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Prevent failure when offset is not a multiple of page size. Add chunk percentage complete to output. Tweak output at various verbosities. Update documentation to reflect improved performance of unlimited mode. Update benchmark results. More tidying.
127 lines
5.6 KiB
Plaintext
127 lines
5.6 KiB
Plaintext
The first comparison is that of a linux kernel tarball (2.6.31). In all cases
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the default options were used. 3 other common compression apps were used for
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comparison, 7z which is an excellent all-round lzma based compression app,
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gzip which is the benchmark fast standard that has good compression, and bzip2
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which is the most common linux used compression.
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In the following tables, lrzip means lrzip default options, lrzip -l means
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lrzip using the lzo backend, lrzip -g means using the gzip backend,
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lrzip -b means using the bzip2 backend and lrzip -z means using the zpaq
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backend.
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linux-2.6.31.tar
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These are benchmarks performed on a 3GHz quad core Intel Core2 with 8GB ram
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using lrzip v0.42.
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Compression Size Percentage Compress Decompress
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None 365711360 100
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7z 53315279 14.6 2m4.770s 0m5.360s
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lrzip 52372722 14.3 2m48.477s 0m8.336s
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lrzip -z 43455498 11.9 10m11.335 10m14.296
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lrzip -l 112151676 30.7 0m14.913s 0m5.063s
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lrzip -g 73476127 20.1 0m29.628s 0m5.591s
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lrzip -b 60851152 16.6 0m43.539s 0m12.244s
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bzip2 62416571 17.1 0m44.493s 0m9.819s
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gzip 80563601 22.0 0m14.343s 0m2.781s
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These results are interesting to note the compression of lrzip by default is
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only slightly better than lzma, but at some cost in time at the compress and
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decompress end of the spectrum. Clearly zpaq compression is much better than any
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other compression algorithm by far, but the speed cost on both compression and
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decompression is extreme. At this size compression, lzo is interesting because
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it's faster than simply copying the file but only offers modest compression.
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What lrzip offers at this end of the spectrum is extreme compression if
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desired.
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Let's take six kernel trees one version apart as a tarball, linux-2.6.31 to
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linux-2.6.36. These will show lots of redundant information, but hundreds
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of megabytes apart, which lrzip will be very good at compressing. For
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simplicity, only 7z will be compared since that's by far the best general
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purpose compressor at the moment:
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These are benchmarks performed on a 2.53Ghz dual core Intel Core2 with 4GB ram
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using lrzip v0.5.1. Note that it was running with a 32 bit userspace so only
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2GB addressing was posible. However the benchmark was run with the -U option
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allowing the whole file to be treated as one large compression window.
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Tarball of 6 consecutive kernel trees.
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Compression Size Percentage Compress Decompress
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None 2373713920 100
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7z 344088002 14.5 17m26s 1m22s
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lrzip -U 73356070 3.1 08m53s 43s
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lrzip -Ul 158851141 6.7 04m31s 35s
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Things start getting very interesting now when lrzip is really starting to
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shine. Note how it's not that much larger for 6 kernel trees than it was for
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one. That's because all the similar data in both kernel trees is being
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compressed as one copy and only the differences really make up the extra size.
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All compression software does this, but not over such large distances. If you
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copy the same data over multiple times, the resulting lrzip archive doesn't
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get much larger at all.
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Using the first example (linux-2.6.31.tar) and simply copying the data multiple
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times over gives these results with lrzip(lzo):
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Copies Size Compressed Compress Decompress
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1 365711360 112151676 0m14.913s 0m5.063s
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2 731422720 112151829 0m16.174s 0m6.543s
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3 1097134080 112151832 0m17.466s 0m8.115s
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I had the amusing thought that this compression software could be used as a
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bullshit detector if you were to compress people's speeches because if their
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talks were full of catchphrases and not much actual content, it would all be
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compressed down. So the larger the final archive, the less bullshit =)
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Now let's move on to the other special feature of lrzip, the ability to
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compress massive amounts of data on huge ram machines by using massive
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compression windows. This is a 10GB virtual image of an installed operating
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system and some basic working software on it. The default options on the
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8GB machine meant that it was using a 5 GB window.
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10GB Virtual image:
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These benchmarks were done on the quad core with version 0.5.1
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Compression Size Percentage Compress Time Decompress Time
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None 10737418240 100.0
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gzip 2772899756 25.8 05m47.35s 2m46.77s
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bzip2 2704781700 25.2 16m15.603s 6m19.718s
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xz 2272322208 21.2 50m58.437s 3m52.734s
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7z 2242897134 20.9 26m36.333s 5m41.198s
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lrzip 1354237684 12.6 29m13.402s 6m55.441s
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lrzip -M 1079528708 10.1 23m44.226s 4m05.461s
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lrzip -l 1793312108 16.7 05m13.246s 3m12.886s
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lrzip -lM 1413268368 13.2 04m18.338s 2m54.650s
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lrzip -z 1299844906 12.1 04h32m14s 04h33m
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lrzip -zM 1066902006 9.9 04h07m14s 04h08m
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At this end of the spectrum things really start to heat up. The compression
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advantage is massive, with the lzo backend even giving much better results than
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7z, and over a ridiculously short time. The default lzma backend is slightly
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slower than 7z, but provides a lot more compression. What appears to be a big
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disappointment is actually zpaq here which takes more than 8 times longer than
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lzma for a measly .2% improvement. The reason is that most of the advantage here
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is achieved by the rzip first stage since there's a lot of redundant space over
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huge distances on a virtual image. The -M option which works the memory
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subsystem rather hard making noticeable impact on the rest of the machine also
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does further wonders for the compression and times.
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This should help govern what compression you choose. Small files are nicely
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compressed with zpaq. Intermediate files are nicely compressed with lzma.
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Large files get excellent results even with lzo provided you have enough ram.
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(Small being < 100MB, intermediate <1GB, large >1GB).
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Or, to make things easier, just use the default settings all the time and be
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happy as lzma gives good results. :D
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Con Kolivas
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Tue, 5th Nov 2010
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