연구 분야: Databases
학회: Asia-Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint International Conference on Web and Big Data
The rapid advancement of sensor technology presents novel challenges in the efficient management of large scale time series data. In this demo, we demonstrate a time series data management module named GaussTS in database, which provides four key components specifically designed for processing and analysis over time series data application scenarios. Among them, TS Data Query and Analysis mainly focuses similarity search which can be used for enabling data mining and information extraction. TS Data Compression consists of data dimensionality reduction and data partitioning facilitating efficient storage and streamlined processing. TS Data cleaning and TS Data evaluation are capable of accurately handling missing or abnormal data and efficiently assessing data quality. GaussTS has been implemented in a domestic open-source database openGauss and the demonstration showcases the effectiveness and usability of GaussTS in managing and analyzing large scale time series data.
| 발행 연도 | 2024년 |
|---|---|
| 인용수 | 0 |
| 출판 국가 | Andorra, China |
| 사이트 | Springer |
| 좋아요 수 | 0 |