rsync VS zstd

So we have our SSH connection all oiled and ready to go. In the next post on the series, we will see how can we use Rsync to sync our music files, bidirectionally. See ya, on the next tab.

Rsync is a command-line tool that enables syncing files and directories between the local and remote system. It's highly flexible and it's similar to scp, if you worked on scp before, the rsync is just scp on steroids.

rsync can be used to synchronize a local disk to the pCloud drive p. Works similarly as the Sync option of the pCloud Drive app. May be useful if one prefers a bulk upload once a day over a continuous synchronization.

Tools that can be used to handle this include Rsync, Duplicati, Cohesity

To overcome this issue, you can use rsync, a powerful command-line tool for synchronizing files and directories, along with a bash script that excludes the node_modules folder and also filter out anything in a .gitignore file that you specify. In this article, I'll guide you through the process of setting up and using this bash script to sync your Node.js project while ignoring the node_modules folder.

On OL9 I installed rsync using https://github.com/WayneD/rsync/blob/master/INSTALL.md and installing dependencies using the For Fedora 33 commands where possible except xxhash which wasn't found, so I used https://oraclelinux.pkgs.org/9/ol9-codeready-builder-aarch64/xxhash-devel-0.8.1-3.el9.aarch64.rpm.html

rsync will probably work better for this use case

I would prefer to use a revision control system, like git if keeping multiple versions of documents is important. Otherwise, if you don't find anything else to your liking, you could write your own scripts based on rsync with the clone-dest, detect-renamed, and detect-renamed-lax patches.

Give rsync a try, it should handle UTF filenames just fine.

I don't think so? It's only seekable with an additional index [1], just like any other compression scheme.

[1] https://github.com/facebook/zstd/blob/dev/contrib/seekable_f...

- latest zstd v1.5.6 ( Mar 30, 2024 https://github.com/facebook/zstd/releases )

You may have also noticed that a new supported data compression format zstd appeared some time ago. I haven't seen any backends that use it yet, but httpx will support decompression in versions above 0.28.0. I already use it to compress server response dumps in my projects; it shows incredible efficiency in asynchronous solutions with aiofiles.

Zstd is a personal project? Surely it's not by accident in the Facebook GitHub organization? And that you need to sign a contract on code.facebook.com before they'll consider merging any contributions? That seems like an odd claim, unless it used to be a personal project and Facebook took it over

(https://github.com/facebook/zstd/blob/dev/CONTRIBUTING.md#co...)

Unmount root and remount the subvolumes and the boot partition. noatime is used for better performance zstd as file compression:

> In such cases, the serialized binary are mostly in 200~1000 bytes. Not big enough for zstd to work

You're not referring to the same dictionary that I am. Look at --train in [1].

If you have a training corpus of representative data, you can generate a dictionary that you preshare on both sides which will perform much better for very small binaries (including 200-1k bytes).

If you want maximum flexibility (i.e. you don't know the universe of representative messages ahead of time or you want maximum compression performance), you can gather this corpus transparently as messages are generated & then generate a dictionary & attach it as sideband metadata to a message. You'll probably need to defer the decoding if it references a dictionary not yet received (i.e. send delivers messages out-of-order from generation). There are other techniques you can apply, but the general rule is that your custom encoding scheme is unlikely to outperform zstd + a representative training corpus. If it does, you'd need to actually show this rather than try to argue from first principles.

[1] https://github.com/facebook/zstd/blob/dev/programs/zstd.1.md

> Doesn't take large amount of GPU resources

This is an understatement, zstd dictionary compression and decompression are blazingly fast: https://github.com/facebook/zstd/blob/dev/README.md#the-case...

My real-world use case for this was JSON files in a particular schema, and the results were fantastic.

This VFS will read a sqlite file after it has been compressed using [zstd seekable format](https://github.com/facebook/zstd/blob/dev/contrib/seekable_f...). Built to support read-only databases for full-text search. Benchmarks are provided in README.

Of course, you may get different results with another dataset.

gzip (zlib -6) [ratio=32%] [compr=35Mo/s] [dec=407Mo/s]

zstd (zstd -2) [ratio=32%] [compr=356Mo/s] [dec=1067Mo/s]

NB1: The default for zstd is -3, but the table only had -2. The difference is probably small. The range is 1-22 for zstd and 1-9 for gzip.

NB2: The default program for gzip (at least with Debian) is the executable from zlib. With my workflows, libdeflate-gzip iscompatible and noticably faster.

NB3: This benchmark is 2 years old. The latest releases of zstd are much better, see https://github.com/facebook/zstd/releases

For a high compression, according to this benchmark xz can do slightly better, if you're willing to pay a 10× penalty on decompression.

xz -9 [ratio=23%] [compr=2.6Mo/s] [dec=88Mo/s]

zstd -9 [ratio=23%] [compr=2.6Mo/s] [dec=88Mo/s]