I recently attended the HBaseCon 2013 conference and talked about building a real-time video analytics platform using Hadoop and HBase.
My presentation is embedded below:
More information about HBaseCon 2013 here: http://blog.cloudera.com/blog/2013/06/the-hbasecon-2013-afterglow/
I recently set up a fully working Ubuntu 12.04.2 32-bit (yes, with working display / video card!) on a Foxconn nT-1200 Nano PC (Intel Atom D2500 with Intel GMA 3600 video card) and a OCZ 120 GB SSD and G-Skill 4 GB RAM.
A little while back, I wrote a PHP script to generate a random set of large arrays and both summate them across one dimenion, and sort them.
Recently we had a problem with s3cmd giving errors while moving or copying (large) files across buckets in S3. This had worked fine perfectly before, but our file sizes were increasing.
I’ve recently been setting up devices that need to have ServerDensity monitoring automatically added to them when I start them up. Setting up the ServerDensity agent itself can be automated through shell commands, but you also need to set the API key in the config. I use a Python file to create a new device in ServerDensity and output the API/agent key for the newly created device.
Below is a WYSIWYG tutorial on how to set up a HBase cluster (and Thrift) on Amazon’s Elastic Map Reduce.
In this post (hopefully the first of more), I hope to provide a gentle introduction to HBase (since I never had one myself!) This specific post is more about the specifics of HBase’s data structure, but I hope to do more posts introducing HBase programming using a combination of HBase on Amazon’s Elastic Map Reduce (I like to call it Amazon’s HAAS or HBase-as-a-Service) and Python using the HappyBase library (this offers a really easy interface to the HBase Thrift interface.)