{"id":11724,"date":"2021-08-17T00:00:12","date_gmt":"2021-08-17T07:00:12","guid":{"rendered":"https:\/\/www.couchbase.com\/blog\/?p=11724"},"modified":"2025-06-13T17:32:19","modified_gmt":"2025-06-14T00:32:19","slug":"level-up-your-data-analytics-with-the-new-cube-functionality-in-couchbase-analytics","status":"publish","type":"post","link":"https:\/\/www.couchbase.com\/blog\/ko\/level-up-your-data-analytics-with-the-new-cube-functionality-in-couchbase-analytics\/","title":{"rendered":"\uce74\uc6b0\uce58\ubca0\uc774\uc2a4 \uc560\ub110\ub9ac\ud2f1\uc2a4\uc758 \uc0c8\ub85c\uc6b4 CUBE \uae30\ub2a5\uc73c\ub85c \ub370\uc774\ud130 \ubd84\uc11d \uc218\uc900 \ud5a5\uc0c1"},"content":{"rendered":"

Couchbase\uc758 \ub370\uc774\ud130 \ubd84\uc11d \uae30\ub2a5\uc774 \ub354\uc6b1 \uac15\ub825\ud574\uc84c\uc2b5\ub2c8\ub2e4.<\/strong> 7.0 \ub9b4\ub9ac\uc2a4\uc640 \ud568\uaed8.<\/p>\n

\uc774\uc81c \uce74\uc6b0\uce58\ubca0\uc774\uc2a4 \uc560\ub110\ub9ac\ud2f1\uc2a4\uc758 \uc77c\ubd80\ub85c \uc81c\uacf5\ub418\ub294 \ub450 \uac00\uc9c0 \uac15\ub825\ud55c \uc0c8 \uae30\ub2a5\uc744 \ubc1c\ud45c\ud558\uac8c \ub418\uc5b4 \uae30\uc069\ub2c8\ub2e4: 1) CUBE<\/code> \uae30\ub2a5, 2) \ub864\uc5c5<\/code> \uc9d1\uacc4\ub294 \uc5ec\ub7ec \ubb38\uc11c \uc18d\uc131\uc5d0\uc11c \ub370\uc774\ud130\ub97c \uc9d1\uacc4\ud558\ub294 \ub370 \ub3c4\uc6c0\uc774 \ub429\ub2c8\ub2e4.<\/p>\n

\ucd94\uac00 CUBE<\/code> \ud655\uc7a5 \uae30\ub2a5\uc744 \uce74\uc6b0\uce58\ubca0\uc774\uc2a4 \uc560\ub110\ub9ac\ud2f1\uc2a4 \uc11c\ube44\uc2a4<\/a> \uc758 \uc77c\ubd80\uc785\ub2c8\ub2e4. \uce74\uc6b0\uce58\ubca0\uc774\uc2a4 \uc11c\ubc84 7.0 \ub9b4\ub9ac\uc988<\/a>. (\uc6b0\ub9ac\ub294 \ub2e4\ub8e8\uc5c8\uc2b5\ub2c8\ub2e4 \uc758 \ub864\uc5c5<\/code> \uae30\ub2a5<\/a> \uc9c0\ub09c \uc8fc \uae30\uc0ac\uc5d0\uc11c)<\/p>\n

\uc0c8\ub85c\uc6b4 CUBE \uae30\ub2a5\uc758 \uc6cc\ud06c\uc2a4\ub8e8 \uc608\uc2dc<\/h2>\n

SQL\uc5d0\uc11c\uc640 \ub9c8\ucc2c\uac00\uc9c0\ub85c, CUBE \uc9d1\uacc4 \uae30\ub2a5\uc740 GROUP BY \uc808<\/a>.<\/p>\n

CUBE \ud655\uc7a5 \ud558\uc704 \uc808\uc744 \uc0ac\uc6a9\ud558\uba74 GROUP BY \uc808\uc5d0 \uc9c0\uc815\ub41c \uadf8\ub8f9\ud654 \uc5f4\uc758 \ubaa8\ub4e0 \uc870\ud569\uc5d0 \ub300\ud55c \uc18c\uacc4\ub97c \uc0dd\uc131\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ud2b9\ud788, \uacb0\uacfc\uc5d0\ub294 \uc77c\ubc18\uc801\uc778 \ucd1d\ud569\uacc4 \ud589\uacfc \ud568\uaed8 \ub370\uc774\ud130\uc758 \uc18c\uacc4\ub97c \ub098\ud0c0\ub0b4\ub294 \ucd94\uac00 \ud589(\uc77c\ubc18\uc801\uc73c\ub85c \ucd08\uc9d1\uacc4 \ud589\uc774\ub77c\uace0 \ud568)\uc774 \ud3ec\ud568\ub429\ub2c8\ub2e4.<\/p>\n

\uc608\ub97c \ub4e4\uc5b4 \uc804\uc790\uc0c1\uac70\ub798 \uc815\ubcf4\ub97c \ucd94\uc801\ud558\ub294 \uc8fc\ubb38\uc774\ub77c\ub294 \uc0d8\ud50c \ubd84\uc11d \uceec\ub809\uc158\uc774 \uc788\ub2e4\uace0 \uac00\uc815\ud574 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4. \uac00\uc7a5 \ucd94\uc801\ud558\ub824\ub294 \uc8fc\uc694 \ub370\uc774\ud130 \uc694\uc18c\ub294 \uc9c0\uc5ed\/\uc8fc, \uc8fc\ubb38 \ub0a0\uc9dc, \uc218\ub7c9 \ubc0f \uac00\uaca9\uc785\ub2c8\ub2e4. Sales(\ub9e4\ucd9c)\ub97c Sales = \uc218\ub7c9 * \uac00\uaca9\uc73c\ub85c \uacc4\uc0b0\ud55c\ub2e4\uace0 \uac00\uc815\ud574 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/p>\n

\uc544\ub798\ub294 \uc774 \uc608\uc81c\uc758 \uc774\ucee4\uba38\uc2a4 \ub370\uc774\ud130 \uc0d8\ud50c\uc785\ub2c8\ub2e4:<\/p>\n

 {\r\n    \"orderDate\": \"2020-11-30\",\r\n    \"region\": \"California\",\r\n    \"qty\": 5,\r\n    \"price\": 596.37\r\n  },\r\n  {\r\n    \"orderDate\": \"2020-05-08\",\r\n    \"region\": \"California\",\r\n    \"qty\": 3,\r\n    \"price\": 814.69\r\n  },\r\n  {\r\n    \"orderDate\": \"2020-03-17\",\r\n    \"region\": \"Connecticut\",\r\n    \"qty\": 2,\r\n    \"price\": 270.04\r\n  },\r\n  {\r\n    \"orderDate\": \"2020-03-11\",\r\n    \"region\": \"Colorado\",\r\n    \"qty\": 4,\r\n    \"price\": 795.73\r\n  }\r\n<\/pre>\n
<\/div>\n
\uc774\uc81c \ube44\uc988\ub2c8\uc2a4 \uc0ac\uc6a9\uc790\uac00 \uc804\uc790\uc0c1\uac70\ub798 \ub370\uc774\ud130\uc5d0\uc11c \ub2e4\uc74c \uc0ac\ud56d\uc744 \uc54c\uace0 \uc2f6\uc5b4\ud55c\ub2e4\uace0 \uac00\uc815\ud574 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4:<\/p>\n
1) \uc9c0\uc5ed\ubcc4 \uc5f0\ub3c4\ubcc4 \ucd1d \ub9e4\ucd9c
\n2) \uc5f0\ub3c4\ubcc4 \ubaa8\ub4e0 \uc9c0\uc5ed\uc758 \ucd1d \ub9e4\ucd9c
\n3) \uc5f0\ub3c4\ubcc4 \uc9c0\uc5ed\ubcc4 \ucd1d \ub9e4\ucd9c
\n4) \ubaa8\ub4e0 \uc9c0\uc5ed \ubc0f \ubaa8\ub4e0 \uc5f0\ub3c4\uc758 \ucd1d \ub9e4\ucd9c<\/p>\n
CUBE \ud655\uc7a5 \ud504\ub85c\uadf8\ub7a8\uc740 \uc774\ub7ec\ud55c \uc9d1\uacc4 \uae30\ubc18 \ub370\uc774\ud130 \ubd84\uc11d \uc9c8\ubb38\uc5d0 \ub2f5\ud560 \uc218 \uc788\ub294 \uc88b\uc740 \uc0ac\uc6a9 \uc0ac\ub840\uc785\ub2c8\ub2e4. \ub370\uc774\ud130 \uc5d4\uc9c0\ub2c8\uc5b4\ub098 \ub370\uc774\ud130 \ubd84\uc11d\uac00\ub294 \ub2e8\uc21c\ud788 N1QL \ucffc\ub9ac<\/a> \ub294 Couchbase \uc560\ub110\ub9ac\ud2f1\uc2a4 \uc11c\ube44\uc2a4 \ub0b4\uc5d0\uc11c \uc544\ub798\uc640 \uac19\uc774 \ud45c\uc2dc\ub429\ub2c8\ub2e4.<\/p>\n
-- Generates four grouping sets:\r\n-- 1. All Region & All Years (Grand Total)\r\n-- 2. All Regions, Year\r\n-- 3. All Years, Region\r\n-- 4. Region, Year\r\nSELECT   IFNULL(region,\"All Regions\") Region,\r\n   IFNULL(year, \"All Years\") Year,\r\n                  ROUND(SUM(o.qty * o.price),0) Sales\r\nFROM      orders o\r\nLET           year = DATE_PART_STR(o.orderDate, \"year\"), \r\n                 region = o.region\r\nGROUP BY CUBE(region, year)\r\nORDER BY region, year\r\n<\/pre>\n
<\/div>\n
In the above N1QL query, we’ve used `year` and `region` as variables for convenience. As a result, `CUBE(region, year)` generates the following query results for our sample data:<\/p>\n
 {  \"Region\": \"All Regions\",\r\n    \"Year\": \"All Years\",\r\n    \"Sales\": 3372854458},\r\n  { \"Region\": \"All Regions\",\r\n    \"Year\": 2020,\r\n    \"Sales\": 3371122342},\r\n  {\r\n    \"Region\": \"All Regions\",\r\n    \"Year\": 2021,\r\n    \"Sales\": 1732116},\r\n  {\r\n    \"Year\": \"All Years\",\r\n    \"Region\": \"Alabama\",\r\n    \"Sales\": 66383297},  \r\n{ \"Year\": \"All Years\",\r\n    \"Region\": \"California\",\r\n    \"Sales\": 66108045},\r\n  { \"Region\": \"California\",\r\n    \"Year\": 2020,\r\n    \"Sales\": 66053233},\r\n...\r\n<\/pre>\n
<\/div>\n
\ucd9c\ub825\uc740 \uc0ac\uc6a9\uc790\uac00 \uc6d0\ub798 \ucc3e\uace0 \uc788\ub358 \uac83\uacfc \uc815\ud655\ud788 \uc77c\uce58\ud569\ub2c8\ub2e4:<\/p>\n
    \n
  1. At the top of the results, a grand total shows the total sales over all years and regions. In the query output, the `NULL` values in the country and region attributes are transformed to “All Years” and “All Regions” respectively to make the output more readable.<\/li>\n
  2. Then, you’ll see the result of another subtotal summarizing All Regions by each Year, e.g., 2020 and 2021, displaying the total sales. In these JSON fields, values in the `region` attribute are transformed from `NULL` to “All Regions”.<\/li>\n
  3. After that, we see another subtotal summary for “All Years” displaying the total sales for each region, e.g., Alabama & California. In these fields, values in the `region` attribute are transformed from `NULL` to “All Regions”.<\/li>\n
  4. \ub9c8\uc9c0\ub9c9\uc73c\ub85c \ucd9c\ub825\uc5d0\ub294 \uc5f0\ub3c4\ubcc4 \uac01 \uc9c0\uc5ed\uc5d0 \ub300\ud574 \ub864\uc5c5\ub41c \ucd1d \ub9e4\ucd9c\uc774 \ud45c\uc2dc\ub429\ub2c8\ub2e4. \uc774 \uc608\uc81c\uc5d0\uc11c\ub294 2020\ub144 \uce98\ub9ac\ud3ec\ub2c8\uc544\uc758 \ub9e4\ucd9c<\/li>\n<\/ol>\n
    <\/div>\n
    \uacb0\ub860<\/h2>\n
    \uce74\uc6b0\uce58\ubca0\uc774\uc2a4 \uc560\ub110\ub9ac\ud2f1\uc2a4\uc5d0\uc11c \uc0ac\uc6a9\ud560 \uc218 \uc788\ub294 \uac15\ub825\ud55c \ubd84\uc11d \ud45c\ud604\uc2dd\uc744 \ud655\uc7a5\ud558\ub294 \uc774 \uc0c8\ub85c\uc6b4 \uc9d1\uacc4 CUBE \uae30\ub2a5\uc5d0 \ub9ce\uc740 \uad00\uc2ec\uc744 \uac00\uc838\uc8fc\uc2dc\uae30 \ubc14\ub78d\ub2c8\ub2e4. \uc790\uc138\ud55c \ub0b4\uc6a9\uc740 \uc5ec\uae30\ub97c \ucc38\uc870\ud558\uc138\uc694, \ub97c \ud655\uc778\ud574\ubcf4\uc138\uc694. CUBE<\/code> \ubb38\uc11c<\/a>. \uc774 \uc0c8\ub85c\uc6b4 \uae30\ub2a5\uc774 \uae30\uc5c5\uc5d0\uc11c \ud5a5\ud6c4 \ub370\uc774\ud130 \ubd84\uc11d \ud504\ub85c\uc81d\ud2b8\uc5d0 \uc720\uc6a9\ud558\uac8c \uc0ac\uc6a9\ub418\uae30\ub97c \ubc14\ub78d\ub2c8\ub2e4.<\/p>\n
    \ub2e4\uc74c\uc744 \uae30\ub300\ud569\ub2c8\ub2e4. \uce74\uc6b0\uce58\ubca0\uc774\uc2a4 \ud3ec\ub7fc\uc5d0 \ub300\ud55c \uadc0\ud558\uc758 \ud53c\ub4dc\ubc31<\/a> - \uc5ec\ub7ec\ubd84\uc758 \uc758\uacac\uc744 \uc54c\ub824\uc8fc\uc138\uc694!<\/p>\n
    <\/div>\n
    \uce74\uc6b0\uce58\ubca0\uc774\uc2a4 \uc560\ub110\ub9ac\ud2f1\uc2a4 \uccb4\ud5d8\ud558\uae30 :
    \uc9c0\uae08 Couchbase \ub2e4\uc6b4\ub85c\ub4dc<\/a><\/strong><\/div>\n
    <\/div>\n
     <\/p>","protected":false},"excerpt":{"rendered":"
    Data analytics capabilities in Couchbase just got more robust with the 7.0 release. I’m excited to announce two new powerful capabilities now available as part of Couchbase Analytics: 1) the CUBE functionality, and 2) ROLLUP aggregation, both to help you […]<\/p>","protected":false},"author":58630,"featured_media":11726,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[2294,1816,1812],"tags":[2014,9237,2155,9354,1261,9353],"ppma_author":[8967],"class_list":["post-11724","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-analytics","category-couchbase-server","category-n1ql-query","tag-data-analysis","tag-data-analytics","tag-ecommerce","tag-group-by","tag-json","tag-super-aggregate-rows"],"acf":[],"yoast_head":"\nLevel Up Your Data Analytics with the New CUBE Functionality in Couchbase Analytics<\/title>\n<meta name=\"description\" content=\"Walk through this example of the new CUBE extension in Couchbase Analytics to learn how to generate super-aggregate rows as part of your data analysis.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.couchbase.com\/blog\/ko\/level-up-your-data-analytics-with-the-new-cube-functionality-in-couchbase-analytics\/\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Level Up Your Data Analytics with the New CUBE Functionality in Couchbase Analytics\" \/>\n<meta property=\"og:description\" content=\"Walk through this example of the new CUBE extension in Couchbase Analytics to learn how to generate super-aggregate rows as part of your data analysis.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.couchbase.com\/blog\/ko\/level-up-your-data-analytics-with-the-new-cube-functionality-in-couchbase-analytics\/\" \/>\n<meta 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