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Get Started Fast with Apache Hadoop� 2, YARN, and Today’s Hadoop Ecosystem
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With Hadoop 2.x and YARN, Hadoop moves beyond MapReduce to become practical for virtually any type of data processing. Hadoop 2.x and the Data Lake concept represent a radical shift away from conventional approaches to data usage and storage. Hadoop 2.x installations offer unmatched scalability and breakthrough extensibility that supports new and existing Big Data analytics processing methods and models.
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Hadoop� 2 Quick-Start Guide is the first easy, accessible guide to Apache Hadoop 2.x, YARN, and the modern Hadoop ecosystem. Building on his unsurpassed experience teaching Hadoop and Big Data, author Douglas Eadline covers all the basics you need to know to install and use Hadoop 2 on personal computers or servers, and to navigate the powerful technologies that complement it.
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Eadline concisely introduces and explains every key Hadoop 2 concept, tool, and service, illustrating each with a simple “beginning-to-end” example and identifying trustworthy, up-to-date resources for learning more.
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This guide is ideal if you want to learn about Hadoop 2 without getting mired in technical details. Douglas Eadline will bring you up to speed quickly, whether you’re a user, admin, devops specialist, programmer, architect, analyst, or data scientist.
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Coverage Includes
- Understanding what Hadoop 2 and YARN do, and how they improve on Hadoop 1 with MapReduce
- Understanding Hadoop-based Data Lakes versus RDBMS Data Warehouses
- Installing Hadoop 2 and core services on Linux machines, virtualized sandboxes, or clusters
- Exploring the Hadoop Distributed File System (HDFS)
- Understanding the essentials of MapReduce and YARN application programming
- Simplifying programming and data movement with Apache Pig, Hive, Sqoop, Flume, Oozie, and HBase
- Observing application progress, controlling jobs, and managing workflows
- Managing Hadoop efficiently with Apache Ambari–including recipes for HDFS to NFSv3 gateway, HDFS snapshots, and YARN configuration
- Learning basic Hadoop 2 troubleshooting, and installing Apache Hue and Apache Spark
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- Sales Rank: #216042 in Books
- Published on: 2015-11-05
- Original language: English
- Number of items: 1
- Dimensions: 9.00" h x .80" w x 6.90" l, 1.02 pounds
- Binding: Paperback
- 304 pages
About the Author
Douglas Eadline began his career as a practitioner and a chronicler of the Linux cluster HPC revolution and now documents Big Data analytics. Starting with the first Beowulf Cluster how-to document, Doug has written hundreds of articles, white papers, and instructional documents covering virtually all aspects of High Performance Computing (HPC). Prior to starting and editing the popular ClusterMonkey.net website in 2005, he served as editor-in-chief for ClusterWorld Magazine, and was senior HPC editor for Linux Magazine. Currently, he is a writer and consultant to the HPC/Data Analytics industry and leader of the Limulus Personal Cluster Project (limulus.basement-supercomputing.com). He authored Hadoop Fundamentals LiveLessons, Second Edition (2015), and Apache Hadoop YARN LiveLessons (2014), and is coauthor of Apache Hadoop™ YARN (2014), all from Addison-Wesley.
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Most helpful customer reviews
4 of 4 people found the following review helpful.
Great Intro to Hadoop at the "Hello World" Level :-)
By Mairtin O. Sullivan
Having never installed or played around with a Hadoop environment myself, I was on the look out for an intro style book that would give me the basics and enough info to start me off.
When browsing this one caught my eye as I didn’t even realise there was a Hadoop 2 and the title was pretty much spot on for what I was looking for so decided to give it a shot.
Overall, I enjoyed the book and it was spot on for what I was looking for. It’s a traditional tutorial/walk through type of book on how to get a Hadoop cluster up and running and how to admin/interact with it, but it also covers enough theory that you don’t need to have any prior experience with Hadoop to follow along.
However, I would say that I think it’s overpriced in the paper edition and retail price ebook so if you’re interested in this book, try and read it on Safari or get a Kindle edition to make it affordable. Other than that definitely recommended.
The book starts off with a really good overview of what Hadoop is, the MapReduce pattern and the changes in Hadoop 2. Good intro material.
The next chapter is a more traditional walk through on how to install Hadoop uses both the Hortonworks distribution and the Apache sources. It also covers use of Ambari for a simple web based admin console for your cluster. Nothing too detailed is explained here as it’s covered off later, but it’s a straight forward walk through so is spot on for that.
The third chapter gives a really good intro to how HDFS works, covering the nodes involved, their roles and the approach taken to replication and then some basic file system commands. I particularly enjoyed this chapter as I hadn’t used HDFS before and so some of the concepts around the different nodes, compute following data, append only files and block sizes were spot on for what I needed to understand.
The forth chapter covers running jobs and monitoring them in the web gui, along with some examples for base lining the performance of the cluster.
The fifth and sixth chapters walks through the MapReduce approach to data analysis, using word counting in text files as the main example and then moves on to the basics of writing code to create MapReduce jobs, covering the basics in Java and Python. Simple and straightforward, but again spot on in term of depth.
The seventh chapter runs through some of the other Apache tools within the Hadoop ecosystem, covering Pig, Hive, Sqoop, Flume, Oozie and HBase. These are just quick overviews but interesting as I wasn’t aware of some of these.
The eight chapter is really nice in that it focuses exclusively on YARN (Yet Another Resource Negotiator), which is new to Hadoop 2 and is one of the big differences in the new version. It walks through how to use YARN for things other than the traditional MapReduce pattern, using the YARN distributed shell as an example, before touching briefly on how some of the other Apache tools can be used with YARN.
The last two chapters focus on admining Hadoop through the commands required and the Ambari interface. I skimmed these as I’m only doing a very basic setup to get my head around Hadoop but would look back to these as needed.
In summary, the author notes initially that this book is written to a "hello world" level in terms of depth and that’s spot on across the book. It gives you enough info to get you to a working example, and then it’s up to you. I really liked this analogy and it’s exactly the level I was looking for. I also liked the author’s style of writing so will also be going looking for more of his book to find some more advanced material on Hadoop.
If you looking for an intro to Hadoop that’s a nice combination of both theory and high level tech implementation, then this is definitely worth a read.
One thing I would say is that I got through the book very quickly (3 hours roughly), and was surprised to see when I checked Amazon that the paper version is just over 300 pages as it really didn’t feel like that. It reads more like a book of around 150 pages, which in my head makes sense for quick start book.
Why I highlight this is that while I really enjoyed the book, as I mention earlier, I don’t think it’s worth the price of $27 that the paper version is currently retailing for. For me it’s more in the $15 - $18 bracket and so if you’re going to read this then definitely try and go for the Kindle edition which is worth it at $17.
4 of 4 people found the following review helpful.
A practical and effective tool.
By Amazon Customer
A quick-start guide is absolutely right. This book is a quick read and an effective guide to getting started with Hadoop. For me, it took the nebulous world of Hadoop and brought it into the realm of understanding with real-world scenarios and practical usage. I've been working with relational databases for over two decades and to be honest the world of big data seemed overwhelming. After reading this book, I have an understanding of Hadoop and the potential solutions to managing big data needs. I would definitely recommend this book.
2 of 2 people found the following review helpful.
Great Introduction & Reference to Hadoop 2
By Len Keighley - BCS Fellow
The book really does take you from soup to nuts, as they say in the US, starting with an introduction to the concepts and history of Hadoop and Big Data, through installation, file system basics, MapReduce Framework & Programming, Hadoop Tools (including Yarn applications), and finally the management and administration of Hadoop under Apache Ambari. The book also has its own web site, complete with code downloads, question & answer forums, resources links and update information.
In essence there is something in the Hadoop 2 Quick Start Guide for everyone, from some that just want to see what all the Hadoop noise is about, to those that are regular Hadoop users or administrators. The format used is excellent for this type of book, and one that should perhaps set the standard for other ‘quick start’ guides. The instructions and code examples are easy to follow and provide all the required background. The layout also aids the reader who wants to pick and choose what they read, dependent on their needs at that time, while still providing for the reader who needs to see the whole picture.
Particularly interesting was the section on HDFS (Hadoop Distributed File System) which provides information on the background to the chosen structure for its storage and command environment.
One of the Appendices even gives a summary of the additional resource content in the full sections so that the really high level ‘helicopter’ reader is also served.
Obviously, as the title suggests, there is more detail to be had and I look forward to reading Douglas Eadline’s books at that level as well.
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