US 11,995,081 B2
Predicting future query rewrite patterns for materialized views
Murali Thiyagarajan, Concord, NH (US); and Praveen T. J. Kumar, Nashua, NH (US)
Assigned to Oracle International Corporation, Redwood Shores, CA (US)
Filed by Oracle International Corporation, Redwood Shores, CA (US)
Filed on Dec. 18, 2020, as Appl. No. 17/127,845.
Claims priority of provisional application 63/078,242, filed on Sep. 14, 2020.
Prior Publication US 2022/0083548 A1, Mar. 17, 2022
Int. Cl. G06F 16/2453 (2019.01); G06F 16/23 (2019.01); G06F 16/248 (2019.01); G06F 18/214 (2023.01); G06F 18/24 (2023.01)
CPC G06F 16/24539 (2019.01) [G06F 16/2358 (2019.01); G06F 16/2393 (2019.01); G06F 16/248 (2019.01); G06F 18/2148 (2023.01); G06F 18/24765 (2023.01)] 20 Claims
OG exemplary drawing
 
1. A method for predicting a future quiet rewrite pattern of a materialized view, the method comprising:
tracking query rewrite activity for queries that are rewritten to access a materialized view;
storing object activity tracking data reflecting the query rewrite activity;
generating, based on the object activity tracking data, a database activity training set that contains a plurality of database activity examples, wherein each database activity example of the plurality of database activity examples contains a corresponding binary label that characterizes a database activity;
using the plurality of database activity examples to learn a classification model for the materialized view; and
using the learned classification model to predict whether query rewrite activity for queries rewritten to access the materialized view will occur during a future time interval;
wherein the method is performed by one or more computing devices.