Scaling Big Data with Hadoop and Solr - Second Edition, by Hrishikesh Vijay Karambelkar
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Scaling Big Data with Hadoop and Solr - Second Edition, by Hrishikesh Vijay Karambelkar
Download Ebook PDF Scaling Big Data with Hadoop and Solr - Second Edition, by Hrishikesh Vijay Karambelkar
Understand, design, build, and optimize your big data search engine with Hadoop and Apache Solr
About This Book
- Explore different approaches to making Solr work on big data ecosystems besides Apache Hadoop
- Improve search performance while working with big data
- A practical guide that covers interesting, real-life use cases for big data search along with sample code
Who This Book Is For
This book is aimed at developers, designers, and architects who would like to build big data enterprise search solutions for their customers or organizations. No prior knowledge of Apache Hadoop and Apache Solr/Lucene technologies is required.
What You Will Learn
- Understand Apache Hadoop, its ecosystem, and Apache Solr
- Explore industry-based architectures by designing a big data enterprise search with their applicability and benefits
- Integrate Apache Solr with big data technologies such as Cassandra to enable better scalability and high availability for big data
- Optimize the performance of your big data search platform with scaling data
- Write MapReduce tasks to index your data
- Configure your Hadoop instance to handle real-world big data problems
- Work with Hadoop and Solr using real-world examples to benefit from their practical usage
- Use Apache Solr as a NoSQL database
In Detail
Together, Apache Hadoop and Apache Solr help organizations resolve the problem of information extraction from big data by providing excellent distributed faceted search capabilities.
This book will help you learn everything you need to know to build a distributed enterprise search platform as well as optimize this search to a greater extent, resulting in the maximum utilization of available resources. Starting with the basics of Apache Hadoop and Solr, the book covers advanced topics of optimizing search with some interesting real-world use cases and sample Java code.
This is a step-by-step guide that will teach you how to build a high performance enterprise search while scaling data with Hadoop and Solr in an effortless manner.
Scaling Big Data with Hadoop and Solr - Second Edition, by Hrishikesh Vijay Karambelkar- Amazon Sales Rank: #1592766 in Books
- Published on: 2015-03-31
- Released on: 2015-04-27
- Original language: English
- Number of items: 1
- Dimensions: 9.25" h x .38" w x 7.50" l, .65 pounds
- Binding: Paperback
- 156 pages
About the Author
Hrishikesh Vijay Karambelkar
Hrishikesh Vijay Karambelkar is an enterprise architect who has been developing a blend of technical and entrepreneurial experience for more than 14 years. His core expertise lies in working on multiple subjects, which include big data, enterprise search, semantic web, link data analysis, analytics, and he also enjoys architecting solutions for the next generation of product development for IT organizations. He spends most of his time at work, solving challenging problems faced by the software industry. Currently, he is working as the Director of Data Capabilities at The Digital Group. In the past, Hrishikesh has worked in the domain of graph databases; some of his work has been published at international conferences, such as VLDB, ICDE, and others. He has also written Scaling Apache Solr, published by Packt Publishing. He enjoys travelling, trekking, and taking pictures of birds living in the dense forests of India. He can be reached at http://hrishikesh.karambelkar.co.in/.
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Most helpful customer reviews
0 of 0 people found the following review helpful. "Scaling Big Data with Hadoop and Solr, Second Edition" Review By PJG This book is a good to Solr and how it can be used to tackle distributed search scenarios. The first chapter is an introduction to the Hadoop stack and it gives a good description and overview of HDFS and fundamental MapReduce concepts.Chapter two gives an overview of the architecture of Apache Solr, and describes how you can install and configure it. 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. This chapter highlights one of the downsides of the book, namely that it reads like a very theoretical guide, rather than providing hands-on and practical advice.The fourth chapter describes how to integrate Hadoop, Solr, and HBase by using Lily. The chapter ends by describing how to divide the Solr index into multiple shards by using SolrCloud and ZooKeeper.Finally, the last chapter focuses upon optimising the performance of Apache Solr, and this is where the advice is very practical and applicable.Overall, the book contains good material but ideally there would be more on applying the theory covered in practice. At only 166 pages, it feels rather light on content, which is a shame as it's a good quality book overall.
0 of 0 people found the following review helpful. Good book but requires that you clearly understand the targeted ... By David Good book but requires that you clearly understand the targeted audience. The book is clear and is a must have for administrator of Hadoop and Solr. It explains how to configure correctly and scale such infrastructure. It also address the most common issues and how to deal with them. As such, it will probably save a lot of time and effort to Hadoop/Solr administrators.It also requires the reader to already have a good knowledge of Hadoop which make sense for a booking called scaling ;). If you are new to Hadoop, you should probably start learning on the Internet or go to a book that will introduce all the concepts because at the exception of Chapter 1 which refresh your memory, you will have to know what are the elements mentioned by the author.
0 of 0 people found the following review helpful. Big Data Doesn't Need to Be Big Headaches By Winston Great Book....Big data is all the rave these days. As technologists we are faced with ever increasing ways to make sense of our data and organize it in a way that makes best business and personal use. The author does a good job of explaining the uses of Hadoop and Solr. I just wish there was more to read but what was offered has me yearning for more in the next edition hopefully.
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