Relevant Search: With examples using Elasticsearch and Solr by Doug Turnbull, John Berryman

Relevant Search: With examples using Elasticsearch and Solr



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Relevant Search: With examples using Elasticsearch and Solr Doug Turnbull, John Berryman ebook
ISBN: 9781617292774
Publisher: Manning Publications Company
Page: 250
Format: pdf


Elastic search stores/retrieves objects via a REST API. Relevant Search is all about leveraging Solr and Elasticsearch to Examples for this book are written in Python 2.7 and use iPython notebook. Similarly for Solr, the examples I have seen usually involve similar The score determines the relevance of a document to a given search query. What are the advantages and disadvantages of using Elasticsearch or Solr? All of these items add a dimension to our relevance ranking. Solr is the natural choice for searching over Hadoop data. At Dataiku, we use extensively search logs and associated navigation information for user behaviours analytics and relevance optimization. Most of our customers today use SOLR or ElasticSearch. When performing classification, for example, we similarly try to identify and incorporate new Throughout this book, we use Elasticsearch as our search engine. We are using JAVA stack with Hibernate and Spring Framework. Sort by mixed relevance and recency, I just haven't pushed back into Lucene yet. Is Elastic search is mature enough to be used for Mongodb full text search? For example with MySql you hit a brick wall once your indexes no longer fit in memory. Apache Solr's wiki leads off it's Why Use Solr page with the following: Solr (and other text-optimized search engines like Elasticsearch) blow database-backed search out of the water in terms of speed, relevance, and functionality. Apache Solr is mainly used for full text search: if you want to find words (singular and plurals for example) in a big set of @2014 is this still relevant – Vish Oct 2 '14 at 8:44 Hibernate search is a "bridge" between Hibernate and Lucene. A few synonym examples, for example try searching for oome . Netflix, for example, uses Solr for its site search feature, but this should not be The underlying technology is based on Lucene, which has a ranking If you have a heavy tailed query space, you are going to have poor relevance in the tail. Using Solr as a key value store actually works reasonably well.





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