Self-tuning is a feature of autonomic databases that includes the problem of automatic
schema design. It aims at providing an optimized schema that increases the overall …

Whether the goal is performance prediction, or insights into the relationships between
algorithm performance and instance characteristics, a comprehensive set of meta-data from …

The suitability of an optimisation algorithm selected from within an algorithm portfolio
depends upon the features of the particular instance to be solved. Understanding the …

Datalog has been applied to several use cases that require very high performance on large
rulesets and factsets. It is common to create indexes for relations to improve search …

Materialized views and indexes are physical structures for accelerating data access that are
casually used in data warehouses. However, these data structures generate some …

Index tuning plays a crucial role in facilitating the efficiency of data retrieval within database
systems, which adjusts index settings to optimize the database performance. Recently, with …

This paper proposes a new methodology to determine the relative performance of
optimization algorithms across various classes of instances. Rather than reporting …

This paper demonstrates how evolutionary computation can be used to acquire difficult to
solve combinatorial problem instances. As a result of this technique, the corresponding …

The queries defined on data warehouses are complex and use several join operations that
induce an expensive computational cost. This cost becomes even more prohibitive when …

Challenges for self-driving database systems, which tune their physical design and
configuration autonomously, are manifold: Such systems have to anticipate future …