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#datalog — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #datalog, aggregated by home.social.

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  1. EyeProlog just got a serious OpenRuleBench boost 🚀

    **166s → 27s**, **1.5GB → 450MB**, all 14 benchmarks running — including WFS cases.

    Code + benchmarks:
    github.com/eyereasoner/eyeprol

  2. All basic test cases pass! Enough for tonight. Tomorrow, we start testing recursion.

    #Draupnir #Datalog

  3. Prolog nezmizel. Jeho hlavní myšlenku dnes potkáváme v nástrojích, které se Prologu na první pohled nepodobají: v CodeQL pro analýzu kódu, v Rego pro policy-as-code, v Z3 pro práci s omezeními a v Leanu pro formální důkazy. Každý řeší jiný problém, ale všechny připomínají totéž: někdy je lepší popsat vztahy, pravidla, omezení nebo tvrzení než vrstvit další if.

    https://zdrojak.cz/clanky/prolog-nezmizel-jen-dnes-zije-v-jinych-nastrojich/
  4. Как я построил Graph RAG систему с точностью 96.7% за 5 дней: от научных статей до production-ready пайплайна

    Я реализовал Graph RAG систему, которая комбинирует 5 техник из свежих научных статей (KET-RAG, HippoRAG 2, VectorCypher) в единый пайплайн с декларативным Datalog reasoning-движком, полной провенансной трассировкой и типизированным API. Результат: 174/180 (96.7%) на билингвальном бенчмарке из 30 вопросов, оценённых в 6 режимах retrieval. Три режима достигли 100%. В статье — архитектура, 10 уроков оптимизации и эволюция от 38% до 96.7% за 10 итераций.

    habr.com/ru/articles/1003064/

    #GraphRAG #RAG #Neo4j #NLP #LLM #Python #Datalog #Knowledge_Graph #embeddings #PageRank

  5. I feel tempted to write a toy(ish) #Datalog database similar to Datomic in #OCaml, just to understand how that type of DBs work, and to learn how to optimize Datalog queries. Maybe not the most efficient way to learn, but I think it's most fun.

  6. Even though I mostly use #Datalog databases these days (mostly #Datomic), many #PostgreSQL tidbits make me (unreasonably?) happy. Like this one: “Aggregate first - join later”

    cybertec-postgresql.com/en/sup

  7. Recursion in #Draupnir is getting closer, making it very nearly a proper #Datalog compiler. What would normally be a simple task is becoming considerably harder due to the need to support general monoid bases for the relations (which we want for cleaner aggregates than Souffle), as well as the need to handle batch scheduling to support disk.

    The main challenge so far has been coming up with an execution plan that safely batches each iteration, while playing nicely with our push+pull scheduler, and simultaneously making sure that it maintains the correct arity of each tuple. Not hard... but very finicky.

    We've come up with a pretty clean set of extensions to our logical pipeline DAG that seem like they elegantly capture recursion, and compiling a simple (count the paths) query to the logical stage appears to be producing a sensible graph. This has revealed some bugs in the pipeline optimizer, and we still need to add support into the interpreter... but it's progressing.

  8. TFW you optimize your compiler to the point where it realizes that your test case is a no-op.

    #Draupnir #Datalog

  9. 🚀 Breaking #news from the cutting-edge world of #database theory: some genius just discovered that "SQL" and "Datalog" are still things! 😲 Apparently, when you combine ancient #tech with buzzwords like "relational #algebra of the environment," you can create a mind-numbing blog post that rivals Ambien. 😴💤
    philipzucker.com/compose_datal #theory #SQL #Datalog #relational #HackerNews #ngated

  10. [New Blog Post] Compositional Datalog on SQL: Relational Algebra of the Environment #datalog #database #sql philipzucker.com/compose_datal