22 citations · 23 across the 4 of their papers we have counts for
4 papers
Combining Aggregation and Sampling (Nearly) Optimally for Approximate Query Processing
Xi Liang, Stavros Sintos, Zechao Shang +1
Sample-based approximate query processing (AQP) suffers from many pitfalls such as the inability to answer very selective queries and unreliable confidence intervals when sample si…
CIAO: An Optimization Framework for Client-Assisted Data Loading
Cong Ding, Dixin Tang, Xi Liang +2
Data loading has been one of the most common performance bottlenecks for many big data applications, especially when they are running on inefficient human-readable formats, such as…
Fast and Reliable Missing Data Contingency Analysis with Predicate-Constraints
Xi Liang, Zechao Shang, Aaron J. Elmore +2
Today, data analysts largely rely on intuition to determine whether missing or withheld rows of a dataset significantly affect their analyses. We propose a framework that can produ…
Opportunistic View Materialization with Deep Reinforcement Learning
Xi Liang, Aaron J. Elmore, Sanjay Krishnan
Carefully selected materialized views can greatly improve the performance of OLAP workloads. We study using deep reinforcement learning to learn adaptive view materialization and e…