The Problem
Fossil has a delta compression feature which removes redundant information from a file — with respect to the version checked in at the tip of the current working branch — when checking in a subsequent version.¹ That delta is then zlib-compressed before being stored in the Fossil repository database file.
Storing pre-compressed data files in a Fossil repository defeats both of these space-saving measures:
Binary data compression algorithms — whether lossless as with zlib or lossy as with JPEG — turn the file data into pseudorandom noise.²
Typical data compression algorithms are not hash functions, where the goal is that a change to each bit in the input has a statistically even chance of changing every bit in the output, but because they do approach that pathological condition, pre-compressed data tends to defeat Fossil’s delta compression algorithm, there being so little correlation between two different outputs from the binary data compression algorithm.
An ideal lossless binary data compression algorithm cannot be applied more than once to make the data even smaller, since random noise is incompressible. The consequence for our purposes here is that pre-compressed data doesn’t benefit from Fossil’s zlib compression.
You might then ask, what does it matter if the space savings comes from the application file format (e.g. JPEG, Zip, etc.) or from Fossil itself? It really doesn’t, as far as point 2 above goes, but point 1 causes the Fossil repository to balloon out of proportion to the size of the input data change on each checkin. This article will illustrate that problem, quantify it, and give a solution to it.
Affected File Formats
In this article’s core experiment, we use 2D image file formats, but this article’s advice also applies to many other file types. For just a few examples out of what must be thousands:
Microsoft Office: The OOXML document format used from Office 2003 onward (
.docx
,.xlsx
,.pptx
, etc.) are Zip files containing an XML document file and several collateral files.Libre Office: Its ODF format is designed in more or less the same way as OOXML.
Java: A Java
.jar
file is a Zip file containing JVM.class
files, manifest files, and more.Windows Installer: An
*.msi
file is a proprietary database format that contains, among other things, Microsoft Cabinet-compressed files, which in turn may hold Windows executables, which may themselves be compressed.SVG, PDF, TIFF, etc.: Many file formats are available in both compressed and uncompressed forms. You should use the uncompressed form with Fossil wherever practical, as we will show below.
Demonstration
The companion image-format-vs-repo-size.ipynb
file (download,
preview) is a Jupyter notebook implementing the following
experiment:
Create an empty Fossil repository; save its initial size.
Use ImageMagick via Wand to generate a JPEG file of a particular size — currently 256 px² — filled with Gaussian noise to make data compression more difficult than with a solid-color image.
Check that image into the new Fossil repo, and remember that size.
Change a random pixel in the image to a random RGB value, save that image, check it in, and remember the new Fossil repo size.
Iterate on step 4 some number of times — currently 10 — and remember the Fossil repo size at each step.
Repeat the above steps for BMP, TIFF,³ and PNG.
Create a bar chart showing how the Fossil repository size changes with each checkin.
We chose to use Jupyter for this because it makes it easy for you to
modify the notebook to try different things. Want to see how the
results change with a different image size? Easy, change the size
value in the second cell of the notebook. Want to try more image
formats? You can put anything ImageMagick can recognize into the
formats
list. Want to find the break-even point for images like those
in your own repository? Easily done with a small amount of code.
Results
Running the notebook gives a bar chart something like⁴ this:
There are a few key things we want to draw your attention to in that chart:
BMP and uncompressed TIFF are nearly identical in size for all checkins, and the repository growth rate is negligible.⁵ We owe this economy to Fossil’s delta compression feature.
The JPEG and TIFF bars increase by large amounts on most checkins even though each checkin encodes only a single-pixel change!
Because JPEG’s lossy nature allows it to start smaller and have smaller size increases than than PNG, the crossover point with BMP/TIFF isn’t until 7-9 checkins in typical runs of this Monte Carlo experiment. Given a choice among these four file formats and a willingness to use lossy image compression, a rational tradeoff is to choose JPEG for repositories where each image will change fewer than that number of times.
Automated Recompression
Since programs that produce and consume binary-compressed data files
often make it either difficult or impossible to work with the
uncompressed form, we want an automated method for producing the
uncompressed form to make Fossil happy while still having the compressed
form to keep our content creation applications happy. This Makefile
should⁶ do that for BMP, PNG, SVG, and XLSX files:
.SUFFIXES: .bmp .png .svg .svgz
.svgz.svg:
gzip -dc < $< > $@
.svg.svgz:
gzip -9c < $< > $@
.bmp.png:
convert -quality 95 $< $@
.png.bmp:
convert $< $@
SS_FILES := $(wildcard spreadsheet/*)
all: $(SS_FILES) illus.svg image.bmp doc-big.pdf
reconstitute: illus.svgz image.png
( cd spreadsheet ; zip -9 ../spreadsheet.xlsx) * )
qpdf doc-big.pdf doc-small.pdf
$(SS_FILES): spreadsheet.xlsx
unzip $@ -d $<
doc-big.pdf: doc-small.pdf
qpdf --stream-data=uncompress $@ $<
This Makefile
allows you to treat the compressed version as the
process input, but to actually check in only the changes against the
uncompressed version by typing “make
” before “fossil ci
”. This is
not actually an extra step in practice, since if you’ve got a
Makefile
-based project, you should be building (and testing!) it
before checking each change in anyway!
Because this technique is based on dependency rules, only the necessary
files are generated on each make
command.
You only have to run “make reconstitute
” once after opening a fresh
Fossil checkout to produce those compressed sources. After that, you
work with the compressed files in your content creation programs. Your
build system might include some kind of bootstrapping or
auto-configuration step that you could attach this to, so that it
doesn’t need to be run by hand.
This Makefile
illustrates two primary strategies:
Input and Output File Formats Differ by Extension
In the case of SVG and the bitmap image formats, the file name extension
differs between the cases, so we can use make
suffix rules to get the
behavior we want. The top half of the Makefile
just tells make
how
to map from *.svg
to *.svgz
and vice versa, and the same for *.bmp
to/from *.png
.
Input and Output Use the Same Extension
We don’t have that luxury for Excel and PDF files, each for a different reason:
Excel: Excel has no way to work with the unpacked Zip file contents at all, so we have to unpack it into a subdirectory, which is what we check into Fossil. On making a fresh Fossil checkout, we have to pack that subdirectory’s contents back up into an
*.xlsx
file with “make reconstitute
” so we can edit it with Excel again.PDF: All PDF readers can display an uncompressed PDF file, but many PDF-producing programs have no option for uncompressed output. Since the file name extension is the same either way, we treat the compressed PDF as the source to the process, yielding an automatically-uncompressed PDF for the benefit of Fossil. Unlike with the Excel case, there is no simple “file base name to directory name” mapping, so we just created the
-big
to-small
name scheme here.
Footnotes and Digressions
Several other programs also do delta compression, so they’ll also be affected by this problem: rsync, Unison, Git, etc. When using file copying and synchronization programs without delta compression, it’s best to use the most highly-compressed file format you can tolerate, since they copy the whole file any time any bit of it changes.
In fact, a good way to gauge the effectiveness of a given compression scheme is to run its output through the same sort of tests we use to gauge how “random” a given PRNG is. Another way to look at it is that if there is a discernible pattern in the output of a compression scheme, it’s information that could be further compressed.
We're using uncompressed TIFF here, not LZW- or Zip-compressed TIFF, either of which would give similar results to PNG, which is always zlib-compressed.
The raw data changes somewhat from one run to the next due to the use of random noise in the image to make the zlib/PNG compression more difficult, and the random pixel changes. Those test design choices make this a Monte Carlo experiment. We’ve found that the overall character of the results doesn’t change from one run to the next.
The code in the notebook’s third cell drops the first three columns of data because the first column (the empty repository size) is boring, and the subsequent two checkins show the SQLite DB file format settling in with its first few checkins. There’s a single line in the notebook you can comment out to get a bar chart with these data included.
If you do this, you’ll see a mildly interesting result: the size of the first checkin in the BMP and TIFF cases is roughly the same as that for the PNG case, because both PNG and Fossil use the zlib binary data compression algorithm.
A low-tech format like BMP will have a small edge in practice because TIFF metadata includes the option for multiple timestamps, UUIDs, etc., which bloat the checkin size by creating many small deltas. If you don't need the advantages of TIFF, a less capable image file format will give smaller checkin sizes for a given amount of change.
The
Makefile
above is not battle-tested. Please report bugs and needed extensions on the forum.