use of org.elasticsearch.search.suggest.completion.CompletionSuggestion in project elasticsearch by elastic.
the class SearchService method shortcutDocIdsToLoad.
/**
* Shortcut ids to load, we load only "from" and up to "size". The phase controller
* handles this as well since the result is always size * shards for Q_A_F
*/
private void shortcutDocIdsToLoad(SearchContext context) {
final int[] docIdsToLoad;
int docsOffset = 0;
final Suggest suggest = context.queryResult().suggest();
int numSuggestDocs = 0;
final List<CompletionSuggestion> completionSuggestions;
if (suggest != null && suggest.hasScoreDocs()) {
completionSuggestions = suggest.filter(CompletionSuggestion.class);
for (CompletionSuggestion completionSuggestion : completionSuggestions) {
numSuggestDocs += completionSuggestion.getOptions().size();
}
} else {
completionSuggestions = Collections.emptyList();
}
if (context.request().scroll() != null) {
TopDocs topDocs = context.queryResult().topDocs();
docIdsToLoad = new int[topDocs.scoreDocs.length + numSuggestDocs];
for (int i = 0; i < topDocs.scoreDocs.length; i++) {
docIdsToLoad[docsOffset++] = topDocs.scoreDocs[i].doc;
}
} else {
TopDocs topDocs = context.queryResult().topDocs();
if (topDocs.scoreDocs.length < context.from()) {
// no more docs...
docIdsToLoad = new int[numSuggestDocs];
} else {
int totalSize = context.from() + context.size();
docIdsToLoad = new int[Math.min(topDocs.scoreDocs.length - context.from(), context.size()) + numSuggestDocs];
for (int i = context.from(); i < Math.min(totalSize, topDocs.scoreDocs.length); i++) {
docIdsToLoad[docsOffset++] = topDocs.scoreDocs[i].doc;
}
}
}
for (CompletionSuggestion completionSuggestion : completionSuggestions) {
for (CompletionSuggestion.Entry.Option option : completionSuggestion.getOptions()) {
docIdsToLoad[docsOffset++] = option.getDoc().doc;
}
}
context.docIdsToLoad(docIdsToLoad, 0, docIdsToLoad.length);
}
use of org.elasticsearch.search.suggest.completion.CompletionSuggestion in project elasticsearch by elastic.
the class SearchPhaseController method merge.
/**
* Enriches search hits and completion suggestion hits from <code>sortedDocs</code> using <code>fetchResultsArr</code>,
* merges suggestions, aggregations and profile results
*
* Expects sortedDocs to have top search docs across all shards, optionally followed by top suggest docs for each named
* completion suggestion ordered by suggestion name
*/
public InternalSearchResponse merge(boolean ignoreFrom, ScoreDoc[] sortedDocs, ReducedQueryPhase reducedQueryPhase, AtomicArray<? extends QuerySearchResultProvider> fetchResultsArr) {
if (reducedQueryPhase.isEmpty()) {
return InternalSearchResponse.empty();
}
List<? extends AtomicArray.Entry<? extends QuerySearchResultProvider>> fetchResults = fetchResultsArr.asList();
SearchHits hits = getHits(reducedQueryPhase, ignoreFrom, sortedDocs, fetchResultsArr);
if (reducedQueryPhase.suggest != null) {
if (!fetchResults.isEmpty()) {
int currentOffset = hits.getHits().length;
for (CompletionSuggestion suggestion : reducedQueryPhase.suggest.filter(CompletionSuggestion.class)) {
final List<CompletionSuggestion.Entry.Option> suggestionOptions = suggestion.getOptions();
for (int scoreDocIndex = currentOffset; scoreDocIndex < currentOffset + suggestionOptions.size(); scoreDocIndex++) {
ScoreDoc shardDoc = sortedDocs[scoreDocIndex];
QuerySearchResultProvider searchResultProvider = fetchResultsArr.get(shardDoc.shardIndex);
if (searchResultProvider == null) {
continue;
}
FetchSearchResult fetchResult = searchResultProvider.fetchResult();
int fetchResultIndex = fetchResult.counterGetAndIncrement();
if (fetchResultIndex < fetchResult.hits().internalHits().length) {
SearchHit hit = fetchResult.hits().internalHits()[fetchResultIndex];
CompletionSuggestion.Entry.Option suggestOption = suggestionOptions.get(scoreDocIndex - currentOffset);
hit.score(shardDoc.score);
hit.shard(fetchResult.shardTarget());
suggestOption.setHit(hit);
}
}
currentOffset += suggestionOptions.size();
}
assert currentOffset == sortedDocs.length : "expected no more score doc slices";
}
}
return reducedQueryPhase.buildResponse(hits);
}
use of org.elasticsearch.search.suggest.completion.CompletionSuggestion in project elasticsearch by elastic.
the class SearchPhaseController method sortDocs.
/**
* Returns a score doc array of top N search docs across all shards, followed by top suggest docs for each
* named completion suggestion across all shards. If more than one named completion suggestion is specified in the
* request, the suggest docs for a named suggestion are ordered by the suggestion name.
*
* Note: The order of the sorted score docs depends on the shard index in the result array if the merge process needs to disambiguate
* the result. In oder to obtain stable results the shard index (index of the result in the result array) must be the same.
*
* @param ignoreFrom Whether to ignore the from and sort all hits in each shard result.
* Enabled only for scroll search, because that only retrieves hits of length 'size' in the query phase.
* @param resultsArr Shard result holder
*/
public ScoreDoc[] sortDocs(boolean ignoreFrom, AtomicArray<? extends QuerySearchResultProvider> resultsArr) throws IOException {
List<? extends AtomicArray.Entry<? extends QuerySearchResultProvider>> results = resultsArr.asList();
if (results.isEmpty()) {
return EMPTY_DOCS;
}
final QuerySearchResult result;
boolean canOptimize = false;
int shardIndex = -1;
if (results.size() == 1) {
canOptimize = true;
result = results.get(0).value.queryResult();
shardIndex = results.get(0).index;
} else {
boolean hasResult = false;
QuerySearchResult resultToOptimize = null;
// lets see if we only got hits from a single shard, if so, we can optimize...
for (AtomicArray.Entry<? extends QuerySearchResultProvider> entry : results) {
if (entry.value.queryResult().hasHits()) {
if (hasResult) {
// we already have one, can't really optimize
canOptimize = false;
break;
}
canOptimize = true;
hasResult = true;
resultToOptimize = entry.value.queryResult();
shardIndex = entry.index;
}
}
result = canOptimize ? resultToOptimize : results.get(0).value.queryResult();
assert result != null;
}
if (canOptimize) {
int offset = result.from();
if (ignoreFrom) {
offset = 0;
}
ScoreDoc[] scoreDocs = result.topDocs().scoreDocs;
ScoreDoc[] docs;
int numSuggestDocs = 0;
final Suggest suggest = result.queryResult().suggest();
final List<CompletionSuggestion> completionSuggestions;
if (suggest != null) {
completionSuggestions = suggest.filter(CompletionSuggestion.class);
for (CompletionSuggestion suggestion : completionSuggestions) {
numSuggestDocs += suggestion.getOptions().size();
}
} else {
completionSuggestions = Collections.emptyList();
}
int docsOffset = 0;
if (scoreDocs.length == 0 || scoreDocs.length < offset) {
docs = new ScoreDoc[numSuggestDocs];
} else {
int resultDocsSize = result.size();
if ((scoreDocs.length - offset) < resultDocsSize) {
resultDocsSize = scoreDocs.length - offset;
}
docs = new ScoreDoc[resultDocsSize + numSuggestDocs];
for (int i = 0; i < resultDocsSize; i++) {
ScoreDoc scoreDoc = scoreDocs[offset + i];
scoreDoc.shardIndex = shardIndex;
docs[i] = scoreDoc;
docsOffset++;
}
}
for (CompletionSuggestion suggestion : completionSuggestions) {
for (CompletionSuggestion.Entry.Option option : suggestion.getOptions()) {
ScoreDoc doc = option.getDoc();
doc.shardIndex = shardIndex;
docs[docsOffset++] = doc;
}
}
return docs;
}
final int topN = result.queryResult().size();
final int from = ignoreFrom ? 0 : result.queryResult().from();
final TopDocs mergedTopDocs;
final int numShards = resultsArr.length();
if (result.queryResult().topDocs() instanceof CollapseTopFieldDocs) {
CollapseTopFieldDocs firstTopDocs = (CollapseTopFieldDocs) result.queryResult().topDocs();
final Sort sort = new Sort(firstTopDocs.fields);
final CollapseTopFieldDocs[] shardTopDocs = new CollapseTopFieldDocs[numShards];
fillTopDocs(shardTopDocs, results, new CollapseTopFieldDocs(firstTopDocs.field, 0, new FieldDoc[0], sort.getSort(), new Object[0], Float.NaN));
mergedTopDocs = CollapseTopFieldDocs.merge(sort, from, topN, shardTopDocs);
} else if (result.queryResult().topDocs() instanceof TopFieldDocs) {
TopFieldDocs firstTopDocs = (TopFieldDocs) result.queryResult().topDocs();
final Sort sort = new Sort(firstTopDocs.fields);
final TopFieldDocs[] shardTopDocs = new TopFieldDocs[resultsArr.length()];
fillTopDocs(shardTopDocs, results, new TopFieldDocs(0, new FieldDoc[0], sort.getSort(), Float.NaN));
mergedTopDocs = TopDocs.merge(sort, from, topN, shardTopDocs, true);
} else {
final TopDocs[] shardTopDocs = new TopDocs[resultsArr.length()];
fillTopDocs(shardTopDocs, results, Lucene.EMPTY_TOP_DOCS);
mergedTopDocs = TopDocs.merge(from, topN, shardTopDocs, true);
}
ScoreDoc[] scoreDocs = mergedTopDocs.scoreDocs;
final Map<String, List<Suggestion<CompletionSuggestion.Entry>>> groupedCompletionSuggestions = new HashMap<>();
// group suggestions and assign shard index
for (AtomicArray.Entry<? extends QuerySearchResultProvider> sortedResult : results) {
Suggest shardSuggest = sortedResult.value.queryResult().suggest();
if (shardSuggest != null) {
for (CompletionSuggestion suggestion : shardSuggest.filter(CompletionSuggestion.class)) {
suggestion.setShardIndex(sortedResult.index);
List<Suggestion<CompletionSuggestion.Entry>> suggestions = groupedCompletionSuggestions.computeIfAbsent(suggestion.getName(), s -> new ArrayList<>());
suggestions.add(suggestion);
}
}
}
if (groupedCompletionSuggestions.isEmpty() == false) {
int numSuggestDocs = 0;
List<Suggestion<? extends Entry<? extends Entry.Option>>> completionSuggestions = new ArrayList<>(groupedCompletionSuggestions.size());
for (List<Suggestion<CompletionSuggestion.Entry>> groupedSuggestions : groupedCompletionSuggestions.values()) {
final CompletionSuggestion completionSuggestion = CompletionSuggestion.reduceTo(groupedSuggestions);
assert completionSuggestion != null;
numSuggestDocs += completionSuggestion.getOptions().size();
completionSuggestions.add(completionSuggestion);
}
scoreDocs = new ScoreDoc[mergedTopDocs.scoreDocs.length + numSuggestDocs];
System.arraycopy(mergedTopDocs.scoreDocs, 0, scoreDocs, 0, mergedTopDocs.scoreDocs.length);
int offset = mergedTopDocs.scoreDocs.length;
Suggest suggestions = new Suggest(completionSuggestions);
for (CompletionSuggestion completionSuggestion : suggestions.filter(CompletionSuggestion.class)) {
for (CompletionSuggestion.Entry.Option option : completionSuggestion.getOptions()) {
scoreDocs[offset++] = option.getDoc();
}
}
}
return scoreDocs;
}
use of org.elasticsearch.search.suggest.completion.CompletionSuggestion in project elasticsearch by elastic.
the class SearchPhaseControllerTests method generateQueryResults.
private AtomicArray<QuerySearchResultProvider> generateQueryResults(int nShards, List<CompletionSuggestion> suggestions, int searchHitsSize, boolean useConstantScore) {
AtomicArray<QuerySearchResultProvider> queryResults = new AtomicArray<>(nShards);
for (int shardIndex = 0; shardIndex < nShards; shardIndex++) {
QuerySearchResult querySearchResult = new QuerySearchResult(shardIndex, new SearchShardTarget("", new Index("", ""), shardIndex));
TopDocs topDocs = new TopDocs(0, new ScoreDoc[0], 0);
if (searchHitsSize > 0) {
int nDocs = randomIntBetween(0, searchHitsSize);
ScoreDoc[] scoreDocs = new ScoreDoc[nDocs];
float maxScore = 0F;
for (int i = 0; i < nDocs; i++) {
float score = useConstantScore ? 1.0F : Math.abs(randomFloat());
scoreDocs[i] = new ScoreDoc(i, score);
if (score > maxScore) {
maxScore = score;
}
}
topDocs = new TopDocs(scoreDocs.length, scoreDocs, maxScore);
}
List<CompletionSuggestion> shardSuggestion = new ArrayList<>();
for (CompletionSuggestion completionSuggestion : suggestions) {
CompletionSuggestion suggestion = new CompletionSuggestion(completionSuggestion.getName(), completionSuggestion.getSize());
final CompletionSuggestion.Entry completionEntry = new CompletionSuggestion.Entry(new Text(""), 0, 5);
suggestion.addTerm(completionEntry);
int optionSize = randomIntBetween(1, suggestion.getSize());
float maxScore = randomIntBetween(suggestion.getSize(), (int) Float.MAX_VALUE);
for (int i = 0; i < optionSize; i++) {
completionEntry.addOption(new CompletionSuggestion.Entry.Option(i, new Text(""), maxScore, Collections.emptyMap()));
float dec = randomIntBetween(0, optionSize);
if (dec <= maxScore) {
maxScore -= dec;
}
}
suggestion.setShardIndex(shardIndex);
shardSuggestion.add(suggestion);
}
querySearchResult.topDocs(topDocs, null);
querySearchResult.size(searchHitsSize);
querySearchResult.suggest(new Suggest(new ArrayList<>(shardSuggestion)));
queryResults.set(shardIndex, querySearchResult);
}
return queryResults;
}
use of org.elasticsearch.search.suggest.completion.CompletionSuggestion in project elasticsearch by elastic.
the class CompletionSuggestSearchIT method testSuggestDocument.
public void testSuggestDocument() throws Exception {
final CompletionMappingBuilder mapping = new CompletionMappingBuilder();
createIndexAndMapping(mapping);
int numDocs = randomIntBetween(10, 100);
List<IndexRequestBuilder> indexRequestBuilders = new ArrayList<>();
for (int i = 1; i <= numDocs; i++) {
indexRequestBuilders.add(client().prepareIndex(INDEX, TYPE, "" + i).setSource(jsonBuilder().startObject().startObject(FIELD).field("input", "suggestion" + i).field("weight", i).endObject().endObject()));
}
indexRandom(true, indexRequestBuilders);
CompletionSuggestionBuilder prefix = SuggestBuilders.completionSuggestion(FIELD).prefix("sugg").size(numDocs);
SearchResponse searchResponse = client().prepareSearch(INDEX).suggest(new SuggestBuilder().addSuggestion("foo", prefix)).get();
CompletionSuggestion completionSuggestion = searchResponse.getSuggest().getSuggestion("foo");
CompletionSuggestion.Entry options = completionSuggestion.getEntries().get(0);
assertThat(options.getOptions().size(), equalTo(numDocs));
int id = numDocs;
for (CompletionSuggestion.Entry.Option option : options) {
assertThat(option.getText().toString(), equalTo("suggestion" + id));
assertSearchHit(option.getHit(), hasId("" + id));
assertSearchHit(option.getHit(), hasScore((id)));
assertNotNull(option.getHit().getSourceAsMap());
id--;
}
}
Aggregations