For very large input tables, building a mining model may take a long time to process. A possible solution is to create the mining model for a random sample of the input data. This is especially useful during the iterative development phase where you want to test different mining settings to find the best combination that creates a good model. Once you are satisfied with the mining setting, you may want to remove the Sampler operator and run the final mining run to build the model on the whole dataset.