EDBT 2026 Demo / reviewers in the wild / expert
Leif Walsh
dblp:06/10842
· DBLP profile ↗
5ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 5Databases, data management, data science and information retrieval · 2
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer architecture, parallel and distributed computing, and storage systems
5 papers |
Storage systems · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Storage systems › file systems
write-optimized file system |
1.2 | 5 | 2017 | Writes Wrought Right, and Other Adventures in File System Optimization · ACM Trans. Storage 2017 Optimizing Every Operation in a Write-optimized File System · USENIX ATC 2016 Optimizing Every Operation in a Write-optimized File System · FAST 2016 |
Storage systems
file systems |
1.0 | 4 | 2017 | Writes Wrought Right, and Other Adventures in File System Optimization · ACM Trans. Storage 2017 Optimizing Every Operation in a Write-optimized File System · USENIX ATC 2016 BetrFS: Write-Optimization in a Kernel File System · ACM Trans. Storage 2015 |
Storage systems › i/o optimization › write optimization
write-optimized data structure |
0.1 | 1 | 2015 | BetrFS: Write-Optimization in a Kernel File System · ACM Trans. Storage 2015 |
Methods — techniques the papers use, named apart from their topics
zoning · 0.3range deletion · 0.3late-binding journaling · 0.3write-optimized data structures · 0.2b-epsilon tree · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | Writes Wrought Right, and Other Adventures in File System OptimizationabstractFile 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. Jun Yuan 0006, Yang Zhan 0001, William Jannen, Prashant Pandey 0001, Amogh Akshintala, Kanchan Chandnani, Pooja Deo, Zardosht Kasheff, Leif Walsh, Michael A. Bender, Martin Farach-Colton, Rob Johnson 0001, Bradley C. Kuszmaul, Donald E. Porter |
ACM Trans. Storage | 9 |
| 2016 | Optimizing Every Operation in a Write-optimized File System
Jun Yuan 0006, Yang Zhan 0001, William Jannen, Prashant Pandey 0001, Amogh Akshintala, Kanchan Chandnani, Pooja Deo, Zardosht Kasheff, Leif Walsh, Michael A. Bender, Martin Farach-Colton, Rob Johnson 0001, Bradley C. Kuszmaul, Donald E. Porter |
FAST | 9 |
| 2016 | Optimizing Every Operation in a Write-optimized File System
Jun Yuan 0006, Yang Zhan 0001, William Jannen, Prashant Pandey 0001, Amogh Akshintala, Kanchan Chandnani, Pooja Deo, Zardosht Kasheff, Leif Walsh, Michael A. Bender, Martin Farach-Colton, Rob Johnson 0001, Bradley C. Kuszmaul, Donald E. Porter |
USENIX ATC | 9 |
| 2015 | BetrFS: A Right-Optimized Write-Optimized File System
William Jannen, Jun Yuan 0006, Yang Zhan 0001, Amogh Akshintala, John Esmet, Yizheng Jiao, Ankur Mittal, Prashant Pandey 0001, Phaneendra Reddy, Leif Walsh, Michael A. Bender, Martin Farach-Colton, Rob Johnson 0001, Bradley C. Kuszmaul, Donald E. Porter |
FAST | 10 |
| 2015 | BetrFS: Write-Optimization in a Kernel File SystemabstractThe B ε -tree File System , or B e trFS (pronounced “better eff ess”), is the first in-kernel file system to use a write-optimized data structure (WODS). WODS are promising building blocks for storage systems because they support both microwrites and large scans efficiently. Previous WODS-based file systems have shown promise but have been hampered in several ways, which B e trFS mitigates or eliminates altogether. For example, previous WODS-based file systems were implemented in user space using FUSE, which superimposes many reads on a write-intensive workload, reducing the effectiveness of the WODS. This article also contributes several techniques for exploiting write-optimization within existing kernel infrastructure. B e trFS dramatically improves performance of certain types of large scans, such as recursive directory traversals, as well as performance of arbitrary microdata operations, such as file creates, metadata updates, and small writes to files. B e trFS can make small, random updates within a large file 2 orders of magnitude faster than other local file systems. B e trFS is an ongoing prototype effort and requires additional data-structure tuning to match current general-purpose file systems on some operations, including deletes, directory renames, and large sequential writes. Nonetheless, many applications realize significant performance improvements on B e trFS. For instance, an in-place rsync of the Linux kernel source sees roughly 1.6--22 × speedup over commodity file systems. William Jannen, Jun Yuan 0006, Yang Zhan 0001, Amogh Akshintala, John Esmet, Yizheng Jiao, Ankur Mittal, Prashant Pandey 0001, Phaneendra Reddy, Leif Walsh, Michael A. Bender, Martin Farach-Colton, Rob Johnson 0001, Bradley C. Kuszmaul, Donald E. Porter |
ACM Trans. Storage | 10 |