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// Copyright 2019 Oath Inc. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
package ai.vespa.rankingexpression.importer;
import com.yahoo.collections.ListMap;
import java.util.ArrayDeque;
import java.util.Deque;
import java.util.HashMap;
import java.util.Iterator;
import java.util.List;
import java.util.Map;
import java.util.Set;
/**
* Solves a dimension naming constraint problem.
*
* @author lesters
* @author bratseth
*/
class NamingConstraintSolver {
private final ListMap<String, Integer> possibleAssignments;
private final ListMap<DimensionRenamer.Arc, DimensionRenamer.Constraint> constraints;
private int iterations = 0;
private final int maxIterations;
private NamingConstraintSolver(Set<String> dimensions,
ListMap<DimensionRenamer.Arc, DimensionRenamer.Constraint> constraints,
int maxIterations) {
this.possibleAssignments = allPossibilities(dimensions);
this.constraints = constraints;
this.maxIterations = maxIterations;
}
/** Returns a list containing a list of all assignment possibilities for each of the given dimensions */
private static ListMap<String, Integer> allPossibilities(Set<String> dimensions) {
ListMap<String, Integer> all = new ListMap<>();
for (String dimension : dimensions) {
for (int i = 0; i < dimensions.size(); ++i)
all.put(dimension, i);
}
return all;
}
/**
* Try the solve the constraint problem given in the arguments, and put the result in renames.
*
* This is done by performing iterative arc consistency until we have found a solution.
* After an initial iteration, the dimensions will have multiple
* valid values. Find a single valid assignment by iteratively locking one
* dimension after another, and running the arc consistency algorithm
* multiple times.
*
* This requires having constraints that result in an absolute ordering:
* equal, lessThan and greaterThan do that, but not necessarily notEqual
* If that is needed, the algorithm needs to be adapted with a backtracking
* (tree) search
*
* @return the solution in the form of the renames to perform
*/
private Map<String, Integer> trySolve() {
// TODO: Evaluate possible improved efficiency by using a heuristic such as min-conflicts
Map<String, Integer> solution = new HashMap<>();
for (String dimension : possibleAssignments.keySet()) {
List<Integer> values = possibleAssignments.get(dimension);
if (values.size() > 1) {
if ( ! ac3()) return null;
values.sort(Integer::compare);
possibleAssignments.replace(dimension, values.get(0));
}
solution.put(dimension, possibleAssignments.get(dimension).get(0)); // Pick the first available solution
if (iterations > maxIterations) return null;
}
return solution;
}
private boolean ac3() {
Deque<DimensionRenamer.Arc> workList = new ArrayDeque<>(constraints.keySet());
while ( ! workList.isEmpty()) {
DimensionRenamer.Arc arc = workList.pop();
iterations++;
if (revise(arc)) {
if (possibleAssignments.get(arc.from).isEmpty()) return false;
for (DimensionRenamer.Arc constraint : constraints.keySet()) {
if (arc.from.equals(constraint.to) && !arc.to.equals(constraint.from))
workList.add(constraint);
}
}
}
return true;
}
private boolean revise(DimensionRenamer.Arc arc) {
boolean revised = false;
for (Iterator<Integer> fromIterator = possibleAssignments.get(arc.from).iterator(); fromIterator.hasNext(); ) {
Integer from = fromIterator.next();
boolean satisfied = false;
for (Iterator<Integer> toIterator = possibleAssignments.get(arc.to).iterator(); toIterator.hasNext(); ) {
Integer to = toIterator.next();
if (constraints.get(arc).stream().allMatch(constraint -> constraint.test(from, to)))
satisfied = true;
}
if ( ! satisfied) {
fromIterator.remove();
revised = true;
}
}
return revised;
}
/**
* Attempts to solve the given naming problem. The input maps are never modified.
*
* @return the solution as a map from existing names to name ids represented as integers, or NULL
* if no solution could be found
*/
public static Map<String, Integer> solve(Set<String> dimensions,
ListMap<DimensionRenamer.Arc, DimensionRenamer.Constraint> constraints,
int maxIterations) {
return new NamingConstraintSolver(dimensions, constraints, maxIterations).trySolve();
}
}
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