Broneske, DavidMeister, AndreasSaake, GunterMitschang, BernhardNicklas, DanielaLeymann, FrankSchöning, HaraldHerschel, MelanieTeubner, JensHärder, TheoKopp, OliverWieland, Matthias2017-06-202017-06-202017978-3-88579-659-6The ever-increasing demand for performance on huge data sets forces database systems to tweak the last bit of performance out of their operators. Especially query compiled plans allow for several tuning opportunities that can be applied depending on the query plan and the underlying data. Apart from classical query optimization opportunities, it includes to tune the code using code optimizations for processor specifics, e.g., using Single Instruction Multiple Data processing or predication. In this paper, we examine code optimizations that can be applied for compiled scan pipelines that include aggregations, evaluate impact factors that influence the performance of the scan pipelines, and derive guidelines that a query compiler should implement to choose the best variant for a given query plan and workload.enMulti-Column Selection PredicatesScansHardware SensitivitySIMDPredicationText/Conference Paper1617-5468