Today, data is being actively generated by a variety of devices, services, and applications. Such data is important not only for the information that it contains, but also for its relationships to other data and to interested users. Most existing Big Data systems focus on
Building an end-to-end BAD application
Traditional big data infrastructures are passive in nature, passively answering user requests to process and return data. In many applications however, users not only need to analyze data, but also to subscribe to and actively receive data of interest, based on their subscriptions. Their interest may include the incoming data's content as well as its relationships to other data. Moreover, data delivered to subscribers may need to be enriched with additional relevant and actionable information. To address this Big Active Data (BAD) challenge we have advocated the need for building scalable BAD systems that continuously and reliably capture big data while enabling timely and automatic delivery of relevant and possibly enriched information to a large pool of subscribers. In this demo we showcase how to build an end-to-end active application using a BAD system and a standard email broker for data delivery. This includes enabling users to register their interests with the bad system, ingesting and monitoring data, and producing customized results and delivering them to the appropriate subscribers. Through this example we demonstrate that even complex active data applications can be created easily and scale to many users, considerably limiting the effort of application developers, if a BAD approach is taken.
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- PAR ID:
- 10293598
- Date Published:
- Journal Name:
- Proceedings of the 15th ACM International Conference on Distributed and Event-based Systems
- Page Range / eLocation ID:
- 184 to 187
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract passively answering queries from users, rather thanactively collecting data, processing it, and serving it to users. To satisfy both passive and active requests at scale, application developers need either to heavily customize an existing passive Big Data system or to glue one together with systems likeStreaming Engines andPub-sub services . Either choice requires significant effort and incurs additional overhead. In this paper, we present the BAD (Big Active Data) system as an end-to-end, out-of-the-box solution for this challenge. It is designed to preserve the merits of passive Big Data systems and introduces new features for actively serving Big Data to users at scale. We show the design and implementation of the BAD system, demonstrate how BAD facilitates providing both passive and active data services, investigate the BAD system’s performance at scale, and illustrate the complexities that would result from instead providing BAD-like services with a “glued” system. -
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3465480.3467840
