src.com.hp.hpl.jena.reasoner.rulesys.impl.oldCode.BasicBackwardRuleInfGraph Maven / Gradle / Ivy
Go to download
Show more of this group Show more artifacts with this name
Show all versions of jena Show documentation
Show all versions of jena Show documentation
Jena is a Java framework for building Semantic Web applications. It provides a programmatic environment for RDF, RDFS and OWL, SPARQL and includes a rule-based inference engine.
/******************************************************************
* File: BasicBackwardRuleInfGraph.java
* Created by: Dave Reynolds
* Created on: 03-May-2003
*
* (c) Copyright 2003, 2004, 2005, 2006, 2007, 2008 Hewlett-Packard Development Company, LP
* [See end of file]
* $Id: BasicBackwardRuleInfGraph.java,v 1.11 2008/01/02 12:09:44 andy_seaborne Exp $
*****************************************************************/
package com.hp.hpl.jena.reasoner.rulesys.impl.oldCode;
import com.hp.hpl.jena.reasoner.rulesys.*;
import com.hp.hpl.jena.reasoner.rulesys.impl.*;
import com.hp.hpl.jena.reasoner.*;
import com.hp.hpl.jena.graph.*;
import java.util.*;
import com.hp.hpl.jena.util.OneToManyMap;
import com.hp.hpl.jena.util.iterator.*;
import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
/**
* An inference graph that runs a set of rules using a tabled
* backward chaining interpreter.
*
* @author Dave Reynolds
* @version $Revision: 1.11 $ on $Date: 2008/01/02 12:09:44 $
*/
public class BasicBackwardRuleInfGraph extends BaseInfGraph implements BackwardRuleInfGraphI {
//=======================================================================
// variables
/** Set for rules being used */
protected List rules;
/** Table of derivation records, maps from triple to RuleDerivation */
protected OneToManyMap derivations;
/** An optional graph of separate schema assertions that should also be processed */
protected FGraph fschema;
/** Cache of deductions made from the rules */
protected FGraph fdeductions;
/** A finder that searches across the data, schema and axioms */
protected Finder dataFind;
/** The core rule engine which includes all the memoized results */
protected BRuleEngine engine;
/** Single context for the reasoner, used when passing information to builtins */
protected BBRuleContext context;
/** Cache of temporary property values inferred through getTemp calls */
protected TempNodeCache tempNodecache;
/** performance stats - number of rules passing initial trigger */
int nRulesTriggered = 0;
/** performance stats - number of rules fired */
long nRulesFired = 0;
/** threshold on the numbers of rule firings allowed in a single operation */
long nRulesThreshold = DEFAULT_RULES_THRESHOLD;
/** Flag which, if true, enables tracing of rule actions to logger.info */
boolean traceOn = false;
/** Default setting for rules threshold */
public static final long DEFAULT_RULES_THRESHOLD = 500000;
static Log logger = LogFactory.getLog(BasicBackwardRuleInfGraph.class);
//=======================================================================
// Core methods
/**
* Constructor. Create a new backward inference graph to process
* the given data. The parent reasoner supplies the ruleset and
* any additional schema graph.
*
* @param reasoner the parent reasoner
* @param ruleStore the indexed set of rules to use
* @param data the data graph to be processed
* @param schema optional precached schema (use null if not required)
*/
public BasicBackwardRuleInfGraph(Reasoner reasoner, RuleStore ruleStore, Graph data, Graph schema) {
super(data, reasoner);
if (schema != null) {
fschema = new FGraph(schema);
}
rules = ruleStore.getAllRules();
// Set up the backchaining engine
engine = new BRuleEngine(this, ruleStore);
tempNodecache = new TempNodeCache(this);
}
/**
* Return the schema graph, if any, bound into this inference graph.
*/
public Graph getSchemaGraph() {
return fschema.getGraph();
}
/**
* Perform any initial processing and caching. This call is optional. Most
* engines either have negligable set up work or will perform an implicit
* "prepare" if necessary. The call is provided for those occasions where
* substantial preparation work is possible (e.g. running a forward chaining
* rule system) and where an application might wish greater control over when
* this prepration is done.
*/
public void prepare() {
if (!isPrepared) {
fdeductions = new FGraph( Factory.createGraphMem() );
extractAxioms();
dataFind = fdata;
if (fdeductions != null) {
dataFind = FinderUtil.cascade(dataFind, fdeductions);
}
if (fschema != null) {
dataFind = FinderUtil.cascade(dataFind, fschema);
}
context = new BBRuleContext(this);
}
isPrepared = true;
}
/**
* Replace the underlying data graph for this inference graph and start any
* inferences over again. This is primarily using in setting up ontology imports
* processing to allow an imports multiunion graph to be inserted between the
* inference graph and the raw data, before processing.
* @param data the new raw data graph
*/
public void rebind(Graph data) {
fdata = new FGraph(data);
engine.reset();
isPrepared = false;
}
/**
* Cause the inference graph to reconsult the underlying graph to take
* into account changes. Normally changes are made through the InfGraph's add and
* remove calls are will be handled appropriately. However, in some cases changes
* are made "behind the InfGraph's back" and this forces a full reconsult of
* the changed data.
*/
public void rebind() {
engine.reset();
isPrepared = false;
}
/**
* Extended find interface used in situations where the implementator
* may or may not be able to answer the complete query. It will
* attempt to answer the pattern but if its answers are not known
* to be complete then it will also pass the request on to the nested
* Finder to append more results.
* @param pattern a TriplePattern to be matched against the data
* @param continuation either a Finder or a normal Graph which
* will be asked for additional match results if the implementor
* may not have completely satisfied the query.
*/
public ExtendedIterator findWithContinuation(TriplePattern pattern, Finder continuation) {
checkOpen();
if (!isPrepared) prepare();
ExtendedIterator result = null;
if (continuation == null) {
result = WrappedIterator.create( new TopGoalIterator(engine, pattern) );
} else {
result = WrappedIterator.create( new TopGoalIterator(engine, pattern) )
.andThen(continuation.find(pattern));
}
return result.filterDrop(Functor.acceptFilter);
}
/**
* Returns an iterator over Triples.
* This implementation assumes that the underlying findWithContinuation
* will have also consulted the raw data.
*/
public ExtendedIterator graphBaseFind(Node subject, Node property, Node object) {
return findWithContinuation(new TriplePattern(subject, property, object), null);
}
/**
* Basic pattern lookup interface.
* This implementation assumes that the underlying findWithContinuation
* will have also consulted the raw data.
* @param pattern a TriplePattern to be matched against the data
* @return a ExtendedIterator over all Triples in the data set
* that match the pattern
*/
public ExtendedIterator find(TriplePattern pattern) {
return findWithContinuation(pattern, null);
}
/**
* Flush out all cached results. Future queries have to start from scratch.
*/
public void reset() {
engine.reset();
isPrepared = false;
version++;
}
/**
* Add one triple to the data graph, run any rules triggered by
* the new data item, recursively adding any generated triples.
*/
public synchronized void performAdd(Triple t) {
fdata.getGraph().add(t);
reset();
}
/**
* Removes the triple t (if possible) from the set belonging to this graph.
*/
public void performDelete(Triple t) {
fdata.getGraph().delete(t);
reset();
}
//=======================================================================
// support for proof traces
/**
* Set to true to enable derivation caching
*/
public void setDerivationLogging(boolean recordDerivations) {
this.recordDerivations = recordDerivations;
if (recordDerivations) {
derivations = new OneToManyMap();
} else {
derivations = null;
}
}
/**
* Return the derivation of at triple.
* The derivation is a List of DerivationRecords
*/
public Iterator getDerivation(Triple t) {
if (derivations == null) {
return new NullIterator();
} else {
return derivations.getAll(t);
}
}
/**
* Change the threshold on the number of rule firings
* allowed during a single operation.
* @param threshold the new cutoff on the number rules firings per external op
*/
public void setRuleThreshold(long threshold) {
nRulesThreshold = threshold;
}
/**
* Set the state of the trace flag. If set to true then rule firings
* are logged out to the Log at "INFO" level.
*/
public void setTraceOn(boolean state) {
traceOn = state;
engine.setTraceOn(state);
}
/**
* Return true if tracing is switched on
*/
public boolean isTraceOn() {
return traceOn;
}
/**
* Dump an a summary of the goal table state to stdout.
* Just debugging, do not use for real.
*/
public void dump() {
engine.dump();
}
// =======================================================================
// Interface between infGraph and the goal processing machinery
/**
* Log a dervivation record against the given triple.
*/
public void logDerivation(Triple t, Object derivation) {
derivations.put(t, derivation);
}
/**
* Match a pattern just against the stored data (raw data, schema,
* axioms) but no derivation.
*/
public ExtendedIterator findDataMatches(TriplePattern pattern) {
return dataFind.find(pattern);
}
/**
* Process a call to a builtin predicate
* @param clause the Functor representing the call
* @param env the BindingEnvironment for this call
* @param rule the rule which is invoking this call
* @return true if the predicate succeeds
*/
public boolean processBuiltin(ClauseEntry clause, Rule rule, BindingEnvironment env) {
if (clause instanceof Functor) {
context.setEnv(env);
context.setRule(rule);
return((Functor)clause).evalAsBodyClause(context);
} else {
throw new ReasonerException("Illegal builtin predicate: " + clause + " in rule " + rule);
}
}
/**
* Assert a new triple in the deduction graph, bypassing any processing machinery.
*/
public void silentAdd(Triple t) {
fdeductions.getGraph().add(t);
}
/**
* Retrieve or create a bNode representing an inferred property value.
* @param instance the base instance node to which the property applies
* @param prop the property node whose value is being inferred
* @param pclass the (optional, can be null) class for the inferred value.
* @return the bNode representing the property value
*/
public Node getTemp(Node instance, Node prop, Node pclass) {
return tempNodecache.getTemp(instance, prop, pclass);
}
// =======================================================================
// Rule engine extras
/**
* Find any axioms (rules with no body) in the rule set and
* add those to the auxilliary graph to be included in searches.
*/
protected void extractAxioms() {
Graph axioms = fdeductions.getGraph();
for (Iterator i = rules.iterator(); i.hasNext(); ) {
Rule rule = (Rule)i.next();
if (rule.bodyLength() == 0) {
// An axiom
for (int j = 0; j < rule.headLength(); j++) {
Object axiom = rule.getHeadElement(j);
if (axiom instanceof TriplePattern) {
axioms.add(((TriplePattern)axiom).asTriple());
}
}
}
}
}
}
/*
(c) Copyright 2003, 2004, 2005, 2006, 2007, 2008 Hewlett-Packard Development Company, LP
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions
are met:
1. Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
3. The name of the author may not be used to endorse or promote products
derived from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR
IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT,
INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT
NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF
THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/