Evaluate different compression tools and their settings by running them on a sample of data.
This utility has many system dependencies, so the easiest way to run it is via Docker:
$ docker pull jdleesmiller/compare_compressors
Generally you will run a
compare step, followed by a
This step runs the compressors on the sample files and saves the results to a CSV. Assuming that your sample files are in a folder called
data in the current directory, and they are called
test2, etc.., the command would look like:
docker run --rm \ --volume `pwd`/data:/home/app/compare_compressors/data:ro \ --volume /tmp:/tmp \ # optional jdleesmiller/compare_compressors compare data/test* >data/compare.csv
--rmflag tells docker to remove the container when it's finished.
--volume `pwd`/data:/home/app/compare_compressors/data:roflag mounts
./dataon the host inside the container, so the utility can access the sample files. The trick here is that
/home/app/compare_compressorsis the utility's working directory inside the container, so the relative paths
data/test*for the sample files will be the same both inside and outside of the container. The
:romakes it a read only mount; this is optional, but it provides added assurance that the utility won't change your data files.
--volume /tmp:/tmpflag is optional but may improve performance. The utility does its compression and decompression in
/tmpinside the container, and all of the writes inside the container go through Docker's union file system. By mounting
/tmpon the host, we bypass the union file system. (Ideally, we'd just do this in the Dockerfile, but unfortunately it's 10x slower on Docker for Mac; hopefully that will improve soon.)
Once you've generated a CSV with results, the tool can read the CSV and generate a
gnuplot script to plot the results. Note that you need to have
gnuplot installed on the host for this to work.
There are several plotting commands:
plot gives you a 2D plot of compression time vs compressed size. There is also a
--decompression option to plot decompression time vs compressed size instead.
docker run --rm \ --volume `pwd`/data:/home/app/compare_compressors/data:ro \ --volume /tmp:/tmp \ jdleesmiller/compare_compressors plot data/compare.csv | gnuplot
plot_costs command takes three cost coefficients: cost per GiB of stored data, cost per hour to run the compression program, and cost per hour to run the decompression program. The program then computes a simple linear cost function. To keep the plot in 2D, the two time costs are added together.
docker run --rm \ --volume `pwd`/data:/home/app/compare_compressors/data:ro \ --gibyte-cost 56.05 \ --compression-hour-cost 32.35 \ --decompression-hour-cost 177.91 \ --currency '£' \ jdleesmiller/compare_compressors plot_costs data/compare.csv | gnuplot
Print a list of the compressors and settings in descending order by cost. The cost function is of the same form as for
docker run --rm \ --volume `pwd`/data:/home/app/compare_compressors/data \ --gibyte-cost 56.05 \ --compression-hour-cost 32.35 \ --decompression-hour-cost 177.91 \ --currency '£' \ jdleesmiller/compare_compressors summarize data/compare.csv
/usr/bin/time utility is required, along with several system packages. See the Dockerfile for a list of the packages that this utility depends on. To make the plot, you will also need
If you are installing natively, without docker, you will need ruby and then to install the gem:
$ gem install compare_compressors
For development, you will probably want (1) override the default entrypoint and (2) mount the application root inside the container. To run the tests, for example:
docker run --rm -it --entrypoint='' \ --volume=compare_compressors_bundle:/home/app/compare_compressors/.bundle \ --volume=`pwd`:/home/app/compare_compressors \ compare_compressors bundle exec rake
The only caveat is that you need to preserve the
.bundle folder inside the container by mounting it as a volume; the above command does this using a named volume,
compare_compressors_bundle, which will persist between runs and be easier to identify in the
docker volume ls output.
- See this blog post for an example of how to use the tool.
- For many more compression algorithms, see https://quixdb.github.io/squash-benchmark/
(The MIT License)
Copyright (c) 2017 John Lees-Miller
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the 'Software'), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
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