US 11,941,016 B2
Using specified performance attributes to configure machine learning pipepline stages for an ETL job
Timothy Jones, Brier, WA (US); Andrew Borthwick, Kirkland, WA (US); Sergei Dobroshinsky, Issaquah, WA (US); Shehzad Qureshi, North Bend, WA (US); Stephen Michael Ash, Seattle, WA (US); Pedrito Uriah Maynard-Zhang, Issaquah, WA (US); Chethan Kommaranahalli Rudramuni, Seattle, WA (US); Abhishek Sharma, Seattle, WA (US); Juliana Saussy, Seattle, WA (US); Adam Lawrence Joseph Heinermann, Vancouver (CA); Alaykumar Navinchandra Desai, Santa Clara, CA (US); Mehul A. Shah, Saratoga, CA (US); Mehul Y. Shah, Redmond, WA (US); Anurag Windlass Gupta, Atherton, WA (US); and Prajakta Datta Damle, San Jose, CA (US)
Assigned to Amazon Technologies, Inc., Seattle, WA (US)
Filed by Amazon Technologies, Inc., Seattle, WA (US)
Filed on Mar. 4, 2022, as Appl. No. 17/687,492.
Application 17/687,492 is a continuation of application No. 16/199,115, filed on Nov. 23, 2018, granted, now 11,269,911.
Prior Publication US 2022/0261413 A1, Aug. 18, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 16/25 (2019.01); G06F 9/54 (2006.01); G06N 20/00 (2019.01)
CPC G06F 16/254 (2019.01) [G06F 9/543 (2013.01); G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A system, comprising: a plurality of computing devices, respectively comprising a processor and a memory, that are configured to implement an Extract Transform Load service, wherein the Extract Transform Load service is configured to: receive, via an interface for the Extract Transform Load service offered by a provider network, one or more ETL job creation requests to create an ETL job, wherein the one or more requests include a selection of a machine learning pipeline with a trained machine learning model to perform a transformation operation in addition to one or more other operations to include in the ETL job, wherein the one or more requests configure one or more parameters of the machine learning pipeline; configure the one or more parameters of a stage in the machine learning pipeline that applies the machine learning model according to the one or more requests; and execute the ETL job including the transformation operation performed by the machine learning pipeline and the one or more other operations in the ETL job.