Share the Tensor Tea: How Databases can Leverage the Machine Learning Ecosystem

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Abstract

In this demo paper we present Tensor Query Processor (TQP): a full query processor built on top of the tensor abstraction. TQP automatically compiles relational operators into tensor programs. By leveraging tensor runtimes such as PyTorch, TQP is able to seamlessly: (1) integrate with ML tools (e.g., Pandas for data ingestion, Tensorboard for visualization); (2) target different hardware (e.g., CPU, GPU) and software (e.g., browser) backends; and (3) end-to-end accelerate queries containing both relational and ML operators. TQP is generic enough to support the TPC-H benchmark, and it provides performance that is comparable to, and often better than, that of specialized CPU and GPU query processors.