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Scaling Big Data with Hadoop and Solr Paperback – August 26, 2013


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Product Details

  • Paperback: 144 pages
  • Publisher: Packt Publishing (August 26, 2013)
  • Language: English
  • ISBN-10: 1783281375
  • ISBN-13: 978-1783281374
  • Product Dimensions: 7.5 x 0.3 x 9.2 inches
  • Shipping Weight: 9.9 ounces (View shipping rates and policies)
  • Average Customer Review: 3.4 out of 5 stars  See all reviews (5 customer reviews)
  • Amazon Best Sellers Rank: #1,934,999 in Books (See Top 100 in Books)

Editorial Reviews

About the Author

Hrishikesh Karambelkar

Hrishikesh Karambelkar is a software architect with a blend of entrepreneurial and professional experience. His core expertise involves working with multiple technologies such as Apache Hadoop and Solr, and architecting new solutions for the next generation of a product line for his organization. He has published various research papers in the domains of graph searches in databases at various international conferences in the past. On a technical note, Hrishikesh has worked on many challenging problems in the industry involving Apache Hadoop and Solr.

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2 of 2 people found the following review helpful By Petri Kainulainen on November 11, 2013
Format: Kindle Edition
Disclosure: I have written a book which was published by Packt Publishing, and I received a free review copy of this book.

I had high hopes on this book because its description promises that

1) It is a step-by-step guide that helps you build high performance search engines with Apache Hadoop and Solr.
2) You can understand the book without any prior experience from Apache Hadoop and Solr.

Let's find out if this book keeps these promises.

The book is divided into five chapters and three appendices which are described in the following:

The first chapter describes the problems which are solved by Big Data. It gives a short introduction to Apache Hadoop and its ecosystem. It also helps you to install and configure Apache Hadoop, and has a section which talks about its administration tools.

The first chapter is solid and it gives a really good description about the Hadoop Distributed File System (HDFS). Also, the description of the map-reduce algorithm is one of the best I have ever seen.

Chapter two gives an overview of the architecture of Apache Solr, and describes how you can install and configure Apache Solr.

This chapter does a good job of explaining the different request handlers but unfortunately the description of the Solr schema is a bit vague. It feels a bit like a reference manual which might be a problem if you don't have any experience from Solr.

The third chapter describes the problems which Solr can solve on its own and identifies the benefits of distributed search. It introduces different data processing work flows, and describes the advantages and disadvantages of each work flow.
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By A. Mefford on August 27, 2014
Format: Kindle Edition Verified Purchase
I recently read several SOLR books, brushing up my skills making sure that I was current with the technology. This was one of the more helpful as it specifically addresses some of the changes that come with SOLR cloud.

The books that I read in order of preference were:

Mastering Apache Solr: A practical guide to get to grips with Apache Solr
Scaling Big Data with Hadoop and Solr (Community Experience Distilled)
Apache Solr High Performance

This book was good, though fell short of detail. If you have little or know Hadoop experience and are interested in SOLR Cloud, this book provides a good primer on Hadoop to the extent needed to support SOLR Cloud. The explanations and description of the various components of Hadoop were very accessible and clear.

This book provided very little in the way of code samples. Most of the topics were covered at a very high level without significant detail. For this reason I cannot rate it 5 stars. The book does contain command line examples to accomplish various tasks, but little in the way of detail in the options of those command lines such that if the example is not precisely what you need the book provides no guidance on how you would customize the command.

The book provides good coverage of the configuration options for solr, both in the server config and schema. There is light coverage of the various options when creating a schema but it is not complete.

In total this was a good read but a little light on detail of SOLR.
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Format: Paperback
'Scaling Big Data with Hadoop and Solr' was somewhat of a disappointment. While you will learn a lot about the theory of using Hadoop and Solr to manage your data as it grows in volume, I didn't feel that there was a lot of practical application and very little in the way of examples. It would have been fun to set up a cluster and work through examples to reinforce the topics.

If you're looking for a hands on book to learn how to use a system like this, I would recommend you keep looking. If you're looking for an overview then this book might help you out.
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Format: Paperback
This book provides a fairly comprehensive and yet basic introduction on the Hadoop and Solr architectures and some step-by-step configuration/examples. I think it could be a fine quick reference for those who wanna get started with Hadoop and Solr, although due to the quick updates on these products, some of the details are hard to be update to date, the general idea and steps should give learners a good hint.
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Format: Paperback
For a beginner , I would rate this 4 star -
but still , if would be good , if this explains some more basic things- As for me hadoop is good for people having mathematical and statistical knowledge. The author mentioned very clearly , this book is good if you have Java knowledge -
More examples is required as well as real time scenario is comparatively less .
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