Abstract

Abstract: Data Mining is one of the most important areas of patternmining research that generates logical and informative information that appliesto raw information. This function aims to extract a set of objects representingany type of sentence of definition of homosexuality and data familiarity. Ourpropulsion operations are based on a very powerful algorithm called Apriorialgorithm and hadoop framework. The proposed system includes the AprioriMapReduce algorithms and the Apriori iterative Max Apriori based on a reducedmap framework designed to extract common pattern mines from large databases.These algorithms extract a set of frequency data from any existing data setregardless of its frequency. Max Apriori Map Reduced Algorithm is our proposedalgorithm that provides the most common object calculation compared to the bigdata set compared to the other three algorithms and with our algorithm wesuggest removing the time required compared to the other Apriori Reduced Mapand -iterative Apriori. The main motivation for this activity is to detectwaves set using large amounts of data and to remove unwanted data from a set oflarge data sets. To evaluate the performance of the proposed algorithms, aseparate data set is considered.

Keywords—BigData, Hadoop, Data Mining, MaxApriori, Mapreduce, Matching.