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Spark in Action, by Petar Zecevic, Marko Bonaci
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Summary
Spark in Action teaches you the theory and skills you need to effectively handle batch and streaming data using Spark. Fully updated for Spark 2.0.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
About the Technology
Big data systems distribute datasets across clusters of machines, making it a challenge to efficiently query, stream, and interpret them. Spark can help. It is a processing system designed specifically for distributed data. It provides easy-to-use interfaces, along with the performance you need for production-quality analytics and machine learning. Spark 2 also adds improved programming APIs, better performance, and countless other upgrades.
About the Book
Spark in Action teaches you the theory and skills you need to effectively handle batch and streaming data using Spark. You'll get comfortable with the Spark CLI as you work through a few introductory examples. Then, you'll start programming Spark using its core APIs. Along the way, you'll work with structured data using Spark SQL, process near-real-time streaming data, apply machine learning algorithms, and munge graph data using Spark GraphX. For a zero-effort startup, you can download the preconfigured virtual machine ready for you to try the book's code.
What's Inside
- Updated for Spark 2.0
- Real-life case studies
- Spark DevOps with Docker
- Examples in Scala, and online in Java and Python
About the Reader
Written for experienced programmers with some background in big data or machine learning.
About the Authors
Petar Zečević and Marko Bonaći are seasoned developers heavily involved in the Spark community.
Table of Contents
PART 1 - FIRST STEPS- Sales Rank: #271617 in Books
- Published on: 2016-12-01
- Original language: English
- Dimensions: 9.30" h x .90" w x 7.30" l, .0 pounds
- Binding: Paperback
- 472 pages
About the Author
Petar Zecevic is a CTO at SV Group. During the last 14 years he has worked on various projects as a Java developer, team leader, consultant and software specialist. He is the founder and, with Marko, organizer of popular Spark@Zg meetup group.
Marko Bonaci has worked with Java for 13 years. He works Sematext as a Spark developer and consultant. Before that, he was team lead for SV Group's IBM Enterprise Content Management team.
Most helpful customer reviews
3 of 3 people found the following review helpful.
An excellent overview of "everything Spark"
By neuron
I've been working as a Data Scientist for the past few years, with a social science background, using R and Python, and I've been looking to up-skill myself into a sort of a Data Science Engineer role, and have learned some Scala in order to do this. The next logical step is learning the basics of Spark, and I decided to pick up this book, as I've never had a book from Manning let me down.
"Spark in Action" definitely delivers the introduction that I needed. Split into 4 parts, the book takes the reader on a tour of the Spark fundamentals, explaining the RDD data model in detail, after which it dives into the main functionality of Spark: Spark SQL, Spark Streaming, MLLib, SparkML, and GraphX. Later on, it covers the operational aspects of setting up a standalone Spark cluster, as well as running it on YARN and Mesos. Finally, a very well written case study of creating a real-time dashboard is presented, together with an explanation on how to use H20's Deep Learning services.
All the code examples in the book are written in Scala, which is ideal in my opinion, but the authors also provide matching examples in Java and Python on the book's GitHub repository. A VM with Spark already set up is also provided, so all the examples can be ran straight out of the box.
The book carefully balances between the Engineering and Data Science aspects of using Spark. Whether this is good or bad, depends on a reader's needs - I needed an initial overview of "everything Spark", and got exactly what I was looking for. On the other hand, the book is not going to teach an experienced Data Engineer how to tune all the nuts and bolts of a cluster, and neither is it going to teach an experienced Data Scientist how move completely from R/Python to Spark when it comes to Machine Learning.
Finally, the book is updated to cover Spark 2.0, which as far as I can see makes it unique on the market in that regard.
11 of 14 people found the following review helpful.
Mediocre book (Far better alternatives are available)
By Akram Ahmad
Page after page of dense and opaque writing left me cringing, but I waded my way through the book. Simply put, most all books by Manning publishers (and I've bought and read literally dozens of them) are uniformly great. Alas, this was an exception in that it left me utterly disappointed because the attempts at explanation were convoluted, unfortunately. It's a mediocre book, and far better alternatives are available, which I'll point out here:
[1] "Learning Spark: Lightning-Fast Big Data Analysis" by Holden Karau et al is plain awesome, clear and sparkling explanations of annotated code in all three Spark API(s) (i.e. Scala, Java, Python), [2] "Advanced Analytics with Spark: Patterns for Learning from Data at Scale" by Sandy Ryza et al is fantastic in its coverage of a broad range of application for the Spark platform, though make sure to digest the "Learning Spark" book first before reading it, and a newer book [3] "Big Data Analytics with Spark: A Practitioner's Guide to Using Spark for Large Scale Data Analysis" by Mohammed Guller is also excellent, with lots of clearly annotated code.
If you want a fuller list of of similar books, I invite you to check out my blog (titled "Best Hadoop and Spark Books") by searching online on the following keywords: programming-digressions blogspot.
4 of 5 people found the following review helpful.
A practical Spark book, good next step
By Mark Kerzner
“Spark in Action” has the standard Manning structure: it has four parts, “First Steps,” “Meet the Spark Family,” “Spark Ops,” (where “ops” stands for operations), and “Bringing it all Together.”
The first part takes you from zero to using Spark on a standalone computer. The second part goes through the tools that come with Spark: SQL, real-time Streaming, Machine Learning, and Graph operations and optimization. The third part is about running real clusters, and the fourth gives an overall example of a real-time implementation, with all components and a dashboard. The book ends with the discussion of machine learning using H2O with Spark.
“In action” really means it. If you have gone through an introductory book, like “Learning Spark” by Holden Karau, then “Spark in Action” is the next step. It will make you a practical developer proficient in the real-world uses of Spark.
It is completely updated with Spark 2. The book is really out of the future: I am writing this review in December 2016, but the printed book in my hands has 2017 as the date of printing. That is more of a joke, but the Spark versions are not a minor thing: Spark is going at a very fast pace, and each dot version introduces new features. Version 2 even changes the Machine Learning component; it was MLLib, and now it ML, based on DataFrames, a completely new object type. All APIs change, so this book is in tune with the times.
I’ve seen reviews complaining about “book’s explanation,” but I did not find any such problem. Books should be evaluated, I believe, on the merit of what they do have, not on what they don’t have although the reviewer would like it to be there. This is a very practical book; it gives usage advice. If you want the internal architecture, you should go to Holden’s book, or read the code (it’s open source). But if you want to get the equivalent of practical experience, then this book is for you.
Happy traveling! (逍遙遊!)
PS. Once you buy the book in paper, you can get all electronic editions for free. There is an insert in the book that gives you the instructions.
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