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    IDENTIFYING SOFTWARE REGRESSIONS BASED ON QUERY RETRY ATTEMPTS IN A DATABASE ENVIRONMENT
    1.
    发明公开
    IDENTIFYING SOFTWARE REGRESSIONS BASED ON QUERY RETRY ATTEMPTS IN A DATABASE ENVIRONMENT 审中-公开

    公开(公告)号：US20240086397A1

    公开(公告)日：2024-03-14

    申请号：US18511204

    申请日：2023-11-16

    Applicant: Snowflake Inc.

    Inventor： Benoit Dageville ,  Johan Harjono ,  Kunal Prafulla Nabar ,  Steven James Pelley

    IPC: G06F16/23 ,  G06F16/2455

    CPC classification number: G06F16/2365 ,  G06F16/2455

    Abstract: Systems, methods, and devices for retrying a query. A method includes receiving a query directed to database data and assigning execution of the query to one or more execution nodes of an execution platform, the one or more execution nodes configured to execute the query on a first version of a database platform. The method includes determining that execution of the query was unsuccessful. The method includes assigning a first retry execution of the query to the one or more execution nodes of the execution platform and determining whether a regression or an intermittent fault caused the execution of the query to be unsuccessful based at least in part on whether the first retry execution of the query was successful or unsuccessful.

    Automated query retry execution in a database system
    3.
    发明授权
    Automated query retry execution in a database system 有权

    公开(公告)号：US11640347B2

    公开(公告)日：2023-05-02

    申请号：US17809780

    申请日：2022-06-29

    Applicant: Snowflake Inc.

    Inventor： Benoit Dageville ,  Johan Harjono ,  Simon Holm Jensen ,  Kunal Prafulla Nabar ,  Steven James Pelley

    IPC: G06F11/30 ,  G06F16/2458 ,  G06F11/34 ,  G06F16/242

    Abstract: Techniques for automated query retry in a database platform include decoding, by at least one hardware processor, a query directed to database data from a client account of a database platform. The method further includes decoding, by the at least one hardware processor, an indication that execution of the query on at least one computing node of the database platform results in a failed execution. The method further includes configuring a processing loop with continuous retry executions of the query on the at least one computing node based on the indication. The method further includes exiting the processing loop based on detecting a retry execution of the continuous retry executions results in at least one successful execution of the query. The method includes logging each attempt to execute the query during the continuous retry executions in a query status log until the at least one successful execution of the query.

    Autoscaling and throttling in an elastic cloud service
    4.
    发明授权
    Autoscaling and throttling in an elastic cloud service 有权

    公开(公告)号：US11347550B1

    公开(公告)日：2022-05-31

    申请号：US17463376

    申请日：2021-08-31

    Applicant: Snowflake Inc.

    Inventor： Johan Harjono ,  Daniel Geoffrey Karp ,  Kunal Prafulla Nabar ,  Rares Radut ,  Arthur Kelvin Shi

    IPC: G06F9/50

    Abstract: Techniques described herein can optimize usage of computing resources in a data system. Dynamic throttling can be performed locally on a computing resource in the foreground and autoscaling can be performed in a centralized fashion in the background. Dynamic throttling can lower the load without overshooting while minimizing oscillation and reducing the throttle quickly. Autoscaling may involve scaling in or out the number of computing resources in a cluster as well as scaling up or down the type of computing resources to handle different types of situations.

    CLUSTER BALANCING FOR ZONES OF A DATABASE SYSTEM
    9.
    发明公开
    CLUSTER BALANCING FOR ZONES OF A DATABASE SYSTEM 审中-公开

    公开(公告)号：US20230325362A1

    公开(公告)日：2023-10-12

    申请号：US18326645

    申请日：2023-05-31

    Applicant: Snowflake Inc.

    Inventor： Johan Harjono ,  Daniel Geoffrey Karp ,  Rares Radut ,  Samir Rehmtulla ,  Arthur Kelvin Shi ,  Thanakul Wattanawong

    IPC: G06F16/182 ,  G06F16/28

    CPC classification number: G06F16/1824 ,  G06F16/285

    Abstract: The subject technology selects a particular zone among multiple zones based on a target skew to meet a global balancing of cluster instances. The subject technology deploys a particular type of cluster instance to the particular zone. The subject technology, for each zone from the multiple zones, determines a respective number of cluster instances. The subject technology identifies a second particular type of cluster instance to add based on a total number of the second particular type of cluster instance in the multiple zones and a second total number of the particular type of cluster instance in the multiple zones. The subject technology adds the second particular type of cluster instance to a second particular zone to meet the global balancing of cluster instances in the multiple zones.

    AUTOSCALING IN AN ELASTIC CLOUD SERVICE
    10.
    发明申请
    AUTOSCALING IN AN ELASTIC CLOUD SERVICE 有权

    公开(公告)号：US20220413913A1

    公开(公告)日：2022-12-29

    申请号：US17463366

    申请日：2021-08-31

    Applicant: Snowflake Inc.

    Inventor： Johan Harjono ,  Daniel Geoffrey Karp ,  Kunal Prafulla Nabar ,  Rares Radut ,  Arthur Kelvin Shi

    IPC: G06F9/50

    Abstract: Techniques described herein can optimize usage of computing resources in a data system. Dynamic throttling can be performed locally on a computing resource in the foreground and autoscaling can be performed in a centralized fashion in the background. Dynamic throttling can lower the load without overshooting while minimizing oscillation and reducing the throttle quickly. Autoscaling may involve scaling in or out the number of computing resources in a cluster as well as scaling up or down the type of computing resources to handle different types of situations.

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