Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Explore a technical talk that delves into the query optimization techniques used in Stardog, a commercial knowledge graph platform. Learn about the architecture of Stardog's query engine, with particular focus on graph statistics and cardinality estimations for graph patterns. Discover how Stardog implements SPARQL 1.1 graph query language and manages RDF graph data, while leveraging fundamental aspects of relational query optimization such as algebraic expression rewriting and cost-based optimization. Understand the unique challenges faced by the query optimizer due to the absence of rigid schema constraints, and gain insights into the reliability of cardinality estimations for different graph patterns. The speaker, Pavel Klinov, who has led Stardog's query engine team since 2011, shares his extensive experience in developing the system from a simple heuristic optimizer to a sophisticated cost-based optimizer, drawing from his background in probabilistic logic reasoning algorithms.