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2006
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Extending RDBMSs To Support Sparse Datasets Using An Interpreted Attribute Storage Format

12 years 1 months ago
Extending RDBMSs To Support Sparse Datasets Using An Interpreted Attribute Storage Format
"Sparse" data, in which relations have many attributes that are null for most tuples, presents a challenge for relational database management systems. If one uses the normal "horizontal" schema to store such data sets in any of the three leading commercial RDBMS, the result is tables that occupy vast amounts of storage, most of which is devoted to nulls. If one attempts to avoid this storage blowup by using a "vertical" schema, the storage utilization is indeed better, but query performance is orders of magnitude slower for certain classes of queries. In this paper, we argue that the proper way to handle sparse data is not to use a vertical schema, but rather to extend the RDBMS tuple storage format to allow the representation of sparse attributes as interpreted fields. The addition of interpreted storage allows for efficient and transparent querying of sparse data, uniform access to all attributes, and schema scalability. We show, through an implementati...
Jennifer L. Beckmann, Alan Halverson, Rajasekar Kr
Added 01 Nov 2009
Updated 01 Nov 2009
Type Conference
Year 2006
Where ICDE
Authors Jennifer L. Beckmann, Alan Halverson, Rajasekar Krishnamurthy, Jeffrey F. Naughton
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