Module org.apache.jena.core
Package org.apache.jena.reasoner.rulesys.impl

Interface FRuleEngineI

All Known Implementing Classes:
FRuleEngine, RETEEngine
public interface FRuleEngineI
Rule engines implement the internals of forward rule inference graphs and the forward part of hybrid graphs. This interface abstracts the interface onto such engines to allow a graph to switch between direct and RETE style implementations.

  • Method Summary

    Modifier and Type
    Method
    Description
    void
    add(Triple t)
    Add one triple to the data graph, run any rules triggered by the new data item, recursively adding any generated triples.
    boolean
    delete(Triple t)
    Remove one triple to the data graph.
    void
    fastInit(Finder inserts)
    Process all available data.
    long
    getNRulesFired()
    Return the number of rules fired since this rule engine instance was created and initialized
    Object
    getRuleStore()
    Access the precomputed internal rule form.
    void
    init(boolean ignoreBrules, Finder inserts)
    Process all available data.
    void
    setDerivationLogging(boolean recordDerivations)
    Set to true to enable derivation caching
    void
    setRuleStore(Object ruleStore)
    Set the internal rule from a precomputed state.
    boolean
    shouldTrace()
    Return true if the internal engine state means that tracing is worthwhile.

  • Method Details

    • init

      void init(boolean ignoreBrules, Finder inserts)
      Process all available data. This should be called once a deductions graph has be prepared and loaded with any precomputed deductions. It will process the rule axioms and all relevant existing exiting data entries.
      Parameters:
      ignoreBrules - set to true if rules written in backward notation should be ignored
      inserts - the set of triples to be processed, normally this is the raw data graph but may include additional deductions made by preprocessing hooks

    • fastInit

      void fastInit(Finder inserts)
      Process all available data. This version expects that all the axioms have already be preprocessed and the rules have been compiled
      Parameters:
      inserts - the set of triples to be processed, normally this is the raw data graph but may include additional deductions made by preprocessing hooks

    • add

      void add(Triple t)
      Add one triple to the data graph, run any rules triggered by the new data item, recursively adding any generated triples.

    • delete

      boolean delete(Triple t)
      Remove one triple to the data graph.
      Returns:
      true if the effects could be correctly propagated or false if not (in which case the entire engine should be restarted).

    • getNRulesFired

      long getNRulesFired()
      Return the number of rules fired since this rule engine instance was created and initialized

    • shouldTrace

      boolean shouldTrace()
      Return true if the internal engine state means that tracing is worthwhile. It will return false during the axiom bootstrap phase.

    • setDerivationLogging

      void setDerivationLogging(boolean recordDerivations)
      Set to true to enable derivation caching

    • getRuleStore

      Object getRuleStore()
      Access the precomputed internal rule form. Used when precomputing the internal axiom closures.

    • setRuleStore

      void setRuleStore(Object ruleStore)
      Set the internal rule from a precomputed state.