Data generation for application-specific benchmarking

Abstract

The Transaction Processing Council (TPC) has played a pivotal role in the database industry's growth over the last twenty-five years. However, its handful of domain-specific benchmarks are increasingly irrelevant to the multitude of data-centric applications, and its top-down process is slow. This mismatch calls for a paradigm shift to a bottom-up community effort to develop tools for application-specific benchmarking. Such a development program would center around techniques for synthetically scaling (up or down) an empirical dataset. This engineering effort in turn requires the development of a database theory on attribute value correlation.