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/*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.drill.exec.util;
import java.util.ArrayList;
import java.util.Collections;
import java.util.List;
public class ApproximateStringMatcher {
// From https://en.wikibooks.org/wiki/Algorithm_Implementation/Strings/Levenshtein_distance.
// This function is not performant and should only be used for small lists. It is useful to
// detect typos in queries entered by the user but not appropriate to do approximate string matching
// on large data sets
private static int LevenshteinDistance(final String s0, final String s1) {
final int len0 = s0.length() + 1;
final int len1 = s1.length() + 1;
// the array of distances
int[] cost = new int[len0];
int[] newcost = new int[len0];
// initial cost of skipping prefix in String s0
for (int i = 0; i < len0; i++) {
cost[i] = i;
}
// dynamically computing the array of distances
// transformation cost for each letter in s1
for (int j = 1; j < len1; j++) {
// initial cost of skipping prefix in String s1
newcost[0] = j;
// transformation cost for each letter in s0
for (int i = 1; i < len0; i++) {
// matching current letters in both strings
final int match = (s0.charAt(i - 1) == s1.charAt(j - 1)) ? 0 : 1;
// computing cost for each transformation
int cost_replace = cost[i - 1] + match;
int cost_insert = cost[i] + 1;
int cost_delete = newcost[i - 1] + 1;
// keep minimum cost
newcost[i] = Math.min(Math.min(cost_insert, cost_delete), cost_replace);
}
// swap cost/newcost arrays
final int[] swap = cost;
cost = newcost;
newcost = swap;
}
// the distance is the cost for transforming all letters in both strings
return cost[len0 - 1];
}
public static String getBestMatch(final List<String> namesToSearch, final String nameToMatch) {
final List<Integer> editDistances = new ArrayList<>();
for (final String name : namesToSearch) {
final int dist = ApproximateStringMatcher.LevenshteinDistance(nameToMatch, name);
editDistances.add(dist);
}
final int minIndex = editDistances.indexOf(Collections.min(editDistances));
final String bestMatch = namesToSearch.get(minIndex);
return bestMatch;
}
}