Clustering based on basic standards like density, shape, and size is very common. In a similar way, DBSCAN is an extensive method of the density-based clustering algorithm.

For MapReduce check this article (https://medium.com/@rrfd/your-first-map-reduce-using-hadoop-with-python-and-osx-ca3b6f3dfe78)

Algorithm description:

1. Choose a random point p.
2. Fetch all points that are density-reachable from p with respect to eps and minPts.
3. A cluster is formed if p is a core point.
4. Visit the next point of the dataset, if p is a border point and none of the points is density-reachable from p.
5. Repeat the above process until all the points have been examined.

#mapreduce #big-data #partitioning #dbscan #clustering-algorithm #big data clustering: mr-dbscan from scratch using python