TY - GEN
T1 - Optimizing every operation in a write-optimized file system
AU - Yuan, Jun
AU - Zhan, Yang
AU - Jannen, William
AU - Pandey, Prashant
AU - Akshintala, Amogh
AU - Chandnani, Kanchan
AU - Deo, Pooja
AU - Kasheff, Zardosht
AU - Walsh, Leif
AU - Bender, Michael A.
AU - Farach-Colton, Martin
AU - Johnson, Rob
AU - Kuszmaul, Bradley C.
AU - Porter, Donald E.
N1 - Publisher Copyright:
© 2016 by The USENIX Association. All Rights Reserved.
PY - 2016
Y1 - 2016
N2 - File systems that employ write-optimized dictionaries (WODs) can perform random-writes, metadata updates, and recursive directory traversals orders of magnitude faster than conventional file systems. However, previous WOD-based file systems have not obtained all of these performance gains without sacrificing performance on other operations, such as file deletion, file or directory renaming, or sequential writes. Using three techniques, late-binding journaling, zoning, and range deletion, we show that there is no fundamental trade-off in write-optimization. These dramatic improvements can be retained while matching conventional file systems on all other operations. BetrFS 0.2 delivers order-of-magnitude better performance than conventional file systems on directory scans and small random writes and matches the performance of conventional file systems on rename, delete, and sequential I/O. For example, BetrFS 0.2 performs directory scans 2.2× faster, and small random writes over two orders of magnitude faster, than the fastest conventional file system. But unlike BetrFS 0.1, it renames and deletes files commensurate with conventional file systems and performs large sequential I/O at nearly disk bandwidth. The performance benefits of these techniques extend to applications as well. BetrFS 0.2 continues to outperform conventional file systems on many applications, such as as rsync, git-diff, and tar, but improves git-clone performance by 35% over BetrFS 0.1, yielding performance comparable to other file systems.
AB - File systems that employ write-optimized dictionaries (WODs) can perform random-writes, metadata updates, and recursive directory traversals orders of magnitude faster than conventional file systems. However, previous WOD-based file systems have not obtained all of these performance gains without sacrificing performance on other operations, such as file deletion, file or directory renaming, or sequential writes. Using three techniques, late-binding journaling, zoning, and range deletion, we show that there is no fundamental trade-off in write-optimization. These dramatic improvements can be retained while matching conventional file systems on all other operations. BetrFS 0.2 delivers order-of-magnitude better performance than conventional file systems on directory scans and small random writes and matches the performance of conventional file systems on rename, delete, and sequential I/O. For example, BetrFS 0.2 performs directory scans 2.2× faster, and small random writes over two orders of magnitude faster, than the fastest conventional file system. But unlike BetrFS 0.1, it renames and deletes files commensurate with conventional file systems and performs large sequential I/O at nearly disk bandwidth. The performance benefits of these techniques extend to applications as well. BetrFS 0.2 continues to outperform conventional file systems on many applications, such as as rsync, git-diff, and tar, but improves git-clone performance by 35% over BetrFS 0.1, yielding performance comparable to other file systems.
UR - http://www.scopus.com/inward/record.url?scp=85077182069&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85077182069&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85077182069
T3 - Proceedings of the 14th USENIX Conference on File and Storage Technologies, FAST 2016
SP - 1
EP - 14
BT - Proceedings of the 14th USENIX Conference on File and Storage Technologies, FAST 2016
PB - USENIX Association
T2 - 14th USENIX Conference on File and Storage Technologies, FAST 2016
Y2 - 22 February 2016 through 25 February 2016
ER -