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PySpark Recipes: A Problem-Solution Approach with PySpark2
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From the Back Cover
Quickly find solutions to common programming problems encountered while processing big data. Content is presented in the popular problem-solution format. Look up the programming problem that you want to solve. Read the solution. Apply the solution directly in your own code. Problem solved!PySpark Recipes covers Hadoop and its shortcomings. The architecture of Spark, PySpark, and RDD are presented. You will learn to apply RDD to solve day-to-day big data problems. Python and NumPy are included and make it easy for new learners of PySpark to understand and adopt the model.What You Will Learn: Understand the advanced features of PySpark and SparkSQLOptimize your codeProgram SparkSQL with PythonUse Spark Streaming and Spark MLlib with PythonPerform graph analysis with GraphFrames
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About the Author
Raju Mishra has strong interests in data science and systems that have the capability of handling large amounts of data and operating complex mathematical models through computational programming. He was inspired to pursue an M. Tech in computational sciences from Indian Institute of Science in Bangalore, India. Raju primarily works in the areas of data science and its different applications. Working as a corporate trainer he has developed unique insights that help him in teaching and explaining complex ideas with ease. Raju is also a data science consultant solving complex industrial problems. He works on programming tools such as R, Python, scikit-learn, Statsmodels, Hadoop, Hive, Pig, Spark, and many others.
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Product details
Paperback: 265 pages
Publisher: Apress; 1st ed. edition (December 10, 2017)
Language: English
ISBN-10: 9781484231401
ISBN-13: 978-1484231401
ASIN: 1484231406
Product Dimensions:
6.1 x 0.7 x 9.2 inches
Shipping Weight: 1 pounds (View shipping rates and policies)
Average Customer Review:
3.7 out of 5 stars
4 customer reviews
Amazon Best Sellers Rank:
#1,609,197 in Books (See Top 100 in Books)
I was looking for a comprehensive pyspark cookbook and came across this. Unfortunately I can’t recommend this book due to a plethora of issues. I don’t have much experience with Apress books, so I can’t speak to the general quality of their editorial process, but this book may quite possibly be the worst edited technical book I’ve ever picked up. Typos, repeat sentences, poor grammar, awkward language, this book has it all. Did anyone bother to proof read this before publication? To cap it off, the formatting on the kindle is atrocious (it’s very difficult to tell apart console commands from the outputs). The content isn’t great either. You’re 40% through the book before you see any pyspark recipes. That first 40% is mostly spent on installation instructions and an underwhelming python tutorial. The installation instructions involve typing commands into the terminal and editing config files. None of this is necessary as 1. there are plenty of great Hadoop installation tutorials online, 2. You can forgo the entire installation process with preconfigured sandbox images, and 3. There are cloud solutions which can get you up and running with Hadoop in minutes. Same can be said of the python tutorial; I don’t think anyone looking to learn python is going to start with a pyspark cookbook, so what’s the point of including a very rudimentary tutorial? All of this leave very little space dedicated to pyspark itself. So unfortunately if you’re looking to learn some advanced pyspark recipes, you’d have to look elsewhere.
The book couldn't have been launched at a better time as it is a comprehensive book that covers the current needs of understanding the big data in a simple and very basic way. The spectrum of the content from basic installation to contextual mathemathics of topics covers almost all aspects of big data required to understand the field.
A 360 degree guide for today's big data processing needs - with a focus on PySpark. The writer recommends and makes you aware of additional stuff you might need - with proper context. That aspect, combined with the Problem/Solution approach - makes the book immensely valuable.
The best and most usefule one I found so far on the subject, I am generally not fond of the paper books, but this one I would not mind maintaining on my shelf.
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