US 12,079,233 B1
Multiple seasonality online data decomposition
Abhinav Mishra, San Francisco, CA (US); Ram Sriharsha, San Francisco, CA (US); and Sichen Zhong, San Francisco, CA (US)
Assigned to Splunk Inc., San Francisco, CA (US)
Filed by SPLUNK INC., San Francisco, CA (US)
Filed on Apr. 30, 2021, as Appl. No. 17/246,241.
Application 17/246,241 is a continuation in part of application No. 17/069,693, filed on Oct. 13, 2020, granted, now 11,729,074.
Claims priority of provisional application 63/064,344, filed on Aug. 11, 2020.
Int. Cl. G06F 16/2458 (2019.01)
CPC G06F 16/2465 (2019.01) 20 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
obtaining a first seasonality parameter and a second seasonality parameter based on a user selection via a user interface, the first seasonality parameter and the second seasonality parameter indicating different seasonalities associated with a time series data set;
obtaining, in real-time, an incoming data point, for the time series data set, to decompose to a set of data components;
based on the first seasonality parameter, performing, via a data decomposition engine, a first iterative process to estimate a first seasonal component associated with the incoming data point based on a set of previous data points of the time series data set and corresponding data components;
based on the second seasonality parameter, performing, via the data decomposition engine, a second iterative process to estimate a second seasonal component associated with the incoming data point based on the set of previous data points of the time series data set and corresponding data components; and
providing the first seasonal component and the second seasonal component for analysis of the incoming data point.