Data stream processing systems (DSPSs) enable users to express and run stream applications to continuously process data streams. To achieve realtime data analytics, recent researches keep focusing on optimizing the system latency and throughput. Witnessing the recent great achievements in the computer architecture community, researchers and practitioners have investigated the potential of adoption hardware-conscious stream processing by better utilizing modern hardware capacity in DSPSs. In this paper, we conduct a systematic survey of recent work in the field, particularly along with the following three directions: 1) computation optimization, 2) stream I/O optimization, and 3) query deployment. Finally, we advise on potential future research directions.

中文翻译：

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硬件意识流处理

数据流处理系统 (DSPS) 使用户能够表达和运行流应用程序以连续处理数据流。为了实现实时数据分析，最近的研究一直专注于优化系统延迟和吞吐量。见证了计算机体系结构社区最近取得的巨大成就，研究人员和从业人员通过更好地利用 DSPS 中的现代硬件容量，研究了采用硬件意识流处理的潜力。在本文中，我们对该领域的近期工作进行了系统调查，特别是以下三个方向：1）计算优化，2）流 I/O 优化，3）查询部署。最后，我们就潜在的未来研究方向提出建议。