Adaptive resolution histogram on complex datatypes

Abstract

Techniques herein map between key spaces to generate a balanced adaptive resolution histogram for dataset partitioning. In embodiments, a computer (C) creates a mapping that associates sparse keys (SKs) with distinct dense keys. C constructs a trie by processing each item of a dataset as follows. Based on the item, C obtains an SK. C navigates from a root NT (node of the trie) to a particular NT based on a sequence of dense digits (SDD). Each dense digit of the SDD is based on the mapping. Each NT identifies a dense prefix comprising dense digits. C assigns the item to a target node based on a threshold and count of items assigned to a subtree rooted at the particular node. C determines a range of SKs for each partition of the dataset, based on: an item count for a node or subtree, dense prefixes of NTs, and the mapping.