Archiving URLs

Archiving the Web, because nothing lasts forever: statistics, online archive services, extracting URLs automatically from browsers, and creating a daemon to regularly back up URLs to multiple sources.
Haskell⁠, archiving⁠, Bitcoin⁠, meta⁠, shell⁠, R⁠, tutorial
2011-03-102019-01-05 finished certainty: certain importance: 8

Links on the Internet last forever or a year, whichever comes first. This is a major problem for anyone serious about writing with good references, as link rot will cripple several% of all links each year, and compounding.

To deal with link rot, I present my multi-pronged archival strategy using a combination of scripts, daemons, and Internet archival services: URLs are regularly dumped from both my web browser’s daily browsing and my website pages into an archival daemon I wrote, which pre-emptively downloads copies locally and attempts to archive them in the Internet Archive. This ensures a copy will be available indefinitely from one of several sources. Link rot is then detected by regular runs of linkchecker, and any newly dead links can be immediately checked for alternative locations, or restored from one of the archive sources.

As an additional flourish, my local archives are efficiently cryptographically timestamped using Bitcoin in case forgery is a concern, and I demonstrate a simple compression trick for substantially reducing sizes of large web archives such as crawls (particularly useful for repeated crawls such as my DNM archives).

Given my interest in long term content and extensive linking, is an issue of deep concern to me. I need backups not just for my files1⁠, but for the web pages I read and use—they’re all part of my ⁠. It’s not much good to have an extensive essay on some topic where half the links are dead and the reader can neither verify my claims nor get context for my claims.


“With every new spring
the blossoms speak not a word
yet expound the Law—
knowing what is at its heart
by the scattering storm winds.”


The first remedy is to learn about broken links as soon as they happen, which allows one to react quickly and scrape archives or search engine caches (‘lazy preservation’). I currently use linkchecker to spider looking for broken links. linkchecker is run in a job like so:

@monthly linkchecker --check-extern --timeout=35 --no-warnings --file-output=html \
                      --ignore-url=^mailto --ignore-url=^irc --ignore-url=http://.*\.onion \

Just this command would turn up many false positives. For example, there would be several hundred warnings on Wikipedia links because I link to redirects; and linkchecker respects s which forbid it to check liveness, but emits a warning about this. These can be suppressed by editing ~/.linkchecker/linkcheckerrc to say ignorewarnings=http-moved-permanent,http-robots-denied (the available warning classes are listed in linkchecker -h).

The quicker you know about a dead link, the sooner you can look for replacements or its new home.


Remote caching

“Anything you post on the internet will be there as long as it’s embarrassing and gone as soon as it would be useful.”


We can ask a third party to keep a cache for us. There are several possibilities:

  1. the
  2. (highly limited)
  3. Linterweb’s WikiWix8⁠.
  4. (defunct as of 2018)
  6. Pinboard (with the $22/year archiving option9)

There are other options but they are not available like Google10 or various commercial/government archives11

(An example would be being archived at⁠.)

These archives are also good for archiving your own website:

  1. you may be keeping backups of it, but your own website/server backups can be lost (I can speak from personal experience here), so it’s good to have external copies
  2. Another benefit is the reduction in ‘bus-factor’: if you were hit by a bus tomorrow, who would get your archives and be able to maintain the websites and understand the backups etc? While if archived in IA, people already know how to get copies and there are tools to download entire domains.
  3. A focus on backing up only one’s website can blind one to the need for archiving the external links as well. Many pages are meaningless or less valuable with broken links. A linkchecker script/daemon can also archive all the external links.

So there are several benefits to doing web archiving beyond simple server backups.

My first program in this vein of thought was a bot which fired off WebCite, Internet Archive/Alexa, & requests: Wikipedia Archiving Bot⁠, quickly followed up by a RSS version⁠. (Or you could install the to get automatic submission to the Internet Archive, if you have ceased to care about privacy.)

The core code was quickly adapted into a wiki plugin which hooked into the save-page functionality and tried to archive every link in the newly-modified page, Interwiki.hs

Finally, I wrote ⁠, a daemon which watches12⁠/reads a text file. Source is available via git clone (A similar tool is Archiveror⁠.)

The library half of archiver is a simple wrapper around the appropriate HTTP requests; the executable half reads a specified text file and loops as it (slowly) fires off requests and deletes the appropriate URL.

That is, archiver is a daemon which will process a specified text file, each line of which is a URL, and will one by one request that the URLs be archived or spidered

Usage of archiver might look like archiver ~/.urls.txt In the past, archiver would sometimes crash for unknown reasons, so I usually wrap it in a while loop like so: while true; do archiver ~/.urls.txt; done. If I wanted to put it in a detached session: screen -d -m -S "archiver" sh -c 'while true; do archiver ~/.urls.txt; done'. Finally, rather than start it manually, I use a cron job to start it at boot, for a final invocation of

@reboot sleep 4m && screen -d -m -S "archiver" sh -c 'while true; do archiver ~/.urls.txt \
        "cd ~/www && nice -n 20 ionice -c3 wget --unlink --limit-rate=20k --page-requisites --timestamping \
        -e robots=off --reject .iso,.exe,.gz,.xz,.rar,.7z,.tar,.bin,.zip,.jar,.flv,.mp4,.avi,.webm \
        --user-agent='Firefox/4.9'" 500; done'

Local caching

Remote archiving, while convenient, has a major flaw: the archive services cannot keep up with the growth of the Internet and are woefully incomplete. I experience this regularly, where a link on goes dead and I cannot find it in the Internet Archive or WebCite, and it is a general phenomenon: find <35% of common Web pages ever copied into an archive service, and typically only one copy exists.

Caching Proxy

The most ambitious & total approach to local caching is to set up a proxy to do your browsing through, and record literally all your web traffic; for example, using Live Archiving Proxy (LAP) or WarcProxy which will save as every page you visit through it. (Zachary Vance explains how to set up a local HTTPS certificate to MITM your HTTPS browsing as well.)

One may be reluctant to go this far, and prefer something lighter-weight, such as periodically extracting a list of visited URLs from one’s web browser and then attempting to archive them.

Batch job downloads

For a while, I used a shell script named, imaginatively enough, local-archiver:

set -euo pipefail

cp `find ~/.mozilla/ -name "places.sqlite"` ~/
sqlite3 places.sqlite "SELECT url FROM moz_places, moz_historyvisits \
                       WHERE = moz_historyvisits.place_id \
                             and visit_date > strftime('%s','now','-1.5 month')*1000000 ORDER by \
                       visit_date;" | filter-urls >> ~/.tmp
rm ~/places.sqlite
split -l500 ~/.tmp ~/.tmp-urls
rm ~/.tmp

cd ~/www/
for file in ~/.tmp-urls*;
 do (wget --unlink --continue --page-requisites --timestamping --input-file $file && rm $file &);

find ~/www -size +4M -delete

The code is not the prettiest, but it’s fairly straightforward:

  1. the script grabs my Firefox browsing history by extracting it from the history SQL database file13⁠, and feeds the URLs into ⁠.

    wget is not the best tool for archiving as it will not run JavaScript or Flash or download videos etc. It will download included JS files but the JS will be obsolete when run in the future and any dynamic content will be long gone. To do better would require a headless browser like which saves to MHT/MHTML, but PhantomJS refuses to support it and I’m not aware of an existing package to do this. In practice, static content is what is most important to archive, most JS is of highly questionable value in the first place, and any important YouTube videos can be archived manually with youtube-dl, so wget’s limitations haven’t been so bad.

  2. The script splits the long list of URLs into a bunch of files and runs that many wgets in parallel because wget apparently has no way of simultaneously downloading from multiple domains. There’s also the chance of wget hanging indefinitely, so parallel downloads continues to make progress.

  3. The filter-urls command is another shell script, which removes URLs I don’t want archived. This script is a hack which looks like this:

    set -euo pipefail
    cat /dev/stdin | sed -e "s/#.*//" | sed -e "s/&sid=.*$//" | sed -e "s/\/$//" | grep -v -e 4chan -e reddit ...
  4. delete any particularly large (>4MB) files which might be media files like videos or audios (podcasts are particular offenders)

A local copy is not the best resource—what if a link goes dead in a way your tool cannot detect so you don’t know to put up your copy somewhere? But it solves the problem decisively.

The downside of this script’s batch approach soon became apparent to me:

  1. not automatic: you have to remember to invoke it and it only provides a single local archive, or if you invoke it regularly as a cron job, you may create lots of duplicates.
  2. unreliable: wget may hang, URLs may be archived too late, it may not be invoked frequently enough, >4MB non-video/audio files are increasingly common…
  3. I wanted copies in the Internet Archive & elsewhere as well to let other people benefit and provide redundancy to my local archive

It was to fix these problems that I began working on archiver—which would run constantly archiving URLs in the background, archive them into the IA as well, and be smarter about media file downloads. It has been much more satisfactory.


archiver has an extra feature where any third argument is treated as an arbitrary sh command to run after each URL is archived, to which is appended said URL. You might use this feature if you wanted to load each URL into Firefox, or append them to a log file, or simply download or archive the URL in some other way.

For example, instead of a big local-archiver run, I have archiver run wget on each individual URL: screen -d -m -S "archiver" sh -c 'while true; do archiver ~/.urls.txt "cd ~/www && wget --unlink --continue --page-requisites --timestamping -e robots=off --reject .iso,.exe,.gz,.xz,.rar,.7z,.tar,.bin,.zip,.jar,.flv,.mp4,.avi,.webm --user-agent='Firefox/3.6' 120"; done'. (For private URLs which require logins, such as darknet markets⁠, wget can still grab them with some help: installing the Firefox extension Export Cookies⁠, logging into the site in Firefox like usual, exporting one’s cookies.txt, and adding the option --load-cookies cookies.txt to give it access to the cookies.)

Alternately, you might use curl or a specialized archive downloader like the Internet Archive’s crawler Heritrix⁠.

Cryptographic timestamping local archives

We may want cryptographic timestamping to prove that we created a file or archive at a particular date and have not since altered it. Using a timestamping service’s API, I’ve written 2 shell scripts which implement downloading (wget-archive) and timestamping strings or files (timestamp). With these scripts, extending the archive bot is as simple as changing the shell command:

@reboot sleep 4m && screen -d -m -S "archiver" sh -c 'while true; do archiver ~/.urls.txt \
        "wget-archive" 200; done'

Now every URL we download is automatically cryptographically timestamped with ~1-day resolution for free.

Resource consumption

The space consumed by such a backup is not that bad; only 30–50 gigabytes for a year of browsing, and less depending on how hard you prune the downloads. (More, of course, if you use linkchecker to archive entire sites and not just the pages you visit.) Storing this is quite viable in the long term; while page sizes have increased 7× between 2003 and 2011 and pages average around 400kb14⁠, has also been operating and has increased disk capacity by ~128×—in 2011, $103$802011 will buy you at least 2 terabytes⁠, that works out to 4 cents a gigabyte or 80 cents for the low estimate for downloads; that is much better than the annual fee that somewhere like Pinboard charges. Of course, you need to back this up yourself. We’re relatively fortunate here—most Internet documents are ‘born digital’ and easy to migrate to new formats or inspect in the future. We can download them and worry about how to view them only when we need a particular document, and Web browser backwards-compatibility already stretches back to files written in the early 1990s. (Of course, we’re probably screwed if we discover the content we wanted was dynamically presented only in Adobe Flash or as an inaccessible ‘cloud’ service.) In contrast, if we were trying to preserve programs or software libraries instead, we would face a much more formidable task in keeping a working ladder of binary-compatible virtual machines or interpreters15⁠. The situation with digital movie preservation hardly bears thinking on.

There are ways to cut down on the size; if you tar it all up and run with maximum compression options, you could probably compact it to 1⁄5th the size. I found that the uncompressed files could be reduced by around 10% by using to look for duplicate files and turning the duplicates into a space-saving to the original with a command like fdupes --recurse --hardlink ~/www/. (Apparently there are a lot of bit-identical JavaScript (eg. ) and images out there.)

Good filtering of URL sources can help reduce URL archiving count by a large amount. Examining my manual backups of Firefox browsing history, over the 1153 days from 2014-02-25 to 2017-04-22, I visited 2,370,111 URLs or 2055 URLs per day; after passing through my filtering script, that leaves 171,446 URLs, which after de-duplication yields 39,523 URLs or ~34 unique URLs per day or 12,520 unique URLs per year to archive.

This shrunk my archive by 9GB from 65GB to 56GB, although at the cost of some archiving fidelity by removing many filetypes like CSS or JavaScript or GIF images. As of 2017-04-22, after ~6 years of archiving, between xz compression (at the cost of easy searchability), aggressive filtering, occasional manual deletion of overly bulky domains I feel are probably adequately covered in the IA etc, my full WWW archives weigh 55GB.

URL sources

Browser history

There are a number of ways to populate the source text file. For example, I have a script firefox-urls:

set -euo pipefail

cp --force `find ~/.mozilla/firefox/ -name "places.sqlite"|sort|head -1` ~/
sqlite3 -batch places.sqlite "SELECT url FROM moz_places, moz_historyvisits \
                       WHERE = moz_historyvisits.place_id and \
                       visit_date > strftime('%s','now','-1 day')*1000000 ORDER by \
                       visit_date;" | filter-urls
rm ~/places.sqlite

(filter-urls is the same script as in local-archiver. If I don’t want a domain locally, I’m not going to bother with remote backups either. In fact, because of WebCite’s rate-limiting, archiver is almost perpetually back-logged, and I especially don’t want it wasting time on worthless links like ⁠.)

This is called every hour by cron:

@hourly firefox-urls >> ~/.urls.txt

This gets all visited URLs in the last time period and prints them out to the file for archiver to process. Hence, everything I browse is backed-up through archiver.

Non-Firefox browsers can be supported with similar strategies; for example, Zachary Vance’s Chromium scripts likewise extracts URLs from Chromium’s SQL history & bookmarks⁠.

Website spidering

Sometimes a particular website is of long-term interest to one even if one has not visited every page on it; one could manually visit them and rely on the previous Firefox script to dump the URLs into archiver but this isn’t always practical or time-efficient. linkchecker inherently spiders the websites it is turned upon, so it’s not a surprise that it can build a or simply spit out all URLs on a domain; unfortunately, while linkchecker has the ability to output in a remarkable variety of formats, it cannot simply output a newline-delimited list of URLs, so we need to post-process the output considerably. The following is the shell one-liner I use when I want to archive an entire site (note that this is a bad command to run on a large or heavily hyper-linked site like the English Wikipedia or LessWrong!); edit the target domain as necessary:

linkchecker --check-extern -odot --complete -v --ignore-url=^mailto --no-warnings
    | fgrep http # [
    | fgrep -v -e "label=" -e "->" -e '" [' -e '" ]' -e "/ "
    | sed -e "s/href=\"//" -e "s/\",//" -e "s/ //"
    | filter-urls
    | sort --unique >> ~/.urls.txt

When linkchecker does not work, one alternative is to do a wget --mirror and extract the URLs from the filenames—list all the files and prefix with a “http://” etc.


Cryptographic timestamping

Due to length, this section has been moved to a separate page⁠.


A raw dump of URLs, while certainly archivable, will typically result in a very large mirror of questionable value (is it really necessary to archive Google search queries or Wikipedia articles? usually, no) and worse, given the rate-limiting necessary to store URLs in the Internet Archive or other services, may wind up delaying the archiving of the important links & risking their total loss. Disabling the remote archiving is unacceptable, so the best solution is to simply take a little time to manually blacklist various domains or URL patterns.

This blacklisting can be as simple as a command like filter-urls | grep -v, but can be much more elaborate. The following shell script is the skeleton of my own custom blacklist, derived from manually filtering through several years of daily browsing as well as spiders of dozens of websites for various people & purposes, demonstrating a variety of possible techniques: regexps for domains & file-types & query-strings, sed-based rewrites, fixed-string matches (both blacklists and whitelists), etc:


# USAGE: `filter-urls` accepts on standard input a list of newline-delimited URLs or filenames,
# and emits on standard output a list of newline-delimited URLs or filenames.
# This list may be shorter and entries altered. It tries to remove all unwanted entries, where 'unwanted'
# is a highly idiosyncratic list of regexps and fixed-string matches developed over hundreds of thousands
# of URLs/filenames output by my daily browsing, spidering of interesting sites, and requests
# from other people to spider sites for them.
# You are advised to test output to make sure it does not remove
# URLs or filenames you want to keep. (An easy way to test what is removed is to use the `comm` utility.)
# For performance, it does not sort or remove duplicates from output; both can be done by
# piping `filter-urls` to `sort --unique`.

set -euo pipefail

cat /dev/stdin \
    | sed -e "s/#.*//" -e 's/>$//' -e "s/&sid=.*$//" -e "s/\/$//" -e 's/$/\n/' -e 's/\?sort=.*$//' \
      -e 's/^[ \t]*//' -e 's/utm_source.*//' -e 's/https:\/\//http:\/\//' -e 's/\?showComment=.*//' \
    | grep "\." \
    | fgrep -v "*" \
    | egrep -v -e '\/\.rss$' -e "\.tw$" -e "//%20www\." -e "/file-not-found" -e "258..\.com/$" \
       -e "3qavdvd" -e "://avdvd" -e "\.avi" -e "\.com\.tw" -e "\.onion" -e "\?fnid\=" -e "\?replytocom=" \
       -e "^$" -e "^$" \
       -e "^$" \
       -e "ftp.*" -e "6..6\.com" -e "6..9\.com" -e "6??6\.com" -e "7..7\.com" -e "7..8\.com" -e "7..\.com" \
       -e "78..\.com" -e "7??7\.com" -e "8..8\.com" -e "8??8\.com" -e "9..9\.com" -e "9??9\.com" \
       -e gold.*sell -e vip.*club \
    | fgrep -v -e "#!" -e ".bin" -e ".mp4" -e ".swf" -e "/mediawiki/index.php?title=" -e "/search?q=cache:" \
      -e "/wiki/Special:Block/" -e "/wiki/Special:WikiActivity" -e "Special%3ASearch" \
      -e "Special:Search" -e "__setdomsess?dest="
      # ...

# prevent URLs from piling up at the end of the file
echo ""

filter-urls can be used on one’s local archive to save space by deleting files which may be downloaded by wget as dependencies. For example:

find ~/www | sort --unique >> full.txt && \
    find ~/www | filter-urls | sort --unique >> trimmed.txt
comm -23 full.txt trimmed.txt | xargs -d "\n" rm
rm full.txt trimmed.txt

sort key compression trick

Programming folklore notes that one way to get better lossless compression efficiency is by the precompression trick of rearranging files inside the archive to group ‘similar’ files together and expose redundancy to the compressor, in accordance with information-theoretical principles. A particularly easy and broadly-applicable way of doing this, which does not require using any unusual formats or tools and is fully compatible with the default archive methods, is to sort the files by filename and especially file extension. I show how to do this with the standard Unix command-line sort tool, using the so-called “sort --key trick”, and give examples of the large space-savings possible from my archiving work for personal website mirrors and for making darknet market mirror datasets where the redundancy at the file level is particularly extreme and the sort --key trick shines compared to the naive approach.

One way to look at data compression is as a form of intelligence (see the & ): a compression tool like is being asked to predict what the next bit of the original file is, and the better its predictions, the less data needs to be stored to correct its mistaken predictions (“I know how to spell ‘banana’, I just don’t know when to stop”). The smarter the program is, the better its compression will be; but on the flip side, you can also improve the compression ratio by giving it a little help and organizing the data into an equivalent form the program can understand better—for example, by using the to expose internal redundancy. Or by compressing a set of files together as a rather than as separate files, giving the compressor more time to learn. Or by preserving spatial locality: keeping similar data together, and not dispersing it all over. (This also explains why multimedia files barely compress: because the lossy encodings are the product of decades of work specialized to the particular domain of audio or images or video, and a general-purpose lossless compression would have to be very intelligent, on par with ⁠, to beat them at their own game.) Files on one topic should be compressed together.


Spatial locality can be subtle. One can accidentally get a size difference. For example, natural language text, though not structured line-by-line as visibly as a dictionary, is still far from random and has many local correlations a compression tool might be able to pick up. If this is true, we would expect that with a sufficiently smart compressor, a text file would compress better in its logical form than if it were shuffled. Is this the case, or are compression utilities are too stupid to see any difference between random lines and English prose? Taking 14M of text from, we can see for ourselves:

## uncompressed
cat *.page */*.page */*/*.page |                                                 wc --bytes
# 13588814

## compressed, files in lexicographic order
cat *.page */*.page */*/*.page |                      xz -9 --extreme --stdout | wc --bytes
# 3626732
## compressed, all lines sorted alphabetically
cat *.page */*.page */*/*.page | sort               | xz -9 --extreme --stdout | wc --bytes
# 3743756
## compressed, all lines randomly shuffled except for non-unique lines sorted together
cat *.page */*.page */*/*.page | sort --random-sort | xz -9 --extreme --stdout | wc --bytes
# 3831740
## compressed, all lines randomly shuffled
cat *.page */*.page */*/*.page | shuf               | xz -9 --extreme --stdout | wc --bytes
# 3862632

The unmolested text compresses to 3.626M, but the same text randomly shuffled is 3.862M! I also included an intermediate form of randomization: despite the name, the --random-sort option to sort is not actually a random shuffle but a random hash (this is not documented in the man page, though it is in the info page) and so any repeated non-unique lines will be sorted together (allowing for some easy duplication deletion), and so we would expect the only-partial randomization of --random-sort to maybe perform a bit better than the true random shuffle of shuf. And it does.

Web archives

Spatial locality also applies to our web archiving. If you are mirroring websites, or otherwise compiling a lot of directories with redundant data on a file-by-file level, there’s a cute trick to massively improve your compression ratios: don’t sort the usual lexicographic way, but sort by a subdirectory. (I learned about this trick a few years ago while messing around with archiving my home directory using find and tar.) This is one of the issues with archiving gigabytes of crawls from thousands of domains: URLs have a historical oddity where they are not consistently hierarchical. URLs were originally modeled after hierarchical Unix filesystems; this page, for example, lives at the name /home/gwern/wiki/, which follows a logical left-to-right pattern of increasing narrowness. If one lists my entire filesystem in lexicographic order, all the files in /home/gwern/ will be consecutive, and the files in wiki/ will be consecutive, and so on. unfortunately, the top level of URLs breaks this scheme—one does not visit https://com/google/mail/?shva=1#search/l%3aunread, one visits; one does not visit http://net/www/gwern/Archiving-URLs but So if I download and then later, a lexicographic list of downloaded files will separate the files as much as possible (even though they are semantically probably similar). A quick example from my current WWW archive:

# ...
# ...

The directories are indeed sorted, but aside from the initial 2 letters or so, look nothing like each other: a Wikia subdomain rubs shoulders with a WordPress blog, a .ca domain is between a .com, a .info, and a .edu (with a .us and .uk thrown in for variety), and so on. Is there any way to sort these directories with a bit of parsing thrown in? For example, maybe we could reverse each line? Some web browsers store URLs reversed right-to-left to enable more efficient database operations, as do Google’s systems16 (to assist their relatively weak compression utility ). Turns out GNU already supports something similar, the --key & --field-separator options; the man page is not very helpful but the page tells us:

     Use character SEPARATOR as the field separator when finding the
     sort keys in each line. By default, fields are separated by the
     empty string between a non-blank character and a blank character.
     By default a blank is a space or a tab, but the 'LC_CTYPE' locale
     can change this.

     That is, given the input line ' foo bar', 'sort' breaks it into
     fields ' foo' and ' bar'. The field separator is not considered
     to be part of either the field preceding or the field following,
     so with 'sort -t " "' the same input line has three fields: an
     empty field, 'foo', and 'bar'. However, fields that extend to the
     end of the line, as '-k 2', or fields consisting of a range, as
     '-k 2,3', retain the field separators present between the
     endpoints of the range.

'-k POS1[,POS2]'
     Specify a sort field that consists of the part of the line between
     POS1 and POS2 (or the end of the line, if POS2 is omitted),

     Each POS has the form 'F[.C][OPTS]', where F is the number of the
     field to use, and C is the number of the first character from the
     beginning of the field. Fields and character positions are
     numbered starting with 1; a character position of zero in POS2
     indicates the field's last character. If '.C' is omitted from
     POS1, it defaults to 1 (the beginning of the field); if omitted
     from POS2, it defaults to 0 (the end of the field). OPTS are
     ordering options, allowing individual keys to be sorted according
     to different rules; see below for details. Keys can span multiple

     Example: To sort on the second field, use '--key=2,2' ('-k 2,2').
     See below for more notes on keys and more examples. See also the
     '--debug' option to help determine the part of the line being used
     in the sort.

Hence, we can do better by ordering sort to break on the dots and focus on the second part of a URL, like so:

ls | sort --key=2 --field-separator="."
# ...
# ...

There’s many possible ways to sort, though. So I took my WWW archive as of 2014-06-15, optimized all PNGs & JPEGs with optipng & jpegoptim, ran all the files through filter-urls & deleted the ones which failed (this took out all of the JS files, which is fine since I don’t think those are useful for archival purposes), and was left with ~86.5GB of files. Then I tested out several ways of sorting the filenames to see what gave the best compression on my corpus.

First, I establish the baseline:

  1. Size of uncompressed unsorted tarball, which eliminates filesystem overhead and tells us how much compression is really saving:

    cd ~/www/ && find ./ -type f -print0 | tar c --to-stdout --no-recursion --null --files-from - | wc --bytes
    # 86469734400
    ## 1×
  2. Size of sorted tarball:

    cd ~/www/ && find . -type f -print0 | sort --zero-terminated | \
                 tar c --to-stdout --no-recursion --null --files-from - | wc --bytes
    # 86469734400
    ## 1×

    So sorting a tarball doesn’t give any benefits. This is mostly as I expected, since tar is only supposed to produce a linear archive packing together all the specified files and otherwise preserve them exactly. I thought there might have been some sort of consolidation of full path-names which might yield a small space savings, but apparently not.

Now we can begin sorting before compression. I thought of 6 approaches; in decreasing order of final archive (smaller = better):

  1. Sort by file names, simply by reversing, sorting, unreverse (foo.png ... bar.png reverses to gnp.oof ... gnp.rab, which then sort together, and then losslessly reverse back to bar.png / foo.png / ...):

    cd ~/www/ && find . -type f | rev | sort | rev | \
                 tar c --to-stdout --no-recursion --files-from - | xz -9 --stdout | wc --bytes
    # 24970605748
    ## 0.2887×

    (Note that find+rev doesn’t correctly handle filenames with the wrong/non-UTF-8 encoding; I ultimately used brute force in the form of detox to find all the non-UTF-8 files and rename them.)

  2. Compress tarball, but without any sorting (files are consumed in the order find produces them in the filesystem):

    cd ~/www/ && find . -type f -print0 | \
                 tar c --to-stdout --no-recursion --null --files-from - | xz -9 --stdout | wc --bytes
    # 24268747400
    ## 0.2806×
  3. Sort by file suffixes, trying to parsing the filenames first:

    cd ~/www/ && find . -type f -printf '%f/%p\n' | sort --field-separator="." --key=2 | cut -f2- -d/ | \
                 tar c --to-stdout --no-recursion --files-from - | xz -9 --stdout | wc --bytes
    # 24097155132
    ## 0.2786×
  4. Sort normally, in lexicographic order (subdomain, domain, TLD, subdirectories & files etc):

    cd ~/www/ && find . -type f -print0 | sort --zero-terminated | \
        tar c --to-stdout --no-recursion --null --files-from - | xz -9 --stdout | wc --bytes
    # 23967317664
    ## 0.2771×
  5. Sort by middle of domain:

    cd ~/www/ && find . -type f -print0 | sort --zero-terminated --key=3 --field-separator="." | \
                  tar c --to-stdout --no-recursion --null --files-from - | xz -9 --stdout | wc --bytes
    # 23946061272
    ## 0.2769×
  6. Sort by first subdirectory (if there’s a bunch of* &* files, then the /wp-content/ files will all sort together regardless of “f” and “b” being far from each other; similarly for, etc):

    cd ~/www/ && find . -type f -print0 | sort --zero-terminated --key=3 --field-separator="/" | \
                 tar c --to-stdout --no-recursion --null --files-from - | xz -9 --stdout | wc --bytes
    # 23897682908
    ## 0.2763×

Surprisingly, #1, reversing filenames in order to sort on the suffixes, turns out to be even worse than not sorting at all. The improved attempt to sort on filetypes doesn’t do much better, although it at least beats the baseline of no-sorting; it may be that to get a compression win real semantic knowledge of filetypes will be needed (perhaps calling file on every file and sorting by the detected filetype?). The regular sort also performs surprisingly well, but my intuitions win for once and it’s beaten by my previous strategy of sorting by the middle of domains. Finally, the winner is a bit of a surprise too, a sort I only threw in out of curiosity because I noticed blogs tend to have similar site layouts.

In this case, the best version saved 2,426,8747,400 - 23,897,682,908 = 371,064,492 or 371MB over the unsorted version. Not as impressive as in the next use case, but enough to show this seems like a real gain

Separate mirrors

Top-level domains are not the only thing we might want to sort differently on. To take my mirrors of darknet market drug sites such as Silk Road 1: I download a site each time as a separate wget run in a timestamped folder. So in my Silk Road 2 folder, I have both 2013-12-25/ & 2014-01-15/. These share many similar & identical files so they compress together with xz down from 1.8GB to 0.3GB.

But they could compress even better: the similar files may be thousands of files and hundreds of megabytes away by alphabetical or file-inode order, so even with a very large window and a top-notch compressor, it will fail to spot many long-range redundancies. In between 2013-12-25/default.css and 2014-01-15/default.css is going to be all sorts of files which have nothing to do with CSS, like 2014-01-16/items/2-grams-of-pure-vanilla-ketamine-powder-dutchdope?vendor_feedback_page=5 and 2014-01-16/items/10-generic-percocet-10-325-plus-1-30mg-morphine. You see the problem.

Because we sort the files by ‘all files starting with “2013”’ and then ‘all files starting “2014”’, we lose all proximity. If instead, we could sort by subfolder and only then by the top-level folder, then we’d have everything line up nicely. Fortunately, we already know how to do this! Reuse the sort-key trick, specify “/” as the delimiter to parse on, and the nth field to sort on. We feed it a file list, tell it to break filenames by “/”, and then to sort on a lower level, and if we did it right, we will indeed get output like 2013-12-25/default.css just before 2014-01-15/default.css, which will do wonders for our compression, and which will pay ever more dividends as we accumulate more partially-redundant mirrors.

Here is an example of output for my Pandora mirrors, where, due to frequent rumors of its demise triggering mirroring on my part, I have 5 full mirrors at the time of testing; and naturally, if we employ the sort-key trick (find . -type f | sort --key=3 --field-separator="/"), we find a lot of similar-sounding files:


Note the interleaving of 5 different mirrors, impossible in a normal left-to-right alphabetical sort. You can bet that these 4 files (in 15 versions) are going to compress much better than if they were separated by a few thousand other profile pages.

So here’s an example invocation (doing everything in pipelines to avoid disk IO):

find . -type f -print0 | sort --zero-terminated --key=3 --field-separator="/"
 | tar --no-recursion --null --files-from - -c
 | xz -9 --extreme --stdout
 > ../mirror.tar.xz

Used on my two Silk Road 2 mirrors which together weigh 1800M, a normal run without the --key/--field-separator options, as mentioned before, yields a 308M archive. That’s not too bad. Certainly much better than hauling around almost 2GB. However—if I switch to the sort-key trick, however, the archive is now 271M, or 37M less. Same compression algorithm, same files, same unpacked results, same speed, just 2 little obscure sort options… and I get an archive 87% the size of the original.

Not impressed? Well, I did say that the advantage increases with the number of mirrors to extract redundancy from. With only 2 mirrors, the SR2 results can’t be too impressive. How about the Pandora mirrors? 5 of them gives the technique more scope to shine. And as expected, it’s even more impressive when I compare the Pandora archives: 71M vs 162M. The sort-keyed archive saves 56% of the regular archive’s size. The final Pandora archive, released as part of my DNM archive⁠, boasts 105 mirrors from 2013-12-25 to 2014-11-05 of 1,745,778 files (many duplicates due to being present over multiple crawls) taking up 32GB uncompressed. This archive is 0.58GB (606,203,320 bytes) when sort-keyed; when sorted alphabetically, it is instead 7.5GB (7,466,374,836 bytes) or 12.31× larger, so the sort-keyed archive saves 92%. Forum mirrors are even more redundant than market mirrors because all content added to a forum will be present in all subsequent crawls, so each crawl will yield the previous crawl plus some additional posts; hence, the Pandora forum’s raw size of 8,894,521,228 bytes shrinks to 283,747,148 bytes when compressed alphabetically but shrinks dramatically to the 31× smaller sort-keyed archive of 9,084,508 bytes, saving 97%!

Clearly in these DNM use-cases, sort-keying has gone from a cute trick to indispensable.


The sort-key trick is most useful when we can infer a lot of spatial locality just from parts of the file names, it’s not a panacea. There are other approaches:

  1. if we have multiple temporally-ordered datasets and we don’t mind making it more difficult to access older copies, it may be simpler to store the data as a DVCS like where each dataset is a large patch

  2. sort files by minimizing binary differences between them using Timm S. Müller’s binsort utility

    The default optimization setting of -o15 underperforms the sort-key trick on both the SR2 and Pandora datasets by 5–10MB, and a higher setting like -o1000 is best. Note that binsort is 𝒪(n2) in number of files, so it’s limited to sorting <10,000 files. An example pipeline for compressing posts from the Silk Road forums regarding a minor Ponzi scheme there⁠, since the filenames offer little guidance for a semantically-meaningful sort:

    find dkn255hz262ypmii.onion/ -type f -exec fgrep -i -l vladimir {} \; >> ponzi.txt
    find dkn255hz262ypmii.onion/ -type f -exec fgrep -i -l Limetless {} \; >> ponzi.txt
    mkdir ponzi/ && cp `cat ponzi.txt` ponzi/
    ~/bin/binsort/binsort -t 6 -o 1000 ponzi/ > ponzi-list.txt
    cat ponzi-list.txt | tar --no-recursion --files-from - -c | xz -9 --extreme --stdout > ~/srf1-ponzi.tar.xz

    (Embarrassingly, binsort seems to underperform on this dataset: the files are 380M uncompressed, 3.536M sort-keyed, and 3.450M sorted.)

  3. if we know there are many duplicates but they are far apart by a lexicographic sort and we don’t have any good way to sort filenames and a lot of RAM, we can try out a compression tool which specifically looks for long-range redundancies throughout the entire bitstream, such as (homepage⁠/ Arch wiki). lrzip is packaged in Debian and should be at least as good as xz since it too uses LZMA; but it is an obscure tool which is not a default install on Linux distributions like xz is, and this makes distributing archives to other people difficult.

  1. I use duplicity & rdiff-backup to backup my entire home directory to a cheap 1.5TB hard drive (bought from Newegg using’s “Storage Analysis—GB/$ for different sizes and media” price-chart); a limited selection of folders are backed up to B2 using duplicity.

    I used to semiannually tar up my important folders, add redundancy, and burn them to DVD, but that’s no longer really feasible; if I ever get a Blu-ray burner, I’ll resume WORM backups. (Magnetic media doesn’t strike me as reliable over many decades, and it would ease my mind to have optical backups.)↩︎

  2. “When the Internet Is My Hard Drive, Should I Trust Third Parties?”⁠, Wired:

    Bits and pieces of the web disappear all the time. It’s called ‘link rot’, and we’re all used to it. A friend saved 65 links in 1999 when he planned a trip to Tuscany; only half of them still work today. In my own blog, essays and news articles and websites that I link to regularly disappear—sometimes within a few days of my linking to them.

  3. “Going, Going, Gone: Lost Internet References”⁠; abstract:

    The extent of Internet referencing and Internet reference activity in medical or scientific publications was systematically examined in more than 1000 articles published between 2000 and 2003 in the New England Journal of Medicine, The Journal of the American Medical Association, and Science. Internet references accounted for 2.6% of all references (672⁄25548) and in articles 27 months old, 13% of Internet references were inactive.

  4. The Million Dollar Homepage still gets a surprising amount of traffic, so one fun thing one could do is buy up expired domains which paid for particularly large links.↩︎

  5. By 2013-01-06, the number has increased to ~12000 external links, ~7200 to non-Wikipedia domains.↩︎

  6. If each link has a fixed chance of dying in each time period, such as 3%, then the total risk of death is an ⁠; over the time period 2011–2070 the cumulative chance it will beat each of the 3% risks is 0.1658. So in 2070, how many of the 2200 links will have beat the odds? Each link is independent, so they are like flipping a biased coin and form a ⁠. The binomial distribution, being discrete, has no easy equation, so we just ask R how many links survive at the 5th percentile/quantile (a lower bound) and how many survive at the 95th percentile (an upper bound):

    qbinom(c(0.05, 0.95), 2200, 0.97^(2070-2011))
    # [1] 336 394
    ## the 50% annual link rot hypothetical:
    qbinom(c(0.05, 0.50), 2200, 0.50^(2070-2011))
    # [1] 0 0
  7. 101, ‘Buddhism related to Blossoms’; ⁠; trans. Steven D. Carter, ISBN 0-231-10576-2↩︎

  8. Which I suspect is only accidentally ‘general’ and would shut down access if there were some other way to ensure that Wikipedia external links still got archived.↩︎

  9. Since Pinboard is a bookmarking service more than an archive site, I asked whether treating it as such would be acceptable and Maciej said “Your current archive size, growing at 20 GB a year, should not be a problem. I’ll put you on the heavy-duty server where my own stuff lives.”↩︎

  10. Google Cache is generally recommended only as a last ditch resort because pages expire quickly from it. Personally, I’m convinced that Google would never just delete colossal amounts of Internet data—this is Google, after all, the epitome of storing unthinkable amounts of data—and that Google Cache merely ceases to make public its copies. And to request a Google spider visit, one has to solve a CAPTCHA—so that’s not a scalable solution.↩︎

  11. Which would not be publicly accessible or submittable; I know they exist, but because they hide themselves, I know only from random comments online eg. “years ago a friend of mine who I’d lost contact with caught up with me and told me he found a cached copy of a website I’d taken down in his employer’s equivalent to the Wayback Machine. His employer was a branch of the federal government.”⁠.↩︎

  12. Version 0.1 of my archiver daemon didn’t simply read the file until it was empty and exit, but actually watched it for modifications with ⁠. I removed this functionality when I realized that the required WebCite choking (just one URL every ~25 seconds) meant that archiver would never finish any reasonable workload.↩︎

  13. Much easier than it was in the past; records his travails with the previous Mozilla history format in the aptly-named “when the database worms eat into your brain”⁠.↩︎

  14. An older 2010 Google article put the average at 320kb, but that was an average over the entire Web, including all the old content.↩︎

  15. Already one runs old games like the classic in emulators of the DOS operating system like ⁠; but those emulators will not always be maintained. Who will emulate the emulators? Presumably in 2050, one will instead emulate some ancient but compatible OS—Windows 7 or Debian 6.0, perhaps—and inside that run DOSBox (to run the DOS which can run the game).↩︎

  16. “BigTable: A Distributed Storage System for Structured Data”⁠, Chang et al 2006:

    BigTable maintains data in lexicographic order by row key. The row range for a table is dynamically partitioned. Each row range is called a tablet, which is the unit of distribution and load balancing. As a result, reads of short row ranges are efficient and typically require communication with only a small number of machines. Clients can exploit this property by selecting their row keys so that they get good locality for their data accesses. For example, in Webtable, pages in the same domain are grouped together into contiguous rows by reversing the hostname components of the URLs. For example, we store data for under the key Storing pages from the same domain near each other makes some host and domain analyses more efficient.