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LMFAO: An Engine for Batches of Group-By Aggregates
August 19, 2020 Β· Declared Dead Β· π Proceedings of the VLDB Endowment
"No code URL or promise found in abstract"
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Authors
Maximilian Schleich, Dan Olteanu
arXiv ID
2008.08657
Category
cs.DB: Databases
Citations
19
Venue
Proceedings of the VLDB Endowment
Last Checked
5 months ago
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.
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