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arXiv · 1512.00757

Tempo: Robust and Self-Tuning Resource Management in Multi-tenant Parallel Databases

Zilong Tan·Shivnath Babu
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Abstract

Multi-tenant database systems have a component called the Resource Manager, or RM that is responsible for allocating resources to tenants. RMs today do not provide direct support for performance objectives such as: "Average job response time of tenant A must be less than two minutes", or "No more than 5% of tenant B's jobs can miss the deadline of 1 hour." Thus, DBAs have to tinker with the RM's low-level configuration settings to meet such objectives. We propose a framework called Tempo that brings simplicity, self-tuning, and robustness to existing RMs. Tempo provides a simple interface for DBAs to specify performance objectives declaratively, and optimizes the RM configuration settings to meet these objectives. Tempo has a solid theoretical foundation which gives key robustness guarantees. We report experiments done on Tempo using production traces of data-processing workloads from companies such as Facebook and Cloudera. These experiments demonstrate significant improvements in meeting desired performance objectives over RM configuration settings specified by human experts.

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Zilong Tan, Shivnath Babu. 2015-12-02. Tempo: Robust and Self-Tuning Resource Management in Multi-tenant Parallel Databases. https://doi.org/10.14778/2977797.2977799

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