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In this paper, we propose OnlineSTL, a novel online algorithm for time series decomposition which is highly scalable and is deployed for real-time metrics monitoring on high-resolution, high-ingest rate data. Experiments on different synthetic and real world time series datasets demonstrate that OnlineSTL achieves orders of magnitude speedups (100x) for large seasonalities while maintaining quality of decomposition.<\/jats:p>","DOI":"10.14778\/3523210.3523219","type":"journal-article","created":{"date-parts":[[2022,6,22]],"date-time":"2022-06-22T22:23:21Z","timestamp":1655936601000},"page":"1417-1425","source":"Crossref","is-referenced-by-count":13,"title":["OnlineSTL"],"prefix":"10.14778","volume":"15","author":[{"given":"Abhinav","family":"Mishra","sequence":"first","affiliation":[{"name":"Splunk"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ram","family":"Sriharsha","sequence":"additional","affiliation":[{"name":"Pinecone"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sichen","family":"Zhong","sequence":"additional","affiliation":[{"name":"Splunk"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2022,6,22]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.14778\/3181-3194"},{"key":"e_1_2_1_2_1","volume-title":"Retrieved","author":"Inc. 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