Automatic scaling of selective SPARQL joins using the TIRAMOLA system

Angelou, E; Papailiou, N; Konstantinou, I; Tsoumakos, D; Koziris, N

dc.contributor.author	Angelou, E	en
dc.contributor.author	Papailiou, N	en
dc.contributor.author	Konstantinou, I	en
dc.contributor.author	Tsoumakos, D	en
dc.contributor.author	Koziris, N	en
dc.date.accessioned	2014-03-01T02:53:33Z
dc.date.available	2014-03-01T02:53:33Z
dc.date.issued	2012	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/36415
dc.subject.other	Automatic scaling	en
dc.subject.other	Commodity hardware	en
dc.subject.other	Large-scale datasets	en
dc.subject.other	Rdf stores	en
dc.subject.other	System administrators	en
dc.subject.other	Throughput maximization	en
dc.subject.other	Virtual hardware	en
dc.subject.other	Elasticity	en
dc.subject.other	Hardware	en
dc.subject.other	Information management	en
dc.subject.other	Quality of service	en
dc.subject.other	Database systems	en
dc.title	Automatic scaling of selective SPARQL joins using the TIRAMOLA system	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1145/2237867.2237868	en
heal.identifier.secondary	http://dx.doi.org/10.1145/2237867.2237868	en
heal.publicationDate	2012	en
heal.abstract	Modern cloud infrastructures based on virtual hardware provide new opportunities and challenges for developers and system administrators alike. Most notable is the promise of resource elasticity, whereby the infrastructure can increase or decrease in size based on demand. Utilizing elastic resources, applications can provide better quality of service and reduce cost by only paying for the required amount of resources. In this work, we extensively study the performance of some popular NoSQL databases over an elastic cloud infrastructure. NoSQL databases focus on analytical processing of large scale datasets, offering increased scalability over commodity hardware. We then proceed to describe TIRAMOLA, a cloud-enabled framework for automatic provisioning of elastic resources on any NoSQL platform. Our system administers cluster resources (VMs) according to user-or application-specified constraints through an expandable monitoring and command-issuing module. Users can easily modify resizing policies, based on application-specific metrics and thus fully utilize the elasticity of the underlying infrastructure. As a realistic use-case, we apply this framework on top of a fully distributed RDF store backed by an elastic NoSQL database. Letting TIRAMOLA manage the number of committed resources results in automated cluster resize actions and throughput maximization, while application experts need only provide simple elasticity rules. © 2012 ACM.	en
heal.journalName	Proceedings of the 4th International Workshop on Semantic Web Information Management, SWIM'12	en
dc.identifier.doi	10.1145/2237867.2237868	en