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arXiv 2007.02802cs.DC
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实时的数据流多租户发布/订阅处理

Multi-tenant Pub/Sub Processing for Real-time Data Streams

Álvaro Villalba, David Carrera

摘要:

设备和传感器在不同的位置和协议上生成数据流。这些数据通常会到达一个用于存储和处理流的中央平台。处理可以实时的进行,转换和丰富可以在运行中进行,但也可以在数据存储和组织在存储库中之后进行。在前一种情况下,需要流处理技术对数据进行操作;在后一种情况下,通常使用批处理分析和查询。本文介绍了一种基于用户提供的代码动态构造数据流处理拓扑的运行时。这些动态拓扑是使用由使用数据的应用程序定义的数据订阅模型动态构建的。每个用户定义的处理单元称为服务对象。每个服务对象都使用输入数据流,并且可以产生其他服务对象可以使用的输出流。基于订阅的编程模型使多个用户能够部署他们自己的数据处理服务。运行时动态转发数据并执行来自不同用户的服务对象。数据流可以源自真实世界的设备,也可以是服务对象的输出。

英文摘要:

Devices and sensors generate streams of data across a diversity of locations and protocols. That data usually reaches a central platform that is used to store and process the streams. Processing can be done in real time, with transformations and enrichment happening on-the-fly, but it can also happen after data is stored and organized in repositories. In the former case, stream processing technologies are required to operate on the data; in the latter batch analytics and queries are of common use. This paper introduces a runtime to dynamically construct data stream processing topologies based on user-supplied code. These dynamic topologies are built on-the-fly using a data subscription model defined by the applications that consume data. Each user-defined processing unit is called a Service Object. Every Service Object consumes input data streams and may produce output streams that others can consume. The subscription-based programing model enables multiple users to deploy their own data-processing services. The runtime does the dynamic forwarding of data and execution of Service Objects from different users. Data streams can originate in real-world devices or they can be the outputs of Service Objects.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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