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Overview
| Comment: | Updated the "Image Format vs Fossil Repo Size" doc and its associated notebook and SVG file: smarter initial repo size handling so we don't have to throw away the first 3 rows of data; now works with Anaconda, allowing simpler local replication of results; using /tmp for the test instead of relying on "open --nested" to protect us from running the experiment in-tree; clarified discussion of results. |
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f281b3dfb794f0b9695dfaa19a98f920 |
| User & Date: | wyoung 2020-06-26 21:49:56 |
Context
|
2020-06-26
| ||
| 23:06 | Attempt to improve the look of the forum when using the 'eagle' skin. (check-in: 9cb1556e user: mistachkin tags: trunk) | |
| 21:49 | Updated the "Image Format vs Fossil Repo Size" doc and its associated notebook and SVG file: smarter initial repo size handling so we don't have to throw away the first 3 rows of data; now works with Anaconda, allowing simpler local replication of results; using /tmp for the test instead of relying on "open --nested" to protect us from running the experiment in-tree; clarified discussion of results. (check-in: f281b3df user: wyoung tags: trunk) | |
|
2020-06-25
| ||
| 13:32 | Add a link to the built-in help to the permuted documentation index. (check-in: db90281c user: drh tags: trunk) | |
Changes
Changes to www/image-format-vs-repo-size.ipynb.
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"# Image Format vs Fossil Repository Size\n",
"\n",
"## Prerequisites\n",
"\n",
"This notebook was developed with [JupyterLab][jl]. To follow in my footsteps, install that and the needed Python packages:\n",
"\n",
" $ pip install jupyterlab matplotlib pandas wand\n",
"\n",
"In principle, it should also work with [Anaconda Navigator][an], but because [Wand][wp] is not currently in the Anaconda base package set, you may run into difficulties making it work, as we did on macOS. There seems to be some sandboxing that causes problems with OS interaction in that environment. Therefore, we recommend using straight JupyterLab.\n",
"\n",
"This notebook was originally written for the Python 2 kernel because macOS does not include Python 3, but it was later updated for Python 3. It should still be compatible with Python 2, though.\n",
"\n",
"[an]: https://www.anaconda.com/distribution/\n",
"[jl]: https://github.com/jupyterlab/\n",
"[wp]: http://wand-py.org/\n",
"\n",
"\n",
"## Running\n",
"\n",
"The next cell generates the test repositories. This takes about 45 seconds to run, primarily due to the `sleep 1` synchronization call, made 40 times in the main test loop.\n",
"\n",
"The one after that produces the bar chart from the collected data, all but instantaneously.\n",
"\n",
"This split allows you to generate the expensive experimental data in a single pass, then play as many games as you like with the generated data.\n",
"\n",
"\n",
"## Discussion\n",
"\n",
"That is kept in [a separate document](image-format-vs-repo-size.md) so we can share that document with Fossil's Markdown renderer."
................................................................................
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Experiment completed in 44.186978816986084 seconds.\n"
]
}
],
"source": [
"import os\n",
"import random\n",
"import time\n",
"\n",
"from wand.color import Color\n",
"from wand.drawing import Drawing\n",
"from wand.image import Image\n",
"\n",
"import pandas as pd\n",
"\n",
"size = 256\n",
"iterations = 10\n",
"start = time.time()\n",
"repo_sizes = []\n",
"\n",
"formats = ['JPEG', 'BMP', 'TIFF', 'PNG']\n",
"for f in formats:\n",
" ext = f.lower()\n",
" tdir = 'test' + '-' + ext\n",
" repo = tdir + '.fossil'\n",
" ifn = 'test.' + ext\n",
" ipath = os.path.join(tdir, ifn)\n",
" rs = []\n",
" \n",
" def add_repo_size():\n",
" rs.append(os.path.getsize(repo) / 1024.0 / 1024.0)\n",
"\n",
" try:\n",
" # Create test repo\n",
" if not os.path.exists(tdir): os.mkdir(tdir, 0o700)\n",
" cmd = 'cd {0} ; fossil init ../{1} && fossil open --nested ../{1} && fossil set binary-glob \"*.{2}\"'.format(\n",
" tdir, repo, ext\n",
" )\n",
" if os.system(cmd) != 0:\n",
" raise RuntimeError('Failed to create test repo ' + repo)\n",
" add_repo_size()\n",
"\n",
" # Create test image and add it to the repo\n",
" img = Image(width = size, height = size, depth = 8,\n",
" background = 'white')\n",
" img.alpha_channel = 'remove'\n",
" img.evaluate('gaussiannoise', 1.0)\n",
" img.save(filename = ipath)\n",
" cmd = 'cd {0} ; fossil add {1} && fossil ci -m \"initial\"'.format(\n",
" tdir, ifn\n",
" )\n",
" if os.system(cmd) != 0:\n",
" raise RuntimeError('Failed to add ' + ifn + ' to test repo')\n",
" #print \"Created test repo \" + repo + \" for format \" + f + \".\"\n",
" add_repo_size()\n",
"\n",
" # Change a random pixel to a random RGB value and check it in\n",
" # $iterations times.\n",
" for i in range(iterations):\n",
" with Drawing() as draw:\n",
" x = random.randint(0, size - 1)\n",
" y = random.randint(0, size - 1)\n",
"\n",
" r = random.randint(0, 255)\n",
" g = random.randint(0, 255)\n",
" b = random.randint(0, 255)\n",
................................................................................
" draw.fill_color = Color('rgb({0},{1},{2})'.format(\n",
" r, g, b\n",
" ))\n",
" draw.color(x, y, 'point')\n",
" draw(img)\n",
" img.save(filename = ipath)\n",
" \n",
" # ImageMagick appears to use some kind of asynchronous\n",
" # file saving mechanism, so we have to give it time to\n",
" # complete.\n",
" time.sleep(1.0)\n",
" \n",
" cmd = 'cd {0} ; fossil ci -m \"change {1} step {2}\"'.format(\n",
" tdir, f, i\n",
" )\n",
" if os.system(cmd) != 0:\n",
" raise RuntimeError('Failed to change ' + f + ' image, step ' + str(i))\n",
" add_repo_size()\n",
" \n",
" # Repo complete for this format\n",
" repo_sizes.append(pd.Series(rs, name=f))\n",
"\n",
" finally:\n",
" if os.path.exists(ipath): os.remove(ipath)\n",
" if os.path.exists(tdir):\n",
" os.system('cd ' + tdir + ' ; fossil close -f')\n",
" os.rmdir(tdir)\n",
" if os.path.exists(repo): os.remove(repo)\n",
" \n",
"print(\"Experiment completed in \" + str(time.time() - start) + \" seconds.\")"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
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}
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"source": [
"%config InlineBackend.figure_formats = ['svg']\n",
"\n",
"import matplotlib as mpl\n",
"import matplotlib.pyplot as plt\n",
"\n",
"# Merge per-format test data into a single DataFrame without the first\n",
"# first 3 rows: the initial empty repo state (boring) and the repo DB\n",
"# size as it \"settles\" in its first few checkins.\n",
"data = pd.concat(repo_sizes, axis=1).drop(range(3))\n",
"\n",
"mpl.rcParams['figure.figsize'] = (6, 4)\n",
"ax = data.plot(kind = 'bar', colormap = 'coolwarm',\n",
" grid = False, width = 0.8,\n",
" edgecolor = 'white', linewidth = 2)\n",
"ax.axes.set_xlabel('Checkin index')\n",
"ax.axes.set_ylabel('Repo size (MiB)')\n",
................................................................................
"version": 3
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"cell_type": "markdown",
"metadata": {},
"source": [
"# Image Format vs Fossil Repository Size\n",
"\n",
"## Prerequisites\n",
"\n",
"This notebook was originally developed with standalone [JupyterLab] and Python 2 but was later moved to JupyterLab under [Anaconda] with Python 3. Backporting to Python 2 may require manual adjustment. Getting it running under stock JupyterLab or plain-old-Jupyter should be straightforward for one familiar with the tools. We will assume you're following in my footsteps, using Anaconda.\n",
"\n",
"One of the reasons we switched to Anaconda is that it comes with all but one of this notebook's prerequisites, that last remaining one of which you install so:\n",
"\n",
" $ pip install wand\n",
"\n",
"That should be done in a shell where \"`pip`\" is the version that came with Anaconda. Otherwise, the package will likely end up in some *other* Python package tree, which Anaconda's Python kernel may not be smart enough to find on its own.\n",
"\n",
"Note that you do *not* use `conda` for this: as of this writing, [Wand] is not available in a form that installs via `conda`.\n",
"\n",
"This notebook was written and tested on a macOS system where `/tmp` exists. Other platforms may require adjustments to the scripts below.\n",
"\n",
"[Anaconda]: https://www.anaconda.com/distribution/\n",
"[JupyterLab]: https://github.com/jupyterlab/\n",
"[Wand]: http://wand-py.org/\n",
"\n",
"\n",
"## Running\n",
"\n",
"The next cell generates the test repositories. This takes about 3 seconds to run on my machine. If you have to uncomment the \"`sleep`\" call in the inner loop, this will go up to about 45 seconds.\n",
"\n",
"The next cell produces the bar chart from the collected data, all but instantaneously.\n",
"\n",
"This split allows you to generate the expensive experimental data in a single pass, then play as many games as you like with the generated data.\n",
"\n",
"\n",
"## Discussion\n",
"\n",
"That is kept in [a separate document](image-format-vs-repo-size.md) so we can share that document with Fossil's Markdown renderer."
................................................................................
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Created test directory /tmp/image-format-vs-repo-size\n",
"Created ../test-jpeg.fossil for format JPEG.\n",
"Created ../test-bmp.fossil for format BMP.\n",
"Created ../test-tiff.fossil for format TIFF.\n",
"Created ../test-png.fossil for format PNG.\n",
"Experiment completed in 3.0627901554107666 seconds.\n"
]
}
],
"source": [
"import os\n",
"import random\n",
"import subprocess\n",
"import time\n",
"\n",
"from wand.color import Color\n",
"from wand.drawing import Drawing\n",
"from wand.image import Image\n",
"\n",
"import pandas as pd\n",
"\n",
"size = 256\n",
"iterations = 10\n",
"start = time.time()\n",
"repo_sizes = []\n",
"fossil = '/usr/local/bin/fossil'\n",
"\n",
"if not os.path.isfile(fossil): raise RuntimeError(\"No such executable \" + fossil)\n",
"if not os.access(fossil, os.X_OK): raise RuntimeError(\"Cannot execute \" + fossil)\n",
"\n",
"tdir = os.path.join('/tmp', 'image-format-vs-repo-size')\n",
"if not os.path.isdir(tdir): os.mkdir(tdir, 0o700)\n",
"print(\"Created test directory \" + tdir)\n",
" \n",
"formats = ['JPEG', 'BMP', 'TIFF', 'PNG']\n",
"for f in formats:\n",
" ext = f.lower()\n",
" wdir = os.path.join(tdir, 'work-' + ext)\n",
" if not os.path.isdir(wdir): os.mkdir(wdir, 0o700)\n",
" os.chdir(wdir)\n",
" repo = '../test-' + ext + '.fossil'\n",
" ifn = 'test.' + ext\n",
" ipath = os.path.join(wdir, ifn)\n",
" rs = []\n",
" \n",
" def add_repo_size():\n",
" rs.append(os.path.getsize(repo) / 1024.0 / 1024.0)\n",
" \n",
" def set_repo_page_size(n):\n",
" subprocess.run([\n",
" fossil,\n",
" 'rebuild',\n",
" '--compress',\n",
" '--pagesize',\n",
" str(n),\n",
" '--vacuum'\n",
" ])\n",
"\n",
" try:\n",
" # Create test repo\n",
" subprocess.run([fossil, 'init', repo])\n",
" subprocess.run([fossil, 'open', repo])\n",
" subprocess.run([fossil, 'set', 'binary-glob', \"*.{0}\".format(ext)])\n",
" set_repo_page_size(512) # minimum\n",
" add_repo_size()\n",
" set_repo_page_size(8192) # default\n",
" print(\"Created \" + repo + \" for format \" + f + \".\")\n",
"\n",
" # Create test image and add it to the repo\n",
" img = Image(width = size, height = size, depth = 8,\n",
" background = 'white')\n",
" img.alpha_channel = 'remove'\n",
" img.evaluate('gaussiannoise', 1.0)\n",
" img.save(filename = ipath)\n",
" subprocess.run([fossil, 'add', ifn])\n",
" subprocess.run([fossil, 'ci', '-m', 'initial'])\n",
" #print(\"Added initial \" + f + \" image.\")\n",
" add_repo_size()\n",
"\n",
" # Change a random pixel to a random RGB value and check it in\n",
" # $iterations times.\n",
" for i in range(iterations - 1):\n",
" with Drawing() as draw:\n",
" x = random.randint(0, size - 1)\n",
" y = random.randint(0, size - 1)\n",
"\n",
" r = random.randint(0, 255)\n",
" g = random.randint(0, 255)\n",
" b = random.randint(0, 255)\n",
................................................................................
" draw.fill_color = Color('rgb({0},{1},{2})'.format(\n",
" r, g, b\n",
" ))\n",
" draw.color(x, y, 'point')\n",
" draw(img)\n",
" img.save(filename = ipath)\n",
" \n",
" # You might need to uncomment the next line if you find that\n",
" # the repo size doesn't change as expected. In some versions\n",
" # of Wand (or is it the ImageMagick underneath?) we have seen\n",
" # what appear to be asynchronous saves, with a zero-length file\n",
" # here if you don't wait for the save to complete.\n",
" #time.sleep(1.0)\n",
" \n",
" subprocess.run([fossil, 'ci', '-m', '\"change {0} step {1}'.format(\n",
" f, i\n",
" )])\n",
" add_repo_size()\n",
" \n",
" # Repo complete for this format\n",
" repo_sizes.append(pd.Series(rs, name=f))\n",
"\n",
" finally:\n",
" if os.path.exists(ipath): os.remove(ipath)\n",
" if os.path.exists(tdir):\n",
" if os.path.isfile(repo):\n",
" subprocess.run([fossil, 'close', '-f'])\n",
" os.unlink(repo)\n",
" os.chdir(tdir);\n",
" os.rmdir(wdir)\n",
" if os.path.exists(repo): os.remove(repo)\n",
" \n",
"print(\"Experiment completed in \" + str(time.time() - start) + \" seconds.\")"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
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"z\n",
"\" style=\"fill:#aac7fd;stroke:#ffffff;stroke-linejoin:miter;stroke-width:2;\"/>\n",
" </g>\n",
" <g id=\"text_20\">\n",
" <!-- BMP -->\n",
" <g transform=\"translate(80.78125 38.476562)scale(0.1 -0.1)\">\n",
" <use xlink:href=\"#DejaVuSans-66\"/>\n",
" <use x=\"68.603516\" xlink:href=\"#DejaVuSans-77\"/>\n",
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"\" style=\"fill:#f7b89c;stroke:#ffffff;stroke-linejoin:miter;stroke-width:2;\"/>\n",
" </g>\n",
" <g id=\"text_21\">\n",
" <!-- TIFF -->\n",
" <defs>\n",
" <path d=\"M -0.296875 72.90625 \n",
"L 61.375 72.90625 \n",
"L 61.375 64.59375 \n",
"L 35.5 64.59375 \n",
"L 35.5 0 \n",
................................................................................
"L 48.578125 34.8125 \n",
"L 19.671875 34.8125 \n",
"L 19.671875 0 \n",
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"\" id=\"DejaVuSans-70\"/>\n",
" </defs>\n",
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"\" style=\"fill:#b40426;stroke:#ffffff;stroke-linejoin:miter;stroke-width:2;\"/>\n",
" </g>\n",
" <g id=\"text_22\">\n",
" <!-- PNG -->\n",
" <defs>\n",
" <path d=\"M 9.8125 72.90625 \n",
"L 23.09375 72.90625 \n",
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" </g>\n",
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"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
................................................................................
}
],
"source": [
"%config InlineBackend.figure_formats = ['svg']\n",
"\n",
"import matplotlib as mpl\n",
"import matplotlib.pyplot as plt\n",
"import pandas as pd\n",
"\n",
"os.chdir(tdir)\n",
"\n",
"# Merge per-format test data into a single DataFrame without the first\n",
"# first row, being the boring initial empty repo state.\n",
"data = pd.concat(repo_sizes, axis=1).drop(range(1))\n",
"\n",
"mpl.rcParams['figure.figsize'] = (6, 4)\n",
"ax = data.plot(kind = 'bar', colormap = 'coolwarm',\n",
" grid = False, width = 0.8,\n",
" edgecolor = 'white', linewidth = 2)\n",
"ax.axes.set_xlabel('Checkin index')\n",
"ax.axes.set_ylabel('Repo size (MiB)')\n",
................................................................................
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.6"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
|
Changes to www/image-format-vs-repo-size.md.
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# Image Format vs Fossil Repo Size ## The Problem Fossil has a [delta compression][dc] 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][zl]-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: 1. Binary data compression algorithms — whether lossless as with zlib or lossy as with JPEG — turn the file data into [pseudorandom noise][prn].² Typical data compression algorithms are not [hash functions][hf], 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 ................................................................................ 2. 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. [dc]: ./delta_format.wiki [hf]: https://en.wikipedia.org/wiki/Hash_function ................................................................................ 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][oox] 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][odf] format is designed in more or less the same way as OOXML. * **Java**: A Java [`.jar` file][jcl] is a Zip file containing JVM `.class` files, manifest files, and more. * **Windows Installer:** An [`*.msi` file][wi] is a proprietary database format that contains, among other things, [Microsoft Cabinet][cab]-compressed files, which in turn may hold Windows ................................................................................ [wi]: https://en.wikipedia.org/wiki/Windows_Installer ## Demonstration The companion `image-format-vs-repo-size.ipynb` file ([download][nbd], [preview][nbp]) is a [Jupyter][jp] notebook implementing the following experiment: 1. Create an empty Fossil repository; save its initial size. 2. Use [ImageMagick][im] via [Wand][wp] 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. 3. Check that image into the new Fossil repo, and remember that size. ................................................................................ the Fossil repo size at each step. 6. Repeat the above steps for BMP, TIFF,³ and PNG. 7. 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. [im]: https://www.imagemagick.org/ [jp]: https://jupyter.org/ [nbd]: ./image-format-vs-repo-size.ipynb [nbp]: https://nbviewer.jupyter.org/urls/fossil-scm.org/fossil/doc/trunk/www/image-format-vs-repo-size.ipynb [wp]: http://wand-py.org/ ## Results ................................................................................  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][mce]. 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. [mce]: https://en.wikipedia.org/wiki/Monte_Carlo_method ## Automated Recompression Since programs that produce and consume binary-compressed data files ................................................................................ here. ---- ## Footnotes and Digressions 1. Several other programs also do delta compression, so they’ll also be affected by this problem: [rsync][rs], [Unison][us], [Git][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. 2. 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][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. 3. We're using *uncompressed* TIFF here, not [LZW][lzw]- or Zip-compressed TIFF, either of which would give similar results to PNG, which is always zlib-compressed. 4. 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][mce]. 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. 5. 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. 6. The `Makefile` above is not battle-tested. Please report bugs and needed extensions [on the forum][for]. [for]: https://fossil-scm.org/forum/forumpost/15e677f2c8 [git]: https://git-scm.com/ [lzw]: https://en.wikipedia.org/wiki/Lempel%E2%80%93Ziv%E2%80%93Welch [prng]: https://en.wikipedia.org/wiki/Pseudorandom_number_generator [rs]: https://rsync.samba.org/ [us]: http://www.cis.upenn.edu/~bcpierce/unison/ |
| < | | < | | | | | | | | | | > > | > > > > > > > > > > | | > > | | | | | > | | | | | | | | | | | | | | | | | < < > |
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# Image Format vs Fossil Repo Size ## The Problem Fossil has a [delta compression][dc] feature which removes redundant information from a file relative to its parent on check-in.¹ That delta is then [zlib][zl]-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: 1. Binary data compression algorithms turn the file data into [pseudorandom noise][prn].² Typical data compression algorithms are not [hash functions][hf], 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 ................................................................................ 2. 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, DOCX, 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. [dc]: ./delta_format.wiki [hf]: https://en.wikipedia.org/wiki/Hash_function ................................................................................ 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][oox] used from Office 2003 onward (`.docx`, `.xlsx`, `.pptx`, etc.) are Zip files containing an XML document file and several collateral files. * **Libre Office**: For the purposes of this article, its [OpenDocument Format][odf] is designed the same basic way as OOXML. * **Java**: A Java [`.jar` file][jcl] is a Zip file containing JVM `.class` files, manifest files, and more. * **Windows Installer:** An [`*.msi` file][wi] is a proprietary database format that contains, among other things, [Microsoft Cabinet][cab]-compressed files, which in turn may hold Windows ................................................................................ [wi]: https://en.wikipedia.org/wiki/Windows_Installer ## Demonstration The companion `image-format-vs-repo-size.ipynb` file ([download][nbd], [preview][nbp]) is a [JupyterLab][jl] notebook implementing the following experiment: 1. Create a new minimum-size Fossil repository. Save this initial size. 2. Use [ImageMagick][im] via [Wand][wp] 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. 3. Check that image into the new Fossil repo, and remember that size. ................................................................................ the Fossil repo size at each step. 6. Repeat the above steps for BMP, TIFF,³ and PNG. 7. Create a bar chart showing how the Fossil repository size changes with each checkin. We chose to use JupyterLab 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. [im]: https://www.imagemagick.org/ [jl]: https://jupyter.org/ [nbd]: ./image-format-vs-repo-size.ipynb [nbp]: https://nbviewer.jupyter.org/urls/fossil-scm.org/fossil/doc/trunk/www/image-format-vs-repo-size.ipynb [wp]: http://wand-py.org/ ## Results ................................................................................  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 past the first commit.⁵ We owe this economy to Fossil’s delta compression feature: it is encoding each of those single-pixel changes in a very small amount of repository space. * The JPEG and TIFF bars increase by large amounts on most checkins even though each checkin *also* encodes only a *single-pixel change*. * 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. This shows that for repos where the image files are committed only once, there is virtually no penalty to using BMP or TIFF over PNG. The file sizes likely differ only because of differences in zlib settings between the cases. * 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][mce]. 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. [mce]: https://en.wikipedia.org/wiki/Monte_Carlo_method ## Automated Recompression Since programs that produce and consume binary-compressed data files ................................................................................ here. ---- ## Footnotes and Digressions 1. This problem is not Fossil-specific. Several other programs also do delta compression, so they’ll also be affected by this problem: [rsync][rs], [Unison][us], [Git][git], etc. You should take this article’s advice when using all such programs, not just Fossil. When using file copying and synchronization programs *without* delta compression, on the other hand, 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. 2. 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][prng] is. Another way to look at it is that if there is a discernible pattern in the output of a compression scheme, that constitutes *information* (in [the technical sense of that word][ith]) that could be further compressed. 3. We're using *uncompressed* TIFF here, not [LZW][lzw]- or Zip-compressed TIFF, either of which would give similar results to PNG, which is always zlib-compressed. 4. 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][mce]. We’ve found that the overall character of the results doesn’t change from one run to the next. 5. It’s not clear to me why there is a one-time jump in size for BMP and TIFF past the first commit. I suspect it is due to the SQLite indices being initialized for the first time. Page size inflation might have something to do with it as well, though we tried to control that by rebuilding the initial DB with a minimal page size. If you re-run the program often enough, you will sometimes see the BMP or TIFF bar jump higher than the other, again likely due to one of the repos crossing a page boundary. Another curious artifact in the data is that the BMP is slightly larger than for the TIFF. This goes against expectation because a low-tech format like BMP should have a small edge in this test because TIFF metadata includes the option for multiple timestamps, UUIDs, etc., which bloat the checkin size by creating many small deltas. 6. The `Makefile` above is not battle-tested. Please report bugs and needed extensions [on the forum][for]. [for]: https://fossil-scm.org/forum/forumpost/15e677f2c8 [git]: https://git-scm.com/ [ith]: https://en.wikipedia.org/wiki/Information_theory [lzw]: https://en.wikipedia.org/wiki/Lempel%E2%80%93Ziv%E2%80%93Welch [prng]: https://en.wikipedia.org/wiki/Pseudorandom_number_generator [rs]: https://rsync.samba.org/ [us]: http://www.cis.upenn.edu/~bcpierce/unison/ |
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