SQL is everywhere. Believe it or not there are legacy relational "schema-with" databases filled with data all over the internet. Chances are even your own office has at least one SQL database lurking in a closet somewhere.
So, how do you leverage your existing "schema-with" databases and still be able to use the power of Map/Reduce? Introducing MR SQL: A Map/Reduce Front-End to SQL.
Often times, I don't get to get my hands dirty at work. Not being one to let myself atrophy, I keep my eyes out for new and exciting things to catch my fancy, and spend hours and hours writing new code: usually reinventing the wheel, often times poking and prodding, just trying to figure out what I'm going to do with what I find.
One of the projects that caught my eye a bit over a year ago was CouchDB, a RESTful document storage engine, that happens to have Map/Reduce support. Being the database freak that I am, I started thinking about all of the projects I've worked on in the past that could have been improved with a document model over pseudo-relational databases. So many came to mind, and I was excited about the flexibility of CouchDB; so useful for so many things, especially with strong data analysis abilities via map and reduce.