Ebook Hadoop in Practice: Includes 104 Techniques
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Hadoop in Practice: Includes 104 Techniques
Ebook Hadoop in Practice: Includes 104 Techniques
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About the Author
Alex Holmes is a software engineer, author, speaker and blogger specializing in large-scale Hadoop projects and solving tough Big Data problems. Alex blogs at grepalex.com.
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Product details
Paperback: 512 pages
Publisher: Manning Publications; 2 edition (October 12, 2014)
Language: English
ISBN-10: 1617292222
ISBN-13: 978-1617292224
Product Dimensions:
7.4 x 1 x 9.2 inches
Shipping Weight: 1.9 pounds (View shipping rates and policies)
Average Customer Review:
4.6 out of 5 stars
7 customer reviews
Amazon Best Sellers Rank:
#206,625 in Books (See Top 100 in Books)
this new second edition is what I was looking for - approximately 100 use case scenarios, including good diagrams and commented code to completely show the problem and solution. This book assumes the reader has some familiarity with Java, but is approachable for most professional coders. There's also 'enough computer science' in this book to arm you with the theory of what's happening during execution. if the table of contents lists stuff you want to learn about, this book is a very good choice.
One of the Top 3 books on Hadoop. My number one is the updated version of "Hadoop The Definitive Guide", but this one is quite excellent, as well.Good examples and a nice index. I've not read it cover to cover (like I did with The Definitive Guide), but this is an excellent reference to find specific solutions.
Well written, excellent second book on Hadoop.
The Hadoop world has undergone some big changes lately, and this hefty, updated edition offers some excellent coverage of a lot of what’s new. If you currently work with Hadoop and MapReduce or are planning to take them up soon, give serious consideration to adding this well-written book to your technical library. A key feature of the book is its “104 techniques.†These show how to accomplish practical and important tasks when working with Hadoop, MapReduce and their growing arrays of software “friends.â€Of course, one book cannot possibly cover everything you need to know about Hadoop, MapReduce, Parquet, Kafka, Camus, YARN and other technologies. And the book's software examples assume that you have had some experience with Java, XML and JSON. However, Hadoop in Practice, Second Edition gives a very good and reasonably deep overview of the Hadoop world, spanning such major topic categories as background and fundamentals, data logistics, Big Data patterns, and moving beyond MapReduce.I don't "love" Hadoop and MapReduce; my experiences with them have been a struggle. So I can't give this book five stars on the review scale. But I am happy to give it four solid stars, and I definitely recommend it to others.
Let me start by saying, if you want to maximize the benefit from reading "Hadoop in Practice," you better have a solid conceptual understanding of HDFS and MapReduce. The book does start with a primer of Hadoop, but it quickly delves into a deep detailed explanation of YARN and how YARN has helped evolve the Hadoop ecosystem. Chapter 2 in particular explains how the Hadoop architecture, including MapReduce, has been overhauled to use YARN applications."Hadoop in Practice" is filled with excellent real-world examples that show Hadoop in motion. Those real-world examples are broken down in a consumable format that includes 85 different use cases with accompanying solutions. Having an intermediate-level knowledge of Java will go a long way as you traverse the examples and source code included with the book.My personal favorite chapter, Chapter 7, shows users how to leverage data structures and algorithms at scale. Whether it is describing and detailing the shortest-path algorithm or friends-of-friends algorithm, "Hadoop in Practice" simply does not skimp on providing legitimate use cases along with pseudo code before breaking down each implementation in MapReduce complete with Java code.Overall, "Hadoop in Practice" is structured well and every chapter begins with a high-level overview and ends with a thorough summery. Most chapters include detailed diagrams that I found useful when trying to understand some of the more complex issues in the book - and trust me, there are many.
Exceptionally well written book on Hadoop 2 and generally distributed computing specifically. Highly recommend for anyone who needs to have a jump start in this subject area. Caution though: distributed computing is complex and involves many different projects and disciplines, so be ready to cross reference to the relevant subject area expertise (from Wikipedia or other relevant books). Don't expect to understand in depth every concept laid out in this book, but it is a good roadmap to get back once the concept in question clarified through other means (say, extra explanation on YARN or AVRO). Good and enjoyable study material. Have fun!
The first book about Hadoop to make any sense ! I am new to Hadoop and went through a bunch of resources before finding this. The author just intuitively knows how to make an abstract concept easy to understand
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