Mapreduce Based Pattern Mining Algorithm In Distributed Environment

Abstract

DCE (Distributed Computing Environment) is an industry-standard software technology for setting up and managing computing and data exchange in a system of distributed computers. The proposed method initially extracts frequent item sets for each zone using existing distributed frequent pattern mining algorithms. It also compares the time efficiency of MapReduce based frequent pattern mining algorithm with Count Distribution Algorithm and Fast Distributed Mining algorithms. It presents novel approach to identify consistent and inconsistent association rules from sales data located in distributed environment and overcomes the main memory bottleneck and computing time overhead of single computing system by applying computations to multi node cluster. Here the association generated from frequent item sets are too large that it becomes complex to analyze it. Thus, the MapReduce based consistent and inconsistent rule detection (MR-CIRD) algorithm is proposed to detect the consistent and inconsistent rules from big data and provide useful and actionable knowledge to the domain experts.