Showing progress of the ELKI DBSCAN clustering model while the model is running?

I am using ELKI's implementation of DBSCAN to cluster different datasets with various sizes (ranging from millions to thousands of observations), and since it can take quite long time for the different datasets when I run the algorithm I was wondering if it somehow is possible to show the progress (or a good estimate) of the algorithm?

I tried unsuccessfully to look in the ELKI documentation for the Clustering Class.

private static Clustering runModel(double eps, int minpts, Database db){

//double eps = 10;

//int minpts = 5;

//db = data in a double[][] format;

Clustering...

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By: StackOverFlow - Tuesday, 8 January

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