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Title: A Queueing Network Model for Performance Prediction of Apache Cassandra

Type Dataset Dipietro Salvatore, Casale Giuliano, Serazzi Giuseppe (2016): A Queueing Network Model for Performance Prediction of Apache Cassandra. Zenodo. Dataset. https://zenodo.org/record/153836

Authors: Dipietro Salvatore (Imperial College London) ; Casale Giuliano (Imperial College London) ; Serazzi Giuseppe (Politecnico di Milano) ;

Links

Summary

The dataset consists in several csv files containing Cassandra and ScyllaDB performance.

The experiments are organized in folders. There are three main folders containing:  - Cassandra 4 nodes: the files related to the Cassandra experiments conducted on a cluster composed of four nodes.  - ScyllaDB 4 nodes: The files related to the ScyllaDB experiments conducted on a cluster composed of four nodes.   - Cassandra QUORUM variant: the simulation data where a different kind of QUORUM is implemented in Cassandra.   "Cassandra 4 nodes" and "ScyllaDB 4 nodes" include some subfolders, each one containing the files of the Consistency Level applied for those experiments. Each experiment is composed by three files (data*.csv) with the data reported by Yahoo! Cloud System Benchmark (YCSB) in the end of the experiment execution. Each folder contains also a sim.csv file with the data gathered from the simulation of the model inside Java Modeling Tool.

The data*.csv files are composed by:  -Number of threads or clients  -Overall Throughput  -Number of Read requests  -Overall Read Response Time  -95 percentile Read Response Time  -99 percentile Read Response Time  -99.9 percentile Read Response Time   Differently, the sim.csv files are composed by:  -Number of threads or clients  -Overall Throughput  -Overall Read Response Time

More information

  • DOI: 10.5281/zenodo.153836

Subjects

  • NoSQL database, Apache Cassandra, queueing network model, simulation

Dates

  • Publication date: 2016
  • Issued: September 16, 2016

Notes

Other: This is part of the DICE (H2020- 644869) project. This project is supported by EPSRC Centre for Doctoral Training in High Performance Embedded and Distributed Systems(EP/L016796/1).

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Funding Information

AwardnumberAwarduriFunderidentifierFunderidentifiertypeFundername
644869info:eu-repo/grantAgreement/EC/H2020/644869/10.13039/100010661Crossref Funder IDEuropean Commission

Format

electronic resource

Relateditems

DescriptionItem typeRelationshipUri
IsPartOfhttps://zenodo.org/communities/ecfunded
IsPartOfhttps://zenodo.org/communities/zenodo