IRIS: Online Reconfiguration of Distributed NoSQL Databases for Dynamic Workloads - Archive ouverte HAL Access content directly
Preprints, Working Papers, ... (Preprint) Year : 2022

IRIS: Online Reconfiguration of Distributed NoSQL Databases for Dynamic Workloads

Paul C Wood
  • Function : Author
  • PersonId : 1109171
Subrata Mitra
  • Function : Author
Somali Chaterji
  • Function : Author
  • PersonId : 1109172
Saurabh Bagchi
  • Function : Author
  • PersonId : 1041097

Abstract

Reconfiguring NoSQL databases in the face of changing workload patterns is crucial for maximizing database throughput. However, this is challenging because of the large configuration parameter search space with complex interdependencies among parameters. While stateof-the-art systems can automatically identify close-tooptimal configurations for static workloads, they suffer for dynamic workloads. This happens due to the following two fundamental limitations. First, they do not account for performance degradation due to database restarting (often needed to apply the new configurations), and second, they overlook the application's availability requirements during reconfiguration. Our solution, IRIS, addresses both these shortcomings and we demonstrate its effectiveness for a multi-tenant, global-scale metagenomics pipeline called MG-RAST and an HPC data analytics job queue, both of which have dynamically changing workloads.We compare the benefit of IRIS in throughput over the default, a static configuration, and a theoretically ideal solution.
Fichier principal
Vignette du fichier
iris_hal22.pdf (1.18 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-03891081 , version 1 (09-12-2022)

Identifiers

  • HAL Id : hal-03891081 , version 1

Cite

Ashraf Mahgoub, Paul C Wood, Subrata Mitra, Folker Meyer, Somali Chaterji, et al.. IRIS: Online Reconfiguration of Distributed NoSQL Databases for Dynamic Workloads. 2022. ⟨hal-03891081⟩
30 View
26 Download

Share

Gmail Facebook X LinkedIn More