indexed_gzip VS rapidgzip

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

The pieces are there. https://github.com/devsnd/tarindexer/blob/master/tarindexer.py is a prototype of indexing and seeking a tar file in python. https://github.com/pauldmccarthy/indexed_gzip allows indexing and seeking a gzip file. If those pieces of code were combined it could give you efficient targeted file extraction, but you'd need to find a coder with enough time and motivation to fuss with it.

I also did benchmarks with zlib and libarchivemount via their library interface here [0]. It has been a while that I have run them, so I forgot. Unfortunately, I did not add libdeflate.

[0] https://github.com/mxmlnkn/rapidgzip/blob/master/src/benchma...

Hi, author here.

You are right in the index being the easy-mode. Over the years there have been lots of implementations trying to add an index like that to the gzip metadata itself or as a sidecar file, with bgzip probably being the most known one. None of them really did stick, hence the necessity for some generic multi-threaded decompressor. A probably incomplete list of such implementations can be found in this issue: https://github.com/mxmlnkn/rapidgzip/issues/8

The index makes it so easy that I can simply delegate decompression to zlib. And since paper publication I've actually improved upon this by delegating to ISA-l / igzip instead, which is twice as fast. This is already in the 0.8.0 release.

As derived from table 1, the false positive rate is 1 Tbit / 202 = 5 Gbit or 625 MB for deflate blocks with dynamic Huffman code. For non-compressed blocks, the false positive rate is roughly one per 500 KB, however non-compressed blocks can basically be memcpied or skipped over and then the next deflate header can be checked without much latency. On the other hand, for dynamic blocks, the whole block needs to be decompressed first to find the next one. So the much higher false positive rate for non-compressed blocks doesn't introduce that much overhead.

I have some profiling built into rapidgzip, which is printed with -v, e.g., rapidgzip -v -d -o /dev/null 20xsilesia.tar.gz :

    Time spent in block finder              : 0.227751 s

I have not only implemented parallel decompression but also random access to offsets in the stream with https://github.com/mxmlnkn/pragzip I did some benchmarks on some really beefy machines with 128 cores and was able to reach almost 20 GB/s decompression bandwidth. The single-core decoder has lots of potential for optimization because I had to write it from scratch, though.

Decompression of arbitrary gzip files can be parallelized with pragzip: https://github.com/mxmlnkn/pragzip

At the very least you are duplicating logic without the exception. The check for eof has to be done implicitly anyway inside read because it has to fill the bit buffer with data from the byte buffer or the byte buffer with data from the file. And if both fail, then we already know the result of eof, so no need to duplicate checking for eof in the outer read calling loop.

Here is the full commit with ad-hoc benchmark results in the commit message:

https://github.com/mxmlnkn/pragzip/commit/0b1af498377838c30f...

and here the benchmarks I ran at that time:

https://github.com/mxmlnkn/pragzip/blob/0b1af498377838c30fea...

As you can see, it's part of my random-seekable multi-threaded gzip and bzip2 parallel decompression libraries.

What you can also see in the commit message is that it wasn't a 50% time reduction but a 50% bandwidth increase, which would translate to a 30% time reduction. It seems I remembered that partly wrong. But it still was a significant optimization for me.