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Apache Solr Search Patterns
Leverage the power of Apache Solr to power up your business by navigating your users to their data quickly and efficientlyAbout This BookLearn the best use cases for using Solr in e-commerce, advertising, real-estate, and other sitesExplore Solr internals and customize the scoring algorithm in SolrThis is an easy-to-follow book with a step-by-step approach to help you get the best out of Solr search patternsWho This Book Is ForThis book is for developers who already know how to use Solr and are looking at procuring advanced strategies for improving their search using Solr. This book is also for people who work with analytics to generate graphs and reports using Solr. Moreover, if you are a search architect who is looking forward to scale your search using Solr, this is a must have book for you.
It would be helpful if you are familiar with the Java programming language.
What You Will LearnCustomize the Solr scoring algorithm to get better and more relevant search resultsUse Solr with big data for analytical purposesGet insights into Solr internals—indexing and searchSetting up and scaling with Solr cloudImplement spatial search with SolrUnderstand Finite State Transducers (FST) and implement text tagging using FSTBreeze through the strategies used in executing search using Solr in e-commerce, advertising, and real estate websitesLearn more about how to use Solr with AJAXIn DetailApache Solr is an open source search platform built on a Java library called Lucene. It serves as a search platform for many websites, as it has the capability of indexing and searching multiple websites to fetch desired results.
We begin with a brief introduction of analyzers and tokenizers to understand the challenges associated with implementing large-scale indexing and multilingual search functionality. We then move on to working with custom queries and understanding how filters work internally. While doing so, we also create our own query language or Solr plugin that does proximity searches. Furthermore, we discuss how Solr can be used for real-time analytics and tackle problems faced during its implementation in e-commerce search. We then dive deep into the spatial features such as indexing strategies and search/filtering strategies for a spatial search. We also do an in-depth analysis of problems faced in an ad serving platform and how Solr can be used to solve these problems.
It would be helpful if you are familiar with the Java programming language.
What You Will LearnCustomize the Solr scoring algorithm to get better and more relevant search resultsUse Solr with big data for analytical purposesGet insights into Solr internals—indexing and searchSetting up and scaling with Solr cloudImplement spatial search with SolrUnderstand Finite State Transducers (FST) and implement text tagging using FSTBreeze through the strategies used in executing search using Solr in e-commerce, advertising, and real estate websitesLearn more about how to use Solr with AJAXIn DetailApache Solr is an open source search platform built on a Java library called Lucene. It serves as a search platform for many websites, as it has the capability of indexing and searching multiple websites to fetch desired results.
We begin with a brief introduction of analyzers and tokenizers to understand the challenges associated with implementing large-scale indexing and multilingual search functionality. We then move on to working with custom queries and understanding how filters work internally. While doing so, we also create our own query language or Solr plugin that does proximity searches. Furthermore, we discuss how Solr can be used for real-time analytics and tackle problems faced during its implementation in e-commerce search. We then dive deep into the spatial features such as indexing strategies and search/filtering strategies for a spatial search. We also do an in-depth analysis of problems faced in an ad serving platform and how Solr can be used to solve these problems.
318 pages, Kindle Edition
Published April 24, 2015
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April 15, 2021The Patterns aren't too useful for my use case
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