Explore new ways to build high performance research repositories using Packt’s book and eBook

September 2013 | Open Source

Packt is pleased to announce the release of Scaling Big Data with Hadoop and Solr, a practical guide to help readers understand the different approaches to make Solr work on Big Data, as well as the benefits and drawbacks.

About the Author :

Hrishikesh Karambelkar is a software architect with entrepreneurial and professional experience. He is an expert on working with multiple technologies such as Apache Hadoop and Solr, as well as creating new solutions for the next generation of product lines for his organization. Hrishikesh has worked on many challenging problems in the industry that involve Apache Hadoop and Solr.

With data growing so rapidly today, extracting information becomes a tiresome activity in itself. Hadoop and Solr are two forms of technologies that help users deal with Big Data; with Hadoop trying to address some of the concerns, and Solr providing a high-speed faceted search. Bringing such technologies together will help organizations resolve the problem of information extraction from Big Data by providing excellent distributed, faceted search capabilities.

Scaling Big Data with Hadoop and Solr is a step-by-step guide that helps developers build high performance enterprise search engines while scaling data. Starting with the basics of Apache, Hadoop, and Solr; the book moves on to explain the advanced topics of optimizing search using real-world use cases and sample Java code.

Through this concise book, readers will learn to build high-speed enterprise search platforms using Hadoop and Solr. Readers will learn everything they need to know to build a distributed enterprise search platform and how to optimize this search, resulting in maximum utilization of available resources.This book is primarily focused on Java programmers.

The topics covered in this book are:

Chapter 1: Processing Big Data Using Hadoop MapReduce
Chapter 2: Understanding Solr

Chapter 3: Making Big Data Work for Hadoop and Solr
Chapter 4: Using Big Data to Build Your Large Indexing
Chapter 5: Improving Performance of Search while Scaling with Big Data

Appendix A: Use Cases for Big Data Search

Appendix B: Creating Enterprise Search Using Apache Solr
Appendix C: Sample MapReduce Programs to Build the Solr Indexes

Packt Publishing has also released, or is due to release the following JavaScript books:

• Implementing Splunk: Big Data Reporting and Development for Operational Intelligence (published)
• TIBCO Spotfire for Developers (Oct 2013)
• Getting Started with Greenplum for Big Data Analytics (Oct 2013)

About Packt:

All Packt JavaScript books are published by Packt Enterprise. Packt Enterprise is a publishing division of Packt Publishing designed to serve the information needs of IT professionals in the Enterprise space. Packt Enterprise also publishes on Microsoft, IBM, Oracle, Citrix, Java, Amazon, Google, and SAP technologies.

 


Scaling Big Data with Hadoop and Solr
Explore new ways to build high performance research repositories

For more information, please visit: http://www.packtpub.com/scaling-big-data-with-hadoop-and-solr/book

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