private string[] QueryOverMultipleWords(SuggestionField field, List <string> words, SuggestionOptions options)
{
options.SortMode = SuggestionSortMode.None;
var result = new HashSet <string>();
var pageSize = options.PageSize;
foreach (var term in words)
{
if (pageSize <= 0)
{
break;
}
foreach (var suggestion in QueryOverSingleWord(field, term, options))
{
if (result.Add(suggestion) == false)
{
continue;
}
pageSize--;
if (pageSize <= 0)
{
break;
}
}
}
return(result.ToArray());
}
private string[] QueryOverSingleWord(SuggestionField field, string word, SuggestionOptions options)
{
// Perform devirtualization of the distance function when supported.
switch (options.Distance)
{
case StringDistanceTypes.JaroWinkler:
return(QueryOverSingleWord(field, word, options, new JaroWinklerDistance()));
case StringDistanceTypes.NGram:
return(QueryOverSingleWord(field, word, options, new NGramDistance()));
default:
return(QueryOverSingleWord(field, word, options, new LevenshteinDistance()));
}
}
public SuggestionResult Suggestions(IndexQueryServerSide query, SuggestionField field, JsonOperationContext documentsContext, CancellationToken token)
{
var options = field.GetOptions(documentsContext, query.QueryParameters) ?? new SuggestionOptions();
var terms = field.GetTerms(documentsContext, query.QueryParameters);
var result = new SuggestionResult
{
Name = field.Alias ?? field.Name
};
result.Suggestions.AddRange(terms.Count > 1
? QueryOverMultipleWords(field, terms, options)
: QueryOverSingleWord(field, terms[0], options));
return(result);
}
private string[] QueryOverSingleWord <TDistance>(SuggestionField suggestionField, string word, SuggestionOptions options, TDistance sd)
where TDistance : IStringDistance
{
var min = options.Accuracy ?? SuggestionOptions.DefaultAccuracy;
var field = suggestionField.Name;
var pageSize = options.PageSize;
var morePopular = options.SortMode == SuggestionSortMode.Popularity;
int lengthWord = word.Length;
var ir = _searcher.IndexReader;
int freq = (ir != null && field != null) ? ir.DocFreq(new Term(FWord, word), _state) : 0;
int goalFreq = (morePopular && ir != null && field != null) ? freq : 0;
// if the word exists in the real index and we don't care for word frequency, return the word itself
if (!morePopular && freq > 0)
{
return(new[] { word });
}
var query = new BooleanQuery();
var alreadySeen = new HashSet <string>();
int ng = GetMin(lengthWord);
int max = ng + 1;
var table = GramsTable;
for (; ng <= max; ng++)
{
string[] grams = FormGrams(word, ng);
if (grams.Length == 0)
{
continue; // hmm
}
if (BoostStart > 0)
{
// should we boost prefixes?
Add(query, table[ng].Start, grams[0], BoostStart); // matches start of word
}
if (BoostEnd > 0)
{
// should we boost suffixes
Add(query, table[ng].End, grams[grams.Length - 1], BoostEnd); // matches end of word
}
for (int i = 0; i < grams.Length; i++)
{
Add(query, table[ng].Gram, grams[i]);
}
}
int maxHits = 10 * pageSize;
// System.out.println("Q: " + query);
ScoreDoc[] hits = _searcher.Search(query, null, maxHits, _state).ScoreDocs;
// System.out.println("HITS: " + hits.length());
var queue = new SuggestWordQueue(pageSize);
// go thru more than 'maxr' matches in case the distance filter triggers
int stop = Math.Min(hits.Length, maxHits);
var suggestedWord = new SuggestWord();
for (int i = 0; i < stop; i++)
{
suggestedWord.Term = _searcher.Doc(hits[i].Doc, _state).Get(FWord, _state); // get orig word
// don't suggest a word for itself, that would be silly
if (suggestedWord.Term.Equals(word, StringComparison.OrdinalIgnoreCase))
{
continue;
}
// edit distance
suggestedWord.Score = sd.GetDistance(word, suggestedWord.Term);
if (suggestedWord.Score < min)
{
continue;
}
if (ir != null && field != null)
{
// use the user index
suggestedWord.Freq = _searcher.DocFreq(new Term(FWord, suggestedWord.Term), _state); // freq in the index
// don't suggest a word that is not present in the field
if ((morePopular && goalFreq > suggestedWord.Freq) || suggestedWord.Freq < 1)
{
continue;
}
}
if (alreadySeen.Add(suggestedWord.Term) == false) // we already seen this word, no point returning it twice
{
continue;
}
queue.InsertWithOverflow(suggestedWord);
if (queue.Size() == pageSize)
{
// if queue full, maintain the minScore score
min = queue.Top().Score;
}
suggestedWord = new SuggestWord();
}
int size = queue.Size();
if (size == 0)
{
return(EmptyArray);
}
// convert to array string
string[] list = new string[size];
for (int i = size - 1; i >= 0; i--)
{
list[i] = queue.Pop().Term;
}
return(list);
}