Cardinality estimation (CardEst) plays a significant role in generating high-quality query
plans for a query optimizer in DBMS. In the last decade, an increasing number of advanced …

Query optimizers rely on accurate cardinality estimation (CardEst) to produce good
execution plans. The core problem of CardEst is how to model the rich joint distribution of …

Cardinality estimation is a fundamental problem in database systems. To capture the rich
joint data distributions of a relational table, most of the existing work either uses data as …

Data has been growing at an unprecedented rate in the past two decades. As a result,
systems that store, process, and analyze data have become mission-critical. Crucial to the …

Normalizing flows model a complex target distribution in terms of a bijective transform
operating on a simple base distribution. As such, they enable tractable computation of a …

The past few years have seen the growth of deep reinforcement learning (RL) as a new and
powerful optimization technique. Similar to deep supervised learning, deep RL has …

As data distribution is non-uniform and attribute correlations vary in strength, challenges are
encountered when using learning-based cardinality estimation methods in database query …

US20230100213A1 - System and method for efficient estimation of cumulative distribution
function - Google Patents US20230100213A1 - System and method for efficient estimation …