![]() Gen 3 - still evolving: Lucidworks Fusion, Cloudera Search Gen 2 - examples include HP IDOL platform, FAST, open-source Solr, Elasticsearch Gen 1 - examples include Verity K2 platform initial stages, open-source Lucene library Search Gen 3 - convergence of search and big data, integration with distributed storage and distributed computation systems.Search Gen 2 - feature rich search, connectors for every data source.Search Gen 1 - full text search, manual indexing of data.We can generalize evolution of enterprise search engines into three generations: Google has influenced enterprise search engines to deliver features like sponsored links, type-ahead and more like this. Search engines on the enterprise side have also evolved though at a slower pace compared to Google and moved on from simple text search to multi-dimensional search features. Google has become synonymous with search and brought the search box to every electronic device in use today. Internet search engines have led the path and arguably set the direction of advancement of overall Information Technology. Search engines have evolved during the past 20 years along with the rest of the Information Technologies. Lucene has come a long way in the last 10+ years so the need for this is very remote, but possible. If we need a deeper customization at the Lucene codec level, we can build a custom Lucene coded and build Solr using the customized Lucene code and deploy it. Source code for the filter is available on Github: SolrCustomFilter Solr plugins use the Factory pattern and we need to create the Filter class and FilterFactory class, package them into a jar file and deploy the jar into one of the directories on the classpath for Solr. The following field-type configuration shows the custom filter "WordConcatenateFilter" added to the pipeline for processing fields of type "text_en": Because the change we are making is at the core level, we need this executed before tokens are generated from the character stream by the search engine. The customization needed to support above requirement is to be able to intercept during the index time for a given field at the character stream level and modify the character stream adding the merged tokens we are looking for before the next stage in the pipeline is called. Solr allows to add custom behavior for both index and search operations by manipulating the index/search pipelines defined in the solrconfig.xml. Solr provides this ability for users to build custom filters which is very powerful and differentiating factor from commercial search engines in the market. But we can build our own custom plugin to meet the above requirement and add it to the platform. This is currently not supported out of the box from any of the Solr analyzers and filters. For example, a name "De Vera Michael" which is an European origin should be returned in search results when someone search for "devera". ![]() In this post, we consider a custom requirement related to name search application which involves names with European and American origins. But there will always be business use cases where a few customization are needed to achieve the desired results. pt=48.1371079,11.Solr has a lot of bells and whistles to use out of the box for building a robust search platform for a company.The views-built search page renders a query against my Solr Server like path=/select params=Īpparently there are some parameters responsible for the distance calculation: I believe there must be something like $result = SolrSearchService('myServer', 'myIndex')->request() There's a solution for D7 here: How to send a custom Solr Query using Search API Solr but none of that seems to be usable with the D8 modules. But I want to do the request by myself (having my own form and submit method). I've managed to create a search form against my Solr Server with views. My nodes have a geofield and my search query should find all the nodes within a range.
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