Understanding Data Compression in Warehouse-Scale Datacenter Services

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 comprehensi...

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Bibliographic Details
Published in2022 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS) pp. 221 - 223
Main Authors Jeong, Geonhwa, Sharma, Bikash, Terrell, Nick, Dhanotia, Abhishek, Zhao, Zhiwei, Agarwal, Niket, Kejariwal, Arun, Krishna, Tushar
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2022
Subjects
Costs
Data centers
Data compression
Finance
Production
Social networking (online)
Software
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Summary: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.
DOI:10.1109/ISPASS55109.2022.00028