VLDB2020
LMFAO: An Engine for Batches of Group-By Aggregates
Maximilian Schleich, Dan Olteanu
20 citations
Abstract
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.