Survey on Partition based Clustering Algorithms in Big Data - Mahima Jane, E; George Dharma Prakash Raj, E (International Journal of Computer Sciences and Engineering, 2025)
Clustering is the task of dividing the data points into a number of groups such that data points in the same groups are more similar to other data points in the same group than those in other groups. As Big Data is referring to terabytes and petabytes of data and clustering algorithms are come with high computational costs, the question is how to cope with this problem and how to deploy clustering techniques to big data and get the results in a reasonable time. This paper focuses on the traditional partition based clustering algorithms such as KMeans, K Medoids, PAM, CLARA and CLARANS and its advantages and disadvantages.