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    NESTED ROW ACCESS POLICIES
    21.
    发明申请
    NESTED ROW ACCESS POLICIES 有权

    公开(公告)号：US20240419828A1

    公开(公告)日：2024-12-19

    申请号：US18394531

    申请日：2023-12-22

    Applicant: Snowflake Inc.

    Inventor： Raja Suresh Krishna Balakrishnan ,  Jashua Gupta ,  Jian Xu

    IPC: G06F21/62

    Abstract: Methods of referencing row access policy (RAP) protected mapping tables in a RAP for a data table are disclosed herein. An example method of referencing a mapping table in a data table using nested RAP includes defining, by a processing device, a first access policy for the mapping table to control access by specific users or under specific conditions. The processing device further defines a second access policy attached to the data table referencing the mapping table. The processing device in response to a query, executes the second access policy of the data table to provide a response or operation of data associated with the data table and the mapping table. Executing the second access policy invokes executing the first access policy of the mapping table. The executing of both the second access policy of the data table and the first access policy of the mapping table are recorded.

    RULE BASED HINT APPLICATION
    23.
    发明申请
    RULE BASED HINT APPLICATION 有权

    公开(公告)号：US20240419666A1

    公开(公告)日：2024-12-19

    申请号：US18336426

    申请日：2023-06-16

    Applicant: Snowflake Inc,

    Inventor： Sangyong Hwang ,  Sourav Sikdar ,  Li Yan

    IPC: G06F16/2453

    Abstract: The subject technology receives a first query plan corresponding to a query, the first query plan comprising a set of join nodes, and a join order hint of a target query plan, each join node of the target query plan associated with a hint. The subject technology generates a second query plan to correct a set of vertical positions of a set of terminal nodes of the first query plan following the join order hint of the target query plan. The subject technology generates a third query plan to correct a set of lateral positions of the set of terminal nodes of the second query plan following the join order hint of the target query plan. The subject technology, for each join node from the set of join nodes of the third query plan, indicates that each join node has been hinted. The subject technology generates, after each join node of the third query plan has been indicated as being hinted, the target query plan based at least in part on the third query plan.

    Container-centric access control on database objects
    24.
    发明授权
    Container-centric access control on database objects 有权

    公开(公告)号：US12169580B2

    公开(公告)日：2024-12-17

    申请号：US18497179

    申请日：2023-10-30

    Applicant: Snowflake Inc.

    Inventor： Artin Avanes ,  Khalid Zaman Bijon ,  Peter Povinec

    IPC: G06F16/00 ,  G06F16/27 ,  G06F21/62

    Abstract: Using container-centric managed access, an administrator is enabled to define a set of future grants for each object that will be created in the future in a container managed by the administrator. When a user creates a database object, the system checks the future grants to determine if any apply to the user, the database object, or the combination. Any applicable future grants are applied to the database object before the user is allowed to modify it. As a result, the administrator is enabled to control the privileges associated with the database object even before the database object is created, while restricting individual object owners from managing privileges on their owned objects.

    Dynamic task allocation and datastore scaling
    26.
    发明授权
    Dynamic task allocation and datastore scaling 有权

    公开(公告)号：US12164966B1

    公开(公告)日：2024-12-10

    申请号：US18351388

    申请日：2023-07-12

    Applicant: Snowflake Inc.

    Inventor： Ganeshan Ramachandran Iyer ,  Raghav Ramachandran ,  Yang Wang

    IPC: G06F9/50 ,  G06F9/48

    Abstract: A system and method of dynamic task allocation and warehouse scaling. The method includes receiving a request to process a task. The method includes monitoring a plurality of execution nodes of a datastore to determine a plurality of central processing unit (CPU) utilizations. Each CPU utilization of the plurality of CPU utilizations is associated with a respective execution node of the plurality of execution nodes. The method includes identifying, by a processing device based on the plurality of CPU utilizations, a particular execution node associated with a maximum CPU utilization to process the task. The method includes allocating the task to the particular execution node.

    BUILT-IN DATA QUALITY MONITORING
    28.
    发明申请
    BUILT-IN DATA QUALITY MONITORING 有权

    公开(公告)号：US20240403276A1

    公开(公告)日：2024-12-05

    申请号：US18326158

    申请日：2023-05-31

    Applicant: Snowflake Inc.

    Inventor： Hossein Ahmadi ,  Raja Suresh Krishna Balakrishnan ,  David Schultz ,  Jian Xu ,  Yunqiao Zhang

    IPC: G06F16/215 ,  G06F16/22

    Abstract: Described herein are techniques for data quality monitoring in a network-based data system. A data metric function used to evaluate data quality can be stored, where the data metric function is defined as schema level object. The data metric function can be attached to a table associated with an account and is evaluated on data associates with the table to generate evaluation results. The evaluation results can be stored in an account-specific central database, from which access is provided to the evaluation results to a user for the account.

    Managing database failover based on transaction request time
    29.
    发明授权
    Managing database failover based on transaction request time 有权

    公开(公告)号：US12158897B2

    公开(公告)日：2024-12-03

    申请号：US18123108

    申请日：2023-03-17

    Applicant: Snowflake Inc.

    Inventor： Benoit Dageville ,  Eric Robinson ,  Martin Hentschel

    IPC: G06F16/00 ,  G06F16/245 ,  G06F16/27 ,  H04L67/1097

    Abstract: Methods and systems of managing database failure based on transaction request time is disclosed. A method includes copying a first dataset stored in a primary deployment to a secondary deployment to generate a second dataset. The method includes determining a first arrival time of a first request to perform a first transaction. The method includes determining a second arrival time of a second request to perform a second transaction. The method includes executing the first transaction on the first dataset at the primary deployment in response to determining the first arrival time of the first request to perform the first transaction. The method includes executing the second transaction on the second dataset at the secondary deployment in response to determining the second arrival time of the second request to perform the second transaction.

    DETERMINING BIAS-CAUSING FEATURES OF A MACHINE LEARNING MODEL
    30.
    发明申请
    DETERMINING BIAS-CAUSING FEATURES OF A MACHINE LEARNING MODEL 有权

    公开(公告)号：US20240394574A1

    公开(公告)日：2024-11-28

    申请号：US18790920

    申请日：2024-07-31

    Applicant: Snowflake Inc.

    Inventor： Anupam Datta ,  Shayak Sen ,  Apoorv Gupta ,  David Sandai Kurokawa

    IPC: G06N5/04 ,  G06N20/00

    Abstract: A computing machine receives a representation of a machine learning model, a representation of a first data segment, and a representation of a second data segment. The computing machine computes an output difference between an output of the machine learning model applied to the first data segment and an output of the machine learning model applied to the second data segment. The computing machine determines a set of reasons for the computed output difference based on a set of metrics defining distance between feature importance distributions, the set of reasons identifying a set of features from a feature vector of the machine learning model along with a relative contribution of each feature to the computed output difference. The computing machine provides an output representing the set of reasons.

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