Abstract
The widespread use of GPS-enabled smart devices and the increased popularity of their applications, e.g., social networks, has led to the generation of huge amounts of spatio-textual data. This spatio-textual data needs to be processed in real-time. However, existing data management systems are either centralized or general-purpose distributed systems, e.g., Spark [2] and Storm [3]. Centralized systems do not scale and general purpose distributed systems are not optimized for the processing of spatio-textual data. In this paper, we present Tornado [7], a distributed in-memory spatio-textual stream processing system. To efficiently process spatio-textual streams, Tornado extends Storm [3] with a spatio-textual indexing layer that significantly improves the overall system performance. Tornado is adaptive, i.e., it dynamically redistributes the workload across worker processes according to changes in the distribution of spatio-textual data and queries.
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