Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that facilitate resource and space efficient analysis of large scale datasets. Methods include obtaining activity data for objects in a dataset. For each data item in the dataset, a hashed parameter having a binary representation is generated using an identifier for the object. A register is identified from among a set of registers based on the hashed parameter. A determination is made that the hashed parameter for the object contributes to an aggregation amount that specifies a number of occurrences of the object in the dataset. Based on this determination, an aggregation amount stored in the register is updated. Based on aggregation amounts stored in the set of registers, a reporting output is generated that provides an aggregate distribution of the objects in the dataset based on the activity data for the objects.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that facilitate resource and space efficient analysis of large scale datasets. Methods include obtaining activity data for objects in a dataset. For each data item the dataset, a hashed parameter having a binary representation is generated using an identifier for the object. A register is identified from in a set of registers based on the hashed parameter. A determination is made that the hashed, parameter for the object contributes to an aggregation amount that specifies a number of occurrences of the object in the dataset Based on this determination, an aggregation amount stored in the register is updated. Based on aggregation amounts stored in the set of registers, a reporting output is generated that provides an aggregate distribution of the objects in the dataset based on the activity data for the objects.