automate your job.

Apache spark moves along the continuum of parallel processing. “Apache Spark is a high-performance, general-purpose distributed computing system that has become the most active Apache open source project with more than 1,000 active contributors”. The authors go on to state “Spark enables us to process large quantities of data, beyond what can fit on a single machine, with a high-level, relatively easy-to-use API”.

Most people in (and out) of IT will never have any contact with Spark. I need to know about it only because my job involves having at least a superficial knowledge of every significant aspect of IT.

This book presumes you are already conversant with Apache Spark and need no education or hand-holding in that regard.

Rather this book’s goal is to help the reader make their Spark queries “faster, able to handle larger data sizes, and use fewer resources”. Being able to at least read Scala is highly recommended.

The entire book is loaded with detailed examples. For the casual reader, such as myself, lacking a Spark environment to play in, there is an empty feeling – you can read the examples, study them, but not run them.

Having read literally dozens or more programming cookbooks during the course of my career, this one feels right, but without being able to run the examples, that’s just as an assumption. It does, however, make me wish I had some huge datasets to work on. Maybe I can get a job with the NSA? I bet there are a lot of Spark experts there.

Jerry

This book is filled with useful optimization tidbits for those already familiar with using Spark. It’s not a fun read, and I couldn’t imagine where to begin to find the resources to practice the content.

Book came in faster than expected and in perfect condition!

much improved compared with 1st edition, more elaboration on joining datasets. good to explain in one language.

This book clarifies lots of my questions on Spark. I especially appreciate the walk through joins.

Overall, I thought this was a very good book. It strikes a good balance between detailed instruction and depth and being a guidebook, not an instruction manual. It's the usual high quality that I've come to expect from O'Reilly, and I feel much more confident about my understanding of Spark, both as a user and of the inner workings.

Much of the book is written with a focus on performance. There's some discussion of statistical concepts, but the book is clearly aimed at helping the reader use Spark in a resource-efficient manner (which makes a lot of sense, given that Spark comes into play when you're tackling large data sets).

Virtually all of the code examples are written in Scala. When I began reading, my Scala abilities were fairly limited, but the authors do a good job of parsing and commenting on the code such that I now feel much stronger in Scala, as well. They do have a chapter that discusses using Python and Java (including JVM), but most of the book is presented through Scala.

My one complaint about this book is that it's a bit heavy on the code. It's possible that it's necessary, but I ended up skimming most of the coding examples, and it made for some tedious reading at times. Then again, there were several examples that I scrutinized closely, and having thorough examples did help me learn quite a bit of Scala.

Good book

Clarity, simplicity and beautiful diagrams and presentation. You cannot get better than this.

The book is well written, but cover a too small part of streaming. I'm looking for a good way to optimize spark streaming jobs. I have done a round in the web but couldn't find something really useful.

El libro es tal y como se espera. Muchos ejemplos, muy bien comentado y bien aclarados los puntos. Perfecto iniciados N el mundo Spark o gente que tenga ciertas dudas.

Best spark in depth reference book