DirectFS: An RDMA-Accelerated Distributed File System with CPU-Oblivious Metadata Indexing

Abstract

The rapid growth of data-intensive applications has imposed significant demands on the performance of distributed file systems, particularly in metadata operations. Traditional systems rely heavily on metadata servers to handle indexing tasks, leading to Central Processing Unit (CPU) bottlenecks and increased latency. To address these challenges, we propose Direct File System (DirectFS), an Remote Direct Memory Access (RDMA)-accelerated distributed file system that offloads metadata indexing to clients by leveraging one-sided RDMA operations. Further, we propose a range of techniques, including hash-based namespace indexing and hotness-aware metadata prefetching, to fully unleash the performance potential of RDMA hardware. We implement DirectFS on top of Moose File System (MooseFS) and compare DirectFS with state-of-the-art distributed file systems using a variety of Filebench v1.4.9.1 and MDTest from the IOR suite v4.0.0 workloads. Evaluation results demonstrate that DirectFS achieves significant performance improvements for metadata-intensive benchmarks compared to other file systems.