Real-time decision making in emerging IoT applications typically relies on computing quantitative summaries of large data streams in an efficient and incremental manner. We give here an introduction to the StreamQRE language, which has recently been proposed for the purpose of simplifying the task of programming the desired logic in such stream processing applications. StreamQRE provides natural and high-level constructs for processing streaming data, and it offers a novel integration of linguistic constructs from two distinct programming paradigms: streaming extensions of relational query languages and quantitative extensions of regular expressions. The former allows the programmer to employ relational constructs to partition the input data by keys and to integrate data streams from different sources, while the latter can be used to exploit the logical hierarchy in the input stream for modular specifications.
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