Storage Optimization for Large Multidimensional Datasets
Sachin More and Alok Choudhary
Abstract
Large multidimensional datasets are found in diverse application areas like
data warehousing, satellite data processing and high energy physics.
Due to the enormous size of the data to be stored, tertiary devices are the
only cost-effective storage option. Due to the sequential access interface
provided by these devices, storage pattern optimization becomes important to
avoid high latency and attain streaming data bandwidth during query processing.
This paper examines issues involved in determining efficient storage patterns
for large multidimensional datasets in a database environment. We propose
and evaluate a heuristic-based online algorithm for tertiary storage management
under limited secondary storage assumption.