在类似mapreduce的框架中，支持用户自定义估计和早期终止的在线分析

International Symposium on Design and Implementation of Symbolic Computation Systems Pub Date : 2015-11-15 DOI:10.1145/2831244.2831247

Yi Wang, Linchuan Chen, G. Agrawal

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引用次数: 4

摘要

基于运行时近似的在线分析已被广泛用于会议时间和/或资源限制。尽管MapReduce在科学和商业领域都很受欢迎，但在MapReduce实现中实现在线分析有几个障碍。在本文中，我们提出了一个类似mapreduce的在线分析框架。我们的系统可以增量地处理输入，提供快速估计，并在达到用户定义的终止状态时立即终止执行。我们扩展了MapReduce API，允许用户自定义估计方法和终止条件。我们还通过三个近似应用展示了系统的功能和效率。与批处理实现的比较显示了至少一个数量级的加速。

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Supporting online analytics with user-defined estimation and early termination in a MapReduce-like framework

Online analytics based on runtime approximation has been widely adopted for meeting time and/or resource constraints. Though MapReduce has been gaining its popularity in both scientific and commercial sectors, there are several obstacles in implementing online analytics in a MapReduce implementation. In this paper, we present a MapReduce-like framework for online analytics. Our system can process the input incrementally, provide fast estimates, and terminate the execution as soon as a user-defined termination state is reached. We have extended the MapReduce API by allowing the user to customize both the estimation method and termination condition. We also have shown both the functionality and efficiency of our system through three approximate applications. A comparison with a batch processing implementation shows a speedup of at least an order of magnitude.

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International Symposium on Design and Implementation of Symbolic Computation Systems

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