(Updated version. Originally Published on: Nov 3, 2013) Here are some things to keep in mind as you go about designing your ElasticSearch cluster. Many of these are from real life experiences and IMO are the basic common sense items you should consider. In addition to these settings noted here, there maybe other settings that are relevant to your use case.
In the tech world one cannot stay a day away from hearing the words API or Microservices. For those who work in startups or tech firms (google type) these are well understood. But once you walk into large non-tech firms, these words are not as well understood.
Experimenting with Ganglia to monitor my nodes. More detailed steps to come.
While I had the privilege of using ElasticSearch to implement media analytics in a past role, it is only recently that I have started looking at it for log analysis.
In this article we will run the example from Part-1 in pseudo-distributed single server mode. Most of the configuration details are clearly laid out on the Hadoop site at Setting Up Single Server Pseudo-Distributed mode. For the sake of additional clarity I will note them here and also run our previous job from Part-1 against the new cluster. I assume that you already have Hadoop downloaded and setup from the previous article.
Note: Updated to Hadoop 2.4.1 and re-published from original Sept 28th, 2011 blog.
Hadoop is a framework that allows you to process large sets of unstructured or semi-structured data. The unstructured/semi-structured nature of the data and the sheer size (terabytes or petabytes) make the current RDMS offerings come short. Enter Apache Hadoop.
Note: Updated to Hadoop 2.4.1 and re-published from original Sept 28th, 2011 blog. Continue reading
I have been playing with ElasticSearch for a while now, both at work as well as personally. In recent discussions I came across a use case to perform faceted searches and figured this would be a good topic for a blog post. Lets explore by example how to implement faceted searches using both the older facet module as well as the newer aggregations module.
Highly experienced & passionate technologists have a challenging task in terms of figuring out their career strategies. For some this process of self discovery and adjustment works itself out quick, but for others its a harder journey. A passionate technologist often feels the need to be exposed to new cutting edge technologies and at the same time expects appropriate career growth and recognition.
Once you spend a lot of time with a set of tools there is a tendency to come up with solutions to every problem with just those tools. This narrow tunnel vision is dangerous for a techie since you can be completely blindsided when something new comes up and you are found lacking in new skills. It also inhibits the ability to learn new things and take in new ideas. Having spent a lot of time in the Java Spring tunnel, it was a welcome break for me to try out SparkJava & JDBI recently – void of any Spring, JEE or IoC.