CPC G06F 11/3419 (2013.01) [G06F 11/302 (2013.01); G06F 16/22 (2019.01)] | 20 Claims |
1. A system, comprising a processor to:
monitor activity on a database server to generate an events stream;
convert the events stream into a time series;
approximate, in response to detecting each event in the events stream, an activity load at the database server using an exponential smoothing, a current time stamp generated at the time of each detected event, and a previous time stamp generated at a previous event time, wherein a plurality of simulated time windows for analyzing the activity load are calculated using a smoothing factor of the exponential smoothing;
send the time series to a streaming analytics engine; and
generate a trained machine learning model for the stream analytics engine for analyzing the time series using the plurality of simulated time windows in parallel.
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