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Jobcast - Parallel and Distributed Processing Framework: Data Processing on a Cloud Style KVS Database

机译:Jobcast-并行和分布式处理框架:云风格KVS数据库上的数据处理

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In this paper, we propose a new architecture for parallel and distributed processing framework, gJobcasth, which enables data processing on a cloud style KVS database. Nowadays, lots of KVS (as known as Key Value Store) systems exist which achieve high scalability for data spaces among a huge number of computers. Some of KVS implementations use gconsistent hashh algorithm to identify the backend data node to store a pair of key and value. Jobcast also uses consistent hash algorithm for a distribution strategy and has a capability to store key and value pairs into huge number of computers as a KVS system. Furthermore, Jobcast also distributes gjobsh into data nodes for parallel and distributed processing. In this paper, we introduce a basic architecture of Jobcast and evaluate a data processing performance for a typical example.
机译:在本文中,我们提出了一种用于并行和分布式处理框架的新架构gJobcasth,它可以在云风格的KVS数据库上进行数据处理。如今,存在许多KVS(称为键值存储)系统,这些系统在大量计算机中的数据空间上实现了高可伸缩性。一些KVS实现使用gconsistent hashh算法来识别后端数据节点以存储一对键和值。 Jobcast还使用一致的哈希算法作为分发策略,并具有将键和值对作为KVS系统存储到大量计算机中的功能。此外,Jobcast还将gjobsh分发到数据节点中,以进行并行和分布式处理。在本文中,我们介绍Jobcast的基本体系结构,并通过一个典型示例评估数据处理性能。

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