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Hadoop in Practice, by Alex Holmes
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Summary
Hadoop in Practice collects 85 Hadoop examples and presents them in a problem/solution format. Each technique addresses a specific task you'll face, like querying big data using Pig or writing a log file loader. You'll explore each problem step by step, learning both how to build and deploy that specific solution along with the thinking that went into its design. As you work through the tasks, you'll find yourself growing more comfortable with Hadoop and at home in the world of big data.
About the TechnologyHadoop is an open source MapReduce platform designed to query and analyze data distributed across large clusters. Especially effective for big data systems, Hadoop powers mission-critical software at Apple, eBay, LinkedIn, Yahoo, and Facebook. It offers developers handy ways to store, manage, and analyze data.
About the BookHadoop in Practice collects 85 battle-tested examples and presents them in a problem/solution format. It balances conceptual foundations with practical recipes for key problem areas like data ingress and egress, serialization, and LZO compression. You'll explore each technique step by step, learning how to build a specific solution along with the thinking that went into it. As a bonus, the book's examples create a well-structured and understandable codebase you can tweak to meet your own needs.
This book assumes the reader knows the basics of Hadoop.
Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.
What's Inside- Conceptual overview of Hadoop and MapReduce
- 85 practical, tested techniques
- Real problems, real solutions
- How to integrate MapReduce and R
- Sales Rank: #648360 in Books
- Brand: Brand: Manning Publications
- Published on: 2012-10-13
- Original language: English
- Number of items: 1
- Dimensions: 9.25" h x 1.29" w x 7.38" l, 1.93 pounds
- Binding: Paperback
- 536 pages
- Used Book in Good Condition
About the Author
Alex Holmes is a senior software engineer with extensive expertise in solving big data problems using Hadoop. He has presented at JavaOne and Jazoon and is a technical lead at VeriSign.
Most helpful customer reviews
22 of 23 people found the following review helpful.
Way too old
By Michael
This book is way too old, it's only really good for giving you ideas of what to try. The versions of all the software that this book is based on are often times impossible to obtain now, many of the hadoop sites are in the habit of removing old versions of their projects so you can't download them. For example, the book is primarily based on using hadoop 0.20 and/or cloudera's hadoop version three. It's no longer possible to download those, if you have an old version then hold on to it in case you need it.
None of the installation instructions in the book will work with the newer versions of applications. In some cases the entire idea of how you would run and use a tool has changed. Also, the entire way that HDFS and Map-reduce works has changed since YARN was added, so the books explanation of that is old.
The book often omits important details like which jar you need to use for a particular piece of code. Classpath and dependency issues are always a nightmare to deal with and the book offers little help with this. He should list everything that you would put in a maven dependency. He often omits the import lines in java code, so you have little idea which class he is referring to in the code.
There are often times when he requires you to use software written by him, such as the "File Slurper" that Alex wrote. I am very wary of using any code like that, if it doesn't have the support of the apache/hadoop community then it's very likely to be out of date and unsupported sooner or later. I skipped any chapter I saw like that. I kept seeing this reference to a bash script called "run.sh" in the book, and could not figure out what he was referring to. I could find no such shell script in any software I downloaded. I think it must be a bash script in his git project, like I said I don't want to depend on any code that is not supported by the community.
There were also COUNTLESS compatibility issues I found when I tried to do anything. Almost no two pieces of hadoop software work together out of the box. It's so bad that using anything besides cloudera's hadoop was practically impossible. I am not a stupid guy either.
Here is my advice to you:
1. Use cloudera's pre-built CDH VM, at least at first. I used the CDH 4.5 pre-built VM, and that is the only thing I got to work.
2. Do not follow any installation instructions in the HIP book
3. Do not follow any installation instructions on the hadoop websites
4. Only follow installation/re-configuration instructions found in Cloudera's manual for CDH 4.5 installation
5. Do not deviate your configuration from what is norm. For example, I encountered a lot of bugs when I tried switching to java 7.
5. You might want to hold off from buying this book until a newer issue is released
6. If you use maven for dependencies, make sure you get your hadoop dependencies from the cloudera repository, not maven central
7. Instead of reading the book, just go into each of the hadoop project's websites. Skip their installation instructions like I said before, but try to follow any tutorials you see, and try to practice using everything you read.
8. After you figure out how to do everything, only then should you try to install stuff from scratch on a new VM. If you try to set up a VM on your own from the start, all the frustration will kill your motivation to learn hadoop.
The one thing this book was good for was giving me ideas of what things to try, which is why I give it two stars instead of one.
16 of 17 people found the following review helpful.
85 advanced hadoop techniques
By Jeanne Boyarsky
"Hadoop in Practice" covers recipes/techniques for working with Hadoop. The 85 techniques range from pure Hadoop to related technologies like Mahout and Pig. There was good discussion of algorithms.
Java is definitely a pre-requisite. The book says you should have some knowledge of HDFS and MapReduce. Yet chapter one starts with "what is hadoop." It reads better as a review than an intro and doesn't fit with the rest of the book. It also assumes you haven't installed/started Hadoop. You really should read an intro book first and skim chapter one.
I particularly liked the chapters on MapReduce and performance. The overview of iostat and vmstat was clear and better than in many UNIX books. I also liked the AST explain plan. The techniques about when to use joins and sorts seemed like they would be in "Hadoop in Action" as well. Yet the comparison of different types fit well.
Each chapter begins with a conceptual overview which was very useful. The book also contains many diagrams to add clarity.
Disclosure: I received a copy of this book from the publisher in exchange for writing this review.
13 of 15 people found the following review helpful.
Too much and too little
By J. Underwood
I'm a Hadoop beginner. If you are too, this is not the book for you. The author has stuffed a bit about every conceivable Hadoop-related application of every related Apache project into this book and, beyond being a useful overview discovery guide, it is simultaneously too wide and too shallow (or brief) to be useful to those without substantial knowledge of many of the topics discussed. I'm sure some of the optimization material is useful to those with well-formed questions but this format does not lend itself well to a reader's bootstrap effort on the subject of Hadoop. In all fairness, it does not claim to. Just sayin'.
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