@article{SchoenbergerScherzingerMauerer, author = {Sch{\"o}nberger, Manuel and Scherzinger, Stefanie and Mauerer, Wolfgang}, title = {Ready to Leap (by Co-Design)? Join Order Optimisation on Quantum Hardware}, series = {Proceedings of the ACM on Management of Data, PACMMOD}, volume = {1}, journal = {Proceedings of the ACM on Management of Data, PACMMOD}, number = {1}, publisher = {ACM}, address = {New York, NY,}, doi = {10.1145/3588946}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-56634}, pages = {1 -- 27}, abstract = {The prospect of achieving computational speedups by exploiting quantum phenomena makes the use of quantum processing units (QPUs) attractive for many algorithmic database problems. Query optimisation, which concerns problems that typically need to explore large search spaces, seems like an ideal match for the known quantum algorithms. We present the first quantum implementation of join ordering, which is one of the most investigated and fundamental query optimisation problems, based on a reformulation to quadratic binary unconstrained optimisation problems. We empirically characterise our method on two state-of-the-art approaches (gate-based quantum computing and quantum annealing), and identify speed-ups compared to the best know classical join ordering approaches for input sizes that can be processed with current quantum annealers. However, we also confirm that limits of early-stage technology are quickly reached. Current QPUs are classified as noisy, intermediate scale quantum computers (NISQ), and are restricted by a variety of limitations that reduce their capabilities as compared to ideal future quantum computers, which prevents us from scaling up problem dimensions and reaching practical utility. To overcome these challenges, our formulation accounts for specific QPU properties and limitations, and allows us to trade between achievable solution quality and possible problem size. In contrast to all prior work on quantum computing for query optimisation and database-related challenges, we go beyond currently available QPUs, and explicitly target the scalability limitations: Using insights gained from numerical simulations and our experimental analysis, we identify key criteria for co-designing QPUs to improve their usefulness for join ordering, and show how even relatively minor physical architectural improvements can result in substantial enhancements. Finally, we outline a path towards practical utility of custom-designed QPUs.}, language = {en} } @inproceedings{MauererScherzinger, author = {Mauerer, Wolfgang and Scherzinger, Stefanie}, title = {Nullius in Verba: Reproducibility for Database Systems Research, Revisited}, series = {2021 IEEE 37th International Conference on Data Engineering (ICDE 2021): 19-22 April 2021, Chania, Greece}, booktitle = {2021 IEEE 37th International Conference on Data Engineering (ICDE 2021): 19-22 April 2021, Chania, Greece}, editor = {Ailamaki, Anastasia}, publisher = {IEEE}, address = {Piscataway, NJ}, isbn = {978-1-7281-9184-3}, doi = {10.1109/ICDE51399.2021.00270}, pages = {2377 -- 2380}, abstract = {Over the last decade, reproducibility of experimental results has been a prime focus in database systems research, and many high-profile conferences award results that can be independently verified. Since database systems research involves complex software stacks that non-trivially interact with hardware, sharing experimental setups is anything but trivial: Building a working reproduction package goes far beyond providing a DOI to some repository hosting data, code, and setup instructions.This tutorial revisits reproducible engineering in the face of state-of-the-art technology, and best practices gained in other computer science research communities. In particular, in the hands-on part, we demonstrate how to package entire system software stacks for dissemination. To ascertain long-term reproducibility over decades (or ideally, forever), we discuss why relying on open source technologies massively employed in industry has essential advantages over approaches crafted specifically for research. Supplementary material shows how version control systems that allow for non-linearly rewriting recorded history can document the structured genesis behind experimental setups in a way that is substantially easier to understand, without involvement of the original authors, compared to detour-ridden, strictly historic evolution.}, language = {en} }