Elasticsearch is the innovative and advanced open source distributed search engine, based on Apache Lucene. Over the past several years, at Trifork we have been doing a lot of search implementations. Driven by the fact that every other customer wanted the ‘Google-experience’ (just a text box, type some text and get relevant results) as part […]
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Tag: Apache Lucene
How to write an elasticsearch river plugin
Up until now I told you why I think elasticsearch is so cool and how you can use it combined with Spring. It’s now time to get to something a little more technical. For example, once you have a search engine running you need to index data; when it comes to indexing data you usually […]
What’s so cool about elasticsearch?
Whenever there’s a new product out there and you start using it, suggest it to customers or colleagues, you need to be prepared to answer this question: “Why should I use it?”. Well, the answer could be as simple as “Because it’s cool!”, which of course is the case with elasticsearch, but then at some […]
Elasticsearch beyond “Big Data” – running elasticsearch embedded
Trifork has a long track record in doing project, training and consulting around open source search technologies. Currently we are working on several interesting search projects using elasticsearch. Elasticsearch is an open source, distributed, RESTful, search engine built on top of Apache Lucene. In contrast to for instance Apache Solr, elasticsearch is built as a […]
On Schemas and Lucene
One of the very first thing users encounter when using Apache Solr is its schema. Here they configure the fields that their Documents will contain and the field types which define amongst other things, how field data will be analyzed. Solr’s schema is often touted as one of its major features and you will find […]
There’s More Lucene in Solr than You Think!
We’ve been providing Lucene & Solr consultancy and training services for quite a few years now and it’s always interesting to see how these two technologies are perceived by different companies and their technical people. More precisely, I find it interesting how little Solr users know about Lucene and more so, how unaware they are […]
Faceting & result grouping
Result grouping and faceting are in essence two different search features. Faceting counts the number of hits for specific field values matching the current query. Result grouping groups documents together with a common property and places these documents under a group. These groups are used as the hits in the search result. Usually result grouping […]
Result grouping made easier
Lucene has result grouping for a while now as a contrib in Lucene 3.x and as a module in the upcoming 4.0 release. In both releases the actual grouping is performed with Lucene Collectors. As a Lucene user you need to use various of these Collectors in searches. However these Collectors have many constructor arguments. […]
Lucene Versions – Stable, Development, 3.x and 4.0
With Solr and Lucene 3.6 soon becoming the last featureful 3.x release and the release of 4.0 slowly drawing near, I thought it might be useful just to recap what all the various versions mean to you the user and why two very different versions are soon going to be made available. A Brief History […]
Using your Lucene index as input to your Mahout job – Part I
This blog shows you how to use an upcoming Mahout feature, the lucene2seq program or https://issues.apache.org/jira/browse/MAHOUT-944. This program reads the contents of stored fields in your Lucene index and converts them into text sequence files, to be used by a Mahout text clustering job. The tool contains both a sequential and MapReduce implementation and can […]