ChopZip: a parallel implementation of arbitrary compression algorithms

Remember plzma.py? I made a wrapper script for running [[LZMA]] in parallel. The script could be readily generalized to use any compression algorithm, following the principle of breaking the file in parts (one per CPU), compressing the parts, then [[tar (file format)|tarring]] them together. In other words, chop the file, zip the parts. Hence the name of the program that evolved from plzma.py: ChopZip.

Introduction

Currently ChopZip supports [[LZMA|lzma]], [[XZ Utils|xz]], [[gzip]] and lzip. Of them, lzip deserves a brief comment. It was brought to my attention by the a reader of this blog. It is based on the LZMA algorithm, as are lzma and xz. Apparently unlike them, multiple files compressed with lzip can be concatenated to form a single valid lzip-compressed file. Uncompressing the latter generates a concatenation of the formers.

To illustrate the point, check the following shell action:

% echo hello > head
% echo bye > tail
% lzip head
% lzip tail
% cat head.lz tail.lz > all.lz
% lzip -d all.lz
% cat all
hello
bye

However, I just discovered that all gzip, bzip2 and xz do that already! It seems that lzma is advertised as capable of doing it, but it doesn’t work for me. Sometimes it will uncompress the concatenated file to the original file just fine, others it will decompress it to just the first chunk of the set, yet other times it will complain that the “data is corrupt” and refuse to uncompress. For that reason, chopzip will accept two working modes: simple concatenation (gzip, lzip, xz) and tarring (lzma). The relevant mode will be used transparently for the user.

Also, if you use Ubuntu, this bug will apply to you, making it impossible to have xz-utils, lzma and lzip installed at the same time.

The really nice thing about concatenability is that it allows for trivial parallelization of the compression, while maintaining compatibility with the serial compression tool, which can still uncompress the product of a parallel compression. Unfortunatelly, for non-concatenatable compression formats, the output of chopzip will be a tar file of the compressed chunks, making it imposible to uncompress with the original compressor alone (first an untar would be needed, then uncompressing, then concatenation of chunks. Or just use chopzip to decompress).

The rationale behind plzma/chopzip is simple: multi-core computers are commonplace nowadays, but still the most common compression programs do not take advantage of this fact. At least the ones that I know and use don’t. There are at least two initiatives that tackle the issue, but I still think ChopZip has a niche to exploit. The most consolidated one is pbzip2 (which I mention in my plzma post). pbzip2 is great, if you want to use bzip2. It scales really nicely (almost linearly), and pbzipped files are valid bzip2 files. The main drawback is that it uses bzip2 as compression method. bzip2 has always been the “extreme” bother of gzip: compresses more, but it’s so slow that you would only resort to it if compression size is vital. LZMA-based programs (lzma, xz, lzip) are both faster, and even compress more, so for me bzip2 is out of the equation.

A second contender in parallel compression is pxz. As its name suggests, it compresses in using xz. Drawbacks? it’s not in the official repositories yet, and I couldn’t manage to compile it, even if it comprises a single C file, and a Makefile. It also lacks ability to use different encoders (which is not necessarily bad), and it’s a compiled program, versus chopzip, which is a much more portable script.

Scalability benchmark

Anyway, let’s get into chopzip. I have run a simple test with a moderately large file (a 374MB tar file of the whole /usr/bin dir). A table follows with the speedup results for running chopzip on that file, using various numbers of chunks (and consequently, threads). The tests were conducted in a 4GB RAM Intel Core 2 Quad Q8200 computer. Speedups are calculated as how many times faster did #chunks perform with respect to just 1 chunk. It is noteworthy that in every case running chopzip with a single chunk is virtually identical in performance to running the orginal compressor directly. Also decompression times (not show) were identical, irrespective of number of chunks. ChopZip version vas r18.

#chunks xz gzip lzma lzip
1 1.000 1.000 1.000 1.000
2 1.862 1.771 1.907 1.906
4 3.265 1.910 3.262 3.430
8 3.321 1.680 3.247 3.373
16 3.248 1.764 3.312 3.451

Note how increasing the number of chunks beyond the amount of actual cores (4 in this case) can have a small benefit. This happens because N equal chunks of a file will not be compressed with equal speed, so the more chunks, the smaller overall effect of the slowest-compressing chunks.

Conclusion

ChopZip speeds up quite noticeably the compression of arbitrary files, and with arbitrary compressors. In the case of concatenatable compressors (see above), the resulting compressed file is an ordinary compressed file, apt to be decompressed with the regular compressor (xz, lzip, gzip), as well as with ChopZip. This makes ChopZip a valid alternative to them, with the parallelization advantage.

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