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In the offline processing phase, Plato (i) segments each time series into several disjoint segmentations using known fixed-length or variable-length segmentation algorithms; (ii) compresses each segment by a compression function that is coming from a user-chosen compression function family; and (iii) associates to each segment 1 to 3 precomputed error measures. In the online query processing phase, Plato uses the error measures to compute the error guarantees. Importantly, we identify certain compression function families that lead to theoretically and experimentally higher quality guarantees.<\/jats:p>","DOI":"10.14778\/3384345.3384357","type":"journal-article","created":{"date-parts":[[2020,3,26]],"date-time":"2020-03-26T14:21:06Z","timestamp":1585232466000},"page":"1105-1118","source":"Crossref","is-referenced-by-count":13,"title":["Plato"],"prefix":"10.14778","volume":"13","author":[{"given":"Chunbin","family":"Lin","sequence":"first","affiliation":[{"name":"Amazon AWS"}]},{"given":"Etienne","family":"Boursier","sequence":"additional","affiliation":[{"name":"ENS Paris-Saclay"}]},{"given":"Yannis","family":"Papakonstantinou","sequence":"additional","affiliation":[{"name":"Amazon AWS &amp; UCSD"}]}],"member":"320","published-online":{"date-parts":[[2020,3,26]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"https:\/\/druid.apache.org\/.  https:\/\/druid.apache.org\/."},{"key":"e_1_2_1_2_1","unstructured":"https:\/\/crate.io\/.  https:\/\/crate.io\/."},{"key":"e_1_2_1_3_1","unstructured":"https:\/\/www.timescale.com\/.  https:\/\/www.timescale.com\/."},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/2465351.2465355"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.is.2015.04.007"},{"key":"e_1_2_1_6_1","volume-title":"Plato: Approximate analytics over compressed time series with tight deterministic error guarantees. 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