Implement a Kmeans algorithm using MapReduce to cluster the provided data set.

A 2-d data with 100,000 instances is provided. You can code it with any programming language you prefer. Basic Tasks: 1. Describe how you implement the K-means using Mapreduce and what problems you’ve encounter. 2. Run the algorithm in a single iteration with different number of k: k =60, k= 80 and k=100. 3. Report the execution time with different k in a single iteration: k =60, k= 80 and k=100. 4. Submit your Java file/ other format of programming file with comments and detail documentation on how to execute your code (or a Readme file). Figure out a way that you can run the algorithm with 30 iterations with a k= 100. Report your results (the final centers and the assignments for each centers). After you’ve finished the first question, visualize your result using a 2-d plot. Testing to be done using hadoop NOTE: the deadline for this project is tuesday 11/25/18 EST 10:00 am