The TSQL2 Temporal Query Language
The TSQL2 Temporal Query Language
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Issues in data stream management
ACM SIGMOD Record
The CQL continuous query language: semantic foundations and query execution
The VLDB Journal — The International Journal on Very Large Data Bases
Tribeca: a system for managing large databases of network traffic
ATEC '98 Proceedings of the annual conference on USENIX Annual Technical Conference
Monitoring streams: a new class of data management applications
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
A query processor for prediction-based monitoring of data streams
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
| Hi-index | 0.00 |
In facility management for plants and buildings, needs of facility diagnosis for saving energy or facility management cost by analyzing time series data from sensors of equipments in facilities have been increasing. This paper proposes a relation-based stream query language TPQL (Trend Pattern Query Language) for expressing constraints in time series data for anomalies detection in facilities. The features of TPQL are the following. (1) TPQL introduces a convolution operator into a stream query language in order to describe constraints over sliding window. A convolution operator which takes a window function as an argument can express various domain dependent functions extracting feature over sliding windows such as duration constraint and hunting constraint. (2) TPQL introduces time-interval based join into stream query language in order to join time series data with different sampling rates.