You probably have heard leadership talk about Digital Transformation in meetings, town halls and blogs. Industry pundits seem to talk/write about it; often using it to rank which companies are competing at the topmost level in their industry. Often though there is confusion among the rank and file employees about this whole “Digital” thing. Is it the latest buzzword that executives are in love with (probably true to some extent)? Is there anything behind it or just a lot of hot air? Who are all those high priced management consultants that show up to tell us about Digital Transformation, without explaining what it is?
(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.
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
You must have surely heard the tag lines “Data is gold” or “Data is oil”! If not, then you heard it now. The notion is that with the right type and volume of data, you can pull out very valuable insights to help support your business/IT goals. This data might be coming from your own applications, log files, social media data, blogs, online news media, etc. Data is everywhere. And when you have that data, you want to search through it for intelligent information. That is where search engines come to the rescue. I will cover one such search engine – ElasticSearch.
Extending from some of my previous posts around the 2012 Presidential political contributions, here I will use Spring Integration, ActiveMQ, JMS and Mongodb to load the CSV data into Mongodb.
Notes from attending today’s (6/26/2012) MongoDB conference – MongoDC.