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arXiv 1505.03060cs.DC
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Actors vs Shared Memory:大数据应用框架中的两种模型

Actors vs Shared Memory: two models at work on Big Data application frameworks

Silvia Crafa, Luca Tronchin

摘要:

这项工作的目的是分析两种不同的并发模型,即共享内存模型和演员模型,可以影响管理大量数据的应用程序的开发,大数据应用程序的独特之处。本文通过对MapReduce和Bulk Synchronous Parallel两种算法方案的具体工程分析,对两种模型进行了比较。这两个项目都在两个具体的平台上双重实现:Akka Cluster和Managed X10。其结果既是大数据分析场景中模型的概念比较,也是基于集群平台上的具体执行的实验分析。

英文摘要:

This work aims at analyzing how two different concurrency models, namely the shared memory model and the actor model, can influence the development of applications that manage huge masses of data, distinctive of Big Data applications. The paper compares the two models by analyzing a couple of concrete projects based on the MapReduce and Bulk Synchronous Parallel algorithmic schemes. Both projects are doubly implemented on two concrete platforms: Akka Cluster and Managed X10. The result is both a conceptual comparison of models in the Big Data Analytics scenario, and an experimental analysis based on concrete executions on a cluster platform.

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。

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