2020/08/19 by Schleich, Maximilian, Olteanu, Dan
#Databases (cs.DB) #FOS: Computer and information sciences
paper · doi:10.48550/arxiv.2008.08657
LMFAO is an in-memory optimization and execution engine for large batches of group-by aggregates over joins. Such database workloads capture the data-intensive computation of a variety of data science applications. We demonstrate LMFAO for three popular models: ridge linear regression with batch gradient descent, decision trees with CART, and clustering with Rk-means.