Scaling Big Data with Hadoop and Solr - Second Edition

by Hrishikesh Vijay Karambelkar

Overview

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.

Product Details

ISBN-13:	9781783553402
Publisher:	Packt Publishing
Publication date:	04/27/2015
Sold by:	Barnes & Noble
Format:	eBook
Pages:	166
File size:	8 MB

About the Author

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/.