By Jayant Kumar
Leverage the ability of Apache Solr to strength up your online business through navigating your clients to their info quick and efficiently
About This Book
research the easiest use instances for utilizing Solr in e-commerce, ads, real-estate, and different sites
discover Solr internals and customise the scoring set of rules in Solr
this is often an easy-to-follow publication with a step by step method of assist you get the easiest out of Solr seek patterns
Who This e-book Is For
This publication is for builders who already know the way to exploit Solr and are paying for complex recommendations for making improvements to their seek utilizing Solr. This booklet is additionally for those that paintings with analytics to generate graphs and experiences utilizing Solr. additionally, when you are a seek architect who's looking ahead to scale your seek utilizing Solr, it is a should have publication for you.
It will be precious while you're conversant in the Java programming language.
Apache Solr is an open resource seek platform equipped on a Java library known as Lucene. It serves as a seek platform for lots of web content, because it has the aptitude of indexing and looking a number of web content to fetch wanted results.
We commence with a quick creation of analyzers and tokenizers to appreciate the demanding situations linked to imposing large-scale indexing and multilingual seek performance. We then stream directly to operating with customized queries and knowing how filters paintings internally. whereas doing so, we additionally create our personal question language or Solr plugin that does proximity searches. moreover, we speak about how Solr can be utilized for real-time analytics and take on difficulties confronted in the course of its implementation in e-commerce seek. We then dive deep into the spatial gains corresponding to indexing recommendations and search/filtering ideas for a spatial seek. We additionally do an in-depth research of difficulties confronted in an advert serving platform and the way Solr can be utilized to resolve those problems.
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Additional resources for Apache Solr Search Patterns
Commit(); Here is the reference to the API for the HttpSolrServer program http://lucene. html. Add all files from the
Ideally, manager is equal to management. Therefore, a search for manager should also return both documents. This intelligence has to be built into Solr with the help of analyzers, tokenizers, and filters. In this case, a synonym filter mentioning manager, management, manages as synonyms should do the trick. Another way to handle the same scenario is to use stemmers. Stemmers reduce words into their stem, base, or root form. In this chase, the stem for all the preceding words will be manage. There is a huge list of analyzers, tokenizers, and filters available with Solr by default that should be able to satisfy any scenario we can think of.
The output of a standard tokenizer is a list of tokens that are passed to the stop filter and lowercase filter during indexing. The stop filter class contains a list of stop words that are discarded from the tokens received by it. The lowercase filter converts all tokens to lowercase. On the other hand, during a search, an additional filter known as synonym filter is applied. This filter replaces a token with its synonyms. txt file specified as an attribute in the filter. txt files in our Solr configuration and see how the input text is analyzed.
Apache Solr Search Patterns by Jayant Kumar