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Proceedings of the 50th Hawaii International Conference on System Sciences (2017)

DOI: 10.24251/hicss.2017.712

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Batch to Real-Time: Incremental Data Collection & Analytics Platform

Proceedings article published in 2017 by Ahmet Aydin, Ken Anderson
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Preprint: policy unknown
Question mark in circle
Postprint: policy unknown
Question mark in circle
Published version: policy unknown

Abstract

Real-time data collection and analytics is a desirable but challenging feature to provide in data-intensive software systems. To provide highly concurrent and efficient real-time analytics on streaming data at interactive speeds requires a well-designed software architecture that makes use of a carefully selected set of software frameworks. In this paper, we report on the design and implementation of the Incremental Data Collection & Analytics Platform (IDCAP). The IDCAP provides incremental data collection and indexing in real-time of social media data; support for real-time analytics at interactive speeds; highly concurrent batch data processing supported by a novel data model; and a front-end web client that allows an analyst to manage IDCAP resources, to monitor incoming data in real-time, and to provide an interface that allows incremental queries to be performed on top of large Twitter datasets.