|Did you know ...||Search Documentation:|
The indexing capabilities of SWI-Prolog are described in section 2.18. Summarizing, SWI-Prolog creates indexes for any applicable argument, pairs of arguments and indexes on the arguments of compound terms when applicable. Extended JIT indexing is not widely supported among Prolog implementations. Programs that aim at portability should consider using term_hash/2 and term_hash/4 to design their database such that indexing on constant or functor (name/arity reference) on the first argument is sufficient. In some cases, using the predicates below to add one or more additional columns (arguments) to a database predicate may improve performance. The overall design of code using these predicates is given below. Note that as term_hash/2 leaves the hash unbound if Term is not ground. This causes the lookup to be fast if Term is ground and correct (but slow) otherwise.
:- dynamic x/2. assert_x(Term) :- term_hash(Term, Hash), assertz(x(Hash, Term)). x(Term) :- term_hash(Term, Hash), x(Hash, Term).
This predicate may be used to build hash tables as well as to exploit argument indexing to find complex terms more quickly.
The hash key does not rely on temporary information like addresses of atoms and may be assumed constant over different invocations and versions of SWI-Prolog.87Last change: version 5.10.4 Hashes differ between big and little endian machines. The term_hash/2 predicate is cycle-safe.bugAll arguments that (indirectly) lead to a cycle have the same hash key.
HashKey is in the range [0 ...Range-1]. Range must be in the range [1 ... 2147483647].
This predicate raises an exception when trying to compute the hash on a cyclic term or attributed term. Attributed terms are not handled because subsumes_chk/2 is not considered well defined for attributed terms. Cyclic terms are not supported because this would require establishing a canonical cycle. That is, given A=[a|A] and B=[a,a|B], A and B should produce the same hash. This is not (yet) implemented.
This hash was developed for lookup of solutions to a goal stored in a table. By using a cryptographic hash, heuristic algorithms can often ignore the possibility of hash collisions and thus avoid storing the goal term itself as well as testing using =@=/2.