|Title||Scaling Big Data with Hadoop and Solr|
|Sub Title||Learn exciting new ways to build efficient, high performance enterprise search repositories for Big Data using Hadoop and Solr|
|Author||Hrishikesh Vijay Karambelkar|
|Category||Computer & Programming|
|Tags||Big Data Data Mining|
|File Size||2.5 MB|
As data grows exponentially day-by-day, extracting information becomes a tedious activity in itself. Technologies like Hadoop are trying to address some of the concerns, while Solr provides high-speed faceted search. Bringing these two technologies together is helping 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 you build high performance enterprise search engines while scaling data. Starting with the basics of Apache Hadoop and Solr, this book then dives into advanced topics of optimizing search with some interesting real-world use cases and sample Java code.