Data @Scale 2016

Facebook’s disaggregated storage and compute for Map/Reduce


To wrap up this year’s Data @Scale, we returned to a classic systems engineering talk. Kestutis Patiejunas and Amisha Jaiswal from Facebook argued that disaggregation of storage and compute provides efficiency through gains in flexibility, latency, and availability by using RS encoding of data warehouse data. As part of the talk, they described warm storage, a new storage system that recently was deployed at Facebook. There was a lively discussion at the end of the talk about purpose-built hardware designs optimized for specific workloads versus generic one-size-fits-all.

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