US 11,727,004 B2
Context dependent execution time prediction for redirecting queries
Mingda Li, Los Angeles, CA (US); Gaurav Saxena, Cupertino, CA (US); and Naresh Chainani, Mountain View, CA (US)
Assigned to Amazon Technologies, Inc., Seattle, WA (US)
Filed by Amazon Technologies, Inc., Seattle, WA (US)
Filed on May 9, 2022, as Appl. No. 17/662,623.
Application 17/662,623 is a continuation of application No. 16/364,055, filed on Mar. 25, 2019, granted, now 11,327,970.
Prior Publication US 2022/0269680 A1, Aug. 25, 2022
Int. Cl. G06F 16/2453 (2019.01); G06N 5/04 (2023.01); G06N 20/00 (2019.01)
CPC G06F 16/24549 (2019.01) [G06N 5/04 (2013.01); G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A system, comprising:
at least one processor; and
a memory, storing program instructions that when executed cause the at least one processor to implement a query engine;
the query engine, configured to:
perform a plurality of queries to a database;
store respective query plans generated to perform the plurality of queries and respective execution times for the plurality of queries;
cause a training technique to be applied to the stored respective query plans and respective execution times of the plurality of queries to train a machine learning model to predict execution times of queries performed by the query engine with respect to the database using a query plan generated for a given query as input to the machine learning model; and
select either the query engine or a different query engine to perform another query to the database based, at least in part, on an execution time prediction for the other query generated by the machine learning model at the query engine according to a query plan generated for the other query by the query engine.