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https://github.com/redox-os/tfs
Mirror of https://gitlab.redox-os.org/redox-os/tfs
https://github.com/redox-os/tfs
chashmap filesystem fs mlcr redox rust seahash tfs zmicro
Last synced: 20 days ago
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Mirror of https://gitlab.redox-os.org/redox-os/tfs
- Host: GitHub
- URL: https://github.com/redox-os/tfs
- Owner: redox-os
- License: mit
- Created: 2016-10-18T20:12:47.000Z (about 8 years ago)
- Default Branch: master
- Last Pushed: 2024-02-07T21:58:54.000Z (9 months ago)
- Last Synced: 2024-04-11T04:02:38.423Z (7 months ago)
- Topics: chashmap, filesystem, fs, mlcr, redox, rust, seahash, tfs, zmicro
- Language: Rust
- Homepage:
- Size: 864 KB
- Stars: 2,947
- Watchers: 126
- Forks: 135
- Open Issues: 33
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-repositories - redox-os/tfs - Mirror of https://gitlab.redox-os.org/redox-os/tfs (Rust)
README
# TFS was replaced by [RedoxFS](https://gitlab.redox-os.org/redox-os/redoxfs) and is no longer maintained, most of the features of TFS have been incorporated into RedoxFS
# TFS: Next-generation file system
TFS is a modular, fast, and feature rich next-gen file system, employing
modern techniques for high performance, high space efficiency, and high
scalability.
TFS was created out of the need for a modern file system for Redox OS,
as a replacement for ZFS, which proved to be slow to implement because
of its monolithic design.
TFS is inspired by the ideas behind ZFS, but at the same time it aims to
be modular and easier to implement.
TFS is not related to the file system of the same name by
*terminalcloud*.
*While many components are complete, TFS itself is not ready for use.*
[](https://en.wikipedia.org/wiki/MIT_License)
## Design goals
TFS is designed with the following goals in mind:
- Concurrent
TFS contains very few locks and aims to be as suitable for
multithreaded systems as possible. It makes use of multiple truly
concurrent structures to manage the data, and scales linearly by the
number of cores. **This is perhaps the most important feature
of TFS.**
- Asynchronous
TFS is asynchronous: operations can happen independently; writes and
reads from the disk need not block.
- Full-disk compression
TFS is the first file system to incorporate complete full-disk
compression through a scheme we call RACC (random-access
cluster compression). This means that every cluster is compressed
only affecting performance slightly. It is estimated that you get
60-120% more usable space.
- Revision history
TFS stores a revision history of every file without imposing
extra overhead. This means that you can revert any file into an
earlier version, backing up the system automatically and without
imposed overhead from copying.
- Data integrity
TFS, like ZFS, stores full checksums of the file (not just
metadata), and on top of that, it is done in the parent block. That
means that almost all data corruption will be detected upon read.
- Copy-on-write semantics
Similarly to Btrfs and ZFS, TFS uses CoW semantics, meaning that no
cluster is ever overwritten directly, but instead it is copied and
written to a new cluster.
- O(1) recursive copies
Like some other file systems, TFS can do recursive copies in
constant time, but there is an unique addition: TFS doesn't copy
even after it is mutated. How? It maintains segments of the file
individually, such that only the updated segment needs copying.
- Guaranteed atomicity
The system will never enter an inconsistent state (unless there is
hardware failure), meaning that unexpected power-off won't ever
damage the system.
- Improved caching
TFS puts a lot of effort into caching the disk to speed up
disk accesses. It uses machine learning to learn patterns and
predict future uses to reduce the number of cache misses. TFS also
compresses the in-memory cache, reducing the amount of
memory needed.
- Better file monitoring
CoW is very suitable for high-performance, scalable file monitoring,
but unfortunately only few file systems incorporate that. TFS is one
of those.
- All memory safe
TFS uses only components written in Rust. As such, memory unsafety
is only possible in code marked unsafe, which is checked
extra carefully.
- Full coverage testing
TFS aims to be full coverage with respect to testing. This gives
relatively strong guarantees on correctness by instantly revealing
large classes of bugs.
- SSD friendly
TFS tries to avoid the write limitation in SSD by repositioning
dead sectors.
- Improved garbage collection
TFS uses Bloom filters for space-efficient and fast
garbage collection. TFS allows the FS garbage collector to run in
the background without blocking the rest of the file system.
## FAQ
### Why do you use SPECK as the default cipher?
- SPECK is a relatively young cipher, yet it has been subject to a lot
of (ineffective) cryptanalysis, so it is relatively secure. It has
really good performance and a simple implementation. Portability is
an important part of the TFS design, and truly portable AES
implementations without side-channel attacks is harder than many
think (particularly, there are issues with SubBytes in most
portable implementations). SPECK does not have this issue, and can
thus be securely implemented portably with minimal effort.
### How similar is TFS and ZFS?
- Not that similar, actually. They share many of the basic ideas, but
otherwise they are essentially unconnected. But ZFS' design has
shaped TFS' a lot.
### Is TFS Redox-only?
- No, and it was never planned to be Redox-only.
### How does whole-disk compression work?
- Whole-disk compression is -- to my knowledge -- exclusive to TFS. It
works by collecting as many "pages" (virtual data blocks) into a
"cluster" (allocation unit). By doing this, the pages can be read by
simply decompressing the respective cluster.
### Why is ZMicro so slow? Will it affect the performance of TFS?
- The reason ZMicro is so slow is because it works on a bit level,
giving excellent compression ratio on the cost of performance. This
horribly slow performance is paid back by the reduced number
of writes. In fact, more than 50% of the allocations with ZMicro
will only write one sector, as opposed to 3. Secondly, no matter how
fast your disk is, it will not get anywhere near the performance of
ZMicro because disk operations are inherently slow, and when put in
perspective, the performance of the compression is
really unimportant.
### Extendible hashing or B+ trees?
- Neither. TFS uses a combination of trees and hash tables: Nested hash tables, a form of hash trees. The idea is that instead of reallocating, a new subtable is created in the bucket.
## Resources on design
I've written a number of pieces on the design of TFS:
- [SeaHash: Explained](http://ticki.github.io/blog/seahash-explained/) - This describes the default checksum algorithm designed for TFS.
- [On Random-Access Compression](http://ticki.github.io/blog/on-random-access-compression/) - This post describes the algorithm used for random-access compression.
- [Ternary as a prediction residue code](http://ticki.github.io/blog/ternary-as-a-prediction-residue-code/) - The use of this is related to creating a good adaptive (headerless) entropy compressor.
- [How LZ4 works](http://ticki.github.io/blog/how-lz4-works/) - This describes how the LZ4 compression algorithm works.
- [Collision Resolution with Nested Hash Tables](https://ticki.github.io/blog/collision-resolution-with-nested-hash-tables/) - This describes the method of nested hash tables we use for the directory structure.
- [An Atomic Hash Table](https://ticki.github.io/blog/an-atomic-hash-table/) - This describes the concurrent, in-memory hash table/key-value store.
## Specification
The full specification can be found in `specification.tex`, to render it install `texlive` or another distribution with XeTeX, and run:
```sh
xelatex --shell-escape specification.tex
```
Then open the file named `specification.pdf`