分布式分析应用的柔性调度
Flexible Scheduling of Distributed Analytic Applications
摘要：
这项工作解决了调度用户定义的分析应用程序，我们定义为高层次的组合框架，它们的组件，以及必要的逻辑进行工作的问题。我们应用程序定义中的关键思想是区分组件的类别，包括刚性和弹性类型：前者是应用程序取得进展所需的，后者有助于减少执行时间。我们发现，调度这样的应用程序的问题提出了新的挑战，现有的方法解决效率低下。因此，我们提出了一种新的，灵活的启发式调度分析应用程序的设计和评估，其目的是在高系统的响应能力，通过有效地分配资源。我们的算法使用跟踪驱动的模拟进行评估，大规模的真实系统跟踪：我们灵活的调度程序优于基线方法在各种指标，包括应用程序的周转时间，和资源分配效率。我们还提出了一个成熟的系统，我们称之为佐伊，它结合了本文提出的想法的设计和评估，并报告具体的改进，在效率和性能方面，相对于我们的系统的前几代。
英文摘要：
This work addresses the problem of scheduling user-defined analytic applications, which we define as high-level compositions of frameworks, their components, and the logic necessary to carry out work. The key idea in our application definition, is to distinguish classes of components, including rigid and elastic types: the first being required for an application to make progress, the latter contributing to reduced execution times. We show that the problem of scheduling such applications poses new challenges, which existing approaches address inefficiently. Thus, we present the design and evaluation of a novel, flexible heuristic to schedule analytic applications, that aims at high system responsiveness, by allocating resources efficiently. Our algorithm is evaluated using trace-driven simulations, with large-scale real system traces: our flexible scheduler outperforms a baseline approach across a variety of metrics, including application turnaround times, and resource allocation efficiency. We also present the design and evaluation of a full-fledged system, which we have called Zoe, that incorporates the ideas presented in this paper, and report concrete improvements in terms of efficiency and performance, with respect to prior generations of our system.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
