35 citations · 70 across the 7 of their papers we have counts for
11 papers · 1 filter
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…
Maintaining Triangle Queries under Updates
Ahmet Kara, Milos Nikolic, Hung Q. Ngo +2
We consider the problem of incrementally maintaining the triangle queries with arbitrary free variables under single-tuple updates to the input relations. We introduce an approach…
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…
Counting Triangles under Updates in Worst-Case Optimal Time
Ahmet Kara, Hung Q. Ngo, Milos Nikolic +2
We consider the problem of incrementally maintaining the triangle count query under single-tuple updates to the input relations. We introduce an approach that exhibits a space-time…