Abstract
Integrating spatial operators in commercial data streaming engines has gained tremendous interest in recent years. Whether to support such operators natively or to enable the operator through an extensibility framework is a challenging and interesting debate. In this paper we leverage the Microsoft StreamInsightTM extensibility framework to support spatial operators enabling developers to integrate their domain expertise within the query execution pipeline.
We first justify our choice of adopting an extensibility approach over a native support approach. Then, we present an example set of spatiotemporal operations, e.g., KNN search, and range search; implemented as user defined operators using the extensibility framework within Microsoft StreamInsight. More interestingly, the demo showcases the how embedded devices and smartphones are shaping the future of streaming spatiotemporal applications. The demo scenario specifically features a smartphone based input adapter that provides a continuous stream of moving object locations as well a continuous stream of moving queries. To demonstrate the scalability of the implemented extensibility framework, the demo includes a simulator that generates a larger set of stationary/moving queries and streams of stationary/moving objects.
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References
Barga, R.S., Goldstein, J., Ali, M., Hong, M.: Consistent Streaming Through Time: A Vision for Event Stream Processing. In: Proceedings of CIDR, pp. 412–422 (2007)
Goldstein, J., Hong, M., Ali, M., Barga, R.: Consistency Sensitive Streaming Operators in CEDR. Tech. Report, MSR-TR-2007-158, Microsoft Research (2007)
Chandramouli, B., Goldstein, J., Maier, D.: On-the-fly Progress Detection in Iterative Stream Queries. In: VLDB (2009)
Chandramouli, B., Goldstein, J., Maier, D.: High-Performance Dynamic Pattern Matching over Disordered Streams. In: VLDB (2010)
Ali, M., et al.: Microsoft CEP Server and Online Behavioral Targeting. In: VLDB (2009)
Chandramouli, B., Ali, M., Goldstein, J., Sezgin, B., Sethu, B.: Data Stream Management Systems for Computational Finance. IEEE Computer 43(12), 45–52 (2010)
Ali, M., Chandramouli, B., Raman, B.S., Katibah, E.: Spatio-Temporal Stream Processing in Microsoft StreamInsight. IEEE Data Eng. Bull. 33(2), 69–74 (2010)
Kazemitabar, J., Demiryurek, U., Ali, M., Akdogan, A., Shahabi, C.: Geospatial Stream Query Processing using Microsoft SQL Server StreamInsight. In: VLDB (2010)
Ali, M.H., Chandramouli, B., Raman, B.S., Katibah, E.: Real-time spatio-temporal analytics using Microsoft StreamInsight. In: ACM GIS (2010)
Ali, M., Chandramouli, B., Goldstein, J., Schindlauer, R.: The Extensibility Framework in Microsoft StreamInsight. In: ICDE (2011)
SQL Server Spatial Library, http://www.microsoft.com/sqlserver/2008/en/us/spatial-data.aspx (last accessed in March 2011)
Pialorsi, P., Russo, M.: Programming Microsoft LINQ. Microsoft Press, Redmond (May 2008)
Bing Maps, http://www.bing.com/maps
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Miller, J. et al. (2011). An Extensibility Approach for Spatio-temporal Stream Processing Using Microsoft StreamInsight. In: Pfoser, D., et al. Advances in Spatial and Temporal Databases. SSTD 2011. Lecture Notes in Computer Science, vol 6849. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22922-0_38
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DOI: https://doi.org/10.1007/978-3-642-22922-0_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-22921-3
Online ISBN: 978-3-642-22922-0
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