Online analytical processing (OLAP) is a core functionality in database systems. The
performance of OLAP is crucial to make online decisions in many applications. However, it is …

Query optimizers depend on selectivity estimates of query predicates to produce a good
execution plan. When a query contains multiple predicates, today's optimizers use a variety …

Estimating selectivities remains a critical task in query processing. Optimizers rely on the
accuracy of selectivities when generating execution plans and, in approximate query …

Database systems heavily rely upon cardinality estimates for finding efficient execution
plans, and estimation errors can easily affect query execution times by large factors. One …

Background. For some years now, Machine Learning (ML) has been applied to the
cardinality estimation problem [8, 12, 32, 33]. In general, ML means arbitrary function …

The exponential growth of data generated by the Internet of Things presents significant
challenges for data communication, storage, and analytics. Consequently, organizations …

An emerging class of data systems partition their data and precompute approximate
summaries (ie, sketches and samples) for each segment to reduce query costs. They can …

While estimating the result size of a group-by operation on a base table is hard on its own,
the presence of selections makes this problem increasingly difficult to solve. We show that …

OLAP is a core functionality in database systems and the performance is crucial to enable
on-time decisions. However, OLAP queries are rather time consuming, especially on large …

Query with aggregates is one of the most important classes of ad-hoc queries. Since query
response time is critical in many scenarios, small errors are usually tolerable for query …