The article compares different algorithms used to analyze customer purchasing patterns in large databases. The focus is on finding frequent item sets and association rules to understand how items are bought together. The researchers looked at three specific algorithms - Apriori, Eclat, and Improved Apriori - to see how they perform in Market Basket Analysis using Hadoop. The goal is to help industries make better decisions, like how to arrange items in stores or supermarkets, by understanding customer behavior.