Patents by Inventor Garrett Frere

Garrett Frere has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • DISTRIBUTED IN-DATABASE VECTORIZED OPERATIONS USING USER DEFINED TABLE FUNCTIONS
    Publication number: 20250139076
    Abstract: The subject technology receives first data. The subject technology transforms first data to a wide format, the wide format comprising a second table. The subject technology splits a set of rows into a set of shards of rows. The subject technology, for each shard from the set of shards, sends a particular user defined table function (UDTF), including a particular shard of rows, to a different execution node to perform a set of operations for determining a rolling correlation over a window size. The subject technology provides a set of output values of each particular UDTF corresponding to each shard from the set of shards in a second UDTF. The subject technology sends the second UDTF to a particular execution node to perform an aggregate operation. The subject technology receives a value of the rolling correlation from the particular execution node based on the aggregate operation.
    Type: Application
    Filed: October 27, 2023
    Publication date: May 1, 2025
    Inventors: Pradeep Dorairaj, Garrett Frere, Carsten Stann, Boyu Wang, Mengjia Xia
  • Distributed in-database vectorized operations using user defined table functions
    Patent number: 12197413
    Abstract: The subject technology receives a set of values for a data set corresponding to a request for determining a Pearson correlation. The subject technology determines a number of rows from the data set. The subject technology determines a number of execution nodes to execute the request. The subject technology determines a set of shards of rows from the data set. The subject technology, for each shard from the set of shards, sends a particular user defined table function (UDTF), including a particular shard of rows, to a different execution node to perform a set of operations. The subject technology provides a set of output values of each particular UDTF corresponding to each shard from the set of shards in a second UDTF. The subject technology sends the second UDTF to a particular execution node to perform an aggregate operation using the set of output values of each particular UDTF.
    Type: Grant
    Filed: September 6, 2023
    Date of Patent: January 14, 2025
    Assignee: Snowflake Inc.
    Inventors: Pradeep Dorairaj, Garrett Frere
  • DISTRIBUTED IN-DATABASE VECTORIZED OPERATIONS USING USER DEFINED TABLE FUNCTIONS
    Publication number: 20240256515
    Abstract: The subject technology receives a set of values for a data set corresponding to a request for determining a Pearson correlation. The subject technology determines a number of rows from the data set. The subject technology determines a number of execution nodes to execute the request. The subject technology determines a set of shards of rows from the data set. The subject technology, for each shard from the set of shards, sends a particular user defined table function (UDTF), including a particular shard of rows, to a different execution node to perform a set of operations. The subject technology provides a set of output values of each particular UDTF corresponding to each shard from the set of shards in a second UDTF. The subject technology sends the second UDTF to a particular execution node to perform an aggregate operation using the set of output values of each particular UDTF.
    Type: Application
    Filed: September 6, 2023
    Publication date: August 1, 2024
    Inventors: Pradeep Dorairaj, Garrett Frere