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GeoBase: Indexing NetCDF Files for Large-Scale Data Analysis
Abstract
Data-rich scientific disciplines increasingly need end-to-end systems that ingest large volumes of data, make it quickly available, and enable processing and exploratory data analysis in a scalable manner. Key-value stores have attracted attention, since they offer highly available data storage, but must be engineered further for end-to-end support. In particular, key-value stores have minimal support for scientific data that resides in self-describing, array-based binary file formats and do not natively support scientific queries on multi-dimensional data. In this chapter, the authors describe GeoBase, which enables querying over scientific data by improving end-to-end support through two integrated, native components: a linearization-based index to enable rich scientific querying on multi-dimensional data and a plugin that interfaces key-value stores with array-based binary file formats. Experiments show that this end-to-end key-value store retains the features of availability and scalability of key-value stores and substantially improves the performance of scientific queries.
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