Tensor Processing Units are specialized hardware devices built to train and apply Machine Learning models at high speed through high-bandwidth memory and massive instruction parallelism. In this short paper, we investigate how relational operations can be translated to those devices. We present mapping of relational operators to TPU-supported TensorFlow operations and experimental results comparing with GPU and CPU implementations. Results show that while raw speeds are enticing, TPUs are unlikely to improve relational query processing for now due to a variety of issues.

Performance benchmarking is one of the most commonly used methods for comparing different systems or algorithms, both in scientific literature and in industrial publications. While performance measurements might seem objective on the surface, there are many different ways to influence benchmark results to favor one system over the other, either by accident or on purpose. In this paper, we perform a study of the common pitfalls in DBMS performance comparisons, and give advice on how they can be spotted and avoided so a fair performance comparison between systems can be made. We illustrate the common pitfalls with a series of mock benchmarks, which show large differences in performance where none should be present.

No abstract

No abstract

User-defined functions (UDFs) are an integral part of performing in-database analytics. Executing data analysis inside a database provides significant improvements over traditional methods, such as close-to-the-data execution, low conversion overhead and automatic parallelization. However, UDFs have poor support for debugging. Since they are executed from within the database process, traditional debugging tools such as Integrated Development Environments (IDEs) and Read-Eval-Print Loops (REPLs) cannot be used during development. As a result, writing functional UDFs is challenging. In this paper, we present an extension to the open-source database system MonetDB that allows developers to debug their UDFs using modern debugging techniques.