Authors:
Yang Zheng
;
Annies Ductan
;
Devin Thomas
and
Mohamed Y. Eltabakh
Affiliation:
Worcester Polytechnic Institute (WPI), United States
Keyword(s):
Spatio-temporal Query Processing, Pattern-matching Queries, GIS, Query Optimization.
Related
Ontology
Subjects/Areas/Topics:
Data Engineering
;
Data Management and Quality
;
Data Management for Analytics
;
Databases and Data Security
;
Nosql Databases
;
Query Processing and Optimization
Abstract:
The increasing complexity of spatio-temporal applications has caused the underlying queries to be more sophisticated
and usually carry complex semantics. As a result, the traditional spatio-temporal query types, e.g.,
range, kNN, and aggregation queries, have become just building blocks in more complex query plans. In this
paper, we present the STEPQ system, which is an extensible spatio-temporal query engine for complex pattern
processing over spatio-temporal data. STEPQ enables full-fledged and optimized integration between spatiotemporal
queries and complex event processing (CEP). This integration enables expressing complex queries
that execute the desired application semantics without the need for indifferent middle-aware or application level
support. The system is implemented using TerraLib module on top of PostgreSQL DBMSs. The experimental
evaluation demonstrates the feasibility and practicality of the STEPQ system, and the efficiency of the
proposed optimizations.