公开(公告)号：US20230176909A1

公开(公告)日：2023-06-08

申请号：US18161044

申请日：2023-01-28

Applicant: Snowflake Inc.

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

IPC: G06F9/50 ,  G06F9/355

CPC classification number: G06F9/5005 ,  G06F9/3555 ,  G06F9/505 ,  G06F9/5077 ,  G06F9/5083

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.

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.

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.

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.

公开(公告)号：US12217088B2

公开(公告)日：2025-02-04

申请号：US18497260

申请日：2023-10-30

Applicant: Snowflake Inc.

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

IPC: G06F9/50 ,  G06F9/355

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.

公开(公告)号：US11966368B2

公开(公告)日：2024-04-23

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: G06F16/00 ,  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.

公开(公告)号：US11698886B2

公开(公告)日：2023-07-11

申请号：US17936169

申请日：2022-09-28

Applicant: Snowflake Inc.

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

IPC: G06F16/00 ,  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 remove 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 removes the second particular type of cluster instance from a second particular zone to meet the global balancing of cluster instances in the multiple zones.

公开(公告)号：US20230069578A1

公开(公告)日：2023-03-02

申请号：US17936169

申请日：2022-09-28

Applicant: Snowflake Inc.

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

IPC: G06F16/182 ,  G06F16/28

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 remove 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 removes the second particular type of cluster instance from a second particular zone to meet the global balancing of cluster instances in the multiple zones.

公开(公告)号：US20240061709A1

公开(公告)日：2024-02-22

申请号：US18497260

申请日：2023-10-30

Applicant: Snowflake, Inc.

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

IPC: G06F9/50 ,  G06F9/355

CPC classification number: G06F9/5005 ,  G06F9/3555 ,  G06F9/505 ,  G06F9/5077 ,  G06F9/5083

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.

公开(公告)号：US11842215B2

公开(公告)日：2023-12-12

申请号：US18161044

申请日：2023-01-28

Applicant: Snowflake Inc.

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

IPC: G06F9/50 ,  G06F9/355

CPC classification number: G06F9/5005 ,  G06F9/3555 ,  G06F9/505 ,  G06F9/5077 ,  G06F9/5083

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.