Solving business problems increasingly requires going beyond the limits of a single data
processing platform (platform for short), such as Hadoop or a DBMS. As a result …

Moving data analysis and processing to the cloud is no longer reserved for a few companies
with petabytes of data. Instead, the flexibility of on-demand resources is attracting an …

Cost-based optimization is widely known to suffer from a major weakness: administrators
spend a significant amount of time to tune the associated cost models. This problem only …

There is an urgent need for unifying data analytics as more and more application tasks
become more complex: Nowadays, it is normal to see tasks performing data preparation …

In this paper, we present Justice, a fair-share deadline-aware resource allocator for big data
cluster managers. In resource constrained environments, where resource contention …

Heterogeneous Computing Architectures: Challenges and Vision provides an updated
vision of the state-of-the-art of heterogeneous computing systems, covering all the aspects …

Data analytics are moving beyond the limits of a single platform. In this paper, we present
the cost-based optimizer of Rheem, an open-source cross-platform system that copes with …

There is a zoo of data processing platforms which help users and organizations to extract
value out of their data. Although each of these platforms excels in specific aspects, users …

In this paper, we present PYTHIA, deadline-aware admission control for systems that
execute jobs from multiple big data (batch) frameworks using shared resources. PYTHIA …

Data analytics are moving beyond the limits of a single data processing platform. A cross-
platform query optimizer is necessary to enable applications to run their tasks over multiple …