In many Big Data applications today, information needs to be actively shared between systems managed by different organizations. To enable sharing Big Data at scale, developers would have to create dedicated server programs and glue together multiple Big Data systems for scalability. Developing and managing such glued data sharing services requires a significant amount of work from developers. In our prior work, we developed a Big Active Data (BAD) system for enabling Big Data subscriptions and analytics with millions of subscribers. Based on that, we introduce a new mechanism for enabling the sharing of Big Data at scale declaratively so that developers can easily create and provide data sharing services using declarative statements and can benefit from an underlying scalable infrastructure. We show our implementation on top of the BAD system, explain the data sharing data flow among multiple systems, and present a prototype system with experimental results.

中文翻译：

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弥补BAD群岛：大规模的声明式数据共享

在当今的许多大数据应用程序中，信息需要在不同组织管理的系统之间主动共享。为了实现大规模共享大数据，开发人员必须创建专用的服务器程序并将多个大数据系统粘合在一起以实现可伸缩性。开发和管理此类粘合数据共享服务需要开发人员进行大量工作。在我们之前的工作中，我们开发了一个大活动数据（BAD）系统，以实现数百万订户的大数据订阅和分析。在此基础上，我们引入了一种新的机制，用于以声明方式大规模共享大数据，以便开发人员可以使用声明性语句轻松创建和提供数据共享服务，并可以从基础可伸缩基础架构中受益。我们将在BAD系统之上展示我们的实现，