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Title: OctopusFS in action: Tiered storage management for data intensive computing
Authors: Kakoulli, Elena 
Karmiris, Nikolaos D. 
Herodotou, Herodotos 
Keywords: MapReduce;Spark workloads
Category: Computer and Information Sciences;Electrical Engineering - Electronic Engineering - Information Engineering
Field: Engineering and Technology
Issue Date: Aug-2018
Publisher: Association Computer Machinery
Source: 44th International Conference on Very Large Data Bases, VLDB 2018; Rio de Janeiro; Brazil; 27 -31 August 2017, Journal Proceedings of the VLDB Endowment, vol. 11, no. 12, pp. 1914-1917
Journal: Journal Proceedings of the VLDB Endowment 
Conference: International Conference on Very Large Data Bases 
Abstract: The continuous improvements in memory, storage devices, and network technologies of commodity hardware introduce new challenges and opportunities in tiered storage management. Whereas past work is exploiting storage tiers in pairs or for specific applications, OctopusFS-a novel distributed file system that is aware of the underlying storage mediaoffers a comprehensive solution to managing multiple storage tiers in a distributed setting. OctopusFS contains automated data-driven policies for managing the placement and retrieval of data across the nodes and storage tiers of the cluster. It also exposes the network locations and storage tiers of the data in order to allow higher-level systems to make locality-aware and tier-aware decisions. This demonstration will showcase the web interface of OctopusFS, which enables users to (i) view detailed utilization information for the various storage tiers and nodes, (ii) browse the directory namespace and perform file-related actions, and (iii) execute caching-related operations while observing their performance impact on MapReduce and Spark workloads.
ISSN: 2150-8097
DOI: 10.14778/3229863.3236223
Rights: © 2018 VLDB Endowment.
Type: Conference Papers
Appears in Collections:Δημοσιεύσεις σε συνέδρια/Conference papers

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