DocumentCode :
3351481
Title :
Using tiling to scale parallel data cube construction
Author :
Jin, Ruoming ; Vaidyanathan, Karthik ; Yang, Ge ; Agrawal, Gagan
Author_Institution :
Dept. of Comput. Sci. & Eng., Ohio State Univ., Columbus, OH, USA
fYear :
2004
fDate :
15-18 Aug. 2004
Firstpage :
365
Abstract :
Data cube construction is a commonly used operation in data warehouses. Because of the volume of data that is stored and analyzed in a data warehouse and the amount of computation involved in data cube construction, it is natural to consider parallel machines for this operation. Also, for both sequential and parallel data cube construction, effectively using the main memory is an important challenge. In our prior work, we have developed parallel algorithms for this problem. We show how sequential and parallel data cube construction algorithms can be further scaled to handle larger problems, when the memory requirements could be a constraint. This is done by tiling the input and output arrays on each node. We address the challenges in using tiling while still maintaining the other desired properties of a data cube construction algorithm, which are, using minimal parents, and achieving maximal cache and memory reuse. We present a parallel algorithm that combines tiling with interprocessor communication. Our experimental results show the following. First, tiling helps in scaling data cube construction in both sequential and parallel environments. Second, choosing tiling parameters as per our theoretical results does result in better performance.
Keywords :
cache storage; data warehouses; multiprocessor interconnection networks; parallel algorithms; parallel machines; cache storage; data warehouses; interprocessor communication; memory reuse; parallel algorithm; parallel data cube construction; parallel machines; sequential data cube construction; Aggregates; Companies; Computer science; Concurrent computing; Data analysis; Data warehouses; Memory management; Parallel algorithms; Performance analysis; Tiles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel Processing, 2004. ICPP 2004. International Conference on
ISSN :
0190-3918
Print_ISBN :
0-7695-2197-5
Type :
conf
DOI :
10.1109/ICPP.2004.1327944
Filename :
1327944
Link To Document :
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