US 12,216,628 B2
Optimized identification of performance regression
Allison Lee, San Carlos, CA (US); Shrainik Jain, Seattle, WA (US); Qiuye Jin, Hillsborough, CA (US); Stratis Viglas, Madison, WI (US); and Jiaqi Yan, San Carlos, CA (US)
Assigned to Snowflake Inc., Bozeman, MT (US)
Filed by SNOWFLAKE INC., Bozeman, MT (US)
Filed on Sep. 20, 2023, as Appl. No. 18/470,706.
Application 18/470,706 is a continuation of application No. 17/842,642, filed on Jun. 16, 2022, granted, now 11,782,890.
Application 17/842,642 is a continuation of application No. 17/463,514, filed on Aug. 31, 2021, granted, now 11,386,059, issued on Jul. 12, 2022.
Application 17/463,514 is a continuation of application No. 16/943,274, filed on Jul. 30, 2020, granted, now 11,138,167, issued on Oct. 5, 2021.
Application 16/943,274 is a continuation of application No. 16/692,927, filed on Nov. 22, 2019, granted, now 10,762,067, issued on Sep. 1, 2020.
Application 16/692,927 is a continuation of application No. 16/359,452, filed on Mar. 20, 2019, granted, now 11,321,290, issued on May 3, 2022.
Claims priority of provisional application 62/646,817, filed on Mar. 22, 2018.
Prior Publication US 2024/0012796 A1, Jan. 11, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 16/00 (2019.01); G06F 11/07 (2006.01); G06F 11/30 (2006.01); G06F 11/34 (2006.01); G06F 16/21 (2019.01); G06F 16/215 (2019.01); G06F 16/2453 (2019.01)
CPC G06F 16/217 (2019.01) [G06F 11/0772 (2013.01); G06F 11/3072 (2013.01); G06F 11/3428 (2013.01); G06F 11/3452 (2013.01); G06F 16/215 (2019.01); G06F 16/24549 (2019.01)] 30 Claims
OG exemplary drawing
 
1. A system comprising:
a processor to:
deduplicate historical client queries based on a workload selection configuration to determine a grouping of historical client queries;
generate a workload based on at least a portion of the grouping of historical client queries;
repeatedly execute a test run of the workload using resources of a cloud environment to determine whether there is a performance difference in the test run;
in response to determining that there is no performance difference, identify one or more sets of decreased resources of the cloud environment; and
re-execute the test run using the one or more sets of decreased resources of the cloud environment to determine whether there is a performance difference in the test run that is attributed to the one or more sets of decreased resources of the cloud environment.