Parallel Computing Framework as a Cloud Service

Author

Lin, Rongheng ; Tu, Huake ; Zou, Hua

Author_Institution

State Key Lab. of Networking & Switching, Beijing Univ. of Posts & Telecommun., Beijing, China

fYear

2012

fDate

24-29 June 2012

Firstpage

672

Lastpage

673

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

application program interfaces; cloud computing; parallel processing; API programming; Hadoop cluster configuration; MapReduce job operation; PCFCS; annotation set; application program interface; cloud service; configuration procedure; operating procedure; parallel computing cluster; parallel computing framework; programming procedure; uploading procedure; Educational institutions; Laboratories; Loading; Parallel processing; Programming; Switches; Web services; Annotation; Cloud Commputing; Hadoop; MapReduce; Parallel Computing;

fLanguage

English

Publisher

ieee

Conference_Titel

Web Services (ICWS), 2012 IEEE 19th International Conference on

Conference_Location

Honolulu, HI

Print_ISBN

978-1-4673-2131-0

Type

conf

DOI

10.1109/ICWS.2012.55

Filename

6257950