To increase utilization, datacenter schedulers often overcommit resources where the sum of
resources allocated to the tasks on a machine exceeds its physical capacity. Setting the right …

Cloud databases have been widely accepted and deployed due to their unique advantages,
such as high elasticity, high availability, and low cost. Many new techniques, such as …

Python has become overwhelmingly popular for ad-hoc data analysis, and Pandas
dataframes have quickly become the de facto standard API for data science. However …

In this tutorial, we review advances made recently in a decades-old problem, namely query
optimization. Along with the traditional optimization techniques many of which are still being …

Storage, as a core function and fundamental component of computers, provides services for
saving and reading digital data. The increasing complexity of data operations and storage …

Modern cloud services aim to find the middle ground between quality of service and
operational cost efficiency by allocating resources if and only if these resources are needed …

Microsoft aims to increase the efficiency of Azure SQL DB by maximizing the number of
databases that can be hosted in a cluster. However, resource contention among customers …

The goal of this tutorial is to educate the audience about the state of the art in ML for cloud
data systems, both in research and in practice. The tutorial is divided in two parts: the …

We present an efficient, parametric modeling framework for predictive resource allocations,
focusing on the amount of computational resources, that can optimize for a range of price …

In Complex Event Recognition (CER), applications express business rules in the form of
patterns and deploy them in a CER Engine which seeks the occurrence of such patterns on …