Skip to main content


Swipe to navigate through the articles of this issue

18-05-2020 | Regular Paper | Issue 6/2020 Open Access

The VLDB Journal 6/2020

RHEEMix in the data jungle: a cost-based optimizer for cross-platform systems

The VLDB Journal > Issue 6/2020
Sebastian Kruse, Zoi Kaoudi, Bertty Contreras-Rojas, Sanjay Chawla, Felix Naumann, Jorge-Arnulfo Quiané-Ruiz
Important notes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


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 these new requirements. The optimizer allocates the subtasks of data analytic tasks to the most suitable platforms. Our main contributions are: (i) a mechanism based on graph transformations to explore alternative execution strategies; (ii) a novel graph-based approach to determine efficient data movement plans among subtasks and platforms; and (iii) an efficient plan enumeration algorithm, based on a novel enumeration algebra. We extensively evaluate our optimizer under diverse real tasks. We show that our optimizer can perform tasks more than one order of magnitude faster when using multiple platforms than when using a single platform.
About this article

Other articles of this Issue 6/2020

The VLDB Journal 6/2020 Go to the issue

Premium Partner

    Image Credits