generate perfect hashes (alpha)
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Perfect::Hash - generate perfect hashes, library backend for pperf


# generate c file for readonly lookup
pperf keyfile --prefix=pperf ...

# pure-perl usage
use Perfect::Hash;
my @dict = split/\n/,`cat /usr/share/dict/words`;
my $ph = Perfect::Hash->new(\@dict, -minimal);
for (@ARGV) {
  my $v = $ph->perfecthash($_);
  print ($dict[$v] eq $_ ? "$_ at line ".$v+1."\n" : "$_ not found\n");

Perfect::Hash->new("keyfile", '-urban', ...)->save_c;
# or just:
pperf keyfile --urban
cc -O3 -msse4.2 pperf.c ... -lz

pperf /usr/share/dict/words --cmph-bdz_ph --nul
cc -O3 pperf.c ... -lcmph


Perfect hashing is a technique for building a static hash table with no collisions, only lookup, no insert and delete methods. Which means guaranteed constant O(1) access time, and for minimal perfect hashes even guaranteed minimal size. It is only possible to build one when we know all of the keys in advance. Minimal perfect hashing implies that the resulting table contains one entry for each key, and no empty slots.

As input we need to provide a set of unique keys, either as arrayref or hashref or as keyfile. The keys can so far only be strings (will be extended to ints on demand) and the values can so far be only ints and strings. More types later.

As generation algorithm there exist various perfect hashing and other fast lookup methods: Hanov, HanovPP, Urban, CMPH::*, Bob, Pearson*, Gperf, Switch, and maybe Cuckoo, RobinHood, HAMT, ... Not all generated lookup methods are perfect hashes per se. I also implemented traditional methods which might be faster for smaller key sets, like nested switches, hash array mapped tries or ordinary open addressing hash tables.

As output there exist several output formater classes, e.g. C and later: XS, Java, Ruby, PHP, Python, PECL. For Lua or Lisp this is probably not needed as they either roll their own, or FFI into the generated C library. For Go, Rust, Scala, Clojure, etc just roll you own library, based on an existing one.

The best algorithm used in Hanov and various others is derived from "Compress, Hash, and Displace algorithm" by Djamal Belazzougui, Fabiano C. Botelho, and Martin Dietzfelbinger

Prior art to pperf

There exist some executables, a library and a simple python script to generate code to access perfect hashes and minimal versions thereof, but nothing to use easily. gperf is not very well suited to create big maps and cannot deal with certain anagrams, but creates fast C code for small dictionaries.

Bob Jenkins' perfect - he called it bob, hence we also - is more stable than gperf, but requires an external lookup function.

Pearson hashes are simplier and fast for small machines, but not guaranteed to be creatable for small or bigger hashes.

cmph CHD, BDZ_PH and the other cmph algorithms might be the best algorithms for big hashes, but lookup time is slower for smaller hashes and you need to link to an external library.

mkhashtable generates a fast cuckoo hash table for integer lookup.


  • new hashref|arrayref|keyfile, algo, options...

    Evaluate the best algorithm given the dict size and output options and generate the minimal perfect hash for the given keys.

    The values in the dict are not needed to generate the perfect hash function, but might be needed later. So you can use either an arrayref where the index is returned, or a full hashref or a keyfile as with gperf.

    Options for output classes are prefixed with -for-, e.g. -for-c. They might be needed to make a better decision which perfect hash to use.

    The following algorithms and options are done and planned:

    • -false-positives

      Do not store the keys of the hash. Needs much less space and is faster, but might only be used either if you know in advance that you'll never lookup not existing keys, or check the result manually by yourself with your already existing keys array to avoid false positives.

    • -minimal (not yet)

      Selects the best available method for a minimal hash, given the dictionary size, the options, and if the compiled algos are available.

    • -optimal-size (not yet)

      Tries various hashes, and uses the one which will create the smallest hash in memory. Those hashes usually will not store the value, so you might need to check the result for a false-positive.

    • -optimal-speed (not yet)

      Tries various hashes, and uses the one which will use the fastest lookup.

    • -hanovpp

      The default pure perl method, based on CHD. Hashes the key 1.5x times, same as for Cuckoo hashing.

    • -hanov

      Improved version of HanovPP, using optimized XS methods, 2-3x faster with HW supported iSCSI CRC32 (via zlib or manually).

      The fast hash function requires a relatively new 64bit Intel, AMD or ARM processor. This might need the external zlib library (-lz) at run-time.

    • -urban

      Improved version of Hanov, using compressed temp. arrays and the same optimized XS methods and hash functionsas in -hanov. But can only store index values in a limited range, not strings.

    • -pearson8

      Strict variant of a 8-bit (256 byte) Pearson hash table. Generates fast lookups for small 8-bit machines, but limited dictionaries with a 8-bit pearson table for 5-255 keys. Returns undef for invalid dictionaries.

    • -pearson

      Non-perfect variant with adjusted pearson table size. Try to find a n-bit sized pearson table for the given dictionary. Keeps the best found hash table, with no guarantees that it is a perfect hash table. If not, collision resolution is done via static binary trees.

      This version generates arbitrary sized pearson lookup tables and thus should be able to find a perfect hash, but success is very unlikely.

    • -pearsonnp

      "np" for non-perfect. Try to find a 8-bit (256 byte) sized pearson table for the given dictionary. Keeps the best found hash table, with no guarantees that it is a perfect hash table. If not, collision resolution is done via static binary search. (currently only linear search).

      This is also a very fast variant for small 8-bit machines as the 256 byte table is guaranteed to fit into every CPU cache, but it only iterates in byte steps.

    • -pearson16 (todo, experimental)

      Generate non-perfect pearson hash with an optimized 16bit hash function, a much bigger 16bit table (size: 65536 shorts), and static binary tree collision resolution.

    • -pearson32 (experimental)

      Generate non-perfect pearson hash with an optimized 32bit hash function, a pearson table of size 256 and static binary tree collision resolution.

    • -gperf

      Generates pretty fast lookup, because it is not hashing the string, it just takes some characters from the string to create a unique key. Only limited dictionaries and smaller sizes.

      Currently only via the gperf executable. Planned to do it in pure-perl to be independent and improve the generated memcpy comparisons, as in -switch.

    • -switch

      Only for smaller dictionaries. Uses no hash function nor hash table, just generates a fast switch table in C as with gperf --switch for smaller dictionaries.

      Generates a nested switch table, first switching on the size and then on the best combination of keys. The difference to gperf --switch is the automatic generation of nested switch levels, depending on the number of collisions, and it is optimized to use word size comparisons for the fixed length comparisons, which is up to 50% faster than memcmp. The performance is comparable to the best perfect hashes.

    • -bob (todo)

      Generates C code more stable than gperf, but requires an external dependency for the lookup function.

    • -cmph-bdz_ph (todo)

      The -cmph-* methods are the current state of the art for bigger dictionaries. This needs the external cmph library even at run-time.

      The performance depends on the dictionary size. -cmph-bdz_ph is usually the fastest cmph method for 1.000 - 250.000 keys, and -cmph-chm is usually the second best option.

    • -cmph-bdz (todo)

    • -cmph-bmz (todo)

    • -cmph-chm (todo)

      So far this is the most stable variant.

    • -cmph-fch (todo)

    • -cmph-chd_ph (todo)

    • -cmph-chd (todo)

    • -cuckoo (not yet)

      Generates good cuckoo tables and hash functions to lookup a string. Unlike the other hash tables here this can be extended to dynamic cuckoo hash tables, by adding insert and delete functions which just resize to dynamic tables. Cuckoo uses 1.5x hashing of the key (same as -hanov) and requires 2 collision-free lookup arrays. See

    • -for-c (default)

      Optimize for C libraries

    • -for-xs (not yet)

      Optimize for shared Perl XS code. Stores the values as perl types.

    • -for-class (not yet)

      Optimize for any CLASS output formatter class, loaded dynamically. Such as PYTHON, RUBY, JAVA, PHP, PECL, ...

    • -hash=name (not yet)

      Use the specified hash function instead of the default. See -hash=help for a list of all supported hash function names: crc32_zlib, fnv, crc32_sse42, aes, GFMultilinear...

      Only useful for hardware assisted crc32, aes and more xmm system calls, provided by compiler intrinsics (sse4.2) or libz. Note that some zlib libraries do not provide a HW-assisted fast crc32 function, rather a slow SW variant.

      The hardware assisted crc32 and aes functions add a run-time probe with slow software fallback code (not yet). crc32_zlib does all this also, and is especially optimized for long keys to hash them in parallel, if implemented in your library.

      GFMultilinear for 64bit Intel and AMD is from

    • -pic (in work)

      Optimize the generated table for inclusion in shared libraries via a constant direct stringpool, in contrast to a table of indirect string pointers. This reduces the startup time of programs using a shared library containing the generated code. As with gperf --pic


      -P/--pic does a perfect optimization but may require some small code changes (see the gperf documentation for details), whereas --null-strings does only a half-hearted optimization but works without needing any change to surrounding code.

    • -nul

      Allow NUL bytes in keys, i.e. store the length for keys and compare binary via memcmp. Does not use strlen.

    • -null-strings (not yet)

      Use NULL strings instead of empty strings for empty keyword table entries without -false-positives. This reduces the startup time of programs using a shared library containing the generated code (but not as much as the declaration -pic option), at the expense of one more test-and-branch instruction at run time.

    • -7bit (not yet)

      Guarantee that all keys consist only of 7-bit ASCII characters, bytes in the range 0..127.

    • -ignore-case (not yet)

      Consider upper and lower case ASCII characters as equivalent. The string comparison will use a case insignificant character comparison. Note that locale dependent case mappings are ignored.

    • -unicode-ignore-case (not yet)

      Consider upper and lower case unicode characters as equivalent. The string comparison will use a case insignificant character comparison. Note that locale dependent case mappings are planned to be done via libicu or the better libunistring.

  • find_best_method $dict, @options

    Scans the given dictionary, honors the given options and current architecture and returns the name of the recommended hash table algorithm for fast lookups.

  • perfecthash $key

    Returns the index into the arrayref, resp. the provided hash value.

  • false_positives

    Returns 1 if perfecthash might return false positives. I.e. will return the index of an existing key when you searched for a non-existing key. Then you'll need to check the result manually again.

    The default is undef, unless you created the hash with the option -false-positives.

  • save_c fileprefix, options

    See "save_c" in Perfect::Hash::C

  • save_xs file, options

    See "save_xs" in Perfect::Hash::XS


script/pperf for the frontend.


Perfect::Hash::HanovPP, Perfect::Hash::Hanov, Perfect::Hash::Urban, Perfect::Hash::Pearson, Perfect::Hash::Pearson8, Perfect::Hash::PearsonNP, Perfect::Hash::Pearson32, Perfect::Hash::Pearson16, Perfect::Hash::Gperf, Perfect::Hash::Switch, Perfect::Hash::Bob, Perfect::Hash::Cuckoo (not yet), Perfect::Hash::CMPH::CHM, Perfect::Hash::CMPH::BMZ, Perfect::Hash::CMPH::BMZ8 (not yet), Perfect::Hash::CMPH::BRZ (not yet), Perfect::Hash::CMPH::FCH Perfect::Hash::CMPH::BDZ, Perfect::Hash::CMPH::BDZ_PH, Perfect::Hash::CMPH::CHD, Perfect::Hash::CMPH::CHD_PH

Output classes

Output classes are loaded dynamically from a -for-class option, the option must be lowercase, the classsname must be uppercase.

Perfect::Hash::C -for-c (C library)

Perfect::Hash::XS -for-xs (compiled perl extension)


Perfect::Hash::PYTHON -for-python (compiled python extension)

Perfect::Hash::RUBY -for-ruby (compiled ruby extension)

Perfect::Hash::JAVA -for-java

Perfect::Hash::PHP -for-php (pure php)

Perfect::Hash::PECL -for-pecl (compiled php extension)

For Lua or Lisp this is probably not needed as they either roll their own, or FFI into the generated C library. For Go, Rust, Scala, Clojure, etc just roll you own library, based on an existing one.


CPAN Testers:




linux/amd64 with a dictionary size=99171, lookup every key. with Intel Core i5-2300 CPU @ 2.80GHz with native iSCSI CRC32-C from zlib.

size=99171  (smaller sec and size is better)
Method       *lookup*  generate compile   c size   exesize  options
hanovpp      0.007391  1.404147 1.319399  1199117  2434100  -false-positives -nul
hanov        0.011482  0.785057 1.324067  1197862  2434154  -false-positives -nul
urban        0.014077  0.910796 1.428419  1197862  2434154  -false-positives -nul
pearson      0.017292 60.923645 4.739699  8530499  8749003  -false-positives -nul
pearsonnp    0.101567 10.510307 2.318995  2647958  4551321  -false-positives -nul
switch       0.006666  0.107138 36.451262 147708238 1650346 -false-positives -nul
gperf                  0.147823 180.766459      0        0  -false-positives -nul
			with -1 errors. (killed)
hanovpp      0.013005  1.688023 2.141894  2393751  3227319  -nul
hanov        0.016095  0.963938 2.163220  2392496  3227389  -nul
urban        0.011075  1.040831 2.221746  2392496  3227389  -nul
pearson      0.030881 61.119899 5.680831  9728955  9540540  -nul
pearsonnp    0.086979 10.663448 3.009915  3842596  5346272  -nul
cmph-bdz_ph  0.017982  0.215315 0.831952    67005  1664617  -nul
cmph-bdz     0.023443  0.225905 0.817219    98105  1674529  -nul
cmph-bmz     0.038583  0.300829 0.976980  1590581  2096417  -nul
cmph-chm     0.027509  0.259225 1.050285  3074292  2469305  -nul
cmph-fch     0.031648 12.190459 0.854709   196138  1698857  -nul
cmph-chd_ph  0.036570  0.211594 0.824568    36049  1652489  -nul
cmph-chd     0.039105  0.215639 0.844438   141652  1692769  -nul
switch       0.005178  0.109766 37.781077 147708238 1650282 -nul
gperf                  0.154852 386.132215      0        0  -nul
			with -1 errors. (killed)
hanovpp      0.013155  1.723117 1.352003  1199134  2434100  -false-positives
hanov        0.010365  1.030929 1.433591  1197879  2434154  -false-positives
urban        0.014317  1.088831 1.402750  1197879  2434154  -false-positives
pearson      0.026460 61.211019 4.794338  8523000  8742950  -false-positives
pearsonnp    0.086456 10.718970 2.348913  2647985  4551001  -false-positives
switch       0.007402  0.112189 37.527018 147708256 1650386 -false-positives
gperf                  0.144518 65.111405       0        0  -false-positives
		with -1 errors. (killed)
hanovpp      0.010637  1.729399 2.189703  2393768  3227327
hanov        0.012009  1.011663 2.147036  2392513  3227381
urban        0.011328  1.092358 2.310917  2392513  3227381
pearson      0.023296 61.009376 5.589329  9728411  9544760
pearsonnp    0.084357 10.755647 3.067713  3842623  5342760
cmph-bdz_ph  0.022976  0.219827 0.853593    66651  1664617
cmph-bdz     0.036118  0.221703 0.825658    97681  1674529
cmph-bmz     0.041349  0.279304 0.966324  1589301  2096417
cmph-chm     0.044141  0.471280 1.085401  3073424  2469305
cmph-fch     0.035379  3.419452 0.872933   196252  1698857
cmph-chd_ph  0.028199  0.212325 0.826772    35938  1652465
cmph-chd     0.039602  0.245328 0.842385   142315  1692801
switch       0.005429  0.117641 37.769247 147708256 1650386
gperf                  0.150903 69.595114       0        0
		with -1 errors. (killed)

Medium sized dictionary with 2000 keys: perl -Mblib examples/ -size 2000 -nul

Method       *lookup*  generate compile   c size   exesize  options
hanovpp      0.001609  0.026357 0.116650    43698    65615  -nul
hanov        0.001611  0.012582 0.124696    43404    65685  -nul
urban        0.001508  0.019618 0.133672    43404    65685  -nul
pearson      0.001831 15.485680 0.193747   181242   181172  -nul
pearsonnp    0.001418  0.198577 0.136419   102856   143324  -nul
cmph-bdz_ph  0.002027  0.005285 0.119930     1563    42057  -nul
cmph-bdz     0.001745  0.005561 0.096891     2261    42057  -nul
cmph-bmz     0.002272  0.005246 0.103500    34671    50377  -nul
cmph-chm     0.001750  0.003973 0.096253    64383    58441  -nul
cmph-fch     0.001999  0.090500 0.088006     6670    42929  -nul
cmph-chd_ph  0.001819  0.002955 0.083981     1102    42057  -nul
cmph-chd     0.002014  0.002584 0.084404     3390    42297  -nul
switch       0.001514  0.004039 0.523429  1042824    50946  -nul
gperf        0.001428  0.005495 0.872581   295195   297154  -nul

Small dictionary with 127 keys:

Method       *lookup*  generate compile   c size   exesize  options
hanovpp      0.001247  0.001904 0.069912     3454    11575
hanov        0.001231  0.000946 0.070709     3200    11629
urban        0.001298  0.001020 0.072471     3200    11629
pearson      0.001178  0.068758 0.072311    12354    19240
pearsonnp    0.001253  0.018204 0.072419    12386    19259
cmph-bdz_ph  0.001271  0.000412 0.066264      335    10009
cmph-bdz     0.001317  0.000403 0.066471      424    10033
cmph-bmz     0.001277  0.000539 0.066814     2431    10577
cmph-chm     0.001325  0.000646 0.067026     4356    11057
cmph-fch     0.001372  0.000511 0.066843      942    10177
cmph-chd_ph  0.001310  0.000361 0.066292      418    10033
cmph-chd     0.001323  0.000343 0.066428      735    10129
switch       0.001190  0.000173 0.131323    12517    17450
gperf        0.001199  0.002180 0.064883     8987    12574


Reini Urban 2014


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