Datalog in miniKanren
deosjr.github.io
deosjr.github.io
Runs in the browser using Hoot (https://spritely.institute/hoot/) which compiles Guile Scheme to WebAssembly.
If you thought this was cool, wait until you see what I ended up using it for: https://deosjr.github.io/dynamicland/ I personally think this is much cooler :) But it needs some more explaining before I can broadly share, I think.
Now that I have you here, a question: am I correct in thinking that in Hoot, eval in the browser does not currently work with macros?
Regarding your question, as of Hoot 0.6.1 we now have a psyntax-based macro expander integrated with eval so you can use syntax-rules and syntax-case. There are still rough edges, though. I'm currently focused on some non-Hoot tasks but the next Hoot priority is to implement a Guile-like REPL and really kick the tires on the interpreter before the 0.7.0 release.
I think the most misunderstood thing about Prolog (and Datalog, the functor-free subset of pure Prolog) is that the syntax is really, really important.
It's like, the whole gimmick of the language. It is designed to efficiently and elegantly query and transform itself. If you lose the syntax you lose all of intermediate and advanced Prolog (and Datalog).
However, syntax does matter, and this is not acceptable
(dl-find
(fresh-vars 1
(lambda (?id)
(dl-findo dl
((,?id reachable ,?id)))))))
reachable(Id, Id).
(?id reachable ?id)
However, the ordering betrays a deeper semantic difference with orthodox Datalog, which is about distinct N-ary relations, like a relational database, not binary relations. This implementation seems to be specific to binary relations, so it's not really Datalog for reasons that go beyond mere syntax.
On the other hand, this (from the initial goal) would be perfectly fine:
(dl-rule! dl (reachable ,?x ,?y) :-
(edge ,?x ,?z) (reachable ,?z ,?y))
reachable(X, Y) :- edge(X, Z), reachable(Z, Y).There is a dl-rule here: https://github.com/deosjr/deosjr.github.io/blob/15b5f7e02153...
Yes, I think the semantic divergence is more fundamental. Triple stores and graph databases and binary relations are awesome, but they aren't what Datalog is.
Should've probably been a bit more clear on the dl-find syntax; I find it just as unacceptable as you do. It is the result of laziness: my intended use of this minimal Datalog does not include any querying whatsoever but abuses fixpoint analysis for side-effects (see https://github.com/deosjr/deosjr.github.io/blob/master/dynam... which I intend to go over in a future post). I initially had it working like you described but butchered it for the above and haven't repaired it yet (see https://github.com/deosjr/whistle?tab=readme-ov-file#datalog). This version relied on some monstrous eval-hacking using a homebrew Lisp, which I've mostly cleaned up now in this version (https://github.com/deosjr/whistle/blob/main/datalog/datalog.... is a crime, for example).
The semantics are indeed limited to binary relations atm, which I agree is the main thing that disqualifies this as a proper Datalog. iirc the tutorial on Datalog that I based this implementation on only handled triples as well so I stopped there, but extending to N-ary relations is on my list to look into for sure.
I am always worried about posting comments like mine because often people get defensive when I try to engage, as I see it, on substance. Responses like yours make it all worthwhile!
Coming from Prolog I'd like to get closer to the original if possible :)
E.g., if you have a fact id=(a,b,c,d), you can record triples (id, 1, a), (id, 2, b), (id, 3, c) and (id, 4, d) and reconstruct original fact.
Look at it as columnar storage in databases.
Then, if your query only needs a third value from a 4-tuple facts, you can get only those, ignoring first, second and fourth values. This is what columnar storage engines do.
In fact, I read that one of most efficient datalog engines use relational query execution under the hood.
Take a look here: https://github.com/philzook58/awesome-egraphs
The paper you'll most probably find interesting is "Better Together: Unifying Datalog and Equality Saturation," but there are many others interesting things there.
The Wikipedia article recommends https://search.worldcat.org/title/30546436 "Foundations of Databases" by Abiteboul, Hull, and Vianu, from 01995, and https://archive.org/details/logicdatabases0000symp/page/n5/m... "Logic and Data Bases [sic]" by Gallaire and Minker from 01978. Some poking at Google Scholar also turns up, in rough order of how promising they look (without having read them that I can recall):
https://dl.acm.org/doi/pdf/10.1145/6012.15399 "Magic Sets and Other Strange Ways to Implement Logic Programs", Bancilhon, Maier, Sagiv, & Ullman (yes, that Ullman), 01985 (15 pp.)
https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&d... "What You Always Wanted to Know About Datalog (And Never Dared to Ask)", Ceri, Gottlob, and Tanca, 01989 (21 pp.)
https://web.cecs.pdx.edu/harry/earley/datalog.pdf "Optimizations to Earley Deduction for DATALOG Programs", Porter, 01985 (12 pp.)
https://dl.acm.org/doi/pdf/10.1145/308386.308420 "Optimizing Existential Datalog Queries", Ramakrishhnan, Beers, & Krishnamurthy, 01988 (14 pp.)
https://dl.acm.org/doi/pdf/10.1145/298514.298542 "On the Expressive Power of Datalog: Tools and a Case Study", Kolaitis & Vardi, 01990
https://dl.acm.org/doi/pdf/10.1145/93605.98724 "A Framework for the Parallel Processing of Datalog Queries", Ganguly, Silberschatz, & Tsur, 01990
https://deepblue.lib.umich.edu/bitstream/handle/2027.42/3116... "Datalog vs First-Order Logic", Ajtai & Gurevich, 01993
https://lat.inf.tu-dresden.de/teaching/ss2014/Seminar/Papers... "Equivalence of Datalog Queries is Undecidable", Shmueli, 01993
It also turned up "Portability of Syntax and Semantics in Datalog" which turned out to be an unrelated NLP AI system called Datalog.
Bancilhon, Maier, Sagiv, & Ullman give as their reference for Datalog "Maier and Warren [1985]", which turns out to be "D. Maier and D. S. Warren [1985]. Introduction to Logic Programming, unpublished memorandum, Oregon Graduate Center," which I can't find a copy of easily. But given that Maier is a shared author we can probably trust their summary of what Datalog is.
Ceri, Gottlob, and Tanca reference "[120], [15], [16]," which are respectively:
J. D. Ullman, “Implementation of logic query languages for databases,” ACM Trans. Database Syst., vol. 10, no. 3, 1985
F. Bancilhon and R. Ramakrishnan, “An amateur’s introduction to recursive query processing,” in Proc. ACM-SIGMOD Conf., May 1986.
-, “Performance evaluation of data intensive logic programs,” in Foundations of Deductive Databases and Logic Programming, J. Minker, Ed. Washington, DC, 1986.
The Ullman paper is https://dl.acm.org/doi/pdf/10.1145/3979.3980, "Implementation of Logical Query Languages for Databases", ACM Transactions on Database Systems, Vol. 10, No. 3, September 1985, Pages 289-321 (33 pp.). Ceri, Gottlob, and Tanca screwed up the title. https://dl.acm.org/doi/10.1145/971699.320000 probably isn't it; the journal name, volume number, and issue number don't match, although it's the right author and year. That seems to be the oldest published Datalog paper, although the word "Datalog" hadn't been invented yet and doesn't appear in the paper.
I think I'm going to read the Bancilhon, Maier, Sagiv, & Ullman paper first, because it's shorter and has a more readable-sounding title, and then maybe Ceri, Gottlob, and Tanca, and then maybe Ullman, and then maybe a relevant chapter or two of Gallaire and Minker.
Yes it started out as a Prolog subset, but the definition as the fragments it supports has become much more prevalent, mainly to contrast it to non-recursive fragments with arbitrary negation (e.g. SQL).
This usage dates back to database literature of the 80s by Ullman et. al.