JOURNAL ARTICLE

Parallel Computing Framework as a Cloud Service

Abstract

Hadoop, the open-source implementation of MapReduce, has been widely used in different projects. However, when users want to use this parallel computing framework, they have to spend time on the Hadoop cluster configuration, learning the programming API, and the MapReduce job operations. This paper proposes the Parallel Computing Framework as a Cloud Service (PCFCS) to provide the users parallel computing cluster, and simplify the configuration, programming, uploading, and operating procedures. Especially, PCFCS defines a set of annotations, with which users can quickly build their own MapReduce job.

Keywords:
Computer science Cloud computing Upload Data-intensive computing Programming paradigm Distributed computing Service (business) Set (abstract data type) Operating system Cluster (spacecraft) Computer cluster Grid computing Programming language

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Cited By
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FWCI (Field Weighted Citation Impact)
3
Refs
0.20
Citation Normalized Percentile
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Citation History

Topics

Cloud Computing and Resource Management
Physical Sciences →  Computer Science →  Information Systems
IoT and Edge/Fog Computing
Physical Sciences →  Computer Science →  Computer Networks and Communications
Distributed and Parallel Computing Systems
Physical Sciences →  Computer Science →  Computer Networks and Communications

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