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Data Analytics with Hadoop: An Introduction for Data Scientists by [Benjamin Bengfort, Jenny Kim]

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Benjamin Bengfort

Jenny Kim

Data Analytics with Hadoop: An Introduction for Data Scientists 1st Edition, Kindle Edition

by Benjamin Bengfort (Author), Jenny Kim (Author) Format: Kindle Edition

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Ready to use statistical and machine-learning techniques across large data sets? This practical guide shows you why the Hadoop ecosystem is perfect for the job. Instead of deployment, operations, or software development usually associated with distributed computing, you’ll focus on particular analyses you can build, the data warehousing techniques that Hadoop provides, and higher order data workflows this framework can produce.

Data scientists and analysts will learn how to perform a wide range of techniques, from writing MapReduce and Spark applications with Python to using advanced modeling and data management with Spark MLlib, Hive, and HBase. You’ll also learn about the analytical processes and data systems available to build and empower data products that can handle—and actually require—huge amounts of data.

Understand core concepts behind Hadoop and cluster computing
Use design patterns and parallel analytical algorithms to create distributed data analysis jobs
Learn about data management, mining, and warehousing in a distributed context using Apache Hive and HBase
Use Sqoop and Apache Flume to ingest data from relational databases
Program complex Hadoop and Spark applications with Apache Pig and Spark DataFrames
Perform machine learning techniques such as classification, clustering, and collaborative filtering with Spark’s MLlib

ISBN-13

978-1491913703
Edition

1st
Publisher

O'Reilly Media
Publication date

1 June 2016
Language

English
File size

9218 KB
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Product description

About the Author

Benjamin Bengfort is a data scientist with a passion for massive machine learning involving gigantic natural language corpora, and has been leveraging that passion to develop a keen understanding of recommendation algorithms at Cobrain in Bethesda, MD where he serves as the Chief Data Scientist. With a professional background in military and intelligence, and an academic background in economics and computer science, he brings a unique set of skills and insights to his work. Ben believes that data is a currency that can pave the way to discovering insights and solve complex problems. He is also currently pursuing a PhD in Computer Science at the University of Maryland. Jenny Kim is an experienced data scientist who works in both commercial software efforts as well as in academia. She has significant experience in working with large scale data, machine learning, and Hadoop implementations in production and research environments. Jenny (with Benjamin Bengfort) built a large scale recommender system that used a web crawler to gather ontological information about apparel products and produce recommendations from transactions. Currently she teaches Introduction to Hadoop and Advanced Hadoop courses on Statistics.com. --This text refers to the paperback edition.

Product details

ASIN ‏ : ‎ B01GGQKXO4
Publisher ‏ : ‎ O'Reilly Media; 1st edition (1 June 2016)
Language ‏ : ‎ English
File size ‏ : ‎ 9218 KB
Simultaneous device usage ‏ : ‎ Unlimited
Text-to-Speech ‏ : ‎ Enabled
Screen Reader ‏ : ‎ Supported
Enhanced typesetting ‏ : ‎ Enabled
X-Ray ‏ : ‎ Not Enabled
Word Wise ‏ : ‎ Not Enabled
Print length ‏ : ‎ 290 pages

Best Sellers Rank: 1,009,145 in Kindle Store (See Top 100 in Kindle Store)
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Customer Reviews:
25 ratings

About the authors

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Benjamin Bengfort
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Benjamin Bengfort is a Data Scientist who lives inside the beltway but ignores politics (the normal business of DC) favoring technology instead. He is currently working to finish his PhD at the University of Maryland where he studies machine learning and artificial intelligence. His lab does have robots (though this field of study is not one he favors) and, much to his chagrin, they seem to constantly arm said robots with knives and tools; presumably to pursue culinary accolades. Having seen a robot attempt to slice a tomato, Benjamin prefers his own adventures in the kitchen where he specializes in fusion French and Guyanese cuisine as well as BBQ of all types. A professional programmer by trade, a Data Scientist by avocation, Benjamin's writing pursues a diverse range of subjects from Natural Language Processing, to Data Science with Python to analytics with Hadoop.
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Jenny Kim
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Customer reviews

5 star		53%
4 star		27%
3 star		9%
2 star		5%
1 star		5%

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Top review from Australia

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Glen Hardingham

Why can't everyone be like this

Reviewed in Australia on 19 January 2020

Verified Purchase

Really quick service, price was also a bonus

Helpful

Top reviews from other countries

Angel Jaime

Its a good option but Its require more examples

Reviewed in Mexico on 15 June 2019

Verified Purchase

Good

Victor

Misleading

Reviewed in the United States on 5 December 2019

Verified Purchase

The book is misleading. Many times the information is simply incorrect. Writing style also leaves much to be desired.
Do not recommend!

Patrick

Did you check your work?

Reviewed in the United States on 15 November 2017

Verified Purchase

Be prepared to spend a lot of time debugging their sample code and the installation instructions for the various software packages. Most of the examples in the book do not match the sample code or data provided. And much of what they refer to in the book is not included in the samples. On top of all this, they even manage to mangle their examples just within the book itself. As an example, they walk through a data exercise first using mapreduce. Then they try to do the same thing using spark. But the spark program produces incorrect results. Yes, it works, but it isn't what mapreduce produced, or the book claimed was the expected output.

On the plus side, the best way to learn something is by doing and this book will give you plenty of opportunities to figure things out on your own. That's always a plus. But not for the authors.

7 people found this helpful

HarmanSS

Nice book to work with hadoop

Reviewed in the United States on 6 February 2019

Verified Purchase

Really nice textbook to work and learn hadoop systems and Mapreduce.

Dr V Gio Nguyen

Five Stars

Reviewed in the United States on 8 August 2017

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