Blog Archive

September 2015

There is an overabundance of terms thrown out today that “everyone” “must” embrace when it comes to data.  Here are a few of the most popular:

In my previous post, I began illustrating what Hadoop would look like as a business organization, focusing on the DataNodes in a Hadoop File System. Assuming all the rooms or DataNodes are in good condition, how do we start the process of gathering and analyzing data? The process begins with the managers (Mappers).  Each Mapper (manager) sits at one of the two desks in each room. It is their job to make sure that all the data that needs to be analyzed together ends up in the same room.

You don’t know what tough is, back in the day when I had to walk uphill both ways to school…” I remember my grandfather saying to me when I would complain about something.

Hadoop has existed for roughly a decade since it was first conceived at Yahoo by Doug Cutting and Mike Cafarella in 2005.

I’ve had the opportunity to research and discuss system performance in a serious amount of detail recently. In practice this involved staring at row after row of testing results on various spreadsheets, along with digging through countless white papers and shuffling through old emails.

Prospective employers have been carousing social media sites such as Facebook, YouTube, Twitter and Instagram to investigate potential employees for some time.