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Towards Engineering a Web-Scale Multimedia Service: A Case Study Using Spark

Abstract : Computing power has now become abundant with multi-core machines, grids and clouds, but it remains a challenge to harness the available power and move towards gracefully handling web-scale datasets. Several researchers have used automatically distributed computing frameworks, notably Hadoop and Spark, for processing multimedia material, but mostly using small collections on small clusters. In this paper , we describe the engineering process for a prototype near-web-scale multimedia service using the Spark framework running on the AWS cloud service. We present experimental results using up to 43 billion SIFT descriptors from the public YFCC 100M collection, making this the largest high-dimensional feature collection reported in the literature. The design of the prototype and performance results demonstrate both the flexibility and scalability of the Spark framework for implementing multimedia services.
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Contributor : Laurent Amsaleg Connect in order to contact the contributor
Submitted on : Wednesday, December 14, 2016 - 8:12:57 AM
Last modification on : Wednesday, November 3, 2021 - 6:05:35 AM
Long-term archiving on: : Wednesday, March 15, 2017 - 1:48:11 PM


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  • HAL Id : hal-01416089, version 1


Gylfi Guðmundsson, Laurent Amsaleg, Björn Thor Jónsson, Michael Franklin. Towards Engineering a Web-Scale Multimedia Service: A Case Study Using Spark. [Research Report] Inria Rennes Bretagne Atlantique; Reykjavik University; UC Berkeley. 2016. ⟨hal-01416089⟩



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