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Efficient organization and access of multi-dimensional datasets on tertiary storage systems

1995; Elsevier BV; Volume: 20; Issue: 2 Linguagem: Inglês

10.1016/0306-4379(95)98559-v

1873-6076

Lingpeng Chen, R. Drach, M. Keating, S. Louis, Doron Rotem, Arie Shoshani,

Data Management and Algorithms

This paper addresses the problem of urgently needed data management techniques for efficiently retrieving requested subsets of large datasets from mass storage devices. This problem is especially critical for scientific investigators who need ready access to the large volume of data generated by large-scale supercomputer simulations and physical experiments as well as the automated collection of observations by monitoring devices and satellites. This problem also negates the benefits of fast networks, because the time to access a subset from a large dataset stored on a mass storage system is much greater than the time to transmit that subset over a fast network. This paper focuses on very large spatial and temporal datasets generated by simulation of climate models, but the techniques described here are applicable to any large multidimensional grid data. The main requirement is to efficiently access relevant information contained within much larger datasets for analysis and interactive visualization. Although these problems are now becoming more widely recognized, the problem persists because the access speed of robotic storage devices continues to be the bottleneck. To address this problem, we have developed algorithms for partitioning the original datasets into “clusters” based on analysis of data access patterns and storage device characteristics. Further, we have designed enhancements to current storage server protocols to permit control over physical placement of data on storage devices. We describe in this paper the approach we have taken, the partitioning algorithms, and simulation and experimental results that show 1 to 2 orders of magnitude in access improvements for predicted query types. We further describe the design and implementation of improvements to a specific storage management system, UniTree, which are necessary to support the enhanced protocols. In addition, we describe the development of a partitioning workbench to help scientists select the preferred solutions.