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ÇѱÛÁ¦¸ñ(Korean Title) |
ÇÏµÓ ±â¹Ý õ¹® ÀÀ¿ë ºÐ¾ß ´ë±Ô¸ð µ¥ÀÌÅÍ ºÐ¼® ±â¹ý |
¿µ¹®Á¦¸ñ(English Title) |
Large-scale Data Analysis based on Hadoop for Astroinformatics |
ÀúÀÚ(Author) |
°ûÀçÇõ
À±ÁØ¿ø
Á¤¿ëȯ
ÇÔÀç±Õ
¹Úµ¿ÀÎ
Jae-Hyuck Kwak
Junweon Yoon
Yonghwan Jung
Jaegyoon Hahm
Dongin Park
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¿ø¹®¼ö·Ïó(Citation) |
VOL 17 NO. 11 PP. 0587 ~ 0591 (2011. 11) |
Çѱ۳»¿ë (Korean Abstract) |
°úÇÐ ÀÀ¿ë ºÐ¾ß¿¡¼ µ¥ÀÌÅÍ Áý¾àÇü ÄÄÇ»ÆÃ(data-intensive computing)ÀÌ Á¡Â÷ÀûÀ¸·Î ÁÖ¸ñ¹ÞÀ¸¸é¼ ´ë±Ô¸ðÀÇ µ¥ÀÌÅ͸¦ ºü¸¥ ½Ã°£ ³»¿¡ È¿À²ÀûÀ¸·Î ó¸®ÇØ¾ß ÇÒ Çʿ伺À¸·Î ÀÎÇØ Å¬¶ó¿ìµå ÄÄÇ»ÆÃÀÌ ÁÖ¸ñ¹Þ°í ÀÖ´Ù. ÇϵÓ(Hadoop)Àº ´ë±Ô¸ð µ¥ÀÌÅÍ Ã³¸® ºÐ¼®À» À§ÇÑ ¼ÒÇÁÆ®¿þ¾î ÇÁ·¹ÀÓ¿öÅ©¸¦ Á¦°øÇϸç Ŭ¶ó¿ìµå ÄÄÇ»ÆÃÀÇ ´ëÇ¥ÀûÀÎ ±â¼ú·Î¼ ³Î¸® »ç¿ëµÇ°í ÀÖ´Ù. ƯÈ÷, ÇϵÓÀº ³ôÀº È®À强°ú ¼º´ÉÀ» Á¦°øÇÏ¸é¼ °áÇÔ Å½Áö¿Í ÀÚµ¿ º¹±¸ ±â´ÉÀÌ ¿ì¼öÇÏ¿© °úÇÐ ±â¼ú ºÐ¾ß¿¡¼µµ Á¡Â÷ÀûÀ¸·Î µµÀԵǾî È°¿ëµÇ°í ÀÖ´Ù.
º» ³í¹®¿¡¼´Â ÇϵÓÀ» ÀÌ¿ëÇÏ¿© õ¹® ÀÀ¿ë ºÐ¾ß¿¡¼ »ý¼ºµÇ´Â ´ë±Ô¸ð µ¥ÀÌÅ͸¦ ºÐ¼®Çϱâ À§ÇÑ ¹æ¹ýÀ» Á¦¾ÈÇÏ¿´´Ù. º» ³í¹®¿¡¼ °ü½ÉÀ» °¡Áö´Â õ¹® ÀÀ¿ë µ¥ÀÌÅÍ´Â Super-WASPÇÁ·ÎÁ§Æ®¿¡¼ »ý¼ºµÇ´Â ´ë·« õ¸¸ °³ÀÇ ÀÛÀº Å©±âÀÇ °üÃø µ¥ÀÌÅ͸¦ ó¸®ÇØ¾ß Çϴµ¥ ÇϵÓÀº ´ë±Ô¸ð µ¥ÀÌÅÍ Ã³¸®¿¡ ƯȵǾî ÀÖ¾î¼ ¸¹Àº °³¼öÀÇ ÀÛÀº Å©±â¸¦ °¡Áö´Â °üÃø µ¥ÀÌÅÍ Ã³¸®¿¡´Â ÀûÇÕÇÏÁö ¾Ê´Ù. º» ³í¹®¿¡¼´Â õ¹® ÀÀ¿ë µ¥ÀÌÅÍ Ã³¸®¸¦ À§ÇÑ ÀÔÃâ·Â ÆÄÀÏÀ» Çϵӿ¡¼ Á¦°øÇϴ Ư¼öÈµÈ µ¥ÀÌÅÍ ±¸Á¶¸¦ ÀÌ¿ëÇÏ¿© ¾ÐÃàÇÏ¿´°í õ¹® ÀÀ¿ë ½ÇÇà Äڵ尡 Çϵӿ¡¼ ½ÇÇà °¡´ÉÇϵµ·Ï ¸Ê¸®µà½º ÀÛ¾÷À¸·Î ·¦ÇÎÇÏ¿© ±¸ÇöÇÏ¿´´Ù.
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¿µ¹®³»¿ë (English Abstract) |
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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Å°¿öµå(Keyword) |
µ¥ÀÌÅÍÁý¾àÇü ÄÄÇ»ÆÃ
õ¹®Á¤º¸
ÇϵÓ
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Data-intensive Computing
Astroinformatics
Hadoop
MapReduce
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