Don't Maintain Twice, It's Alright: Merged Metadata Management in Deduplication File System with GogetaFS
Yanqi Pan, Wen Xia, Erci Xu, Hao Huang, Xiangyu Zou, Shiyi Li
Abstract
Emerging storage technologies, such as persistent memory and ultra-low latency SSD, enable the deduplication file system (DedupFS) to use non-cryptographic hash for fast fingerprinting. However, we find that the accelerated computation exposes another major performance penalty: the seemingly innocuous in-storage deduplication metadata maintenance incurs up to 38% overhead in the I/O path.
We find the root cause is that DedupFSes maintain dedupspecific fingerprint-to-physical mappings, which incurs additional crash consistency overheads. However, this overhead is unnecessary. Our insight is that the deduplication mapping can be merged with the file system logical-to-physical mapping, forming a logical-fingerprint-physical (LFP) mapping. Thus, we can persist deduplication metadata alongside file system metadata in a single I/O. We propose GOGETAFS to realize the efficiency of LFP. Using a series of techniques to manage data and metadata atop LFP, GOGETAFS achieves compatible, effective, and memory-efficient deduplication within the file system. Experiments across a range of workloads show that GOGETAFS consistently outperforms existing DedupF-Ses and can minimize metadata maintenance overheads.
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