Analysis of Big data using MapReduce Framewok with comparison between Apriori Algorithm and FP Growth Algorithm
Keywords:
Big Data,Apriori Algorithm,FP Growth,Map Reduce,Candidate Generation,Itemsets,Frequent Itemsets .Abstract
Now days data is generated at high rate from
different sources such as Business , Education, Research Internet
Archive ,Social Sites etc .In Short data that is generated from
different sources at high rate having massive volumes is known
as Big Data . Earlier Centralized systems were not designed
keeping Big Data needs in mind which made difficult to process
Big Data on these systems. Hadoop is Parallel Distributed
Infrastructure developed to store and handle Big Data.We are
implementing MapReduce Framework to harness its parallel
and simultaneously processing capabilities to analyze Big Data.
MapReduce is Parallel Distributed Programming Paradigm that
runs on HDFS and processes Big Data. In this Project we are
using two algorithms Apriori and FP-Growth on MapReduce
Framework for Analysing Big Data. Apriori and FP-Growth
Algorithms are used to for finding association rules and frequent
patterns which is nothing but knowledge which and enterprise or
an individual can utilize to make profit to make better decision
or to bulid a strategy which yield best result and much more
We will be using online shopping data as our dataset for the
particular operations.
