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Current Result Document :
ÇѱÛÁ¦¸ñ(Korean Title) |
H*-tree/H*-cubing: µ¥ÀÌÅÍ ½ºÆ®¸²ÀÇ OLAP¸¦ À§ÇÑ Çâ»óµÈ µ¥ÀÌÅÍ Å¥ºê ±¸Á¶ ¹× Å¥ºù ±â¹ý |
¿µ¹®Á¦¸ñ(English Title) |
H*-tree/H*-cubing: Improved Data Cube Structure and Cubing Method for OLAP on Data Stream |
ÀúÀÚ(Author) |
½É»ó¿¹
ÀÌ ¿¬
À̵¿¿í
±è°æ¹è
¹èÇØ¿µ
Xiangrui Chen
Yan Li
Dong-Wook Lee
Gyoung-Bae Kim
Hae-Young Bae
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¿ø¹®¼ö·Ïó(Citation) |
VOL 16-D NO. 04 PP. 0475 ~ 0486 (2009. 08) |
Çѱ۳»¿ë (Korean Abstract) |
µ¥ÀÌÅÍ Å¥ºê´Â ´ÙÂ÷¿ø µ¥ÀÌÅÍ ºÐ¼® ¹× ¸ÖƼ·¹º§ µ¥ÀÌÅÍ ºÐ¼®¿¡ ¸¹ÀÌ »ç¿ëµÇ°í ÀÖ´Â Áß¿äÇÑ µ¥ÀÌÅÍ ±¸Á¶ÀÌ´Ù. ÃÖ±Ù µ¥ÀÌÅÍ ½ºÆ®¸²ÀÇ ¿Â¶óÀÎ ºÐ¼®¿¡ ´ëÇÑ ¼ö¿ä°¡ Áõ°¡ÇÏ¸é¼ ½ºÆ®¸² Å¥ºê, Flow Å¥ºê, S-Å¥ºê µîÀÇ ´Ù¾çÇÑ µ¥ÀÌÅÍ Å¥ºê ±¸Á¶¿Í ±â¹ýÀÌ Á¦¾ÈµÇ¾ú´Ù. ±×·¯³ª ±âÁ¸ ±â¹ýµéÀº µ¥ÀÌÅÍ Å¥ºê »ý¼º ½Ã °íºñ¿ëÀÌ ¿ä±¸µÇ´Â ´ÜÁ¡À» °¡Áö°í ÀÖ¾î È¿°úÀûÀÎ µ¥ÀÌÅÍ ±¸Á¶, ÁúÀÇ ¹æ¹ý ¹× ¾Ë°í¸®Áò¿¡ ´ëÇÑ ¿¬±¸°¡ ÇÊ¿äÇÏ´Ù. ½ºÆ®¸² Å¥ºê ±â¹ý¿¡¼´Â H-Å¥ºù ±â¹ýÀ» »ç¿ëÇÏ¿© Å¥º¸À̵带 ¼±ÅÃÇÏ°í, °è»êµÈ ¼¿µéÀ» Àαâ Æнº¿¡ Àִ ťº¸À̵åµé·Î ±¸¼ºµÈ H-Æ®¸®¿¡ ÀúÀåÇÑ´Ù. ±×·¯³ª ½ºÆ®¸² Å¥ºê ±â¹ý¿¡¼´Â H-Æ®¸®¿¡ µ¥ÀÌÅ͸¦ ºñ¼øÂ÷ÀûÀ¸·Î »ðÀÔÇϱ⠶§¹®¿¡ H-Å¥ºù ±â¹ýÀ» »ç¿ëÇÏ¿© ÁúÀǸ¦ ó¸®ÇÒ ¶§ Á¦ÇѼºÀ» °®°í ÀÖ´Ù. º» ³í¹®¿¡¼´Â µ¥ÀÌÅÍÀÇ Æ®¸® ±¸Á¶ÀÇ °¢ Ãþ¿¡ ´ëÇÑ À妽º¸¦ ±¸ÃàÇÏ¿© ½ºÆ®¸² µ¥ÀÌÅÍ¿¡ ´ëÇÑ ºü¸¥ »ðÀÔ ¿¬»êÀ» Áö¿øÇÏ´Â H*-tree ±¸Á¶¿Í, popular-path¿¡ Á¸ÀçÇÏÁö ¾Ê´Â Å¥º¸À̵带 »¡¸® °è»êÇÏ¿© ½ºÆ®¸² µ¥ÀÌÅÍ¿¡ ´ëÇÑ ºü¸¥ ¾Öµå Ȥ ÁúÀÇ ÀÀ´äÀ» Áö¿øÇÏ´Â H*-cubing ±â¹ýÀ» Á¦¾ÈÇÑ ´Ù. ¼º´ÉÆò°¡¸¦ ÅëÇÏ¿© Á¦¾ÈÇÑ H*-tree ±â¹ýÀº º¸´Ù ÀûÀº Å¥ºê ±¸Ãà ½Ã°£À» Áö¿øÇϸç, H*-cubing ±â¹ýÀÌ stream cube ±â¹ýº¸´Ù ºü¸¥ ¾Öµå Ȥ ÁúÀÇ ÀÀ´ä ½Ã°£À» ¼Ò¿äÇϸç, º¸´Ù ÀûÀº¸Þ¸ð¸®¸¦ »ç¿ëÇÔÀ» º¸¿©ÁØ´Ù. |
¿µ¹®³»¿ë (English Abstract) |
Data cube plays an important role in multi-dimensional, multi-level data analysis. Meeting on-line analysis requirements of data stream, several cube structures have been proposed for OLAP on data stream, such as stream cube, flowcube, S-cube. Since it is costly to construct data cube and execute ad-hoc OLAP queries, more research works should be done considering efficient data structure, query method and algorithms. Stream cube uses H-cubing to compute selected cuboids and store the computed cells in an H-tree, which form the cuboids along popular-path. However, the H-tree layoutis disorderly and H-cubing method relies too much on popular path.In this paper, first, we propose H*-tree, an improved data structure, which makes the retrieval operation in tree structure more efficient. Second, we propose an improved cubing method, H*-cubing, with respect to computing the cuboids that cannot be retrieved along popular-path when an ad-hoc OLAP query is executed. H*-tree construction and H*-cubing algorithms are given. Performance study turns out that during the construction step, H*-tree outperforms H-tree with a more desirable trade-off between time and memory usage, and H*-cubing is better adapted to ad-hoc OLAP querieswith respect to the factors such as time and memory space. |
Å°¿öµå(Keyword) |
OLAP
µ¥ÀÌÅÍ ½ºÆ®¸²
µ¥ÀÌÅÍ Å¥ºê
Ad-HocÁúÀÇ Ã³¸®
On-line Analytic Processing(OLAP)
Data Stream
Data Cube
Ad-Hoc Query Answering
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