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com.browseengine.bobo.facets.impl.CompactMultiValueFacetHandler Maven / Gradle / Ivy
Bobo is a Faceted Search implementation written purely in Java, an extension of Apache Lucene
package com.browseengine.bobo.facets.impl;
import it.unimi.dsi.fastutil.floats.FloatArrayList;
import it.unimi.dsi.fastutil.floats.FloatList;
import it.unimi.dsi.fastutil.ints.IntArrayList;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;
import java.util.Map;
import java.util.Properties;
import org.apache.lucene.index.AtomicReader;
import org.apache.lucene.index.DocsEnum;
import org.apache.lucene.index.Term;
import org.apache.lucene.index.Terms;
import org.apache.lucene.index.TermsEnum;
import org.apache.lucene.search.Explanation;
import org.apache.lucene.search.ScoreDoc;
import org.apache.lucene.util.BytesRef;
import com.browseengine.bobo.api.BoboSegmentReader;
import com.browseengine.bobo.api.BrowseFacet;
import com.browseengine.bobo.api.BrowseSelection;
import com.browseengine.bobo.api.FacetIterator;
import com.browseengine.bobo.api.FacetSpec;
import com.browseengine.bobo.facets.FacetCountCollector;
import com.browseengine.bobo.facets.FacetCountCollectorSource;
import com.browseengine.bobo.facets.FacetHandler;
import com.browseengine.bobo.facets.data.FacetDataCache;
import com.browseengine.bobo.facets.data.TermListFactory;
import com.browseengine.bobo.facets.data.TermStringList;
import com.browseengine.bobo.facets.data.TermValueList;
import com.browseengine.bobo.facets.filter.CompactMultiValueFacetFilter;
import com.browseengine.bobo.facets.filter.EmptyFilter;
import com.browseengine.bobo.facets.filter.RandomAccessAndFilter;
import com.browseengine.bobo.facets.filter.RandomAccessFilter;
import com.browseengine.bobo.facets.filter.RandomAccessNotFilter;
import com.browseengine.bobo.query.scoring.BoboDocScorer;
import com.browseengine.bobo.query.scoring.FacetScoreable;
import com.browseengine.bobo.query.scoring.FacetTermScoringFunctionFactory;
import com.browseengine.bobo.sort.DocComparator;
import com.browseengine.bobo.sort.DocComparatorSource;
import com.browseengine.bobo.util.BigIntArray;
import com.browseengine.bobo.util.BigSegmentedArray;
import com.browseengine.bobo.util.StringArrayComparator;
public class CompactMultiValueFacetHandler extends FacetHandler> implements
FacetScoreable {
private static final int MAX_VAL_COUNT = 32;
private final TermListFactory _termListFactory;
private final String _indexFieldName;
public CompactMultiValueFacetHandler(String name, String indexFieldName,
TermListFactory termListFactory) {
super(name);
_indexFieldName = indexFieldName;
_termListFactory = termListFactory;
}
public CompactMultiValueFacetHandler(String name, TermListFactory termListFactory) {
this(name, name, termListFactory);
}
public CompactMultiValueFacetHandler(String name, String indexFieldName) {
this(name, indexFieldName, null);
}
public CompactMultiValueFacetHandler(String name) {
this(name, name, null);
}
@Override
public DocComparatorSource getDocComparatorSource() {
return new CompactMultiFacetDocComparatorSource(this);
}
@Override
public RandomAccessFilter buildRandomAccessFilter(String value, Properties prop)
throws IOException {
return new CompactMultiValueFacetFilter(this, value);
}
@Override
public RandomAccessFilter buildRandomAccessAndFilter(String[] vals, Properties prop)
throws IOException {
ArrayList filterList = new ArrayList(vals.length);
for (String val : vals) {
RandomAccessFilter f = buildRandomAccessFilter(val, prop);
if (f != null) {
filterList.add(f);
} else {
return EmptyFilter.getInstance();
}
}
if (filterList.size() == 1) return filterList.get(0);
return new RandomAccessAndFilter(filterList);
}
@Override
public RandomAccessFilter buildRandomAccessOrFilter(String[] vals, Properties prop, boolean isNot)
throws IOException {
RandomAccessFilter filter = null;
if (vals.length > 0) {
filter = new CompactMultiValueFacetFilter(this, vals);
} else {
filter = EmptyFilter.getInstance();
}
if (isNot) {
filter = new RandomAccessNotFilter(filter);
}
return filter;
}
private static int countBits(int val) {
int c = 0;
for (c = 0; val > 0; c++) {
val &= val - 1;
}
return c;
}
@Override
public int getNumItems(BoboSegmentReader reader, int id) {
FacetDataCache dataCache = getFacetData(reader);
if (dataCache == null) return 0;
int encoded = dataCache.orderArray.get(id);
return countBits(encoded);
}
@Override
public String[] getFieldValues(BoboSegmentReader reader, int id) {
FacetDataCache dataCache = getFacetData(reader);
if (dataCache == null) return new String[0];
int encoded = dataCache.orderArray.get(id);
if (encoded == 0) {
return new String[] { "" };
} else {
int count = 1;
ArrayList valList = new ArrayList(MAX_VAL_COUNT);
while (encoded != 0) {
if ((encoded & 0x00000001) != 0x0) {
valList.add(dataCache.valArray.get(count));
}
count++;
encoded >>>= 1;
}
return valList.toArray(new String[valList.size()]);
}
}
@Override
public Object[] getRawFieldValues(BoboSegmentReader reader, int id) {
FacetDataCache dataCache = getFacetData(reader);
if (dataCache == null) return new String[0];
int encoded = dataCache.orderArray.get(id);
if (encoded == 0) {
return new Object[0];
} else {
int count = 1;
ArrayList valList = new ArrayList(MAX_VAL_COUNT);
while (encoded != 0) {
if ((encoded & 0x00000001) != 0x0) {
valList.add(dataCache.valArray.getRawValue(count));
}
count++;
encoded >>>= 1;
}
return valList.toArray(new Object[valList.size()]);
}
}
@Override
public FacetCountCollectorSource getFacetCountCollectorSource(final BrowseSelection sel,
final FacetSpec ospec) {
return new FacetCountCollectorSource() {
@Override
public FacetCountCollector getFacetCountCollector(BoboSegmentReader reader, int docBase) {
final FacetDataCache dataCache = CompactMultiValueFacetHandler.this.getFacetData(reader);
return new CompactMultiValueFacetCountCollector(_name, sel, dataCache, docBase, ospec);
}
};
}
@SuppressWarnings({ "unchecked", "rawtypes" })
@Override
public FacetDataCache load(BoboSegmentReader reader) throws IOException {
int maxDoc = reader.maxDoc();
BigIntArray order = new BigIntArray(maxDoc);
TermValueList mterms = _termListFactory == null ? new TermStringList() : _termListFactory
.createTermList();
IntArrayList minIDList = new IntArrayList();
IntArrayList maxIDList = new IntArrayList();
IntArrayList freqList = new IntArrayList();
int t = 0; // current term number
mterms.add(null);
minIDList.add(-1);
maxIDList.add(-1);
freqList.add(0);
t++;
Terms terms = reader.terms(_indexFieldName);
if (terms != null) {
TermsEnum termsEnum = terms.iterator(null);
BytesRef text;
while ((text = termsEnum.next()) != null) {
// store term text
// we expect that there is at most one term per document
if (t > MAX_VAL_COUNT) {
throw new IOException("maximum number of value cannot exceed: " + MAX_VAL_COUNT);
}
String val = text.utf8ToString();
mterms.add(val);
int bit = (0x00000001 << (t - 1));
Term term = new Term(_indexFieldName, val);
DocsEnum docsEnum = reader.termDocsEnum(term);
// freqList.add(termEnum.docFreq()); // removed because the df doesn't take into account the
// num of deletedDocs
int df = 0;
int minID = -1;
int maxID = -1;
int docID = -1;
while ((docID = docsEnum.nextDoc()) != DocsEnum.NO_MORE_DOCS) {
df++;
order.add(docID, order.get(docID) | bit);
minID = docID;
while (docsEnum.nextDoc() != DocsEnum.NO_MORE_DOCS) {
docID = docsEnum.docID();
df++;
order.add(docID, order.get(docID) | bit);
}
maxID = docID;
}
freqList.add(df);
minIDList.add(minID);
maxIDList.add(maxID);
t++;
}
}
mterms.seal();
return new FacetDataCache(order, mterms, freqList.toIntArray(), minIDList.toIntArray(),
maxIDList.toIntArray(), TermCountSize.large);
}
private static class CompactMultiFacetDocComparatorSource extends DocComparatorSource {
private final CompactMultiValueFacetHandler _facetHandler;
private CompactMultiFacetDocComparatorSource(CompactMultiValueFacetHandler facetHandler) {
_facetHandler = facetHandler;
}
@Override
public DocComparator getComparator(final AtomicReader reader, int docbase) throws IOException {
if (!(reader instanceof BoboSegmentReader)) throw new IllegalStateException(
"reader must be instance of " + BoboSegmentReader.class);
final FacetDataCache dataCache = _facetHandler.getFacetData((BoboSegmentReader) reader);
return new DocComparator() {
@Override
public int compare(ScoreDoc doc1, ScoreDoc doc2) {
int encoded1 = dataCache.orderArray.get(doc1.doc);
int encoded2 = dataCache.orderArray.get(doc2.doc);
return encoded1 - encoded2;
}
@Override
public Comparable value(ScoreDoc doc) {
return new StringArrayComparator(_facetHandler.getFieldValues((BoboSegmentReader) reader,
doc.doc));
}
};
}
}
@Override
public BoboDocScorer getDocScorer(BoboSegmentReader reader,
FacetTermScoringFunctionFactory scoringFunctionFactory, Map boostMap) {
FacetDataCache dataCache = getFacetData(reader);
float[] boostList = BoboDocScorer.buildBoostList(dataCache.valArray, boostMap);
return new CompactMultiValueDocScorer(dataCache, scoringFunctionFactory, boostList);
}
private static final class CompactMultiValueDocScorer extends BoboDocScorer {
private final FacetDataCache _dataCache;
CompactMultiValueDocScorer(FacetDataCache dataCache,
FacetTermScoringFunctionFactory scoreFunctionFactory, float[] boostList) {
super(scoreFunctionFactory.getFacetTermScoringFunction(dataCache.valArray.size(),
dataCache.orderArray.size()), boostList);
_dataCache = dataCache;
}
@Override
public Explanation explain(int doc) {
int encoded = _dataCache.orderArray.get(doc);
int count = 1;
FloatList scoreList = new FloatArrayList(_dataCache.valArray.size());
ArrayList explList = new ArrayList(scoreList.size());
while (encoded != 0) {
if ((encoded & 0x00000001) != 0x0) {
int idx = count - 1;
scoreList.add(_function.score(_dataCache.freqs[idx], _boostList[idx]));
explList.add(_function.explain(_dataCache.freqs[idx], _boostList[idx]));
}
count++;
encoded >>>= 1;
}
Explanation topLevel = _function.explain(scoreList.toFloatArray());
for (Explanation sub : explList) {
topLevel.addDetail(sub);
}
return topLevel;
}
@Override
public final float score(int docid) {
_function.clearScores();
int encoded = _dataCache.orderArray.get(docid);
int count = 1;
while (encoded != 0) {
int idx = count - 1;
if ((encoded & 0x00000001) != 0x0) {
_function.scoreAndCollect(_dataCache.freqs[idx], _boostList[idx]);
}
count++;
encoded >>>= 1;
}
return _function.getCurrentScore();
}
}
private static final class CompactMultiValueFacetCountCollector extends
DefaultFacetCountCollector {
private final BigSegmentedArray _array;
private final int[] _combinationCount = new int[16 * 8];
private int _noValCount = 0;
private boolean _aggregated = false;
CompactMultiValueFacetCountCollector(String name, BrowseSelection sel,
FacetDataCache dataCache, int docBase, FacetSpec ospec) {
super(name, dataCache, docBase, sel, ospec);
_array = _dataCache.orderArray;
}
@Override
public final void collectAll() {
_count = BigIntArray.fromArray(_dataCache.freqs);
_aggregated = true;
}
@Override
public final void collect(int docid) {
int encoded = _array.get(docid);
if (encoded == 0) {
_noValCount++;
} else {
int offset = 0;
while (true) {
_combinationCount[(encoded & 0x0F) + offset]++;
encoded = (encoded >>> 4);
if (encoded == 0) break;
offset += 16;
}
}
}
@Override
public BrowseFacet getFacet(String value) {
if (!_aggregated) aggregateCounts();
return super.getFacet(value);
}
@Override
public int getFacetHitsCount(Object value) {
if (!_aggregated) aggregateCounts();
return super.getFacetHitsCount(value);
}
@Override
public BigSegmentedArray getCountDistribution() {
if (!_aggregated) aggregateCounts();
return _count;
}
@Override
public List getFacets() {
if (!_aggregated) aggregateCounts();
return super.getFacets();
}
private void aggregateCounts() {
_count.add(0, _noValCount);
for (int i = 1; i < _combinationCount.length; i++) {
int count = _combinationCount[i];
if (count > 0) {
int offset = (i >> 4) * 4;
int encoded = (i & 0x0F);
int index = 1;
while (encoded != 0) {
if ((encoded & 0x00000001) != 0x0) {
int idx = index + offset;
_count.add(idx, _count.get(idx) + count);
}
index++;
encoded >>>= 1;
}
}
}
_aggregated = true;
}
@Override
public FacetIterator iterator() {
if (!_aggregated) aggregateCounts();
return super.iterator();
}
}
}
