Real-time analysis of market data leveraging Apache Flink

Cecilia Calavaro, G. Russo, V. Cardellini
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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.
利用Apache Flink实时分析市场数据
在本文中,我们提出了DEBS 2022大挑战(GC)的解决方案。根据GC要求,提出的软件持续观察正在交易的金融工具的通知,旨在及时发现突破模式。我们的解决方案利用了Apache Flink,这是一个开源的、可扩展的流处理平台,它允许我们以低延迟处理传入的数据流,并利用底层计算基础设施提供的并行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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