Research on Improved FP-Growth Algorithm with MapReduce
LI Long-shu · Computer Technology and Development · 2012
Nowadays,the massively parallel computing model MapReduce is very popular in the current industry.It will introduce it into the improvement of association rules of data mining algorithms in parallelization,propose the improved MR-FP algorithm based on paralleled FP-Growth algorithm,and provide the parallelization association rules mining with node scalable,fault tolerance and operation.Draw a conclusion that the system can still maintain pretty high performance when the transactions are under the orders of magnitude level.The theoretical analysis and the case studies demonstrate that data mining theory and methods can show their full abilities based on the cloud computing.It deserves more valuable research.