I am very excited about the power that In-Database MapReduce puts in the hands of the larger BI community. I’ll be leading a Night School session on In-Database MapReduce at the TDWI World Conference in November in New Orleans.
Please join me if you are interested in learning more about the MapReduce framework and its applications. I will introduce MapReduce from the basic principles, and then help build up your intuition. If we have time, I will even address why MapReduce is not UDF re-discovered.
If you are unable to attend, or eager to understand, here are some MapReduce resources you may find informative: Aster’s whitepaper on In-Database MapReduce; Google Labs’ MapReduce research paper; Curt Monash’s post on Known Applications of MapReduce.
A great open-source project that I’d like to commend and draw your attention to illustrate the power of MapReduce is Apache’s Mahout Project, which is building machine learning algorithms on the MapReduce framework (Classification, Clustering, Regression, Dimension reduction and Evolutionary Algorithms).
I am sure this is just a snippet of the MapReduce resources available. If you have some that you have found helpful, please share them in your comments. I will be happy to review and cover them in our TDWI Night School!