The search business is evolving and those developing capabilities in enterprise search and custom website search have two choices: buy or build. First, offerings from Google Custom Search and Amazon CloudSearch and a few other players offer a managed search option. The second option is to build a custom search application using the open-source Lucene search library and customize it with Apache Solr search or Elasticsearch.
Any comprehensive review starts with a test environment on a local server in what is called standalone mode in Solr. Next, to plan for increased search volumes and a move to production it is important to review distributed search in Apache Solr in SolrCloud mode.
In this Solr Reference we start with the main Solr command line script
bin/solr from the
directory where Solr was installed. It offers 12 commands used for
Solr search administration.
From there, posting data to an index, modifying configuration files and learning how the Apache Lucene Solr combination of tools analyzes the data becomes relevant. And last, bringing a custom search application to the production environment is the big payoff.
If you are interested in a linear approach to learning Solr we also offer free tutorials on this website and on our YouTube Channel. Happy searching!
We start with introductory material used when building a Solr test environment and then the difficulty level picks up. We identify the difficulty level on each web page.
At the beginner level, information on Apache Solr is generally high-level and more general. These topics cover the general features of Solr search, its capabilities and how to plan a course of action for your specific needs.
At this level you have likely committed to using Apache Solr professionally as your search application. Here we focus on installation, search concepts and customization. We dig into the configuration files, schemas, topics on indexes and building out search features.
Here you are proficient with Solr and are ready to move your search application to a production environment. Topics here include coding the front-end of the application, scaling, SolrCloud, Lucene and sharing data across applications in the back end with APIs.
Q: What are the prerequisites?
A: A comfort level with the Linux command line, the client/server relationship, networking, XML and the concept of an inverted index.
Q: Can FactorPad provide additional Solr
consulting and guidance?
A: Yes. Contact us through social media.
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