Machine learning database memory use prediction and adaptation

Abstract

Methods, systems, and computer-readable storage media for machine learning database memory use prediction and adaptation. An example method includes determining a sampling interval for an application for sampling memory use by a database for the application. A plurality of historical memory use samples of amounts of memory used by the database are determined for the application based on the sampling interval. The plurality of historical memory use samples are provided for training of a machine learning model to predict memory use for the application by the database for a future time period. A set of current memory use samples are provided to the machine learning model and a memory use prediction for the application for an upcoming time period is received from the machine learning model. A determination is made as to whether to extend memory of the database for the application based on the memory use prediction.