Disaggregating RocksDB: A Production Experience

Author:

Dong Siying1ORCID,P Shiva Shankar1ORCID,Pan Satadru1ORCID,Ananthabhotla Anand1ORCID,Ekambaram Dhanabal1ORCID,Sharma Abhinav1ORCID,Dayal Shobhit1ORCID,Parikh Nishant Vinaybhai1ORCID,Jin Yanqin1ORCID,Kim Albert1ORCID,Patil Sushil1ORCID,Zhuang Jay1ORCID,Dunster Sam1ORCID,Mahajan Akanksha1ORCID,Chelluri Anirudh1ORCID,Datye Chaitanya1ORCID,Santana Lucas Vasconcelos1ORCID,Garg Nitin1ORCID,Gawde Omkar1ORCID

Affiliation:

1. Meta, Menlo Park, CA, USA

Abstract

As in the general industry, there is a trend in Meta's data centers to migrate data from locally attached SSDs to cloud storage. We extended RocksDB [26], a widely used open-source storage engine designed and built for local SSDs, to leverage disaggregated storage. RocksDB's design, such as its data and log files' access patterns, makes an append-only distributed file system a desirable underlying storage. At Meta, we built disaggregated RocksDB using Tectonic File System [35], which so far had mainly been used for our data warehouse and blob storage stacks. We identified that metadata overhead and tail latencies were Tectonic's major performance gaps and addressed them accordingly. We improved the reliability, performance and other requirements with both general and customized optimizations to the core engine in RocksDB. We also took the time to deeply understand the common challenges presented by applications running on RocksDB and implemented enhancements to address them. This architecture enabled RocksDB to adapt to a more distributed architecture for performance enhancements.

Publisher

Association for Computing Machinery (ACM)

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