Preface

With the growth of information assets in enterprises, the need to build a rich, scalable search application that can handle a lot of data has becomes critical. Today, Apache Solr is one of the most widely adapted, scalable, feature-rich, and best performing open source search application servers. Similarly, Apache Hadoop is one of the most popular Big Data platforms and is widely preferred by many organizations to store and process large datasets.

Scaling Big Data with Hadoop and Solr, Second Edition is intended to help its readers build a high performance Big Data enterprise search engine with the help of Hadoop and Solr. This starts with a basic understanding of Hadoop and Solr, and gradually develops into building an efficient, scalable enterprise search repository for Big Data, using various techniques throughout the practical chapters.