An Introduction to MapReduce is a video offering from O’Reilly which provides a simple introduction to the use of map-reduce without a great deal of overhead. The product contains four video segments, starting with a description of the difficulties encountered when using simple scripting against large data sets and swiftly moving into the use of Python scripts to implement a map-reduce job.
From there, the scripts are migrated to the Amazon map-reduce offerings, to demonstrate that the same algorithm can be used in a more sophisticated (Hadoop) environment. The use of Amazon tools consumes two segments, or approximately half the content of this product. An Amazon account will therefore be necessary to fully participate in the exercises.
The provided example case (word count from a novel) is easily understood and does not interfere with the concept presentation. Python is used, but at a novice level, so a deep understanding of that language is not required; obviously access to a machine with Python installed would be helpful in order to run the jobs locally.
One minor problem with the product is that the related content links mentioned within the video do not appear to have been provided; these resources are not essential to use of the videos.
Overall, if you’ve had difficulty with the concept of map-reduce, this product would be worth a look; best audience are those who have not (successfully) run a map-reduce job on their own.