Title
The dataflow model: a practical approach to balancing correctness, latency, and cost in massive-scale, unbounded, out-of-order data processing
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.
Year
DOI
Venue
2015
10.14778/2824032.2824076
Proceedings of The Vldb Endowment
Field
DocType
Volume
Data mining,Data processing,Abstraction,Latency (engineering),Computer science,Correctness,Implementation,Theoretical computer science,Out-of-order execution,Distributed computing,Wireless sensor network,Semantics,Database
Journal
8
Issue
ISSN
Citations 
12
2150-8097
94
PageRank 
References 
Authors
2.70
21
11
Name
Order
Citations
PageRank
Tyler Akidau128110.63
Robert Bradshaw237020.18
Craig Chambers33161351.45
Slava Chernyak42809.90
Rafael Fernández-Moctezuma5942.70
Reuven Lax62809.57
Sam McVeety72809.57
Daniel Mills866128.07
Frances Perry9943.04
Eric Schmidt10942.70
Sam Whittle112829.94