Physical and virtual partitioning in OLAP database clusters

On-line analytical processing (OLAP) applications require high performance database support to achieve good response time (crucial for decision making). Database clusters provide a cost-effective alternative to parallel database systems. For OLAP applications, that typically use heavy weight queries...

Full description

Saved in:
Bibliographic Details
Main Authors: Furtado, C., Lima, A.A.B., Pacitti, E., Valduriez, P., Mattoso, M.
Format: Conference Proceeding
Language:English
Subjects:
Availability
Control systems
Database systems
Decision making
Delay
Hardware
Middleware
Parallel processing
Performance analysis
Query processing
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:On-line analytical processing (OLAP) applications require high performance database support to achieve good response time (crucial for decision making). Database clusters provide a cost-effective alternative to parallel database systems. For OLAP applications, that typically use heavy weight queries, intra-query parallelism yields better performance as it reduces the execution time of individual queries. Intra-query parallelism is based on processing the same query on different subsets of the query table. Combining physical and virtual partitioning to define table subsets provides flexibility in intra-query parallelism while optimizing disk space usage and data availability. Experiments with our partitioning technique using TPC-H benchmark queries on a 32-dual node cluster gave linear and super-linear speedup, thereby reducing significantly the time of typical OLAP heavy weight queries.
ISSN:1550-6533
2643-3001
DOI:10.1109/CAHPC.2005.32