Understanding Data Compression in Warehouse-Scale Datacenter Services

2022 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)(2022)

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摘要
Data compression has emerged as a promising technique to alleviate the memory, storage, and network cost with some associated compute overheads in warehouse-scale datacenter services. Despite being one of the most important components of the overall datacenter taxes, there has not been a comprehensive characterization of compression usage in data center workloads. In this work, we first provide a holistic characterization of compression as used by various warehouse-scale datacenter services at a global social media provider (Meta). Next, we deep dive into a few representative use cases of compression in the production environment and characterize compression usage of services while running live traffic.
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关键词
data compression,warehouse-scale datacenter services,datacenter taxes,compression usage,data center workloads
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