T-Cube: Quick Response to Ad-Hoc Time Series Queries against Large Datasets

We present a novel data structure called T-Cube which dramatically improves response time to ad-hoc time series queries against large datasets. We have tested T-Cube on both synthetic and real world data (emergency room patient visits, pharmacy sales) containing millions of records. The results indicate that T-Cube responds to complex queries 1,000 times faster when compared to the state-of-the-art commercial time series extraction tools. This speedup has two main benefits: (1) It enables massive scale statistical data mining of large collections of time series, and (2) It allows its users to perform many complex ad-hoc queries without inconvenient delays.