NDLI: Building large ROLAP data cubes in parallel

Content Provider	IEEE Xplore Digital Library
Author	Ying Chen Dehne, F. Eavis, T. Rau-Chaplin, A.
Copyright Year	2004
Description	Author affiliation: Dalhousie Univ., Halifax, NS, Canada (Ying Chen)
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. However, as the size of data warehouses grows, the time it takes to perform this pre-computation becomes a significant performance bottleneck. This work presents a fast parallel method for generating ROLAP data cubes on a shared-nothing multiprocessor based on a novel optimized data partitioning technique. Since no shared disk is required, this method can be applied on highly scalable processor clusters consisting of standard PCs with local disks, connected via a data switch. The approach taken, which uses a ROLAP representation of the data cube, is well suited to large data warehouses on high dimensional data, and supports the generation of both fully materialized and partially materialized cubes. In comparison with previous approaches, our new method does significantly improve the scalability with respect to both, the number of processors and the I/O bandwidth (number of parallel disks). We have implemented our new parallel shared-nothing data cube generation method and evaluated it on a PC cluster, exploring relative speedup, scaleup, sizeup, output sizes and data skew. For a fact table with 16 million rows and 8 attributes, our parallel data cube generation method achieves close to optimal speedup for as many as 32 processors, generating a full data cube in under 7 minutes. For a fact table with 256 million rows and 8 attributes, our parallel method achieves optimal speedup for 32 processors, generating a full data cube consisting of /spl ap/7 billion rows (200 Gigabytes) in under 88 minutes.
Sponsorship	Oracle Portugal
Starting Page	367
Ending Page	377
File Size	333843
Page Count	11
File Format	PDF
ISBN	0769521681
ISSN	10988068
DOI	10.1109/IDEAS.2004.1319810
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-07-09
Publisher Place	Portugal
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data warehouses Switches Delay Instruments Acceleration Data mining Optimization methods Personal communication networks Scalability Bandwidth
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in