占领云:99%人口的分布式计算

Eric Jonas, Qifan Pu, S. Venkataraman, I. Stoica, B. Recht
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引用次数: 449

摘要

尽管有许多开源平台和广泛的商业产品,但大量用户仍然无法使用分布式计算。虽然分布式计算框架已经超越了简单的map-reduce模型,但许多用户仍然要与复杂的集群管理和配置工具作斗争,即使是运行简单的令人尴尬的并行作业。我们认为无状态函数为这些用户提供了一个可行的平台,消除了集群管理开销,实现了弹性的承诺。此外,使用我们的原型实现PyWren,我们证明了该模型足够通用,可以有效地实现许多分布式计算模型,例如BSP。从网络带宽的最新趋势和分解存储的出现推断,我们认为无状态函数是未来计算环境中数据处理的自然选择。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Occupy the cloud: distributed computing for the 99%
Distributed computing remains inaccessible to a large number of users, in spite of many open source platforms and extensive commercial offerings. While distributed computation frameworks have moved beyond a simple map-reduce model, many users are still left to struggle with complex cluster management and configuration tools, even for running simple embarrassingly parallel jobs. We argue that stateless functions represent a viable platform for these users, eliminating cluster management overhead, fulfilling the promise of elasticity. Furthermore, using our prototype implementation, PyWren, we show that this model is general enough to implement a number of distributed computing models, such as BSP, efficiently. Extrapolating from recent trends in network bandwidth and the advent of disaggregated storage, we suggest that stateless functions are a natural fit for data processing in future computing environments.
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