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Ever wondered how a search engine works? In this post I would like to show you a high level view of the internal workings of a search engine and how it can be used to give fast access to your data. I won't go into any technical details, what I am describing here holds true for any Lucene based search engine, be it Lucene itself, Solr or Elasticsearch.
BEDCon is over again. This marks the third year I have been there and it still has the cheapest prices for a general conference I have seen in Germany. If you are looking for a nice conference in Berlin you should definitively consider it.
This week on Tuesday and Wednesday parts of the German Java community met for JavaLand, the conference of the German Java community. In this post I would like to talk about the conference in general, some of the talks I attended and show you some facts about what happened on Twitter.
Indexing, the process of putting data in a search engine, often is the foundation of anything when building a search based application. With Instant Apache Solr Indexing Data Howto Alexandre Rafalovitch has written a book dedicated to different aspects of indexing.
Though the classic use case for search engines is keyword search nowadays they are often used to serve content that doesn't resemble a search result list at all. As they are optimized for read access they make good candidates for serving any part of a website that needs a dynamic query mechanism. Faceting is most often used to display filters for refining the search results but it can also be used to build hierarchical navigations from results. I am using Solr in this post but the concept can also be used with Elasticsearch or even plain Lucene.