Abstract
A huge volume of sensor stream data can be efficiently handle with the MapReduce framework for processing multi-dimensional continuous queries. The MapReduce originally has been used for batch processing, not real-time querying. In this paper, we propose a new idea of transforming query regions of multi-dimensional continuous queries into multiple key values. At the Map stage, key-value pairs of input data stream would be mapped into CQ-based key values that would be also grouped by the same continuous query in the Reduce stage.
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Jeong, D., Jeon, S., Hong, B. (2013). A Study on MapReduce Processing for Multi-dimensional Continuous Query. In: Hong, B., Meng, X., Chen, L., Winiwarter, W., Song, W. (eds) Database Systems for Advanced Applications. DASFAA 2013. Lecture Notes in Computer Science, vol 7827. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40270-8_6
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DOI: https://doi.org/10.1007/978-3-642-40270-8_6
Publisher Name: Springer, Berlin, Heidelberg
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