MICRO-PARTITION CLUSTERING BASED ON EXPRESSION PROPERTY METADATA

    公开(公告)号:US20240354315A1

    公开(公告)日:2024-10-24

    申请号:US18302234

    申请日:2023-04-18

    Applicant: SNOWFLAKE INC.

    CPC classification number: G06F16/285 G06F16/24556

    Abstract: A method for selecting micro-partitions for a clustering operation includes: storing table data in a plurality of micro-partitions of a storage device, wherein each of the plurality of micro-partitions comprises a portion of the table data, wherein subsets of the plurality of micro-partitions are associated with a respective one of a plurality of expression property (EP) files, and wherein each of the plurality of EP files comprises an EP data region that represents the portions of the table data of the subset of the plurality of micro-partitions associated with the EP file; determining sub-ranges of the table data based on the EP data regions of the plurality of EP files; selecting a subset of the plurality of EP files for a clustering operation based on the sub-ranges of the table data; and performing the clustering operation on the micro-partitions associated with the subset of the EP files.

    HEURISTIC SEARCH FOR OPTIMAL NODE IN A GENERALIZATION LATTICE

    公开(公告)号:US20240346334A1

    公开(公告)日:2024-10-17

    申请号:US18756936

    申请日:2024-06-27

    Applicant: SNOWFLAKE INC.

    Inventor: David Jensen

    CPC classification number: G06N5/01 G06F16/24564

    Abstract: An approach is disclosed that determines a path through multiple levels of a generalization lattice. The path includes multiple nodes corresponding to the multiple levels, and each of the nodes is determined from a scoring function that utilizes a corresponding parent node that was previously added to the path. The approach then selects an optimal node from the nodes in the path.

    Grant inheritance in RBAC
    45.
    发明授权

    公开(公告)号:US12105828B2

    公开(公告)日:2024-10-01

    申请号:US18227818

    申请日:2023-07-28

    Applicant: Snowflake Inc.

    Abstract: Embodiments of the present disclosure provide systems and methods for using inherited grants to grant privileges to objects in a container. An inherited grant may be generated that specifies a permission on a first type of object in a container and a grant of the permission to a role. The inherited grant may be attached to the container, wherein the container includes a set of objects of the first type. In response to a first object of the set of objects being referenced via the role, a virtual implied grant may be created based on the inherited grant. Authorization of utilization of the permission on the first object is performed using the virtual implied grant, wherein the virtual implied grant is transient and exists in-memory only for the purpose of authorizing the utilization of the permission on the first object.

    Secure message exchange between deployments

    公开(公告)号:US12101294B2

    公开(公告)日:2024-09-24

    申请号:US18341954

    申请日:2023-06-27

    Applicant: Snowflake Inc.

    CPC classification number: H04L63/0218 H04L63/0236 H04L63/0245

    Abstract: Different database deployments, or other data system deployments, may want to communicate with each other without sacrificing security or control. To this end, embodiments of the present disclosure may provide secure message exchange techniques for a source and/or target deployment. Configurable rule sets may be stored in the deployments; the rule sets may define what messages may be communicated between deployments. The deployments may implement a selective filtering scheme in one or more stages based on the rule sets to filter outgoing and/or incoming messages.

    Horizontally-scalable data de-identification

    公开(公告)号:US12086287B2

    公开(公告)日:2024-09-10

    申请号:US17980371

    申请日:2022-11-03

    Applicant: SNOWFLAKE INC.

    CPC classification number: G06F21/6254 G06F16/221 G06F16/282 G06F21/6227

    Abstract: A method receives data from a data source. The method generates a plurality of generalizations of the data. The method sends the plurality of generalizations of the data to a plurality of execution nodes, wherein each of the plurality of execution nodes includes computational resources to compute a candidate generalization using an information loss scoring function. The method receives a candidate generalization from each of the plurality of execution nodes. The method selects a preferred generalization from the plurality of candidate generalizations. The method generates an anonymized view of the data set using the preferred generalization.

    GENERATING OVERLAP QUERIES ON A DATABASE SYSTEM

    公开(公告)号:US20240296162A1

    公开(公告)日:2024-09-05

    申请号:US18659616

    申请日:2024-05-09

    Applicant: Snowflake Inc.

    CPC classification number: G06F16/24568 G06F16/244 G06F16/2456 G06F16/24564

    Abstract: An advanced system for refining overlap queries in a database system based on user feedback. The system monitors interactions of a first user with a first dataset on the database system, where the first dataset is associated with the first user. Feedback regarding the quality of a results dataset, generated from an executed overlap query, is received from the first user. This feedback informs the generation of a similarity score dataset that enhances the creation of new overlap queries. These new overlap queries are designed to output refined overlap datasets between the first dataset and a second dataset associated with a second user. A new joined dataset is generated by executing these overlap queries, comprising data from both the first and second datasets. A new results dataset is generated, providing the first user with refined recommendations based on additional feedback.

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