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StreamQRE: Modular Specification and Efficient Evaluation of Quantitative Queries over Streaming Data.

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|November 21, 2017
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Summary
This summary is machine-generated.

StreamQRE simplifies real-time IoT data processing with novel programming constructs. This framework offers natural query specifications and achieves higher throughput and memory savings compared to existing systems.

Keywords:
Information systems → Stream managementQuantitative Regular ExpressionsSoftware and its engineering → General programming languagesTheory of computation → Streaming modelsdata stream processing

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Area of Science:

  • Computer Science
  • Data Engineering
  • Programming Languages

Background:

  • Real-time decision-making in IoT requires efficient processing of large data streams.
  • Existing programming models for streaming data can be complex and lack high-level abstractions.

Purpose of the Study:

  • To introduce StreamQRE, a novel language for simplified and efficient processing of streaming data.
  • To provide natural, high-level constructs by integrating relational query languages and quantitative regular expressions.
  • To enable efficient real-time analytics for Internet of Things (IoT) applications.

Main Methods:

  • Developed StreamQRE with a core language, formal semantics, and a decidable type system.
  • Designed a compilation algorithm translating high-level queries into streaming algorithms with complexity bounds.
  • Integrated approximation algorithms for memory optimization.
  • Implemented StreamQRE in Java and conducted performance evaluations against existing systems.

Main Results:

  • StreamQRE enables more natural and succinct query specifications than existing frameworks.
  • The StreamQRE implementation demonstrates higher throughput (2-4x greater than RxJava).
  • Integrated approximation algorithms offer significant memory savings.

Conclusions:

  • StreamQRE provides an effective and efficient solution for real-time streaming data processing in IoT.
  • The language's novel integration of programming paradigms enhances usability and performance.
  • StreamQRE offers a promising alternative for high-performance stream processing with reduced resource consumption.