your list of stuff to learn is rather heavy on implementation - wouldn't it make more sense to use a poor implementation of an algorithm in hadoop that uses 10

your list of stuff to learn is rather heavy on implementation - wouldn't it make more sense to use a poor implementation of an algorithm in hadoop that uses 10 machines than to squeeze every ounce of performance using GPU's, cache locality etc. in a single machine, at great expense in programmer time? I think that one nice thing about the idea of "big data" is being about to parallelize the problem and just throw more cores at it. But on the other hand, I do think that when people think of "big data" they have in some magic solution that doesn't really exist. At the end of the day big data is just statistics.