Rafael Fernández-Moctezuma

Rafael Fernández-Moctezuma

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    Preview abstract Unbounded, unordered, global-scale datasets are increasingly common in day-to-day business (e.g. Web logs, mobile usage statistics, and sensor networks). At the same time, consumers of these datasets have evolved sophisticated requirements, such as event-time ordering and windowing by features of the data themselves, in addition to an insatiable hunger for faster answers. Meanwhile, practicality dictates that one can never fully optimize along all dimensions of correctness, latency, and cost for these types of input. As a result, data processing practitioners are left with the quandary of how to reconcile the tensions between these seemingly competing propositions, often resulting in disparate implementations and systems. We propose that a fundamental shift of approach is necessary to deal with these evolved requirements in modern data processing. We as a field must stop trying to groom unbounded datasets into finite pools of information that eventually become complete, and instead live and breathe under the assumption that we will never know if or when we have seen all of our data, only that new data will arrive, old data may be retracted, and the only way to make this problem tractable is via principled abstractions that allow the practitioner the choice of appropriate tradeoffs along the axes of interest: correctness, latency, and cost. In this paper, we present one such approach, the Dataflow Model, along with a detailed examination of the semantics it enables, an overview of the core principles that guided its design, and a validation of the model itself via the real-world experiences that led to its development. View details
    Towards execution guarantees for stream queries
    David Maier
    Kristin Tufte
    IPDPS Workshops(2010), pp. 1-8
    Framing the question: detecting and filling spatial-temporal windows
    James Whiteneck
    Kristin Tufte
    Amit Bhat
    David Maier
    GIS-IWGS(2010), pp. 19-22
    Support for Schema Evolution in Data Stream Management Systems
    James F. Terwilliger
    Lois M. L. Delcambre
    David Maier
    J. UCS, 16(2010), pp. 3073-3101
    Inter-Operator Feedback in Data Stream Management Systems via Punctuation
    Kristin Tufte
    Jin Li
    CIDR(2009)
    Toward Formal Semantics for Data and Schema Evolution in Data Stream Management Systems
    James F. Terwilliger
    Lois M. L. Delcambre
    David Maier
    ER Workshops(2009), pp. 85-94