8 papers · 1 filter
Join Size Bounds using Lp-Norms on Degree Sequences
Mahmoud Abo Khamis, Vasileios Nakos, Dan Olteanu +1
Estimating the output size of a query is a fundamental yet longstanding problem in database query processing. Traditional cardinality estimators used by database systems can routin…
Optimizing Recursive Queries with Program Synthesis
Yisu Remy Wang, Mahmoud Abo Khamis, Hung Q. Ngo +2
Most work on query optimization has concentrated on loop-free queries. However, data science and machine learning workloads today typically involve recursive or iterative computati…
Learning Models over Relational Data: A Brief Tutorial
Maximilian Schleich, Dan Olteanu, Mahmoud Abo-Khamis +2
This tutorial overviews the state of the art in learning models over relational databases and makes the case for a first-principles approach that exploits recent developments in da…
A Layered Aggregate Engine for Analytics Workloads
Maximilian Schleich, Dan Olteanu, Mahmoud Abo Khamis +2
This paper introduces LMFAO (Layered Multiple Functional Aggregate Optimization), an in-memory optimization and execution engine for batches of aggregates over the input database.…
Functional Aggregate Queries with Additive Inequalities
Mahmoud Abo Khamis, Ryan R. Curtin, Benjamin Moseley +4
Motivated by fundamental applications in databases and relational machine learning, we formulate and study the problem of answering functional aggregate queries (FAQ) in which some…
AC/DC: In-Database Learning Thunderstruck
Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen +2
We report on the design and implementation of the AC/DC gradient descent solver for a class of optimization problems over normalized databases. AC/DC decomposes an optimization pro…