I’m working on a jBPM prototype since last couple of days. The integration with Spring wasn’t a smooth ride. In my previous projects, I used jBPM3.2. But it seems jBPM4 is pretty much a rewrite. There are couple of few nice additions like service API’ for task and process management, support for java task and many more. And there are few changes which I didn’t like. Till 4.2 the support for JPA was provided, which is taken off starting 4.3 release. Yes definitely you can write some wrappers and still achieve it. But!! Between 4.3 and 4.4 also there are some major API changes. So the whole point is to get the app running, I had to digg into mailing lists and source code. Now that it works, I thought I would write a short blog about it.
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Enterprise Search is becoming one of the common requirements of any consumer web application that we build these days. So I thought of learning some stuff in this domain. If you think about open source frameworks providing enterprise search functionality, probably Lucene is the one and only answer that comes to your mind. Lucene is a fully featured full text search engine library. Some other platforms and frameworks are developed that leverages core search functionality of Lucene.
Solr is one of such platforms that provide cool features like token highlighting, faceted search and many many more. Solr runs as a standalone search server and can be integrated into the applications using HTTP/XML API. Solr is typically used (or suggested to be used) when the underlying data that you are trying to index doesn’t change often.
Hibernate Search is a framework built on top of Lucene and Hibernate Core. In the following blog post, I would explain how to integrate Hibernate Search into your application.
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Recently I was playing around with Spring Integration. To understand any new framework one cannot just rely on documentation. So I created a demo application to try out different features of the framework. Since my main motivation was to understand Spring Integration framework, I wanted to spend minimal efforts in input data generation. So I decided to work with Twitter messages.
Most of you must be familiar with Twitter. Twitter is a service for friends, family, and co–workers to communicate and stay connected through the exchange of quick, frequent messages. There are different clients available to use Twitter. In the sample application, I first read the friends timeline. Then based on the source/client used for tweeting, the tweets are routed to different channels. The tweets originated from “web” are simply logged, while the tweets originated from “Dzone.com” are dispatched using a mail sender. The basic flow of the application is depicted in the following diagram.
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