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Abstract ▼ AI-Helper

Data-intensive computing being highly regarded in science application area, cloud computing has engaged public attention due to the necessity of efficiently processing large-scale data as soon as possible. Hadoop provides software framework for large-scale data processing and analysis, and is widely...

Data-intensive computing being highly regarded in science application area, cloud computing has engaged public attention due to the necessity of efficiently processing large-scale data as soon as possible. Hadoop provides software framework for large-scale data processing and analysis, and is widely adopted and used as the representative technology of cloud computing. Especially, roviding high-scalability and performance and getting an excellence in fault-tolerence and automatic recovery functionalities, Hadoop is gradually used in scientific communities. In this paper, we propose a Hadoop-based method to analyse large-scale data generated from astroinformatics research area. astroinformatics data we are dealing with are generated from Super WASP project, which need to process about ten million of small-sized observation data. However, Hadoop is specialized in large-scale data analysis and it is not suitable for many small-sized astroinformatics data. In this paper, we packed many small-sized astroinformatics data into large-sized ones using the specialized data structure of Hadoop and implemented MapReduce wrapper program to execute astroinformatics analysis code on Hadoop.

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