Planning  Which data / data sets should be used?  Which workload / queries should be run?  Which hardware & software should be used?  Metrics: What to measure? How to measure?  Comparison: How to compare Matthias Boehm, Graz University of Technology, WS 2021/22 Presentation – Experimental Setting  Hardware Selection  Multiple nodes for distributed computation  Avoid too outdated HW (irrelevance)  results wrt parameters and environments  Examples: different data and workload characteristics, hardware Reproducibility and RDM 26 706.015 Introduction to Scientific Writing – 03 Experiments & Reproducibility

PVLDB 7(10) 2014  #15.6 Thomas Neumann: Efficiently Compiling Efficient Query Plans for Modern Hardware. Proc. VLDB Endow. 4(9) 2011 Paper Project Proposals 35 706.015 Introduction to Scientific Writing Sándor Héman, Niels Nes, Peter A. Boncz: Super-Scalar RAM-CPU Cache Compression. ICDE 2006  Modern Hardware  #17.1 Lasse Thostrup, Jan Skrzypczak, Matthias Jasny, Tobias Ziegler, Carsten Binnig: DFI: The