This paper presents MLOS (ML Optimized Systems), a flexible framework that bridges the
gap between benchmarking, experimentation, and optimization of software systems. It …

Many index advisors have recently been proposed to build indexes automatically to improve
query performance. However, they mainly consider performance improvement in static …

We propose cloud oracles, an alternative to machine learning for online optimization of
cloud configurations. Our cloud oracle approach guarantees complete accuracy and …

The exponential growth of data in the Cloud has highlighted the need for more efficient data
processing. In-Memory Computing frameworks (eg, Spark) offer improved efficiency for large …

Cloud computing has emerged as a dominant paradigm, where a colossal scale serves as
the claim to fame. Scheduling exists as a key component of cloud computing, and small …

Query Optimizer sind ein wichtiger Teil eines DBMS. Die Aufgabe, aus einer Anfrage einen
Ausführungsplan zu erstellen, ist sehr komplex. Reinforcement Learning (RL) zeigt gute …