An enhancement of the mapreduce apriori algorithm using vertical data layout and set theory concept of intersection
The process of Association Rule Generation is an important task in Data Mining. It is widely used for the Market Basket Analysis. The data that is used for the generation of Association Rules is usually distributed and complex. This can be efficiently implemented using the Hadoop Framework as it can process large datasets with less cost and good performance. We have proposed an efficient algorithm for MapReduce Apriori based on Hadoop MapReduce model using Vertical Database Layout and Set Theory concept of Intersection.