  The containment rate of query Q1 in query Q2 over database D is the
percentage of Q1's result tuples over D that are also in Q2's result over D. We
directly estimate containment rates between pairs of queries over a specific
database. For this, we use a specialized deep learning scheme, CRN, which is
tailored to representing pairs of SQL queries. Result-cardinality estimation is
a core component of query optimization. We describe a novel approach for
estimating queries result-cardinalities using estimated containment rates among
queries. This containment rate estimation may rely on CRN or embed, unchanged,
known cardinality estimation methods. Experimentally, our novel approach for
estimating cardinalities, using containment rates between queries, on a
challenging real-world database, realizes significant improvements to state of
the art cardinality estimation methods.
