You can find a list of all posts in the archive
In my last post I showed how you can index tweets for an event in Elasticsearch and how to do some simple queries on it using its HTTP API. This week I will show how you can use Kibana 3 to visualize the data and make it explorable without having to learn the Elasticsearch API.
Tweets can say a lot about an event. The hashtags that are used and the time that is used for tweeting can be interesting to see. Some of the questions you might want answers to:
During this years FrOSCon I indexed all relevant tweets in ElasticSearch using the Twitter River. In this post I'll show you how you can index tweets in ElasticSearch to have a dataset you can do analytics with. We will see how we can get answers to the first two questions using the ElasticSearch Query DSL. Next week I will show how Kibana can help you to get a visual representation of the data.
A while ago I had the chance to attend a training on web development with CoreMedia. It's a quite enterprisey commercial Content Management System that powers large corporate websites like telekom.com as well as news sites like Bild.de (well, you can't hold CoreMedia responsible for the kind of "content" people put into their system). As I have been working with different Java based Content Management Systems over the years I was really looking forward to learn about the system I heard really good things about. In this post I'll describe the basic structure of the system as well how it feels like to develop with it.
Last weekend I attended FrOSCon, the Free and Open Source Software Conference taking place in St. Augustin near Bonn. It's a community organized conference with an especially low entrance fee and a relaxed vibe. The talks are a good mixture of development and system administration topics.
This is the second part of the article on things I learned while building a simple Java based search application on top of ElasticSearch. In the first part of this article we looked at how to index data in ElasticSearch and what the mapping is. Though ElasticSearch is often called schema free specifying the mapping is still a crucial part of creating a search application. This time we will look at the query side and see how we can get our indexed talks out of it again.