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com.browseengine.bobo.facets.impl.CompactMultiValueFacetHandler Maven / Gradle / Ivy
/**
* This software is licensed to you under the Apache License, Version 2.0 (the
* "Apache License").
*
* LinkedIn's contributions are made under the Apache License. If you contribute
* to the Software, the contributions will be deemed to have been made under the
* Apache License, unless you expressly indicate otherwise. Please do not make any
* contributions that would be inconsistent with the Apache License.
*
* You may obtain a copy of the Apache License at http://www.apache.org/licenses/LICENSE-2.0
* Unless required by applicable law or agreed to in writing, this software
* distributed under the Apache License is distributed on an "AS IS" BASIS, WITHOUT
* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the Apache
* License for the specific language governing permissions and limitations for the
* software governed under the Apache License.
*
* © 2012 LinkedIn Corp. All Rights Reserved.
*/
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.log4j.Logger;
import org.apache.lucene.index.IndexReader;
import org.apache.lucene.index.Term;
import org.apache.lucene.index.TermDocs;
import org.apache.lucene.index.TermEnum;
import org.apache.lucene.search.Explanation;
import org.apache.lucene.search.ScoreDoc;
import com.browseengine.bobo.api.BoboIndexReader;
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 Logger logger = Logger.getLogger(CompactMultiValueFacetHandler.class);
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(BoboIndexReader 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(BoboIndexReader 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(BoboIndexReader 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(BoboIndexReader reader,
int docBase) {
final FacetDataCache dataCache = CompactMultiValueFacetHandler.this.getFacetData(reader);
return new CompactMultiValueFacetCountCollector(_name,sel,dataCache,docBase,ospec);
}
};
}
@Override
public FacetDataCache load(BoboIndexReader 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();
TermDocs termDocs = null;
TermEnum termEnum = null;
int t = 0; // current term number
mterms.add(null);
minIDList.add(-1);
maxIDList.add(-1);
freqList.add(0);
t++;
try {
termDocs = reader.termDocs();
termEnum = reader.terms(new Term(_indexFieldName, ""));
do {
if (termEnum == null)
break;
Term term = termEnum.term();
if (term == null || !_indexFieldName.equals(term.field()))
break;
// 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 = term.text();
mterms.add(val);
int bit = (0x00000001 << (t-1));
termDocs.seek(termEnum);
//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;
if(termDocs.next())
{
df++;
int docid = termDocs.doc();
order.add(docid, order.get(docid) | bit);
minID = docid;
while (termDocs.next())
{
df++;
docid = termDocs.doc();
order.add(docid, order.get(docid) | bit);
}
maxID = docid;
}
freqList.add(df);
minIDList.add(minID);
maxIDList.add(maxID);
t++;
} while (termEnum.next());
} finally {
try {
if (termDocs != null) {
termDocs.close();
}
} finally {
if (termEnum != null) {
termEnum.close();
}
}
}
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 IndexReader reader, int docbase)
throws IOException {
if (!(reader instanceof BoboIndexReader))
throw new IllegalStateException("reader must be instance of "+BoboIndexReader.class);
final FacetDataCache dataCache = _facetHandler.getFacetData((BoboIndexReader)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((BoboIndexReader)reader,doc.doc));
}
};
}
}
public BoboDocScorer getDocScorer(BoboIndexReader 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();
}
}
}
