In this post I explain how we implemented the way we created the RSS feeds in a project and the challenges that we had during the set-up.
My colleague Jettro Coenradie explained in a previous post how you can create a feed using Rome and Spring 3, but didn’t elaborated on the Spring 3 part. I will explain how we used Spring 3 to create the feeds.
Today, I finalized the 0.5 release of the Axon Framework. There is quite a number of changes since the 0.4 version. The 0.5 version is a major step towards production readiness of the framework.
Besides some changes to existing building blocks, such as the event bus, which is now much more powerful, the 0.5 version also includes some new features.
Read on to find out more.
The Enterprise Search market has long been dominated by commercial vendors and their products (e.g. Autonomy and Fast). We at JTeam feel that this era is finally over. At least for certain customers and requirements, there is finally a good Open Source alternative: Apache Solr, which is the Enterprise Search server based on Apache Lucene. In this blog post we’ll give our view on enterprise search and explain how Lucene and Solr can help you realize your projects.
Good, solid language analysis is a very important asset for the quality of your search results. It is one of the features that for instance Microsoft Fast and Endeca are using as one of their unique selling points. However, you can get the same powerful analysis when using Apache Solr to implement your search.
Last week, I published the 0.4 release of the Axon Framework. Axon helps developers build high performance, scalable and extensible applications using the CQRS pattern. The 0.4 release is a major step towards 1.0, and includes transactional event handling, high-performance caching repositories and easy configuration of event sourcing support. Furthermore, we have also built a demo application that uses Flex to get real-time updates pushed from the server.
Read on to find out more.
Lately I have been looking into and playing around with the Google App Engine. In this post I want to give a little introduction to the Google App Engine, why it can be interesting and how to work with it.
Read the rest of this entry »
In a number of blog entries we have spoken about the spatial search functionality that we have been developing here at Jteam. In the last two weeks, I have had a chance to contribute much of this work back to the Apache Lucene project with the goal of furthering the development of Lucene’s open source spatial search support. If you want to dive immediately into the code, then jump to LUCENE-2139, if you want more details, then read on.
Introducing the Solr Spatial Plugin
What do a directory services company, a wholesaler of bathroom fittings, a social events guide, an oceanographic data centre and the pan-European library initiative have in common? They all need to offer their clients the ability to search and filter results within a flexible geographic area, defined by the user.
With a variety of businesses needing to customize search results to the preferences of a narrowly targeted audience, there’s an increasing demand for incorporating geographical location information into standard search functionality.
In response, JTeam has recently launched the Solr Spatial Plugin (SSP): a free, standalone, enterprise-ready plugin enabling location based search, built on top of the open source project Apache Solr.
Tomorrow, JTeam is hosting the second edition of our Search Symposium. The following two session (see read more / below) will be presented and will serve as input for the discussion afterward. If you are working in the search domain and would like to join us, sign up by sending an email to: signup@jteam.nl.
Hope to see you all there!
In a number of search projects that I have done using Lucene and Solr there was a lot of almost identical data. From a user perspective, when searching the first result pages were full of documents that look very similar, for instance getting a full page of the same car model, where only the edition differs, when searching for a specific car brand. What actually is desired is to only show the different models. Then and only when a user is interested in a certain model, the user can view all the editions of the model by clicking on the result. We simply want to group our search result, based on some criteria. Although this is not support out-of-the-box with Lucene/Solr, luckily it is possible using a patch that I’ve created and contributed to Solr. This blog entry explains what result grouping (also known as field collapsing) is and how you can start using it in your own projects.