/**
* Sets boost of termClaimsDescriptionAbstractTitles. boost = weight = factor(tf*idf)
*
* @param vecsTerms
* @param currentField
* @param factor - adjustment factor ( ex. alpha or beta )
* @param decayFactor
* @return
* @throws java.io.IOException
*/
public Map<String, TermQuery> setBoost(
Map<TermFreqVector, String> vecsTerms, String currentField, float factor, float decayFactor)
throws IOException {
Map<String, TermQuery> terms = new HashMap<>();
// setBoost for each of the terms of each of the docs
int i = 0;
float norm = (float) 1 / vecsTerms.size();
// System.out.println("--------------------------");
for (Map.Entry<TermFreqVector, String> e : vecsTerms.entrySet()) {
// Increase decay
String field = e.getValue();
TermFreqVector docTerms = e.getKey();
float decay = decayFactor * i;
// Populate terms: with TermQuries and set boost
for (String termTxt : docTerms.getTerms()) {
// Create Term
Term term = new Term(currentField, termTxt);
// Calculate weight
float tf = docTerms.getFreq(termTxt);
// float idf = ir.docFreq(termTitle);
int docs;
float idf;
if (sourceField.equals(PatentQuery.all)) {
docs = ir.getDocCount(field);
idf = (float) Math.log10((double) docs / (ir.docFreq(new Term(field, termTxt)) + 1));
} else {
docs = ir.getDocCount(sourceField);
idf =
(float) Math.log10((double) docs / (ir.docFreq(new Term(sourceField, termTxt)) + 1));
}
float weight = tf * idf;
// System.out.println(term.text() + " -> tf= " + tf + " idf= " + idf + "
// tfidf= " + weight);
// Adjust weight by decay factor
weight = weight - (weight * decay);
// Create TermQuery and add it to the collection
TermQuery termQuery = new TermQuery(term);
// Calculate and set boost
float boost;
if (vecsTerms.size() == 1) {
boost = factor * tf;
} else {
boost = factor;
}
if (boost != 0) {
termQuery.setBoost(boost * norm);
if (terms.containsKey(termTxt)) {
TermQuery tq = terms.get(termTxt);
tq.setBoost(tq.getBoost() + termQuery.getBoost());
} else {
terms.put(termTxt, termQuery);
}
}
}
i++;
}
return terms;
}
/**
* Merges <code>termClaimsDescriptionAbstractTitleQueries</code> into a single query. In the
* future this method should probably be in <code>Query</code> class. This is akward way of doing
* it; but only merge queries method that is available is mergeBooleanQueries; so actually have to
* make a string termClaimsDescriptionAbstractTitle1^boost1,
* termClaimsDescriptionAbstractTitle2^boost and then parse it into a query
*
* @param termQueries - to merge
* @param maxTerms
* @return query created from termClaimsDescriptionAbstractTitleQueries including boost parameters
* @throws org.apache.lucene.queryparser.classic.ParseException
*/
public Query mergeQueries(List<TermQuery> termQueries, int maxTerms) throws ParseException {
BooleanQuery query = new BooleanQuery();
// Select only the maxTerms number of terms
int termCount = Math.min(termQueries.size(), maxTerms);
for (int i = 0; i < termCount; i++) {
TermQuery termQuery = termQueries.get(i);
query.add(termQuery, BooleanClause.Occur.SHOULD);
}
return query;
}
private void readIndexInputFullyWithRandomSeeks(IndexInput indexInput) throws IOException {
BytesRef ref = new BytesRef(scaledRandomIntBetween(1, 1024));
long pos = 0;
while (pos < indexInput.length()) {
assertEquals(pos, indexInput.getFilePointer());
int op = random().nextInt(5);
if (op == 0) {
int shift = 100 - randomIntBetween(0, 200);
pos = Math.min(indexInput.length() - 1, Math.max(0, pos + shift));
indexInput.seek(pos);
} else if (op == 1) {
indexInput.readByte();
pos++;
} else {
int min = (int) Math.min(indexInput.length() - pos, ref.bytes.length);
indexInput.readBytes(ref.bytes, ref.offset, min);
pos += min;
}
}
}
/**
* Adjust termClaimsDescriptionAbstractTitle features of the docs with alpha * query; and beta;
* and assign weights/boost to termClaimsDescriptionAbstractTitles (tf*idf).
*
* @param query
* @param currentField
* @param alpha
* @param beta - factor of the equation
* @param gamma
* @param decay
* @param maxExpandedQueryTerms - maximum number of termClaimsDescriptionAbstractTitles in
* expanded query
* @return expandedQuery with boost factors adjusted using Rocchio's algorithm
* @throws IOException
* @throws ParseException
*/
public Query adjust(
Query query,
String currentField,
float alpha,
float beta,
float gamma,
float decay,
int maxExpandedQueryTerms)
throws IOException, ParseException {
Query expandedQuery;
// setBoost of docs terms
Map<String, TermQuery> relevantDocsTerms =
setBoost(docsTermVectorReldocs, currentField, beta, decay);
Map<String, TermQuery> irrrelevantDocsTerms =
setBoost(docsTermVectorIrreldocs, currentField, gamma, decay);
// Map<String, TermQuery> relevantDocsTerms = new HashMap<>();
// Map<String, TermQuery> irrrelevantDocsTerms = new HashMap<>();
// setBoost of query terms
// Get queryTerms from the query
// combine weights according to expansion formula
List<TermQuery> expandedQueryTerms =
combine(new HashMap<String, TermQuery>(), relevantDocsTerms, irrrelevantDocsTerms);
// Sort by boost=weight
Comparator comparator = new QueryBoostComparator();
Collections.sort(expandedQueryTerms, comparator);
relevantDocsTerms.clear();
int termCount = Math.min(expandedQueryTerms.size(), maxExpandedQueryTerms);
for (int i = 0; i < termCount; i++) {
TermQuery tq = expandedQueryTerms.get(i);
relevantDocsTerms.put(tq.getTerm().text(), tq);
System.out.print(tq.getTerm().text() + ", ");
}
TermFreqVector queryTermsVector = new TermFreqVector(query);
Map<String, TermQuery> queryTerms;
queryTerms = setBoost(queryTermsVector, currentField, alpha);
// List<TermQuery> queryTermsList=new ArrayList(queryTerms.values());
// Collections.sort(queryTermsList, comparator);
// queryTerms.clear();
// for(TermQuery tq:queryTermsList){
// queryTerms.put(tq.getTerm().text(), tq);
// }
expandedQueryTerms = combine(queryTerms, relevantDocsTerms, new HashMap<String, TermQuery>());
Collections.sort(expandedQueryTerms, comparator);
// Create Expanded Query
expandedQuery = mergeQueries(expandedQueryTerms, Integer.MAX_VALUE);
return expandedQuery;
}
/**
* Create a PriorityQueue from a word->tf map.
*
* @param words a map of words keyed on the word(String) with Int objects as the values.
* @param fieldNames an array of field names to override defaults.
*/
private PriorityQueue<ScoreTerm> createQueue(Map<String, Int> words, String... fieldNames)
throws IOException {
// have collected all words in doc and their freqs
int numDocs = ir.numDocs();
final int limit = Math.min(maxQueryTerms, words.size());
FreqQ queue = new FreqQ(limit); // will order words by score
for (String word : words.keySet()) { // for every word
int tf = words.get(word).x; // term freq in the source doc
if (minTermFreq > 0 && tf < minTermFreq) {
continue; // filter out words that don't occur enough times in the source
}
// go through all the fields and find the largest document frequency
String topField = fieldNames[0];
int docFreq = 0;
for (String fieldName : fieldNames) {
int freq = ir.docFreq(new Term(fieldName, word));
topField = (freq > docFreq) ? fieldName : topField;
docFreq = (freq > docFreq) ? freq : docFreq;
}
if (minDocFreq > 0 && docFreq < minDocFreq) {
continue; // filter out words that don't occur in enough docs
}
if (docFreq > maxDocFreq) {
continue; // filter out words that occur in too many docs
}
if (docFreq == 0) {
continue; // index update problem?
}
float idf = similarity.idf(docFreq, numDocs);
float score = tf * idf;
if (queue.size() < limit) {
// there is still space in the queue
queue.add(new ScoreTerm(word, topField, score, idf, docFreq, tf));
} else {
ScoreTerm term = queue.top();
if (term.score < score) { // update the smallest in the queue in place and update the queue.
term.update(word, topField, score, idf, docFreq, tf);
queue.updateTop();
}
}
}
return queue;
}
private void corruptFile(Directory dir, String fileIn, String fileOut) throws IOException {
IndexInput input = dir.openInput(fileIn, IOContext.READONCE);
IndexOutput output = dir.createOutput(fileOut, IOContext.DEFAULT);
long len = input.length();
byte[] b = new byte[1024];
long broken = randomInt((int) len);
long pos = 0;
while (pos < len) {
int min = (int) Math.min(input.length() - pos, b.length);
input.readBytes(b, 0, min);
if (broken >= pos && broken < pos + min) {
// Flip one byte
int flipPos = (int) (broken - pos);
b[flipPos] = (byte) (b[flipPos] ^ 42);
}
output.writeBytes(b, min);
pos += min;
}
IOUtils.close(input, output);
}
@Test
public void testVerifyingIndexOutput() throws IOException {
Directory dir = newDirectory();
IndexOutput output = dir.createOutput("foo.bar", IOContext.DEFAULT);
int iters = scaledRandomIntBetween(10, 100);
for (int i = 0; i < iters; i++) {
BytesRef bytesRef = new BytesRef(TestUtil.randomRealisticUnicodeString(random(), 10, 1024));
output.writeBytes(bytesRef.bytes, bytesRef.offset, bytesRef.length);
}
CodecUtil.writeFooter(output);
output.close();
IndexInput indexInput = dir.openInput("foo.bar", IOContext.DEFAULT);
String checksum = Store.digestToString(CodecUtil.retrieveChecksum(indexInput));
indexInput.seek(0);
BytesRef ref = new BytesRef(scaledRandomIntBetween(1, 1024));
long length = indexInput.length();
IndexOutput verifyingOutput =
new Store.LuceneVerifyingIndexOutput(
new StoreFileMetaData("foo1.bar", length, checksum),
dir.createOutput("foo1.bar", IOContext.DEFAULT));
while (length > 0) {
if (random().nextInt(10) == 0) {
verifyingOutput.writeByte(indexInput.readByte());
length--;
} else {
int min = (int) Math.min(length, ref.bytes.length);
indexInput.readBytes(ref.bytes, ref.offset, min);
verifyingOutput.writeBytes(ref.bytes, ref.offset, min);
length -= min;
}
}
Store.verify(verifyingOutput);
verifyingOutput.writeByte((byte) 0x0);
try {
Store.verify(verifyingOutput);
fail("should be a corrupted index");
} catch (CorruptIndexException | IndexFormatTooOldException | IndexFormatTooNewException ex) {
// ok
}
IOUtils.close(indexInput, verifyingOutput, dir);
}
@Test
public void testRandom() throws Exception {
Directory directory = newDirectory();
final Random r = random();
final IndexWriterConfig iwc =
LuceneTestCase.newIndexWriterConfig(r, new MockAnalyzer(r))
.setMaxBufferedDocs(IndexWriterConfig.DISABLE_AUTO_FLUSH)
.setRAMBufferSizeMB(
scaledRandomIntBetween(16, 64)); // we might index a lot - don't go crazy here
RandomIndexWriter indexWriter = new RandomIndexWriter(r, directory, iwc);
int numUniqueChildValues = scaledRandomIntBetween(100, 2000);
String[] childValues = new String[numUniqueChildValues];
for (int i = 0; i < numUniqueChildValues; i++) {
childValues[i] = Integer.toString(i);
}
IntOpenHashSet filteredOrDeletedDocs = new IntOpenHashSet();
int childDocId = 0;
int numParentDocs = scaledRandomIntBetween(1, numUniqueChildValues);
ObjectObjectOpenHashMap<String, NavigableMap<String, FloatArrayList>> childValueToParentIds =
new ObjectObjectOpenHashMap<>();
for (int parentDocId = 0; parentDocId < numParentDocs; parentDocId++) {
boolean markParentAsDeleted = rarely();
boolean filterMe = rarely();
String parent = Integer.toString(parentDocId);
Document document = new Document();
document.add(
new StringField(UidFieldMapper.NAME, Uid.createUid("parent", parent), Field.Store.YES));
document.add(new StringField(TypeFieldMapper.NAME, "parent", Field.Store.NO));
if (markParentAsDeleted) {
filteredOrDeletedDocs.add(parentDocId);
document.add(new StringField("delete", "me", Field.Store.NO));
}
if (filterMe) {
filteredOrDeletedDocs.add(parentDocId);
document.add(new StringField("filter", "me", Field.Store.NO));
}
indexWriter.addDocument(document);
int numChildDocs = scaledRandomIntBetween(0, 100);
for (int i = 0; i < numChildDocs; i++) {
boolean markChildAsDeleted = rarely();
String childValue = childValues[random().nextInt(childValues.length)];
document = new Document();
document.add(
new StringField(
UidFieldMapper.NAME,
Uid.createUid("child", Integer.toString(childDocId++)),
Field.Store.NO));
document.add(new StringField(TypeFieldMapper.NAME, "child", Field.Store.NO));
document.add(
new StringField(
ParentFieldMapper.NAME, Uid.createUid("parent", parent), Field.Store.NO));
document.add(new StringField("field1", childValue, Field.Store.NO));
if (markChildAsDeleted) {
document.add(new StringField("delete", "me", Field.Store.NO));
}
indexWriter.addDocument(document);
if (!markChildAsDeleted) {
NavigableMap<String, FloatArrayList> parentIdToChildScores;
if (childValueToParentIds.containsKey(childValue)) {
parentIdToChildScores = childValueToParentIds.lget();
} else {
childValueToParentIds.put(childValue, parentIdToChildScores = new TreeMap<>());
}
if (!markParentAsDeleted && !filterMe) {
FloatArrayList childScores = parentIdToChildScores.get(parent);
if (childScores == null) {
parentIdToChildScores.put(parent, childScores = new FloatArrayList());
}
childScores.add(1f);
}
}
}
}
// Delete docs that are marked to be deleted.
indexWriter.deleteDocuments(new Term("delete", "me"));
indexWriter.commit();
IndexReader indexReader = DirectoryReader.open(directory);
IndexSearcher searcher = new IndexSearcher(indexReader);
Engine.Searcher engineSearcher =
new Engine.Searcher(ChildrenQueryTests.class.getSimpleName(), searcher);
((TestSearchContext) SearchContext.current())
.setSearcher(new ContextIndexSearcher(SearchContext.current(), engineSearcher));
int max = numUniqueChildValues / 4;
for (int i = 0; i < max; i++) {
// Simulate a parent update
if (random().nextBoolean()) {
final int numberOfUpdatableParents = numParentDocs - filteredOrDeletedDocs.size();
int numberOfUpdates =
RandomInts.randomIntBetween(
random(), 0, Math.min(numberOfUpdatableParents, TEST_NIGHTLY ? 25 : 5));
for (int j = 0; j < numberOfUpdates; j++) {
int parentId;
do {
parentId = random().nextInt(numParentDocs);
} while (filteredOrDeletedDocs.contains(parentId));
String parentUid = Uid.createUid("parent", Integer.toString(parentId));
indexWriter.deleteDocuments(new Term(UidFieldMapper.NAME, parentUid));
Document document = new Document();
document.add(new StringField(UidFieldMapper.NAME, parentUid, Field.Store.YES));
document.add(new StringField(TypeFieldMapper.NAME, "parent", Field.Store.NO));
indexWriter.addDocument(document);
}
indexReader.close();
indexReader = DirectoryReader.open(indexWriter.w, true);
searcher = new IndexSearcher(indexReader);
engineSearcher =
new Engine.Searcher(ChildrenConstantScoreQueryTests.class.getSimpleName(), searcher);
((TestSearchContext) SearchContext.current())
.setSearcher(new ContextIndexSearcher(SearchContext.current(), engineSearcher));
}
String childValue = childValues[random().nextInt(numUniqueChildValues)];
int shortCircuitParentDocSet = random().nextInt(numParentDocs);
ScoreType scoreType = ScoreType.values()[random().nextInt(ScoreType.values().length)];
// leave min/max set to 0 half the time
int minChildren = random().nextInt(2) * scaledRandomIntBetween(0, 110);
int maxChildren = random().nextInt(2) * scaledRandomIntBetween(minChildren, 110);
QueryBuilder queryBuilder =
hasChildQuery("child", constantScoreQuery(termQuery("field1", childValue)))
.scoreType(scoreType.name().toLowerCase(Locale.ENGLISH))
.minChildren(minChildren)
.maxChildren(maxChildren)
.setShortCircuitCutoff(shortCircuitParentDocSet);
// Using a FQ, will invoke / test the Scorer#advance(..) and also let the Weight#scorer not
// get live docs as acceptedDocs
queryBuilder = filteredQuery(queryBuilder, notFilter(termFilter("filter", "me")));
Query query = parseQuery(queryBuilder);
BitSetCollector collector = new BitSetCollector(indexReader.maxDoc());
int numHits = 1 + random().nextInt(25);
TopScoreDocCollector actualTopDocsCollector = TopScoreDocCollector.create(numHits);
searcher.search(query, MultiCollector.wrap(collector, actualTopDocsCollector));
FixedBitSet actualResult = collector.getResult();
FixedBitSet expectedResult = new FixedBitSet(indexReader.maxDoc());
TopScoreDocCollector expectedTopDocsCollector = TopScoreDocCollector.create(numHits);
if (childValueToParentIds.containsKey(childValue)) {
LeafReader slowLeafReader = SlowCompositeReaderWrapper.wrap(indexReader);
final FloatArrayList[] scores = new FloatArrayList[slowLeafReader.maxDoc()];
Terms terms = slowLeafReader.terms(UidFieldMapper.NAME);
if (terms != null) {
NavigableMap<String, FloatArrayList> parentIdToChildScores = childValueToParentIds.lget();
TermsEnum termsEnum = terms.iterator(null);
DocsEnum docsEnum = null;
for (Map.Entry<String, FloatArrayList> entry : parentIdToChildScores.entrySet()) {
int count = entry.getValue().elementsCount;
if (count >= minChildren && (maxChildren == 0 || count <= maxChildren)) {
TermsEnum.SeekStatus seekStatus =
termsEnum.seekCeil(Uid.createUidAsBytes("parent", entry.getKey()));
if (seekStatus == TermsEnum.SeekStatus.FOUND) {
docsEnum =
termsEnum.docs(slowLeafReader.getLiveDocs(), docsEnum, DocsEnum.FLAG_NONE);
expectedResult.set(docsEnum.nextDoc());
scores[docsEnum.docID()] = new FloatArrayList(entry.getValue());
} else if (seekStatus == TermsEnum.SeekStatus.END) {
break;
}
}
}
}
MockScorer mockScorer = new MockScorer(scoreType);
final LeafCollector leafCollector =
expectedTopDocsCollector.getLeafCollector(slowLeafReader.getContext());
leafCollector.setScorer(mockScorer);
for (int doc = expectedResult.nextSetBit(0);
doc < slowLeafReader.maxDoc();
doc =
doc + 1 >= expectedResult.length()
? DocIdSetIterator.NO_MORE_DOCS
: expectedResult.nextSetBit(doc + 1)) {
mockScorer.scores = scores[doc];
leafCollector.collect(doc);
}
}
assertBitSet(actualResult, expectedResult, searcher);
assertTopDocs(actualTopDocsCollector.topDocs(), expectedTopDocsCollector.topDocs());
}
indexWriter.close();
indexReader.close();
directory.close();
}
public int compare(ScoreDoc o1, ScoreDoc o2) {
return (int) Math.signum(o2.score - o1.score);
}
/**
* Creates a set of reference objects and stores it in a new index (name "<indexPath>-ro"). Then
* creates ordered lists of reference object positions for each data item in the index with given
* feature. Finally a new index (name "<indexPath>-ms") is created where all the original
* documents as well as the new data are stored.
*
* @param indexPath the path to the original index
* @throws IOException
*/
public void createIndex(String indexPath) throws IOException {
IndexReader reader = DirectoryReader.open(FSDirectory.open(new File(indexPath)));
int numDocs = reader.numDocs();
if (numDocs < numReferenceObjects) {
throw new UnsupportedOperationException("Too few documents in index.");
}
// progress report
progress.setNumDocsAll(numDocs);
progress.setCurrentState(State.RoSelection);
boolean hasDeletions = reader.hasDeletions();
// init reference objects:
IndexWriter iw = LuceneUtils.createIndexWriter(indexPath + "-ro", true);
HashSet<Integer> referenceObjsIds = new HashSet<Integer>(numReferenceObjects);
double numDocsDouble = (double) numDocs;
while (referenceObjsIds.size() < numReferenceObjects) {
referenceObjsIds.add((int) (numDocsDouble * Math.random()));
}
int count = 0;
if (hasDeletions) {
System.err.println(
"WARNING: There are deleted docs in your index. You should "
+ "optimize your index before using this method.");
}
// progress report
progress.setCurrentState(State.RoIndexing);
// find them in the index and put them into a separate index:
for (int i : referenceObjsIds) {
count++;
Document document = reader.document(i);
document.add(new Field("ro-id", count + "", StringField.TYPE_STORED));
iw.addDocument(document);
}
iw.commit();
iw.close();
// progress report
progress.setCurrentState(State.Indexing);
// now find the reference objects for each entry ;)
IndexReader readerRo = DirectoryReader.open(FSDirectory.open(new File(indexPath + "-ro")));
ImageSearcher searcher =
new GenericImageSearcher(numReferenceObjectsUsed, featureClass, featureFieldName);
Map<String, Analyzer> analyzerPerField = new HashMap<String, Analyzer>();
analyzerPerField.put("ro-order", new WhitespaceAnalyzer(LuceneUtils.LUCENE_VERSION));
PerFieldAnalyzerWrapper aWrapper =
new PerFieldAnalyzerWrapper(
new SimpleAnalyzer(LuceneUtils.LUCENE_VERSION), analyzerPerField);
iw =
new IndexWriter(
FSDirectory.open(new File(indexPath)),
new IndexWriterConfig(LuceneUtils.LUCENE_VERSION, aWrapper)
.setOpenMode(IndexWriterConfig.OpenMode.CREATE));
StringBuilder sb = new StringBuilder(256);
// Needed for check whether the document is deleted.
Bits liveDocs = MultiFields.getLiveDocs(reader);
for (int i = 0; i < numDocs; i++) {
if (reader.hasDeletions() && !liveDocs.get(i)) continue; // if it is deleted, just ignore it.
Document document = reader.document(i);
ImageSearchHits hits = searcher.search(document, readerRo);
sb.delete(0, sb.length());
for (int j = 0; j < numReferenceObjectsUsed; j++) {
sb.append(hits.doc(j).getValues("ro-id")[0]);
sb.append(' ');
}
// System.out.println(sb.toString());
document.add(new TextField("ro-order", sb.toString(), Field.Store.YES));
iw.updateDocument(
new Term(
DocumentBuilder.FIELD_NAME_IDENTIFIER,
document.getValues(DocumentBuilder.FIELD_NAME_IDENTIFIER)[0]),
document);
// progress report
progress.setNumDocsProcessed(progress.getNumDocsProcessed() + 1);
}
iw.commit();
iw.close();
// progress report
progress.setCurrentState(State.Idle);
}
/** @return number of bytes per term, based on the NumericValue.requiredBits() */
@Override
public long bytesPerValue(BytesRef term) {
// Estimate about about 0.8 (8 / 10) compression ratio for
// numbers, but at least 4 bytes
return Math.max(type.requiredBits() / 10, 4);
}
protected CommonSettings.MemoryStorageFormat chooseStorageFormat(
LeafReader reader,
PackedLongValues values,
Ordinals build,
RandomAccessOrds ordinals,
long minValue,
long maxValue,
float acceptableOverheadRatio,
int pageSize) {
CommonSettings.MemoryStorageFormat format;
// estimate memory usage for a single packed array
long packedDelta = maxValue - minValue + 1; // allow for a missing value
// valuesDelta can be negative if the difference between max and min values overflows the
// positive side of longs.
int bitsRequired = packedDelta < 0 ? 64 : PackedInts.bitsRequired(packedDelta);
PackedInts.FormatAndBits formatAndBits =
PackedInts.fastestFormatAndBits(reader.maxDoc(), bitsRequired, acceptableOverheadRatio);
final long singleValuesSize =
formatAndBits.format.longCount(
PackedInts.VERSION_CURRENT, reader.maxDoc(), formatAndBits.bitsPerValue)
* 8L;
// ordinal memory usage
final long ordinalsSize = build.ramBytesUsed() + values.ramBytesUsed();
// estimate the memory signature of paged packing
long pagedSingleValuesSize =
(reader.maxDoc() / pageSize + 1) * RamUsageEstimator.NUM_BYTES_OBJECT_REF; // array of pages
int pageIndex = 0;
long pageMinOrdinal = Long.MAX_VALUE;
long pageMaxOrdinal = Long.MIN_VALUE;
for (int i = 1; i < reader.maxDoc(); ++i, pageIndex = (pageIndex + 1) % pageSize) {
ordinals.setDocument(i);
if (ordinals.cardinality() > 0) {
long ordinal = ordinals.ordAt(0);
pageMaxOrdinal = Math.max(ordinal, pageMaxOrdinal);
pageMinOrdinal = Math.min(ordinal, pageMinOrdinal);
}
if (pageIndex == pageSize - 1) {
// end of page, we now know enough to estimate memory usage
pagedSingleValuesSize +=
getPageMemoryUsage(
values, acceptableOverheadRatio, pageSize, pageMinOrdinal, pageMaxOrdinal);
pageMinOrdinal = Long.MAX_VALUE;
pageMaxOrdinal = Long.MIN_VALUE;
}
}
if (pageIndex > 0) {
// last page estimation
pageIndex++;
pagedSingleValuesSize +=
getPageMemoryUsage(
values, acceptableOverheadRatio, pageSize, pageMinOrdinal, pageMaxOrdinal);
}
if (ordinalsSize < singleValuesSize) {
if (ordinalsSize < pagedSingleValuesSize) {
format = CommonSettings.MemoryStorageFormat.ORDINALS;
} else {
format = CommonSettings.MemoryStorageFormat.PAGED;
}
} else {
if (pagedSingleValuesSize < singleValuesSize) {
format = CommonSettings.MemoryStorageFormat.PAGED;
} else {
format = CommonSettings.MemoryStorageFormat.PACKED;
}
}
return format;
}
