5 citations · 7 across the 4 of their papers we have counts for
6 papers
A Novel Framework Using Deep Reinforcement Learning for Join Order Selection
Chang Liu, Amin Kamali, Verena Kantere +2
Join order selection is a sub-field of query optimization that aims to find the optimal join order for an SQL query with the minimum cost. The challenge lies in the exponentially g…
LearnedWMP: Workload Memory Prediction Using Distribution of Query Templates
Shaikh Quader, Andres Jaramillo, Sumona Mukhopadhyay +5
In a modern DBMS, working memory is frequently the limiting factor when processing in-memory analytic query operations such as joins, sorting, and aggregation. Existing resource es…
Robust Plan Evaluation based on Approximate Probabilistic Machine Learning
Amin Kamali, Verena Kantere, Calisto Zuzarte +1
Query optimizers in RDBMSs search for execution plans expected to be optimal for given queries. They use parameter estimates, often inaccurate, and make assumptions that may not ho…
Guided Automated Learning for query workload re-Optimization
Guilherme Damasio, Vincent Corvinelli, Parke Godfrey +4
Query optimization is a hallmark of database systems enabling complex SQL queries of today's applications to be run efficiently. The query optimizer often fails to find the best pl…
OptImatch: Semantic Web System with Knowledge Base for Query Performance Problem Determination
Guilherme Damasio, Piotr Mierzejewski, Jaroslaw Szlichta +1
Database query performance problem determination is often performed by analyzing query execution plans (QEPs) in addition to other performance data. As the query workloads that org…
Processing Analytical Workloads Incrementally
Priyank Gupta, Nick Koudas, Europa Shang +2
Analysis of large data collections using popular machine learning and statistical algorithms has been a topic of increasing research interest. A typical analysis workload consists…