TARDIS: Distributed Indexing Framework for Big Time Series Data

2019 IEEE 35th International Conference on Data Engineering (ICDE), pp. 1202-1213, 2019.

被引用5|引用|浏览21|DOI:https://doi.org/10.1109/ICDE.2019.00110
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其它链接dblp.uni-trier.de|academic.microsoft.com

摘要

The massive amounts of time series data continuously generated and collected by applications warrant the need for large scale distributed time series processing systems. Indexing plays a critical role in speeding up time series similarity queries on which various analytics and applications rely. However, the state-of-the-art indexing tech...更多

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