{"id":13188,"date":"2021-12-07T20:31:53","date_gmt":"2021-12-08T01:31:53","guid":{"rendered":"https:\/\/carleton.ca\/scs\/?page_id=13188"},"modified":"2026-06-02T14:59:24","modified_gmt":"2026-06-02T18:59:24","slug":"tr-07-02-parallel-rolap-data-cubes-performance-comparison-and-analysis","status":"publish","type":"page","link":"https:\/\/carleton.ca\/scs\/research\/scs-technical-reports\/technical-reports-2007\/tr-07-02-parallel-rolap-data-cubes-performance-comparison-and-analysis\/","title":{"rendered":"TR-07-02: Parallel ROLAP Data Cubes Performance Comparison and Analysis"},"content":{"rendered":"\n
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\n TR-07-02: Parallel ROLAP Data Cubes Performance Comparison and Analysis\n <\/h1>\n \n \n <\/header>\n\n <\/div>\n\n <\/div>\n\n <\/div>\n<\/section>\n\n

Carleton University
\nTechnical Report<\/a> TR-07-02
\nJanuary 26, 2007<\/p>\n\n\n\n

Parallel ROLAP Data Cubes Performance Comparison and Analysis<\/h2>\n\n\n\n
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Wei Shi, Qi Deng, Boyong Liang<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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Abstract<\/h3>\n

The pre-computation of data cubes is critical to improving the response time of On-Line Analytical Processing (OLAP) systems and can be instrumental in accelerating data mining tasks in large data warehouses.<\/p>\n

In order to meet the need for improved performance created by growing data sizes, parallel solutions for generating the data cube are becoming increasingly important. This Project Report reports the test result of building and querying data cube between large parallel database: DB2 and Panda system. We have investigated two large parallel databases: DB2 and Oracle 9i.<\/p>\n

Under the default setup of DB2 and Panda system, we tested the performance of building a cube in both Panda system and DB2 and also some data cube queries. We mainly studied the Partition difference between Panda system and DB2, then analyze the reason of the test result after the serious study of these two systems.<\/p>\n

TR-07-02.pdf<\/a><\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

Carleton University Technical Report TR-07-02 January 26, 2007 Parallel ROLAP Data Cubes Performance Comparison and Analysis Wei Shi, Qi Deng, Boyong Liang Abstract The pre-computation of data cubes is critical to improving the response time of On-Line Analytical Processing (OLAP) systems and can be instrumental in accelerating data mining tasks in large data warehouses. In […]<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":12385,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"_cu_dining_location_slug":"","footnotes":"","_links_to":"","_links_to_target":""},"cu_page_type":[],"class_list":["post-13188","page","type-page","status-publish","hentry"],"acf":{"cu_post_thumbnail":false},"_links":{"self":[{"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/pages\/13188","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/comments?post=13188"}],"version-history":[{"count":1,"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/pages\/13188\/revisions"}],"predecessor-version":[{"id":13189,"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/pages\/13188\/revisions\/13189"}],"up":[{"embeddable":true,"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/pages\/12385"}],"wp:attachment":[{"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/media?parent=13188"}],"wp:term":[{"taxonomy":"cu_page_type","embeddable":true,"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/cu_page_type?post=13188"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}