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The first comparison is that of a linux kernel tarball (2.6.37). In all cases
the default options were used. 4 other common compression apps were used for
comparison, 7z which is an excellent all-round lzma based compression app,
gzip which is the benchmark fast standard that has good compression, and bzip2
which is the most common linux used compression. xz was included for
completeness.
In the following tables, lrzip means lrzip default options, lrzip -l means
lrzip using the lzo backend, lrzip -g means using the gzip backend,
lrzip -b means using the bzip2 backend and lrzip -z means using the zpaq
backend.
linux-2.6.37.tar
These are benchmarks performed on a 3GHz quad core Intel Core2 with 8GB ram
using lrzip v0.612 on an SSD drive.
Compression Size Percentage Compress Decompress
None 430612480 100
7z 63636839 14.8 2m28s 0m6.6s
xz 63291156 14.7 4m02s 0m8.7
lrzip 64561485 14.9 1m12s 0m4.3s
lrzip -z 51588423 12.0 2m02s 2m08s
lrzip -l 137515997 31.9 0m14s 0m2.7s
lrzip -g 86142459 20.0 0m17s 0m3.0s
lrzip -b 72103197 16.7 0m21s 0m6.5s
bzip2 74060625 17.2 0m48s 0m12.8s
gzip 94512561 21.9 0m17s 0m4.0s
These results are interesting to note the compression of lrzip by default is
about the same as 7z, but it's significantly faster thanks to its heavily
multithreaded nature. Zpaq offers by far the best compression but at the cost
of extra time. However with the heavily threaded nature of lrzip, it's not a lot
longer given how much better its compression is. It's actually faster than xz
on compression on a quad core machine.
Let's take six kernel trees one version apart as a tarball, linux-2.6.31 to
linux-2.6.36. These will show lots of redundant information, but hundreds
of megabytes apart, which lrzip will be very good at compressing. For
simplicity, only 7z will be compared since that's by far the best general
purpose compressor at the moment:
These are benchmarks performed on a 2.53Ghz dual core Intel Core2 with 4GB ram
using lrzip v0.5.1. Note that it was running with a 32 bit userspace so only
2GB addressing was posible. However the benchmark was run with the -U option
allowing the whole file to be treated as one large compression window.
Tarball of 6 consecutive kernel trees.
Compression Size Percentage Compress Decompress
None 2373713920 100
7z 344088002 14.5 17m26s 1m22s
lrzip 104874109 4.4 11m37s 56s
lrzip -l 223130711 9.4 05m21s 1m01s
lrzip -U 73356070 3.1 08m53s 43s
lrzip -Ul 158851141 6.7 04m31s 35s
lrzip -Uz 62614573 2.6 24m42s 25m30s
Things start getting very interesting now when lrzip is really starting to
shine. Note how it's not that much larger for 6 kernel trees than it was for
one. That's because all the similar data in both kernel trees is being
compressed as one copy and only the differences really make up the extra size.
All compression software does this, but not over such large distances. If you
copy the same data over multiple times, the resulting lrzip archive doesn't
get much larger at all. You might find this example interesting because the
-U option is actually faster as well as providing better compression. The
reason is that the window is not much larger than the amount of ram addressable
(2GB), and it compresses so much more in the rzip stage that it makes up the
time by not needing to compress anywhere near as much data with the backend
compressor.
Using the first example (linux-2.6.31.tar) and simply copying the data multiple
times over gives these results with lrzip(lzo):
Copies Size Compressed Compress Decompress
1 365711360 112151676 0m14.9s 0m5.1s
2 731422720 112151829 0m16.2s 0m6.5s
3 1097134080 112151832 0m17.5s 0m8.1s
I had the amusing thought that this compression software could be used as a
bullshit detector if you were to compress people's speeches because if their
talks were full of catchphrases and not much actual content, it would all be
compressed down. So the larger the final archive, the less bullshit =)
Now let's move on to the other special feature of lrzip, the ability to
compress massive amounts of data on huge ram machines by using massive
compression windows. This is a 10GB virtual image of an installed operating
system and some basic working software on it. The default options on the
8GB machine meant that it was using a 5 GB window.
10GB Virtual image:
These benchmarks were done on the quad core with version 0.612
Compression Size Percentage Compress Time Decompress Time
None 10737418240 100.0
gzip 2772899756 25.8 05m47s 2m46s
bzip2 2704781700 25.2 16m15s 6m19s
xz 2272322208 21.2 50m58s 3m52s
7z 2242897134 20.9 26m36s 5m41s
lrzip 1372218189 12.8 10m23s 2m53s
lrzip -U 1095735108 10.2 08m44s 2m45s
lrzip -l 1831894161 17.1 04m53s 2m37s
lrzip -lU 1414959433 13.2 04m48s 2m38s
lrzip -zU 1067169419 9.9 39m32s 39m46s
At this end of the spectrum things really start to heat up. The compression
advantage is massive, with the lzo backend even giving much better results than
7z, and over a ridiculously short time. The improvements in version 0.530 in
scalability with multiple CPUs has a huge impact on compression time here,
with zpaq almost being faster on quad core than xz is, yet producing a file
less than half the size.
What appears to be a big disappointment is actually zpaq here which takes more
than 4 times longer than r/lzma for a measly .3% improvement. The reason is that
most of the advantage here is achieved by the rzip first stage since there's a
lot of redundant space over huge distances on a virtual image. The -U option
which works the memory subsystem rather hard making noticeable impact on the
rest of the machine also does further wonders for the compression (virtually
always) and even the times in this particular case.
This should help govern what compression you choose. Small files are nicely
compressed with zpaq. Intermediate files are nicely compressed with lzma.
Large files get excellent results even with lzo provided you have enough ram.
(Small being < 100MB, intermediate <1GB, large >1GB).
Or, to make things easier, just use the default settings all the time and be
happy as lzma gives good results. :D
Con Kolivas
Fri, 17 Mar 2011
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