@inproceedings{mahmood2015tornado,
author = {Mahmood, Ahmed R. and Aly, Ahmed M. and Qadah, Thamir and Rezig, Elkindi and Daghastani, Anas and Madkour, Amgad and Abdelhamid, Ahmed S. and Hassan, Mohamed S. and Aref, Walid G. and Basalamah, Saleh},
title = {Tornado: A Distributed Spatio-Textual Stream Processing System},
booktitle = {VLDB Demonstration Track},
year = {2015},
month = {May},
abstract = {The widespread use of location-aware devices together with the increased popularity of micro-blogging applications (e.g., Twitter) led to the creation of large streams of spatio-textual data. In order to serve real-time applications, the processing of these large-scale spatio-textual streams needs to be distributed. However, existing distributed stream processing systems (e.g., Spark and Storm) are not optimized for spatial/textual content. In this demonstration, we introduce Tornado, a distributed in-memory spatio-textual stream processing server that extends Storm. To efficiently process spatiotextual streams, Tornado introduces a spatio-textual indexing layer to the architecture of Storm. The indexing layer is adaptive, i.e., dynamically re-distributes the processing across the system according to changes in the data distribution and/or query workload. In addition to keywords, higher-level textual concepts are identified and are semantically matched against spatio-textual queries. Tornado provides data deduplication and fusion to eliminate redundant textual data. We demonstrate a prototype of Tornado running against real Twitter streams, where the users can register continuous or snapshot spatio-textual queries using a map-assisted query-interface.},
url = {http://approjects.co.za/?big=en-us/research/publication/tornado-a-distributed-spatio-textual-stream-processing-system/},
}