Now the database won't be destroyed on write errors
jdupes is a program for identifying and taking actions upon duplicate files such as deleting, hard linking, symlinking, and block-level deduplication (also known as "dedupe" or "reflink"). It is faster than most other duplicate scanners. It prioritizes data safety over performance while also giving expert users access to advanced (and sometimes dangerous) features.
Please consider financially supporting continued development of jdupes using the links on my home page (Ko-fi, PayPal, SubscribeStar, etc.):
Why use jdupes instead of the original fdupes or other duplicate finders?
The biggest reason is raw speed. In testing on various data sets, jdupes is over 7 times faster than fdupes-1.51 on average.
jdupes provides a native Windows port. Most duplicate scanners built on Linux and other UNIX-like systems do not compile for Windows out-of-the-box and even if they do, they don't support Unicode and other Windows-specific quirks and features.
jdupes is generally stable. All releases of jdupes are compared against a known working reference versions of fdupes or jdupes to be certain that output does not change. You get the benefits of an aggressive development process without putting your data at increased risk.
Code in jdupes is written with data loss avoidance as the highest priority. If a choice must be made between being aggressive or careful, the careful way is always chosen.
jdupes includes features that are not always found elsewhere. Examples of such
features include block-level data deduplication and control over which file is
kept when a match set is automatically deleted. jdupes is not afraid of
dropping features of low value; a prime example is the
-1 switch which
outputs all matches in a set on one line, a feature which was found to be
useless in real-world tests and therefore thrown out.
While jdupes maintains some degree of compatibility with fdupes from which it was originally derived, there is no guarantee that it will continue to maintain such compatibility in the future. However, compatibility will be retained between minor versions, i.e. jdupes-1.6 and jdupes-1.6.1 should not have any significant differences in results with identical command lines.
If the program eats your dog or sets fire to your lawn, the authors cannot be held responsible. If you notice a bug, please report it.
What jdupes is not: a similar (but not identical) file finding tool
Please note that jdupes ONLY works on 100% exact matches. It does not have any sort of "similarity" matching, nor does it know anything about any specific file formats such as images or sounds. Something as simple as a change in embedded metadata such as the ID3 tags in an MP3 file or the EXIF information in a JPEG image will not change the sound or image presented to the user when opened, but technically it makes the file no longer identical to the original.
Plenty of excellent tools already exist to "fuzzy match" specific file types using knowledge of their file formats to help. There are no plans to add this type of matching to jdupes.
There are some match options available in jdupes that enable dangerous file
matching based on partial or likely but not 100% certain matching. These are
considered expert options for special situations and are clearly and loudly
documented as being dangerous. The
-T options are notable examples,
and the extreme danger of the
-T option is safeguarded by a requirement to
specify it twice so it can't be used accidentally.
How can I do stuff with jdupes that isn't supported by fdupes?
The standard output format of jdupes is extremely simple. Match sets are presented with one file path per line, and match sets are separated by a blank line. This is easy to process with fairly simple shell scripts. You can find example shell scripts in the "example scripts" directory in the jdupes source code. The main example script, "example.sh", is easy to modify to take basic actions on each file in a match set. These scripts are used by piping the standard jdupes output to them:
jdupes dir1 dir2 dir3 | example.sh scriptparameters
Usage: jdupes [options] DIRECTORY...
Duplicate file sets will be printed by default unless a different action option is specified (delete, summarize, link, dedupe, etc.)
-@ --loud output annoying low-level debug info while running -0 --print-null output nulls instead of CR/LF (like 'find -print0') -1 --one-file-system do not match files on different filesystems/devices -A --no-hidden exclude hidden files from consideration -B --dedupe do a copy-on-write (reflink/clone) deduplication -C --chunk-size=# override I/O chunk size in KiB (min 4, max 262144) -d --delete prompt user for files to preserve and delete all others; important: under particular circumstances, data may be lost when using this option together with -s or --symlinks, or when specifying a particular directory more than once; refer to the documentation for additional information -D --debug output debug statistics after completion -e --error-on-dupe exit on any duplicate found with status code 255 -f --omit-first omit the first file in each set of matches -h --help display this help message -H --hard-links treat any linked files as duplicate files. Normally linked files are treated as non-duplicates for safety -i --reverse reverse (invert) the match sort order -I --isolate files in the same specified directory won't match -j --json produce JSON (machine-readable) output -l --link-soft make relative symlinks for duplicates w/o prompting -L --link-hard hard link all duplicate files without prompting Windows allows a maximum of 1023 hard links per file -m --summarize summarize dupe information -M --print-summarize will print matches and --summarize at the end -N --no-prompt together with --delete, preserve the first file in each set of duplicates and delete the rest without prompting the user -o --order=BY select sort order for output, linking and deleting: by mtime (BY=time) or filename (BY=name, the default) -O --param-order sort output files in order of command line parameter sequence Parameter order is more important than selected -o sort which applies should several files share the same parameter order -p --permissions don't consider files with different owner/group or permission bits as duplicates -P --print=type print extra info (partial, early, fullhash) -q --quiet hide progress indicator -Q --quick skip byte-by-byte duplicate verification. WARNING: this may delete non-duplicates! Read the manual first! -r --recurse for every directory, process its subdirectories too -R --recurse: for each directory given after this option follow subdirectories encountered within (note the ':' at the end of the option, manpage for more details) -s --symlinks follow symlinks -S --size show size of duplicate files -t --no-change-check disable security check for file changes (aka TOCTTOU) -T --partial-only match based on partial hashes only. WARNING: EXTREMELY DANGEROUS paired with destructive actions! -T must be specified twice to work. Read the manual! -u --print-unique print only a list of unique (non-matched) files -U --no-trav-check disable double-traversal safety check (BE VERY CAREFUL) This fixes a Google Drive File Stream recursion issue -v --version display jdupes version and license information -X --ext-filter=x:y filter files based on specified criteria Use '-X help' for detailed extfilter help -y --hash-db=file use a hash database text file to speed up repeat runs Passing '-y .' will expand to '-y jdupes_hashdb.txt' -z --zero-match consider zero-length files to be duplicates -Z --soft-abort If the user aborts (i.e. CTRL-C) act on matches so far You can send SIGUSR1 to the program to toggle this Detailed help for jdupes -X/--extfilter options General format: jdupes -X filter[:value][size_suffix] noext:ext1[,ext2,...] Exclude files with certain extension(s) onlyext:ext1[,ext2,...] Only include files with certain extension(s) size[+-=]:size[suffix] Only Include files matching size criteria Size specs: + larger, - smaller, = equal to Specs can be mixed, i.e. size+=:100k will only include files 100KiB or more in size. nostr:text_string Exclude all paths containing the string onlystr:text_string Only allow paths containing the string HINT: you can use these for directories: -X nostr:/dir_x/ or -X onlystr:/dir_x/ newer:datetime Only include files newer than specified date older:datetime Only include files older than specified date Date/time format: "YYYY-MM-DD HH:MM:SS" Time is optional (remember to escape spaces!) Some filters take no value or multiple values. Filters that can take a numeric option generally support the size multipliers K/M/G/T/P/E with or without an added iB or B. Multipliers are binary-style unless the -B suffix is used, which will use decimal multipliers. For example, 16k or 16kib = 16384; 16kb = 16000. Multipliers are case-insensitive. Filters have cumulative effects: jdupes -X size+:99 -X size-:101 will cause only files of exactly 100 bytes in size to be included. Extension matching is case-insensitive. Path substring matching is case-sensitive.
--no-trav-check option disables the double-traversal protection.
In the VAST MAJORITY of circumstances, this SHOULD NOT BE DONE, as it protects
against several dangerous user errors, including specifying the same files or
directories twice causing them to match themselves and potentially be lost or
irreversibly damaged, or a symbolic link to a directory making an endless loop
of recursion that will cause the program to hang indefinitely. This option was
added because Google Drive File Stream presents directories in the virtual hard
drive used by GDFS with identical device:inode pairs despite the directories
actually being different. This triggers double-traversal prevention against
every directory, effectively blocking all recursion. Disabling this check will
reduce safety, but will allow duplicate scanning inside Google Drive File
Stream drives. This also results in a very minor speed boost during recursion,
but the boost is unlikely to be noticeable.
--no-change-check option disables file change checks during/after
scanning. This opens a security vulnerability that is called a TOCTTOU (time of
check to time of use) vulnerability. The program normally runs checks
immediately before scanning or taking action upon a file to see if the file has
changed in some way since it was last checked. With this option enabled, the
program will not run any of these checks, making the algorithm slightly faster,
but also increasing the risk that the program scans a file, the file is changed
after the scan, and the program still acts like the file was in its previous
state. This is particularly dangerous when considering actions such as linking
and deleting. In the most extreme case, a file could be deleted during scanning
but match other files prior to that deletion; if the file is the first in the
list of duplicates and auto-delete is used, all of the remaining matched files
will be deleted as well. This option was added due to user reports of some
filesystems (particularly network filesystems) changing the reported file
information inappropriately, rendering the entire program unusable on such
--no-empty option was removed for safety. Matching zero-length files
as duplicates now requires explicit use of the
Duplicate files are listed together in groups with each file displayed on a separate line. The groups are then separated from each other by blank lines.
--symlinks option will treat symlinked files as regular files, but
direct symlinks will be treated as if they are hard linked files and the
-H/--hard-links option will apply to them in the same manner.
--delete, care should be taken to insure against
accidental data loss. While no information will be immediately lost, using this
option together with
--symlink can lead to confusing information
being presented to the user when prompted for files to preserve. Specifically,
a user could accidentally preserve a symlink while deleting the file it points
to. A similar problem arises when specifying a particular directory more than
once. All files within that directory will be listed as their own duplicates,
leading to data loss should a user preserve a file without its "duplicate" (the
--one-file-system prevents matches that cross filesystems, but
a more relaxed form of this option may be added that allows cross-matching for
all filesystems that each parameter is present on.
--soft-abort used to be
--hard-abort in jdupes prior to v1.5 and had
the opposite behavior. Defaulting to taking action on abort is probably not
what most users would expect. The decision to invert rather than reassign to a
different option was made because this feature was still fairly new at the time
of the change.
On non-Windows platforms that support SIGUSR1, you can toggle the state of the
-Z option by sending a SIGUSR1 to the program. This is handy if you want to
abort jdupes, didn't specify
-Z, and changed your mind and don't want to lose
all the work that was done so far. Just do '
killall -USR1 jdupes' and you will
be able to abort with
-Z. This works in reverse: if you want to prevent a
-Z from happening, a SIGUSR1 will toggle it back off. That's a lot less
useful because you can just stop and kill the program to get the same effect,
but it's there if you want it for some reason. Sending the signal twice while
the program is stopped will behave as if it was only sent once, as per normal
POSIX signal behavior.
--param-order option allows the user greater control over what
appears in the first position of a match set, specifically for keeping the
option from deleting all but one file in a set in a seemingly random way. All
directories specified on the command line will be used as the sorting order of
result sets first, followed by the sorting algorithm set by the
--order option. This means that the order of all match pairs for a single
directory specification will retain the old sorting behavior even if this
option is specified.
When used together with options
--symlink, a user could accidentally
preserve a symlink while deleting the file it points to.
--quick option only reads each file once, hashes it, and performs
comparisons based solely on the hashes. There is a small but significant risk
of a hash collision which is the purpose of the failsafe byte-for-byte
comparison that this option explicitly bypasses. Do not use it on ANY data set
for which any amount of data loss is unacceptable. You have been warned!
--partial-only option produces results based on a hash of the
first block of file data in each file, ignoring everything else in the file.
Partial hash checks have always been an important exclusion step in the jdupes
algorithm, usually hashing the first 4096 bytes of data and allowing files that
are different at the start to be rejected early. In certain scenarios it may be
a useful heuristic for a user to see that a set of files has the same size and
the same starting data, even if the remaining data does not match; one example
of this would be comparing files with data blocks that are damaged or missing
such as an incomplete file transfer or checking a data recovery against
known-good copies to see what damaged data can be deleted in favor of restoring
the known-good copy. This option is meant to be used with informational actions
and can result in EXTREME DATA LOSS if used with options that delete files,
create hard links, or perform other destructive actions on data based on the
matching output. Because of the potential for massive data destruction, this
option MUST BE SPECIFIED TWICE to take effect and will error out if it is only
--isolate option attempts to block matches that are contained in the
same specified directory parameter on the command line. Due to the underlying
nature of the jdupes algorithm, a lot of matches will be blocked by this option
that probably should not be. This code could use improvement.
--chunk-size option overrides the size of the I/O "chunk" used for
all file operations. Larger numbers will increase the amount of data read at
once from each file and may improve performance when scanning lots of files
that are larger than the default chunk size by reducing "thrashing" of the hard
disk heads. Smaller numbers may increase algorithm speed depending on the
characteristics of your CPU but will usually increase I/O and system call
overhead as well. The number also directly affects memory usage: I/O chunk size
is used for at least three allocations in the program, so using a chunk size of
16777216 (16 MiB) will require 48 MiB of RAM. The default is usually between
32768 and 65536 which results in the fastest raw speed of the algorithm and
generally good all-around performance. Feel free to experiment with the number
on your data set and report your experiences (preferably with benchmarks and
info on your data set.)
--hash-db feature creates and maintains a text file with a list of
file paths, hashes, and other metadata that enables jdupes to "remember" file
data across runs. Specifying a period '.' as the database file name will use a
name of "jdupes_hashdb.txt" instead; this alias makes it easy to use the hash
database feature without typing a descriptive name each time. THIS FEATURE IS
CURRENTLY UNDER DEVELOPMENT AND HAS MANY QUIRKS. USE IT AT YOUR OWN RISK. In
particular, one of the biggest problems with this feature is that it stores
every path exactly as specified on the command line; if any paths are passed
into jdupes on a subsequent run with a different prefix then they will not be
recognized and they will be treated as totally different files. For example,
jdupes -y . foo/ is not the same as
jdupes -y . ./foo nor the same
as (from a sibling directory)
jdupes -y ../foo. You must run jdupes from the
same working directory and with the same path specifications to take advantage
of the hash database feature. When used correctly, a fully populated hash
database can reduce subsequent runs with hundreds of thousands of files that
normally take a very long time to run down to the directory scanning time plus
a couple of seconds. If the directory data is already in the OS disk cache,
this can make subsequent runs with over 100K files finish in under one second.
Hard and soft (symbolic) linking status symbols and behavior
A set of arrows are used in file linking to show what action was taken on each link candidate. These arrows are as follows:
----> File was hard linked to the first file in the duplicate chain
-@@-> File was symlinked to the first file in the chain
-##-> File was cloned from the first file in the chain
-==-> Already a hard link to the first file in the chain
-//-> File linking failed due to an error during the linking process
If your data set has linked files and you do not use
-H to always consider
them as duplicates, you may still see linked files appear together in match
sets. This is caused by a separate file that matches with linked files
independently and is the correct behavior. See notes below on the "triangle
problem" in jdupes for technical details.
Microsoft Windows platform-specific notes
Windows has a hard limit of 1024 hard links per file. There is no way to change this. The documentation for CreateHardLink() states: "The maximum number of hard links that can be created with this function is 1023 per file. If more than 1023 links are created for a file, an error results." (The number is actually 1024, but they're ignoring the first file.)
The current jdupes algorithm's "triangle problem"
Pairs of files are excluded individually based on how the two files compare.
For example, if
--hard-links is not specified then two files which are hard
linked will not match one another for duplicate scanning purposes. The problem
with only examining files in pairs is that certain circumstances will lead to
the exclusion being overridden.
Let's say we have three files with identical contents:
a/file1 a/file2 a/file3
a/file1 is linked to
a/file3. Here's how
jdupes a/ sees them:
Are 'a/file1' and 'a/file2' matches? Yes [point a/file1->duplicates to a/file2] Are 'a/file1' and 'a/file3' matches? No (hard linked already, `-H` off) Are 'a/file2' and 'a/file3' matches? Yes [point a/file2->duplicates to a/file3]
Now you have the following duplicate list:
a/file1->duplicates ==> a/file2->duplicates ==> a/file3
The solution is to split match sets into multiple sets, but doing this will also remove the guarantee that files will only ever appear in one match set and could result in data loss if handled improperly. In the future, options for "greedy" and "sparse" may be introduced to switch between allowing triangle matches to be in the same set vs. splitting sets after matching finishes without the "only ever appears once" guarantee.
Does jdupes meet the "Good Practice when Deleting Duplicates" by rmlint?
Yes. If you've not read this list of cautions, it is available at http://rmlint.readthedocs.io/en/latest/cautions.html
Here's a breakdown of how jdupes addresses each of the items listed.
"Backup your data"/"Measure twice, cut once"
These guidelines are for the user of duplicate scanning software, not the software itself. Back up your files regularly. Use jdupes to print a list of what is found as duplicated and check that list very carefully before automatically deleting the files.
"Beware of unusual filename characters"
The only character that poses a concern in jdupes is a newline
\n and that is
only a problem because the duplicate set printer uses them to separate file
names. Actions taken by jdupes are not parsed like a command line, so spaces
and other weird characters in names aren't a problem. Escaping the names
properly if acting on the printed output is a problem for the user's shell
script or other external program.
"Consider safe removal options"
This is also an exercise for the user.
jdupes tracks each directory traversed by dev:inode pair to avoid adding the contents of the same directory twice. This prevents the user from being able to register all of their files twice by duplicating an entry on the command line. Symlinked directories are only followed if they weren't already followed earlier. Files are renamed to a temporary name before any linking is done and if the link operation fails they are renamed back to the original name.
jdupes uses xxHash for file data hashing. This hash is extremely fast with a low collision rate, but it still encounters collisions as any hash function will ("secure" or otherwise) due to the pigeonhole principle. This is why jdupes performs a full-file verification before declaring a match. It's slower than matching by hash only, but the pigeonhole principle puts all data sets larger than the hash at risk of collision, meaning a false duplicate detection and data loss. The slower completion time is not as important as data integrity. Checking for a match based on hashes alone is irresponsible, and using secure hashes like MD5 or the SHA families is orders of magnitude slower than xxHash while still suffering from the risk brought about by the pigeonholing. An example of this problem is as follows: if you have 365 days in a year and 366 people, the chance of having at least two birthdays on the same day is guaranteed; likewise, even though SHA512 is a 512-bit (64-byte) wide hash, there are guaranteed to be at least 256 pairs of data streams that causes a collision once any of the data streams being hashed for comparison is 65 bytes (520 bits) or larger.
"Unusual Characters Robustness"
jdupes does not protect the user from putting ASCII control characters in their file names; they will mangle the output if printed, but they can still be operated upon by the actions (delete, link, etc.) in jdupes.
"Seek Thrash Robustness"
jdupes uses an I/O chunk size that is optimized for reading as much as possible from disk at once to take advantage of high sequential read speeds in traditional rotating media drives while balancing against the significantly higher rate of CPU cache misses triggered by an excessively large I/O buffer size. Enlarging the I/O buffer further may allow for lots of large files to be read with less head seeking, but the CPU cache misses slow the algorithm down and memory usage increases to hold these large buffers. jdupes is benchmarked periodically to make sure that the chosen I/O chunk size is the best compromise for a wide variety of data sets.
"Memory Usage Robustness"
This is a very subjective concern considering that even a cell phone in someone's pocket has at least 1GB of RAM, however it still applies in the embedded device world where 32MB of RAM might be all that you can have. Even when processing a data set with over a million files, jdupes memory usage (tested on Linux x86-64 with -O3 optimization) doesn't exceed 2GB. A low memory mode can be chosen at compile time to reduce overall memory usage with a small performance penalty.
How does a duplicate scanner algorithm work?
The most naive way to look for files that are the same is to compare all files
to all other files using a tool like
cmp command on Linux/macOS/BSD or the
fc command on Windows/DOS. This works but is extremely slow and wastes a lot
of time. For every new file to compare, the number of comparisons increases
exponentially (the formula is n(n-1)/2 for the discrete math nerds):
Let's say that every file is 1,000 bytes in size and you have 10,000 files for a total size of 10,000,000 bytes (about 9.53 MiB). Using this naive comparison approach means the actual amount of data to compare is around 47,679 MiB. You should be able to see how extreme this can get--especially with larger files.
A slightly smarter approach is to use file hashes as a substitute for the full file contents. A hash is a number based on the data fed into a hash function and the number is always the same when the same data is fed in. If the hash for two files is different then the contents of those files are guaranteed to be different; if the hash is the same then the data might be the same, though this is not guaranteed due to the birthday problem: the size of the number is much smaller than the size of the data it represents, so there will always be many different inputs that produce the same hash value. Files with matching hash values must still be compared just to be sure that they are 100% identical.
49,995,000 comparisons can be done much quicker when you're only comparing a single big number every time instead of thousands or millions of bytes. This makes a big difference in performance since the only files being compared are files that look likely to be identical.
Fast exclusion of non-duplicates is the main purpose of duplicate scanners.
jdupes uses a lot of fast exclusion techniques beyond this. A partial list of these in the order they're performed is as follows:
- Files that the user asks the program to exclude are skipped entirely
- Files with different sizes can't be identical, so they're not compared
- The first 4 KiB is hashed and compared which avoids reading full files
- Entire files are hashed and compared which avoids comparing data directly
- Finally, actual file data is compared to verify that they are duplicates
The vast majority of non-duplicate file pairs never make it past the partial (4 KiB) hashing step. This reduces the amount of data read from disk and time spent comparing things to the smallest amount possible.
v1.20.0 specific: most long options have changed and -n has been removed
Long options now have consistent hyphenation to separate the words used in the
option names. Run
jdupes -h to see the correct usage. Legacy options will
remain in place until the next major or minor release (v2.0 or v1.21.0) for
compatibility purposes. Users should change any scripts using the old options
to use the new ones...or better yet, stop using long options in your scripts
in the first place, because it's unnecessarily verbose and wasteful to do so.
v1.15+ specific: Why is the addition of single files not working?
If a file was added through recursion and also added explicitly, that file would end up matching itself. This issue can be seen in v1.14.1 or older versions that support single file addition using a command like this in the jdupes source code directory:
/usr/src/jdupes$ jdupes -rH testdir/isolate/1/ testdir/isolate/1/1.txt testdir/isolate/1/1.txt testdir/isolate/1/1.txt testdir/isolate/1/2.txt
Even worse, using the special dot directory will make it happen without the -H option, which is how I discovered this bug:
/usr/src/jdupes/testdir/isolate/1$ jdupes . 1.txt ./1.txt ./2.txt 1.txt
This works for any path with a single dot directory anywhere in the path, so it has a good deal of potential for data loss in some use cases. As such, the best option was to shove out a new minor release with this feature turned off until some additional checking can be done, e.g. by making sure the canonical paths aren't identical between any two files.
A future release will fix this safely.
Website and contact information
General program information, help, and tech info: https://www.jdupes.com/
Development, source code, and releases: https://codeberg.org/jbruchon/jdupes
Have a bug report or questions? contact Jody Bruchon email@example.com
Legal information and software license
jdupes is Copyright (C) 2015-2023 by Jody Bruchon firstname.lastname@example.org
Derived from the original 'fdupes' 1.51 (C) 1999-2014 by Adrian Lopez
The MIT License
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:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.