We explore the trade-offs of performing linear algebra in Apache Spark versus the traditional C and MPI approach by examining three widely-used matrix factorizations: NMF (for physical plausibility), PCA (for its ubiquit

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Date: 2016-06-23 15:50:48		We explore the trade-offs of performing linear algebra in Apache Spark versus the traditional C and MPI approach by examining three widely-used matrix factorizations: NMF (for physical plausibility), PCA (for its ubiquit Add to Reading List Source URL: mmds-data.org Download Document from Source Website File Size: 12,13 KB Share Document on Facebook