demonstration

TIRAMOLA: elastic nosql provisioning through a cloud management platform

Authors:

Ioannis Konstantinou,

Evangelos Angelou,

Dimitrios Tsoumakos,

Christina Boumpouka,

Nectarios Koziris,

Spyros SioutasAuthors Info & Claims

SIGMOD '12: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data

Pages 725 - 728

https://doi.org/10.1145/2213836.2213943

Published: 20 May 2012 Publication History

Abstract

NoSQL databases focus on analytical processing of large scale datasets, offering increased scalability over commodity hardware. One of their strongest features is elasticity, which allows for fairly portioned premiums and high-quality performance. Yet, the process of adaptive expansion and contraction of resources usually involves a lot of manual effort, often requiring the definition of the conditions for scaling up or down to be provided by the users. To date, there exists no open-source system for automatic resizing of NoSQL clusters. In this demonstration, we present TIRAMOLA, a modular, cloud-enabled framework for monitoring and adaptively resizing NoSQL clusters. Our system incorporates a decision-making module which allows for optimal cluster resize actions in order to maximize any quantifiable reward function provided together with life-long adaptation to workload or infrastructural changes. The audience will be able to initiate HBase clusters of various sizes and apply varying workloads through multiple YCSB clients. The attendees will be able to watch, in real-time, the system perform automatic VM additions and removals as well as how cluster performance metrics change relative to the optimization parameters of their choice.

References

[1]

Amazon CloudWatch. http://aws.amazon.com/cloudwatch/.

[2]

Amazon Elastic Compute Cloud (Amazon EC2). http://aws.amazon.com/ec2/.

[3]

Amazon SimpleDB. http://aws.amazon.com/simpledb/.

[4]

AzureWatch. http://www.paraleap.com/azurewatch.

[5]

Google AppEngine. code.google.com/appengine.

[6]

HBase Homepage. http://hbase.apache.org.

[7]

OpenStack: The open source, open standards cloud. http://openstack.org.

[8]

Project Voldemort. http://project-voldemort.com.

[9]

Riak Homepage. https://wiki.basho.com/display/RIAK/Riak.

[10]

Windows Azure Platform. http://www.microsoft.com/windowsazure/.

[11]

A. Qureshi et al. Cutting the Electric Bill for Internet-Scale Systems. In SIGCOMM, 2009.

Digital Library

[12]

D. J. Abadi. Data Management in the Cloud: Limitations and Opportunities. IEEE Data Eng. Bull, 32(1):3--12, 2009.

[13]

B. F. Cooper, A. Silberstein, E. Tam, R. Ramakrishnan, and R. Sears. Benchmarking Cloud Serving Systems with YCSB. In ACM SOCC, pages 143--154, 2010.

Digital Library

[14]

F. Galán, A. Sampaio, L. Rodero-Merino, I. Loy, V. Gil, and L. M. Vaquero. Service Specification in Cloud Environments Based on Extensions to Open Standards. In COMSWARE, 2009.

Digital Library

[15]

E. Horowitz. Foursquare Outage Post Mortem. http://bit.ly/c4GnV0.

[16]

I. Konstantinou, E. Angelou, C. Boumpouka, D. Tsoumakos, and N. Koziris. On the Elasticity of NoSQL Databases over Cloud Management Platforms. In CIKM, 2011.

Digital Library

[17]

D. Kossmann, T. Kraska, and S. Loesing. An Evaluation of Alternative Architectures for Transaction Processing in the Cloud. In SIGMOD, pages 579--590, 2010.

Digital Library

[18]

A. Lakshman and P. Malik. Cassandra: A Decentralized Structured Storage System. SIGOPS Oper. Syst. Rev., 44(2):35--40, 2010.

Digital Library

[19]

H. C. Lim, S. Babu, and J. S. Chase. Automated Control for Elastic Storage. In ICAC, 2010.

Digital Library

[20]

P. Marshall, K. Keahey, and T. Freeman. Elastic Site: Using Clouds to Elastically Extend Site Resources. In CCGRID, 2010.

Digital Library

[21]

M. L. Massie, B. N. Chun, and D. E. Culler. The Ganglia Distributed Monitoring System: Design, Implementation, and Experience. Parallel Computing, 30(7):817--840, 2004.

[22]

D. Nurmi, R. Wolski, C. Grzegorczyk, G. Obertelli, S. Soman, L. Youseff, and D. Zagorodnov. The Eucalyptus Open-Source Cloud-Computing System. In CCGRID, pages 124--131, 2009.

Digital Library

[23]

A. Pavlo, E. Paulson, A. Rasin, D. J. Abadi, D. J. DeWitt, S. Madden, and M. Stonebraker. A Comparison of Approaches to Large-Scale Data Analysis. In SIGMOD, pages 165--178, 2009.

Digital Library

[24]

R. Sutton and A. Barto. Reinforcement Learning: An Introduction. MIT Press, 1998.

Digital Library

[25]

K. Tsakalozos, H. Kllapi, E. Sitaridi, M. Roussopoulos, D. Paparas, and A. Delis. Flexible Use of Cloud Resources through Profit Maximization and Price Discrimination. In ICDE, 2011.

Digital Library

[26]

P. Xiong, Y. Chi, S. Zhu, H. J. Moon, C. Pu, and H. Hacigümüs. Intelligent Management of Virtualized Resources for Database Systems in Cloud Environment. In ICDE, 2011.

Digital Library

Cited By

Lahande PKaveri P(2022)Reinforcement Learning Applications for Performance Improvement in Cloud Computing—A Systematic ReviewSustainable Advanced Computing10.1007/978-981-16-9012-9_9(91-112)Online publication date: 31-Mar-2022
https://doi.org/10.1007/978-981-16-9012-9_9
Karniavoura FMagoutis K(2019)Decision-Making Approaches for Performance QoS in Distributed Storage Systems: A SurveyIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2019.2893940(1-1)Online publication date: 2019
https://doi.org/10.1109/TPDS.2019.2893940
Al-Dhuraibi YParaiso FDjarallah NMerle P(2018)Elasticity in Cloud Computing: State of the Art and Research ChallengesIEEE Transactions on Services Computing10.1109/TSC.2017.271100911:2(430-447)Online publication date: 1-Mar-2018
https://doi.org/10.1109/TSC.2017.2711009
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Index Terms

TIRAMOLA: elastic nosql provisioning through a cloud management platform
1. Information systems
  1. Data management systems
    1. Database management system engines
      1. Parallel and distributed DBMSs

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Information & Contributors

Information

Published In

cover image ACM Conferences

SIGMOD '12: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data

May 2012

886 pages

ISBN:9781450312479

DOI:10.1145/2213836

General Chairs:
K. Selçuk Candan
Arizona State University
,
Yi Chen
Arizona State University
,
Richard Snodgrass
University of Arizona
,
Program Chair:
Luis Gravano
Columbia University
,
Publications Chair:
Ariel Fuxman
Microsoft Research

Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGMOD: ACM Special Interest Group on Management of Data

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 May 2012

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Demonstration

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SIGMOD/PODS '12

Sponsor:

SIGMOD

SIGMOD/PODS '12: International Conference on Management of Data

May 20 - 24, 2012

Arizona, Scottsdale, USA

Acceptance Rates

SIGMOD '12 Paper Acceptance Rate 48 of 289 submissions, 17%;

Overall Acceptance Rate 785 of 4,003 submissions, 20%

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Cited By

Lahande PKaveri P(2022)Reinforcement Learning Applications for Performance Improvement in Cloud Computing—A Systematic ReviewSustainable Advanced Computing10.1007/978-981-16-9012-9_9(91-112)Online publication date: 31-Mar-2022
https://doi.org/10.1007/978-981-16-9012-9_9
Karniavoura FMagoutis K(2019)Decision-Making Approaches for Performance QoS in Distributed Storage Systems: A SurveyIEEE Transactions on Parallel and Distributed Systems10.1109/TPDS.2019.2893940(1-1)Online publication date: 2019
https://doi.org/10.1109/TPDS.2019.2893940
Al-Dhuraibi YParaiso FDjarallah NMerle P(2018)Elasticity in Cloud Computing: State of the Art and Research ChallengesIEEE Transactions on Services Computing10.1109/TSC.2017.271100911:2(430-447)Online publication date: 1-Mar-2018
https://doi.org/10.1109/TSC.2017.2711009
Dipietro SBuyya RCasale G(2018)PAX: Partition-aware autoscaling for the Cassandra NoSQL databaseNOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium10.1109/NOMS.2018.8406271(1-9)Online publication date: Apr-2018
https://doi.org/10.1109/NOMS.2018.8406271
Naskos AGounaris AKonstantinou I(2018)Elton: A Cloud Resource Scaling-Out Manager for NoSQL Databases2018 IEEE 34th International Conference on Data Engineering (ICDE)10.1109/ICDE.2018.00196(1641-1644)Online publication date: Apr-2018
https://doi.org/10.1109/ICDE.2018.00196
Farias VSousa FMaia JGomes JMachado J(2018)Regression based performance modeling and provisioning for NoSQL cloud databasesFuture Generation Computer Systems10.1016/j.future.2017.08.06179:P1(72-81)Online publication date: 1-Feb-2018
https://dl.acm.org/doi/10.1016/j.future.2017.08.061
Khoshkbarforoushha ARanjan RWang QFriedrich C(2017)FlowerProceedings of the VLDB Endowment10.14778/3137765.313780210:12(1893-1896)Online publication date: 1-Aug-2017
https://dl.acm.org/doi/10.14778/3137765.3137802
Floratou AAgrawal A(2017)Self-Regulating Streaming SystemsProceedings of the International Workshop on Real-Time Business Intelligence and Analytics10.1145/3129292.3129295(1-5)Online publication date: 28-Aug-2017
https://dl.acm.org/doi/10.1145/3129292.3129295
Ortiz JCheung AElmore A(2017)PerfEnforce OverviewProceedings of the 2017 ACM International Conference on Management of Data10.1145/3055167.3055175(31-33)Online publication date: 14-May-2017
https://dl.acm.org/doi/10.1145/3055167.3055175
Papaioannou AMagoutis K(2017)Incremental Elasticity for NoSQL Data Stores2017 IEEE 36th Symposium on Reliable Distributed Systems (SRDS)10.1109/SRDS.2017.26(174-183)Online publication date: Sep-2017
https://doi.org/10.1109/SRDS.2017.26
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