{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T19:29:47Z","timestamp":1777490987695,"version":"3.51.4"},"publisher-location":"New York, NY, USA","reference-count":30,"publisher":"ACM","license":[{"start":{"date-parts":[[2015,8,27]],"date-time":"2015-08-27T00:00:00Z","timestamp":1440633600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"PDL Consortium"},{"name":"Intel Science and Technology Center for Cloud Computing"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2015,8,27]]},"DOI":"10.1145\/2806777.2806839","type":"proceedings-article","created":{"date-parts":[[2015,8,24]],"date-time":"2015-08-24T14:09:20Z","timestamp":1440425360000},"page":"395-407","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":10,"title":["Using data transformations for low-latency time series analysis"],"prefix":"10.1145","author":[{"given":"Henggang","family":"Cui","sequence":"first","affiliation":[{"name":"Carnegie Mellon University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kimberly","family":"Keeton","sequence":"additional","affiliation":[{"name":"Hewlett-Packard Laboratories"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Indrajit","family":"Roy","sequence":"additional","affiliation":[{"name":"Hewlett-Packard Laboratories"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Krishnamurthy","family":"Viswanathan","sequence":"additional","affiliation":[{"name":"Hewlett-Packard Laboratories"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gregory R.","family":"Ganger","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2015,8,27]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"https:\/\/cloud.google.com\/bigquery\/docs\/dataset-gsod.  https:\/\/cloud.google.com\/bigquery\/docs\/dataset-gsod."},{"key":"e_1_3_2_1_2_1","unstructured":"Haar wavelet. http:\/\/en.wikipedia.org\/wiki\/Haar_wavelet.  Haar wavelet. http:\/\/en.wikipedia.org\/wiki\/Haar_wavelet."},{"key":"e_1_3_2_1_3_1","unstructured":"Apache HBase. http:\/\/hbase.apache.org\/.  Apache HBase. http:\/\/hbase.apache.org\/."},{"key":"e_1_3_2_1_4_1","unstructured":"https:\/\/cloud.google.com\/bigquery\/docs\/dataset-mlab.  https:\/\/cloud.google.com\/bigquery\/docs\/dataset-mlab."},{"key":"e_1_3_2_1_5_1","unstructured":"OpenTSDB. http:\/\/opentsdb.net\/.  OpenTSDB. http:\/\/opentsdb.net\/."},{"key":"e_1_3_2_1_6_1","unstructured":"Pearson's product-moment correlation coefficient. http:\/\/en.wikipedia.org\/wiki\/Pearson_product-moment_correlation_coefficient.  Pearson's product-moment correlation coefficient. http:\/\/en.wikipedia.org\/wiki\/Pearson_product-moment_correlation_coefficient."},{"key":"e_1_3_2_1_7_1","unstructured":"Apache Storm. http:\/\/storm.apache.org\/.  Apache Storm. http:\/\/storm.apache.org\/."},{"key":"e_1_3_2_1_8_1","unstructured":"How Twitter monitors millions of time series. http:\/\/radar.oreilly.com\/2013\/09\/how-twitter-monitors-millions-of-time-series.html.  How Twitter monitors millions of time series. http:\/\/radar.oreilly.com\/2013\/09\/how-twitter-monitors-millions-of-time-series.html."},{"key":"e_1_3_2_1_9_1","unstructured":"HP Vertica Live Aggregate Projections. http:\/\/www.vertica.com\/2014\/07\/01\/live-aggregate-projections-with-hp-vertica\/.  HP Vertica Live Aggregate Projections. http:\/\/www.vertica.com\/2014\/07\/01\/live-aggregate-projections-with-hp-vertica\/."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.14778\/2536222.2536231"},{"key":"e_1_3_2_1_11_1","volume-title":"NSDI","author":"Agarwal R.","year":"2015","unstructured":"R. Agarwal , A. Khandelwal , and I. Stoica . Succinct: Enabling queries on compressed data . NSDI , 2015 . R. Agarwal, A. Khandelwal, and I. Stoica. Succinct: Enabling queries on compressed data. NSDI, 2015."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/2465351.2465355"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/1496909.1496923"},{"key":"e_1_3_2_1_14_1","unstructured":"P. J.\n      Brockwell\n     and \n      R. A.\n      Davis\n  . \n  Time series: theory and methods\n  . \n  Springer Science & Business Media 2009\n  .  P. J. Brockwell and R. A. Davis. Time series: theory and methods. Springer Science & Business Media 2009."},{"key":"e_1_3_2_1_15_1","first-page":"126","volume-title":"Data Engineering, 1999. Proceedings., 15th International Conference on","author":"Chan K.-P.","year":"1999","unstructured":"K.-P. Chan and A. W.-C. Fu . Efficient time series matching by wavelets . In Data Engineering, 1999. Proceedings., 15th International Conference on , pages 126 -- 133 . IEEE, 1999 . K.-P. Chan and A. W.-C. Fu. Efficient time series matching by wavelets. In Data Engineering, 1999. Proceedings., 15th International Conference on, pages 126--133. IEEE, 1999."},{"key":"e_1_3_2_1_16_1","volume-title":"An introduction to wavelets","author":"Chui C. K.","year":"2014","unstructured":"C. K. Chui . An introduction to wavelets , volume 1 . Academic Press , 2014 . C. K. Chui. An introduction to wavelets, volume 1. Academic Press, 2014."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/2168836.2168854"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jalgor.2003.12.001"},{"key":"e_1_3_2_1_19_1","volume-title":"the definitive guide. \"O'Reilly Media","author":"George L.","year":"2011","unstructured":"L. George . HBase : the definitive guide. \"O'Reilly Media , Inc .\", 2011 . L. George. HBase: the definitive guide. \"O'Reilly Media, Inc.\", 2011."},{"key":"e_1_3_2_1_20_1","first-page":"79","volume-title":"VLDB","volume":"1","author":"Gilbert A. C.","year":"2001","unstructured":"A. C. Gilbert , Y. Kotidis , S. Muthukrishnan , and M. Strauss . Surfing wavelets on streams: One-pass summaries for approximate aggregate queries . In VLDB , volume 1 , pages 79 -- 88 , 2001 . A. C. Gilbert, Y. Kotidis, S. Muthukrishnan, and M. Strauss. Surfing wavelets on streams: One-pass summaries for approximate aggregate queries. In VLDB, volume 1, pages 79--88, 2001."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/376284.375680"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/253262.253332"},{"key":"e_1_3_2_1_23_1","volume-title":"Hokusai-sketching streams in real time. arXiv preprint arXiv:1210.4891","author":"Matusevych S.","year":"2012","unstructured":"S. Matusevych , A. Smola , and A. Ahmed . Hokusai-sketching streams in real time. arXiv preprint arXiv:1210.4891 , 2012 . S. Matusevych, A. Smola, and A. Ahmed. Hokusai-sketching streams in real time. arXiv preprint arXiv:1210.4891, 2012."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.14778\/1687627.1687639"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.14778\/1687553.1687609"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/2588555.2595641"},{"key":"e_1_3_2_1_27_1","volume-title":"Mysql Reference Manual. O'Reilly & Associates","author":"Widenius M.","year":"2002","unstructured":"M. Widenius and D. Axmark . Mysql Reference Manual. O'Reilly & Associates , Inc., Sebastopol, CA, USA, 1 st edition, 2002 . ISBN 0596002653. M. Widenius and D. Axmark. Mysql Reference Manual. O'Reilly & Associates, Inc., Sebastopol, CA, USA, 1st edition, 2002. ISBN 0596002653.","edition":"1"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/354756.354857"},{"key":"e_1_3_2_1_29_1","first-page":"10","volume-title":"Proceedings of the 4th USENIX conference on Hot Topics in Cloud Ccomputing","author":"Zaharia M.","year":"2012","unstructured":"M. Zaharia , T. Das , H. Li , S. Shenker , and I. Stoica . Discretized streams: an efficient and fault-tolerant model for stream processing on large clusters . In Proceedings of the 4th USENIX conference on Hot Topics in Cloud Ccomputing , pages 10 -- 10 . USENIX Association , 2012 . M. Zaharia, T. Das, H. Li, S. Shenker, and I. Stoica. Discretized streams: an efficient and fault-tolerant model for stream processing on large clusters. In Proceedings of the 4th USENIX conference on Hot Topics in Cloud Ccomputing, pages 10--10. USENIX Association, 2012."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.5555\/1287369.1287401"}],"event":{"name":"SoCC '15: ACM Symposium on Cloud Computing","location":"Kohala Coast Hawaii","acronym":"SoCC '15","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGOPS ACM Special Interest Group on Operating Systems"]},"container-title":["Proceedings of the Sixth ACM Symposium on Cloud Computing"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2806777.2806839","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/2806777.2806839","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T05:07:22Z","timestamp":1750223242000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2806777.2806839"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,8,27]]},"references-count":30,"alternative-id":["10.1145\/2806777.2806839","10.1145\/2806777"],"URL":"https:\/\/doi.org\/10.1145\/2806777.2806839","relation":{},"subject":[],"published":{"date-parts":[[2015,8,27]]},"assertion":[{"value":"2015-08-27","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}