In this paper, we present a solution to the DEBS 2022 Grand Challenge (GC). According to the GC requirements, the proposed software continuously observes notifications about financial instruments being traded, aiming to timely detect breakout patterns. Our solution leverages Apache Flink, an open-source, scalable stream processing platform, which allows us to process incoming data streams with low latency and exploit the parallelism offered by the underlying computing infrastructure.

Calavaro, C., Russo Russo, G., Cardellini, V. (2022). Real-time analysis of market data leveraging Apache Flink. In DEBS '22: Proceedings of the 16th ACM International Conference on Distributed and Event-Based Systems (pp.162-165). ACM [10.1145/3524860.3539650].

Real-time analysis of market data leveraging Apache Flink

Valeria Cardellini
2022

Abstract

In this paper, we present a solution to the DEBS 2022 Grand Challenge (GC). According to the GC requirements, the proposed software continuously observes notifications about financial instruments being traded, aiming to timely detect breakout patterns. Our solution leverages Apache Flink, an open-source, scalable stream processing platform, which allows us to process incoming data streams with low latency and exploit the parallelism offered by the underlying computing infrastructure.
16th ACM International Conference on Distributed and Event-Based Systems
Copenhagen, Denmark
2022
Rilevanza internazionale
contributo
29-giu-2022
Settore ING-INF/05
English
https://dl.acm.org/doi/10.1145/3524860.3539650
Intervento a convegno
Calavaro, C., Russo Russo, G., Cardellini, V. (2022). Real-time analysis of market data leveraging Apache Flink. In DEBS '22: Proceedings of the 16th ACM International Conference on Distributed and Event-Based Systems (pp.162-165). ACM [10.1145/3524860.3539650].
Calavaro, C; Russo Russo, G; Cardellini, V
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/305214
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