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Çмú´ëȸ ÇÁ·Î½Ãµù

Ȩ Ȩ > ¿¬±¸¹®Çå > Çмú´ëȸ ÇÁ·Î½Ãµù > Çѱ¹Á¤º¸Åë½ÅÇÐȸ Çмú´ëȸ > 2017³â Ãß°èÇмú´ëȸ

2017³â Ãß°èÇмú´ëȸ

Current Result Document :

ÇѱÛÁ¦¸ñ(Korean Title) RHadoopÀ» ÀÌ¿ëÇÑ º¸°ÇÀÇ·á ºòµ¥ÀÌÅÍ ºÐ¼®ÀÇ À¯È¿¼º
¿µ¹®Á¦¸ñ(English Title) Usefulness of RHadoop in Case of Healthcare Big Data Analysis
ÀúÀÚ(Author) ·ù¿ì¼®   Wooseok Ryu  
¿ø¹®¼ö·Ïó(Citation) VOL 21 NO. 02 PP. 0115 ~ 0116 (2017. 10)
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(Korean Abstract)
RÀº °­·ÂÇÑ ºÐ¼®°ú °¡½ÃÈ­ ±â´ÉÀ» Á¦°øÇÔ¿¡ µû¶ó ºòµ¥ÀÌÅÍ ½Ã´ë¿¡¼­ÀÇ ±âº» ºÐ¼® Ç÷§ÆûÀ¸·Î °¢±¤¹Þ°í ÀÖÀ½¿¡µµ ºÒ±¸ÇÏ°í ±Ô¸ð È®À强 ¹Ìºñ¿¡ µû¸¥ ¼º´É Á¦¾àÀ̶ó´Â ´ÜÁ¡À» °¡Áö°í ÀÖ´Ù. À̸¦ ÇØ°áÇϱâ À§ÇÑ ¹æ¹ýÀ¸·Î RHadoop ÆÐÅ°Áö°¡ °ø°³µÇ¾î ÀÖÀ¸¸ç À̸¦ ÅëÇØ R·Î °³¹ßµÈ ÇÁ·Î±×·¥ÀÌ ÇϵÓÀ» ÅëÇØ º´·Ä ºÐ»ê 󸮰¡ °¡´ÉÇÑ Æ¯Â¡ÀÌ ÀÖ´Ù. º» ³í¹®¿¡¼­´Â °ø°øµ¥ÀÌÅÍÀÇ °³¹æ¿¡ µû¶ó ÀÎÅͳÝÀ» ÅëÇØ °ø°³µÈ °¢Á¾ º¸°ÇÀÇ·á ºòµ¥ÀÌÅÍÀÇ ºÐ¼®¿¡¼­ RHadoop ÆÐÅ°ÁöÀÇ È°¿ëÀÌ ¾ó¸¶³ª À¯È¿ÇÑ Áö¸¦ °ËÁõÇÏ°íÀÚ ÇÏ¿´´Ù. À̸¦ À§ÇØ ±¹¹Î°Ç°­º¸Çè°ø´Ü¿¡¼­ Á¦°øÇÑ 2015³â Áø·á³»¿ªÁ¤º¸¸¦ ÀÌ¿ëÇÏ¿© R°ú RHadoopÀÇ ºÐ¼® ¼º´ÉÀ» ºñ±³ °ËÁõÇÑ °á°ú RHadoopÀÌ È¿°úÀûÀ¸·Î ºÐ¼® ¼º´ÉÀ» °³¼±½Ãų ¼ö ÀÖÀ½À» ÀÔÁõÇÏ¿´´Ù.
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(English Abstract)
R has become a popular analytics platform as it provides powerful analytic functions as well as visualizations. However, it has a weakness in which scalability is limited. As an alternative, the RHadoop package facilitates distributed processing of R programs under the Hadoop platform. This paper investigates usefulness of the RHadoop package when analyzing healthcare big data that is widely open in the internet space. To do this, this paper has compared analytic performances of R and RHadoop using the medical treatment records of year 2015 provided by National Health Insurance Service. The result shows that RHadoop effectively enhances processing performance of healthcare big data compared with R.
Å°¿öµå(Keyword) R   RHadoop   ÇϵӠ  NHIS   ¼º´Éºñ±³  
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