Abstract: This disclosure describes, in part, techniques for estimating frequency values of top contributors of a high cardinality data set in a computationally efficient manner. In one example, the techniques utilize a probabilistic data structure, such as a count-min-sketch, for identifying which contributors are the largest contributors to a particular metric. After identifying these largest contributors using the probabilistic data structure, the techniques may store the contributor IDs and the their respective estimated cumulative value (e.g., frequency counts) in a top-N list.