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FileScale: Fast and Elastic Metadata Management for Distributed File Systems

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FileScale: Fast and Elastic Metadata Management for Distributed File Systems

Recent work has shown that distributed database systems are a promising solution for scaling metadata management in scalable file systems. This work has shown that systems that store metadata on a single machine, or over a shared-disk abstraction, struggle to scale performance to deployments including billions of files. In contrast, leveraging a scalable, shared-nothing, distributed system for metadata storage can achieve much higher levels of scalability, without giving up high availability guarantees. However, for low-scale deployments – where metadata can fit in memory on a single machine – these systems that store metadata in a distributed database typically perform an order of magnitude worse than systems that store metadata in memory on a single machine. This has limited the impact of these distributed database approaches, since they are only currently applicable to file systems of extreme scale.

FileScale is a three-tier architecture that incorporates a distributed database system as part of a comprehensive approach to metadata management in distributed file systems. In contrast to previous approaches, the architecture described in the paper performs comparably to the single-machine architecture at a small scale, while enabling linear scalability as the file system metadata increases.

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FileScale resources in this repository are released under the Apache License 2.0

Acknowledgements

This work was supported by the National Science Foundation under grant IIS-1910613.