isa-l
ratarmount
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isa-l | ratarmount | |
---|---|---|
5 | 10 | |
904 | 628 | |
2.8% | - | |
8.6 | 8.6 | |
29 days ago | 6 days ago | |
C | Python | |
GNU General Public License v3.0 or later | MIT License |
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isa-l
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Intel QuickAssist Technology Zstandard Plugin for Zstandard
For using accelerators (QAT, I assume, because the article is about this) from the CLI, then QATzip[3] comes with a command line tool qatzip which can be used as described in the project ReadMe. I didn't test it, though, as I have no QAT-enabled device.
[1] https://github.com/intel/isa-l/tree/master/igzip
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iHaveNoReasonToDoThisOtherThanBraggingRights
Ex 1: https://github.com/intel/isa-l/blob/master/README.md
- Pigz: Parallel gzip for modern multi-processor, multi-core machines
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At least college isn't making me learn Objective-C.
Examples: - Someone I know created machine-optimized library in c and asm to accelerate compression, erasure coding, and encryption on Intel Xeon CPUs (https://github.com/intel/isa-l) which runs those ops WAY faster than the standard linux libraries. - My friend is making a retro SEGA genesis game using a C and asm dev kit (https://github.com/Stephane-D/SGDK)
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How Much Faster Is Making a Tar Archive Without Gzip?
igzip (https://github.com/intel/isa-l) is much faster than gzip or pigz when it comes to decompression, 2-3x in my experience. There is also a Python module (isal) that provides a GzipFile-like wrapper class, for an easy speed-up of Python scripts that read gzipped files.
However, it only supports up to level 3 when compressing data, so it can't be used as a drop-in replacement for gzip. You also need to make sure to use the latest version if you are going to use it in the context of bioinformatics, since older versions choke on concatenated gzip files common in that field.
ratarmount
- Ratarmount: Access large archives as a filesystem efficiently
- Show HN: Rapidgzip – Parallel Gzip Decompressing with 10 GB/S
- Ratarmount: Random Access Tar Mount
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Ask HN: Most interesting tech you built for just yourself?
This is basically the same reason why I started with ratarmount (https://github.com/mxmlnkn/ratarmount) but the focus was more on runtime performance and random access and as the name suggests it started out with access to recursive tar archives. The current version should also work for your use case with recursive zips.
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Looking for advice uploading data while at uni. I need to split the data i need to upload to carry it with me
As an added complication this would need to work under windows (i need onenote and that's win only :/ ) ; this alone makes the majority of solutions that i came up with impossible. One way could've been splitting the data onto various tar files and then mounting those with rartarmount but...linux only :( .
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How Much Faster Is Making a Tar Archive Without Gzip?
Pragzip actually decompress in parallel and also access at random. I did a Show HN here: https://news.ycombinator.com/item?id=32366959
indexed_gzip https://github.com/pauldmccarthy/indexed_gzip can also do random access but is not parallel.
Both have to do a linear scan first though. The implementations however can do the linear scan on-demand, i.e., they scan only as far as needed.
bzip2 works very well with this approach. xz only works with this approach when compressed with multiple blocks. Similar is true for zstd.
For zstd, there also exists a seekable variant, which stores the block index at the end as metadata to avoid the linear scan. indexed_zstd offers random access to those files https://github.com/martinellimarco/indexed_zstd
I wrote pragzip and also combined all of the other random access compression backends in ratarmount to offer random access to TAR files that is magnitudes faster than archivemount: https://github.com/mxmlnkn/ratarmount
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Ratarmount – Fast transparent access to archives through FUSE
Or via the experimental AppImage I created this week:
wget -O ratarmount 'https://github.com/mxmlnkn/ratarmount/releases/download/v0.10.0/ratarmount-manylinux2014_x86_64.AppImage'
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Hop: 25x faster than unzip and 10x faster than tar at reading individual files
I've recently been looking into this same issue because I analyse a lot of data like sosreports or other tar/compressed data from customer systems. Currently I untar these onto my zfs filesystem which works out OK because it has zstd compression enabled but I end up decompressing and recompressing which is quite expensive as often the files are GBs or more compressed.
But I've started using a tool called "ratarmount" (https://github.com/mxmlnkn/ratarmount) which creates an index once (and something I could automate our upload system to generate in advance, but you can also just process it lcoally) and then lets you fuse mount the file. This works pretty great with the only exception that I can't create scratch files inside the directory layout which in the past I'd wanted to do.
I was surprised how hard a problem to solve it is to get a bundle file format that is indexable and compressed with a good and fast compression algorithm which mostly boils down to zstd at this point.
While it works quite well, especially with gzip and bzip2, sadly the zstd and xz (and some other compression formats) don't allow for decompressing only parts of a file by default, even though it's possible the default tools aren't doing it. The nitty gritty details are summarised here:
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Is there a way to accelerate extracting .tar contents?
Well, you could try to skip extraction and access the tar archive using ratarmount, and stack overlayfs on top to allow writing, but that will have an impact on compilation time.
What are some alternatives?
solaris-userland - Open Source software in Solaris using gmake based build system to drive building various software components.
tarindexer - python module for indexing tar files for fast access
pigz - A parallel implementation of gzip for modern multi-processor, multi-core machines.
asar - Simple extensive tar-like archive format with indexing
DirectStorage - DirectStorage for Windows is an API that allows game developers to unlock the full potential of high speed NVMe drives for loading game assets.
PyFilesystem2 - Python's Filesystem abstraction layer
QATzip - Compression Library accelerated by Intel® QuickAssist Technology
InstaPy - 📷 Instagram Bot - Tool for automated Instagram interactions
lib842
pixz - Parallel, indexed xz compressor
rapidgzip - Gzip Decompression and Random Access for Modern Multi-Core Machines
icoextract - Extract icons from Windows PE files (.exe/.dll)