Methods and apparatus to virtually estimate cardinality with global registers

Patent metadata

Field	Value
Publication number	US-12554693-B2
Application number	US-202519022160-A
Country	US
Kind code	B2
Filing date	Jan 15, 2025
Priority date	Oct 28, 2022
Publication date	Feb 17, 2026
Grant date	Feb 17, 2026

Abstract

Methods, apparatus, systems, and articles of manufacture to virtually estimate cardinality with global registers are disclosed. An example apparatus includes processor circuitry to s assign subsets of a sample dataset to a shared global register array, the shared global register array having a first number of registers, the sample dataset selected from a reference dataset of media assets; identify a virtual register array from the shared global register array that includes data elements associated with a label value, the virtual register array including a second number of registers less than the first number of registers; determine a maximum rank value of the label value across the virtual register array; and calculate a cardinality estimate of the label value across the virtual register array based on the second number of registers and the maximum rank value.

First claim

The invention claimed is:

1 . A computing system comprising a processor and a memory, the computing system configured to perform a set of operations comprising:
assigning subsets of a sample dataset to a shared global register array, the shared global register array having a first number of registers, the sample dataset selected from a reference dataset; identifying a virtual register array from the shared global register array that includes data elements associated with a label value, the virtual register array including a second number of registers less than the first number of registers; determining a maximum rank value of the label value across the virtual register array; and calculating a cardinality estimate of the label value across the virtual register array based on the second number of registers and the maximum rank value.

2 . The computing system of claim 1 , wherein the cardinality estimate is a first cardinality estimate, and the set of operations further comprises calculating a second cardinality estimate of the label value across the shared global register array based on the first cardinality estimate, the first number of registers, and the second number of registers.

3 . The computing system of claim 1 , wherein the set of operations further comprises generating a first rank distribution array for the shared global register array.

4 . The computing system of claim 3 , wherein the set of operations further comprises generating a second rank distribution array for the virtual register array.

5 . The computing system of claim 4 , wherein the set of operations further comprises generating an estimated recovered rank distribution array for the label value based on the first rank distribution array and the second rank distribution array.

6 . The computing system of claim 5 , wherein the set of operations further comprises determining an estimated cumulative distribution function for the label value based on the estimated recovered rank distribution array.

7 . The computing system of claim 6 , wherein the maximum rank value for the label value is based on the estimated cumulative distribution function.

8 . A non-transitory computer-readable medium having stored therein instructions that when executed by a computing system cause the computing system to perform a set of operations comprising:
assigning subsets of a sample dataset to a shared global register array, the shared global register array having a first number of registers, the sample dataset selected from a reference dataset; identifying a virtual register array from the shared global register array that includes data elements associated with a label value, the virtual register array including a second number of registers less than the first number of registers; determining a maximum rank value of the label value across the virtual register array; and calculating a cardinality estimate of the label value across the virtual register array based on the second number of registers and the maximum rank value.

9 . The non-transitory computer-readable medium of claim 8 , wherein the cardinality estimate is a first cardinality estimate, and the set of operations further comprises calculating a second cardinality estimate of the label value across the shared global register array based on the first cardinality estimate, the first number of registers, and the second number of registers.

10 . The non-transitory computer-readable medium of claim 8 , wherein the set of operations further comprises generating a first rank distribution array for the shared global register array.

11 . The non-transitory computer-readable medium of claim 10 , wherein the set of operations further comprises generating a second rank distribution array for the virtual register array.

12 . The non-transitory computer-readable medium of claim 11 , wherein the set of operations further comprises generating an estimated recovered rank distribution array for the label value based on the first rank distribution array and the second rank distribution array.

13 . The non-transitory computer-readable medium of claim 12 , wherein the set of operations further comprises determining an estimated cumulative distribution function for the label value based on the estimated recovered rank distribution array.

14 . The non-transitory computer-readable medium of claim 13 , wherein the maximum rank value for the label value is based on the estimated cumulative distribution function.

15 . A method comprising:
assigning subsets of a sample dataset to a shared global register array, the shared global register array having a first number of registers, the sample dataset selected from a reference dataset; identifying a virtual register array from the shared global register array that includes data elements associated with a label value, the virtual register array including a second number of registers less than the first number of registers; determining a maximum rank value of the label value across the virtual register array; and calculating a cardinality estimate of the label value across the virtual register array based on the second number of registers and the maximum rank value.

16 . The method of claim 15 , wherein the cardinality estimate is a first cardinality estimate, and the method further comprises calculating a second cardinality estimate of the label value across the shared global register array based on the first cardinality estimate, the first number of registers, and the second number of registers.

17 . The method of claim 15 , further comprising generating a first rank distribution array for the shared global register array.

18 . The method of claim 17 , further comprising generating a second rank distribution array for the virtual register array.

19 . The method of claim 18 , further comprising generating an estimated recovered rank distribution array for the label value based on the first rank distribution array and the second rank distribution array.

20 . The method of claim 19 , further comprising determining an estimated cumulative distribution function for the label value based on the estimated recovered rank distribution array.

Assignees

• Nielsen Co Us Llc

Inventors

• Sheppard Michael R

Classifications

• G06F16/24556

  Aggregation; Duplicate elimination · CPC title

• G06F16/2228 Primary

  Indexing structures · CPC title