Items related to Scaling Big Data with Hadoop and Solr
Synopsis
Understand, design, build, and optimize your big data search engine with Hadoop and Apache Solr 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. 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.
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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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