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Ȩ Ȩ > ¿¬±¸¹®Çå > ±¹³» ³í¹®Áö > Çѱ¹Á¤º¸°úÇÐȸ ³í¹®Áö > Á¤º¸°úÇÐȸ ³í¹®Áö C : ÄÄÇ»ÆÃÀÇ ½ÇÁ¦

Á¤º¸°úÇÐȸ ³í¹®Áö C : ÄÄÇ»ÆÃÀÇ ½ÇÁ¦

Current Result Document :

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¿ÀΠ  Jae-Hyuck Kwak   Junweon Yoon   Yonghwan Jung   Jaegyoon Hahm   Dongin Park  
¿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¦°øÇϸ鼭 °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¸®¿¡ ƯȭµÇ¾î À־ ¸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.
¿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.
Å°¿öµå(Keyword) µ¥ÀÌÅÍÁý¾àÇü ÄÄÇ»Æà  õ¹®Á¤º¸   ÇϵӠ  ¸Ê¸®µà½º   Data-intensive Computing   Astroinformatics   Hadoop   MapReduce  
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