Over 70 hands-on recipes to quickly and effectively integrate Lucene into your search application
This book is for software developers who are new to Lucene and who want to explore the more advanced topics to build a search engine. Knowledge of Java is necessary to follow the code samples. You will learn core concepts, best practices, and also advanced features, in order to build an effective search application.
Lucene 4 Cookbook is a practical guide that shows you how to build a scalable search engine for your application, from an internal documentation search to a wide-scale web implementation with millions of records. Starting with helping you to successfully install Apache Lucene, it will guide you through creating your first search application. Furthermore, the book walks you through analyzing your text and indexing your data to leverage the performance of your search application. As you progress through the chapters, you will learn to effectively search your indexes and successfully employ real-time searching.
The chapters start off with simple concepts and build up to complex solutions that should help you on your way to becoming a search engine expert.
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Edwood Ng is a technologist with over a decade of experience in building scalable solutions from proprietary implementations to client-facing web-based applications. Currently, he's the director of DevOps at Wellframe, leading infrastructure and DevOps operations. His background in search engine began at Endeca Technologies in 2004, where he was a technical consultant helping numerous clients to architect and implement faceted search solutions. After Endeca, he drew on his knowledge and began designing and building Lucene-based solutions. His first Lucene implementation that went to production was the search engine behind http://UpDown.com. From there on, he continued to create search applications using Lucene extensively to deliver robust and scalable systems for his clients. Edwood is a supporter of an open source software. He has also contributed to the plugin sfI18NGettextPluralPlugin to the Symphony project.
Vineeth Mohan is a data scientist whose major expertise lies in search analytics and data science. His career started at Yahoo! India, working with a team facilitated by a real-time feed processing platform based on Hadooop across all verticals in Yahoo!. He was also in the team that migrated Right Media technologies to Yahoo! stack. He then moved to Algotree, where he worked across many data science projects such as technical pattern detection in TimeSeries. Later, he designed a real-time news analysis platform based on natural language processing and machine learning approaches. He was also the architect of the search solution for this. Vineeth is passionate about Big Data and data science and has extensive knowledge and experience in Elasticsearch/Solr/Lucene and algorithm design.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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