FileScale: Fast and Elastic Metadata Management for Distributed File Systems

Abstract

File systems that store metadata on a single machine or via a shared-disk abstraction face scalability challenges, especially in contexts demanding the management of billions of files. Recent work has shown that employing shared-nothing, distributed database system (DDBMS) for metadata storage can alleviate these scalability challenges without compromising on high availability guarantees. However, for low-scale deployments – where metadata can fit in memory on a single machine – these DDBMS-based systems 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. This paper describes FileScale, a three-tier architecture that incorporates a DDBMS as part of a comprehensive approach to file system metadata management. In contrast to previous approaches, FileScale performs comparably to the single-machine architecture at a small scale, while enabling linear scalability as the file system metadata increases1