public PathFacetHandler(string name)
: base(name)
{
dataCache = null;
termListFactory = TermListFactory.StringListFactory;
separator = DEFAULT_SEP;
}
public SimpleFacetHandler(string name, string indexFieldName, TermListFactory termListFactory)
: base(name)
{
_indexFieldName = indexFieldName;
_dataCache = null;
_termListFactory = termListFactory;
}
public RangeFacetHandler(string name, string indexFieldName, TermListFactory termListFactory, IEnumerable<string> predefinedRanges)
: base(name)
{
this.indexFieldName = indexFieldName;
this.dataCache = null;
this.termListFactory = termListFactory;
this.predefinedRanges = predefinedRanges;
this.autoRange = false;
}
public MultiValueFacetHandler(string name, string indexFieldName, TermListFactory termListFactory, Term sizePayloadTerm, IEnumerable<string> depends)
: base(name, depends)
{
_depends = depends;
_indexFieldName = (indexFieldName != null ? indexFieldName : name);
_termListFactory = termListFactory;
_sizePayloadTerm = sizePayloadTerm;
_dataCache = null;
}
public RangeFacetHandler(string name, string indexFieldName, TermListFactory termListFactory, bool autoRange)
: base(name)
{
this.dataCache = null;
this.indexFieldName = indexFieldName;
this.termListFactory = termListFactory;
this.predefinedRanges = null;
this.autoRange = autoRange;
}
public AttributesFacetHandler(string name, string indexFieldName, TermListFactory termListFactory, Term sizePayloadTerm, IDictionary<string, string> facetProps)
: base(name, indexFieldName, sizePayloadTerm, termListFactory, new string[0])
{
if (facetProps.ContainsKey(SEPARATOR_PROP_NAME))
{
this.separator = Narrow(facetProps.Get(SEPARATOR_PROP_NAME))[0];
}
else
{
this.separator = DEFAULT_SEPARATOR;
}
if (facetProps.ContainsKey(MAX_FACETS_PER_KEY_PROP_NAME))
{
this.numFacetsPerKey = int.Parse(Narrow(facetProps.Get(MAX_FACETS_PER_KEY_PROP_NAME)));
}
}
public override void Load(string fieldName, AtomicReader reader, TermListFactory listFactory)
{
this.Load(fieldName, reader, listFactory, new BoboSegmentReader.WorkArea());
}
public virtual void Load(string fieldName, IndexReader reader, TermListFactory listFactory)
{
string field = string.Intern(fieldName);
int maxDoc = reader.MaxDoc;
BigSegmentedArray order = this.orderArray;
if (order == null) // we want to reuse the memory
{
int dictValueCount = GetDictValueCount(reader, fieldName);
order = NewInstance(dictValueCount, maxDoc);
}
else
{
order.EnsureCapacity(maxDoc); // no need to fill to 0, we are reseting the
// data anyway
}
this.orderArray = order;
List <int> minIDList = new List <int>();
List <int> maxIDList = new List <int>();
List <int> freqList = new List <int>();
int length = maxDoc + 1;
ITermValueList list = listFactory == null ? (ITermValueList) new TermStringList() : listFactory.CreateTermList();
int negativeValueCount = GetNegativeValueCount(reader, field);
TermDocs termDocs = reader.TermDocs();
TermEnum termEnum = reader.Terms(new Term(field, ""));
int t = 0; // current term number
list.Add(null);
minIDList.Add(-1);
maxIDList.Add(-1);
freqList.Add(0);
int totalFreq = 0;
//int df = 0;
t++;
try
{
do
{
Term term = termEnum.Term;
if (term == null || string.CompareOrdinal(term.Field, field) != 0)
{
break;
}
// store term text
// we expect that there is at most one term per document
// Alexey: well, we could get now more than one term per document. Effectively, we could build facet against tokenized field
//if (t >= length)
//{
// throw new RuntimeException("there are more terms than " + "documents in field \"" + field
// + "\", but it's impossible to sort on " + "tokenized fields");
//}
list.Add(term.Text);
termDocs.Seek(termEnum);
// freqList.add(termEnum.docFreq()); // doesn't take into account deldocs
int minID = -1;
int maxID = -1;
int df = 0;
int valId = (t - 1 < negativeValueCount) ? (negativeValueCount - t + 1) : t;
if (termDocs.Next())
{
df++;
int docid = termDocs.Doc;
order.Add(docid, valId);
minID = docid;
while (termDocs.Next())
{
df++;
docid = termDocs.Doc;
order.Add(docid, valId);
}
maxID = docid;
}
freqList.Add(df);
totalFreq += df;
minIDList.Add(minID);
maxIDList.Add(maxID);
t++;
} while (termEnum.Next());
}
finally
{
termDocs.Dispose();
termEnum.Dispose();
}
list.Seal();
this.valArray = list;
this.freqs = freqList.ToArray();
this.minIDs = minIDList.ToArray();
this.maxIDs = maxIDList.ToArray();
int doc = 0;
while (doc <= maxDoc && order.Get(doc) != 0)
{
++doc;
}
if (doc <= maxDoc)
{
this.minIDs[0] = doc;
// Try to get the max
doc = maxDoc;
while (doc > 0 && order.Get(doc) != 0)
{
--doc;
}
if (doc > 0)
{
this.maxIDs[0] = doc;
}
}
this.freqs[0] = maxDoc + 1 - totalFreq;
}
public override void Load(string fieldName, IndexReader reader, TermListFactory listFactory, BoboIndexReader.WorkArea workArea)
{
long t0 = System.Environment.TickCount;
int maxdoc = reader.MaxDoc;
BigNestedIntArray.BufferedLoader loader = GetBufferedLoader(maxdoc, workArea);
BigNestedIntArray.BufferedLoader weightLoader = GetBufferedLoader(maxdoc, null);
TermEnum tenum = null;
TermDocs tdoc = null;
var list = (listFactory == null ? new TermStringList() : listFactory.CreateTermList());
List <int> minIDList = new List <int>();
List <int> maxIDList = new List <int>();
List <int> freqList = new List <int>();
OpenBitSet bitset = new OpenBitSet(maxdoc + 1);
int negativeValueCount = GetNegativeValueCount(reader, string.Intern(fieldName));
int t = 0; // current term number
list.Add(null);
minIDList.Add(-1);
maxIDList.Add(-1);
freqList.Add(0);
t++;
_overflow = false;
string pre = null;
int df = 0;
int minID = -1;
int maxID = -1;
int valId = 0;
try
{
tdoc = reader.TermDocs();
tenum = reader.Terms(new Term(fieldName, ""));
if (tenum != null)
{
do
{
Term term = tenum.Term;
if (term == null || !fieldName.Equals(term.Field))
{
break;
}
string val = term.Text;
if (val != null)
{
int weight = 0;
string[] split = val.Split(new char[] { '\0' }, StringSplitOptions.RemoveEmptyEntries);
if (split.Length > 1)
{
val = split[0];
weight = int.Parse(split[split.Length - 1]);
}
if (pre == null || !val.Equals(pre))
{
if (pre != null)
{
freqList.Add(df);
minIDList.Add(minID);
maxIDList.Add(maxID);
}
list.Add(val);
df = 0;
minID = -1;
maxID = -1;
valId = (t - 1 < negativeValueCount) ? (negativeValueCount - t + 1) : t;
t++;
}
tdoc.Seek(tenum);
if (tdoc.Next())
{
df++;
int docid = tdoc.Doc;
if (!loader.Add(docid, valId))
{
LogOverflow(fieldName);
}
else
{
weightLoader.Add(docid, weight);
}
if (docid < minID)
{
minID = docid;
}
bitset.FastSet(docid);
while (tdoc.Next())
{
df++;
docid = tdoc.Doc;
if (!loader.Add(docid, valId))
{
LogOverflow(fieldName);
}
else
{
weightLoader.Add(docid, weight);
}
bitset.FastSet(docid);
}
if (docid > maxID)
{
maxID = docid;
}
}
pre = val;
}
}while (tenum.Next());
if (pre != null)
{
freqList.Add(df);
minIDList.Add(minID);
maxIDList.Add(maxID);
}
}
}
finally
{
try
{
if (tdoc != null)
{
tdoc.Dispose();
}
}
finally
{
if (tenum != null)
{
tenum.Dispose();
}
}
}
list.Seal();
try
{
_nestedArray.Load(maxdoc + 1, loader);
_weightArray.Load(maxdoc + 1, weightLoader);
}
catch (System.IO.IOException e)
{
throw e;
}
catch (Exception e)
{
throw new RuntimeException("failed to load due to " + e.ToString(), e);
}
this.valArray = list;
this.freqs = freqList.ToArray();
this.minIDs = minIDList.ToArray();
this.maxIDs = maxIDList.ToArray();
int doc = 0;
while (doc <= maxdoc && !_nestedArray.Contains(doc, 0, true))
{
++doc;
}
if (doc <= maxdoc)
{
this.minIDs[0] = doc;
doc = maxdoc;
while (doc > 0 && !_nestedArray.Contains(doc, 0, true))
{
--doc;
}
if (doc > 0)
{
this.maxIDs[0] = doc;
}
}
this.freqs[0] = maxdoc + 1 - (int)bitset.Cardinality();
}
public RangeFacetHandler(string name, TermListFactory termListFactory, bool autoRange)
: this(name, name, termListFactory, autoRange)
{
}
public MultiValueWithWeightFacetHandler(string name, string indexFieldName, TermListFactory termListFactory)
: base(name, indexFieldName, termListFactory, null, null)
{
}
public MultiValueFacetHandler(string name, string indexFieldName, TermListFactory termListFactory)
: this(name, indexFieldName, termListFactory, null, null)
{
}
public override void Load(string fieldName, IndexReader reader, TermListFactory listFactory)
{
this.Load(fieldName, reader, listFactory, new BoboIndexReader.WorkArea());
}
public override void Load(string fieldName, IndexReader reader, TermListFactory listFactory, BoboIndexReader.WorkArea workArea)
{
long t0 = System.Environment.TickCount;
int maxdoc = reader.MaxDoc;
BigNestedIntArray.BufferedLoader loader = GetBufferedLoader(maxdoc, workArea);
BigNestedIntArray.BufferedLoader weightLoader = GetBufferedLoader(maxdoc, null);
TermEnum tenum = null;
TermDocs tdoc = null;
var list = (listFactory == null ? new TermStringList() : listFactory.CreateTermList());
List<int> minIDList = new List<int>();
List<int> maxIDList = new List<int>();
List<int> freqList = new List<int>();
OpenBitSet bitset = new OpenBitSet(maxdoc + 1);
int negativeValueCount = GetNegativeValueCount(reader, string.Intern(fieldName));
int t = 0; // current term number
list.Add(null);
minIDList.Add(-1);
maxIDList.Add(-1);
freqList.Add(0);
t++;
_overflow = false;
string pre = null;
int df = 0;
int minID = -1;
int maxID = -1;
int valId = 0;
try
{
tdoc = reader.TermDocs();
tenum = reader.Terms(new Term(fieldName, ""));
if (tenum != null)
{
do
{
Term term = tenum.Term;
if (term == null || !fieldName.Equals(term.Field))
break;
string val = term.Text;
if (val != null)
{
int weight = 0;
string[] split = val.Split(new char[] { '\0' }, StringSplitOptions.RemoveEmptyEntries);
if (split.Length > 1)
{
val = split[0];
weight = int.Parse(split[split.Length - 1]);
}
if (pre == null || !val.Equals(pre))
{
if (pre != null)
{
freqList.Add(df);
minIDList.Add(minID);
maxIDList.Add(maxID);
}
list.Add(val);
df = 0;
minID = -1;
maxID = -1;
valId = (t - 1 < negativeValueCount) ? (negativeValueCount - t + 1) : t;
t++;
}
tdoc.Seek(tenum);
if (tdoc.Next())
{
df++;
int docid = tdoc.Doc;
if (!loader.Add(docid, valId)) LogOverflow(fieldName);
else weightLoader.Add(docid, weight);
if (docid < minID) minID = docid;
bitset.FastSet(docid);
while (tdoc.Next())
{
df++;
docid = tdoc.Doc;
if (!loader.Add(docid, valId)) LogOverflow(fieldName);
else weightLoader.Add(docid, weight);
bitset.FastSet(docid);
}
if (docid > maxID) maxID = docid;
}
pre = val;
}
}
while (tenum.Next());
if (pre != null)
{
freqList.Add(df);
minIDList.Add(minID);
maxIDList.Add(maxID);
}
}
}
finally
{
try
{
if (tdoc != null)
{
tdoc.Dispose();
}
}
finally
{
if (tenum != null)
{
tenum.Dispose();
}
}
}
list.Seal();
try
{
_nestedArray.Load(maxdoc + 1, loader);
_weightArray.Load(maxdoc + 1, weightLoader);
}
catch (System.IO.IOException e)
{
throw e;
}
catch (Exception e)
{
throw new RuntimeException("failed to load due to " + e.ToString(), e);
}
this.valArray = list;
this.freqs = freqList.ToArray();
this.minIDs = minIDList.ToArray();
this.maxIDs = maxIDList.ToArray();
int doc = 0;
while (doc <= maxdoc && !_nestedArray.Contains(doc, 0, true))
{
++doc;
}
if (doc <= maxdoc)
{
this.minIDs[0] = doc;
doc = maxdoc;
while (doc > 0 && !_nestedArray.Contains(doc, 0, true))
{
--doc;
}
if (doc > 0)
{
this.maxIDs[0] = doc;
}
}
this.freqs[0] = maxdoc + 1 - (int)bitset.Cardinality();
}
/// <summary>
/// loads multi-value facet data. This method uses a workarea to prepare loading.
/// </summary>
/// <param name="fieldName"></param>
/// <param name="reader"></param>
/// <param name="listFactory"></param>
/// <param name="workArea"></param>
public virtual void Load(string fieldName, IndexReader reader, TermListFactory listFactory, BoboIndexReader.WorkArea workArea)
{
long t0 = Environment.TickCount;
int maxdoc = reader.MaxDoc;
BigNestedIntArray.BufferedLoader loader = GetBufferedLoader(maxdoc, workArea);
TermEnum tenum = null;
TermDocs tdoc = null;
ITermValueList list = (listFactory == null ? (ITermValueList)new TermStringList() : listFactory.CreateTermList());
List<int> minIDList = new List<int>();
List<int> maxIDList = new List<int>();
List<int> freqList = new List<int>();
OpenBitSet bitset = new OpenBitSet();
int negativeValueCount = GetNegativeValueCount(reader, string.Intern(fieldName));
int t = 0; // current term number
list.Add(null);
minIDList.Add(-1);
maxIDList.Add(-1);
freqList.Add(0);
t++;
_overflow = false;
try
{
tdoc = reader.TermDocs();
tenum = reader.Terms(new Term(fieldName, ""));
if (tenum != null)
{
do
{
Term term = tenum.Term;
if (term == null || !fieldName.Equals(term.Field))
break;
string val = term.Text;
if (val != null)
{
list.Add(val);
tdoc.Seek(tenum);
//freqList.add(tenum.docFreq()); // removed because the df doesn't take into account the num of deletedDocs
int df = 0;
int minID = -1;
int maxID = -1;
int valId = (t - 1 < negativeValueCount) ? (negativeValueCount - t + 1) : t;
if (tdoc.Next())
{
df++;
int docid = tdoc.Doc;
if (!loader.Add(docid, valId))
LogOverflow(fieldName);
minID = docid;
bitset.Set(docid);
while (tdoc.Next())
{
df++;
docid = tdoc.Doc;
if (!loader.Add(docid, valId))
LogOverflow(fieldName);
bitset.Set(docid);
}
maxID = docid;
}
freqList.Add(df);
minIDList.Add(minID);
maxIDList.Add(maxID);
}
t++;
}
while (tenum.Next());
}
}
finally
{
try
{
if (tdoc != null)
{
tdoc.Dispose();
}
}
finally
{
if (tenum != null)
{
tenum.Dispose();
}
}
}
list.Seal();
try
{
_nestedArray.Load(maxdoc + 1, loader);
}
catch (System.IO.IOException e)
{
throw e;
}
catch (Exception e)
{
throw new RuntimeException("failed to load due to " + e.ToString(), e);
}
this.valArray = list;
this.freqs = freqList.ToArray();
this.minIDs = minIDList.ToArray();
this.maxIDs = maxIDList.ToArray();
int doc = 0;
while (doc <= maxdoc && !_nestedArray.Contains(doc, 0, true))
{
++doc;
}
if (doc <= maxdoc)
{
this.minIDs[0] = doc;
doc = maxdoc;
while (doc > 0 && !_nestedArray.Contains(doc, 0, true))
{
--doc;
}
if (doc > 0)
{
this.maxIDs[0] = doc;
}
}
this.freqs[0] = maxdoc + 1 - (int)bitset.Cardinality();
}
public override void Load(string fieldName, IndexReader reader, TermListFactory listFactory)
{
this.Load(fieldName, reader, listFactory, new BoboIndexReader.WorkArea());
}
public virtual void Load(string fieldName, AtomicReader reader, TermListFactory listFactory)
{
#if FEATURE_STRING_INTERN
string field = string.Intern(fieldName);
#else
string field = fieldName;
#endif
int maxDoc = reader.MaxDoc;
int dictValueCount = GetDictValueCount(reader, fieldName);
BigSegmentedArray order = NewInstance(dictValueCount, maxDoc);
this.m_orderArray = order;
List <int> minIDList = new List <int>();
List <int> maxIDList = new List <int>();
List <int> freqList = new List <int>();
int length = maxDoc + 1;
ITermValueList list = listFactory == null ? (ITermValueList) new TermStringList() : listFactory.CreateTermList();
int negativeValueCount = GetNegativeValueCount(reader, field);
int t = 1; // valid term id starts from 1
list.Add(null);
minIDList.Add(-1);
maxIDList.Add(-1);
freqList.Add(0);
int totalFreq = 0;
Terms terms = reader.GetTerms(field);
if (terms != null)
{
TermsEnum termsEnum = terms.GetIterator(null);
BytesRef text;
while ((text = termsEnum.Next()) != null)
{
// store term text
// we expect that there is at most one term per document
if (t >= length)
{
throw new RuntimeException("there are more terms than "
+ "documents in field \"" + field + "\", but it's impossible to sort on "
+ "tokenized fields");
}
string strText = text.Utf8ToString();
list.Add(strText);
Term term = new Term(field, strText);
DocsEnum docsEnum = reader.GetTermDocsEnum(term);
// freqList.add(termEnum.docFreq()); // doesn't take into account
// deldocs
int minID = -1;
int maxID = -1;
int docID = -1;
int df = 0;
int valId = (t - 1 < negativeValueCount) ? (negativeValueCount - t + 1) : t;
while ((docID = docsEnum.NextDoc()) != DocsEnum.NO_MORE_DOCS)
{
df++;
order.Add(docID, valId);
minID = docID;
while (docsEnum.NextDoc() != DocsEnum.NO_MORE_DOCS)
{
docID = docsEnum.DocID;
df++;
order.Add(docID, valId);
}
maxID = docID;
}
freqList.Add(df);
totalFreq += df;
minIDList.Add(minID);
maxIDList.Add(maxID);
t++;
}
}
list.Seal();
this.m_valArray = list;
this.m_freqs = freqList.ToArray();
this.m_minIDs = minIDList.ToArray();
this.m_maxIDs = maxIDList.ToArray();
int doc = 0;
while (doc < maxDoc && order.Get(doc) != 0)
{
++doc;
}
if (doc < maxDoc)
{
this.m_minIDs[0] = doc;
// Try to get the max
doc = maxDoc - 1;
while (doc >= 0 && order.Get(doc) != 0)
{
--doc;
}
this.m_maxIDs[0] = doc;
}
this.m_freqs[0] = reader.NumDocs - totalFreq;
}
public CompactMultiValueFacetHandler(string name, TermListFactory termListFactory)
: this(name, name, termListFactory)
{
}
public CompactMultiValueFacetHandler(string name, string indexFieldName, TermListFactory termListFactory)
: base(name)
{
_indexFieldName = indexFieldName;
_termListFactory = termListFactory;
}
/// <summary>
/// loads multi-value facet data. This method uses a workarea to prepare loading.
/// </summary>
/// <param name="fieldName"></param>
/// <param name="reader"></param>
/// <param name="listFactory"></param>
/// <param name="workArea"></param>
public virtual void Load(string fieldName, AtomicReader reader, TermListFactory listFactory, BoboSegmentReader.WorkArea workArea)
{
#if FEATURE_STRING_INTERN
string field = string.Intern(fieldName);
#else
string field = fieldName;
#endif
int maxdoc = reader.MaxDoc;
BigNestedInt32Array.BufferedLoader loader = GetBufferedLoader(maxdoc, workArea);
ITermValueList list = (listFactory == null ? (ITermValueList) new TermStringList() : listFactory.CreateTermList());
List <int> minIDList = new List <int>();
List <int> maxIDList = new List <int>();
List <int> freqList = new List <int>();
OpenBitSet bitset = new OpenBitSet(maxdoc + 1);
int negativeValueCount = GetNegativeValueCount(reader, field);
int t = 1; // valid term id starts from 1
list.Add(null);
minIDList.Add(-1);
maxIDList.Add(-1);
freqList.Add(0);
m_overflow = false;
Terms terms = reader.GetTerms(field);
if (terms != null)
{
TermsEnum termsEnum = terms.GetIterator(null);
BytesRef text;
while ((text = termsEnum.Next()) != null)
{
string strText = text.Utf8ToString();
list.Add(strText);
Term term = new Term(field, strText);
DocsEnum docsEnum = reader.GetTermDocsEnum(term);
int df = 0;
int minID = -1;
int maxID = -1;
int docID = -1;
int valId = (t - 1 < negativeValueCount) ? (negativeValueCount - t + 1) : t;
while ((docID = docsEnum.NextDoc()) != DocsEnum.NO_MORE_DOCS)
{
df++;
if (!loader.Add(docID, valId))
{
LogOverflow(fieldName);
}
minID = docID;
bitset.FastSet(docID);
while (docsEnum.NextDoc() != DocsEnum.NO_MORE_DOCS)
{
docID = docsEnum.DocID;
df++;
if (!loader.Add(docID, valId))
{
LogOverflow(fieldName);
}
bitset.FastSet(docID);
}
maxID = docID;
}
freqList.Add(df);
minIDList.Add(minID);
maxIDList.Add(maxID);
t++;
}
}
list.Seal();
try
{
m_nestedArray.Load(maxdoc + 1, loader);
}
catch (Exception e)
{
throw new RuntimeException("failed to load due to " + e.ToString(), e);
}
this.m_valArray = list;
this.m_freqs = freqList.ToArray();
this.m_minIDs = minIDList.ToArray();
this.m_maxIDs = maxIDList.ToArray();
int doc = 0;
while (doc < maxdoc && !m_nestedArray.Contains(doc, 0, true))
{
++doc;
}
if (doc < maxdoc)
{
this.m_minIDs[0] = doc;
doc = maxdoc - 1;
while (doc >= 0 && !m_nestedArray.Contains(doc, 0, true))
{
--doc;
}
this.m_maxIDs[0] = doc;
}
this.m_freqs[0] = maxdoc - (int)bitset.Cardinality();
}
public virtual void Load(string fieldName, IndexReader reader, TermListFactory listFactory)
{
string field = string.Intern(fieldName);
int maxDoc = reader.MaxDoc;
if (orderArray == null) // we want to reuse the memory
{
orderArray = NewInstance(termCountSize, maxDoc);
}
else
{
orderArray.EnsureCapacity(maxDoc); // no need to fill to 0, we are reseting the data anyway
}
List<int> minIDList = new List<int>();
List<int> maxIDList = new List<int>();
List<int> freqList = new List<int>();
int length = maxDoc + 1;
ITermValueList list = listFactory == null ? new TermStringList() : listFactory.CreateTermList();
TermDocs termDocs = reader.TermDocs();
TermEnum termEnum = reader.Terms(new Term(field));
int t = 0; // current term number
list.Add(null);
minIDList.Add(-1);
maxIDList.Add(-1);
freqList.Add(0);
//int df = 0;
t++;
try
{
do
{
Term term = termEnum.Term;
if (term == null || string.CompareOrdinal(term.Field, field) != 0)
break;
if (t >= orderArray.MaxValue())
{
throw new System.IO.IOException("maximum number of value cannot exceed: " + orderArray.MaxValue());
}
// Alexey: well, we could get now more than one term per document. Effectively, we could build facet againsts tokenized field
/*// we expect that there is at most one term per document
if (t >= length)
{
throw new RuntimeException("there are more terms than " + "documents in field \"" + field + "\", but it's impossible to sort on " + "tokenized fields");
}*/
// store term text
list.Add(term.Text);
termDocs.Seek(termEnum);
// freqList.add(termEnum.docFreq()); // doesn't take into account deldocs
int minID = -1;
int maxID = -1;
int df = 0;
if (termDocs.Next())
{
df++;
int docid = termDocs.Doc;
orderArray.Add(docid, t);
minID = docid;
while (termDocs.Next())
{
df++;
docid = termDocs.Doc;
orderArray.Add(docid, t);
}
maxID = docid;
}
freqList.Add(df);
minIDList.Add(minID);
maxIDList.Add(maxID);
t++;
} while (termEnum.Next());
}
finally
{
termDocs.Dispose();
termEnum.Dispose();
}
list.Seal();
this.valArray = list;
this.freqs = freqList.ToArray();
this.minIDs = minIDList.ToArray();
this.maxIDs = maxIDList.ToArray();
}
public MultiValueFacetHandler(string name, TermListFactory termListFactory, Term sizePayloadTerm)
: this(name, name, termListFactory, sizePayloadTerm, null)
{
}
public SimpleFacetHandler(string name, TermListFactory termListFactory)
: this(name, name, termListFactory)
{
}
public override void Load(string fieldName, AtomicReader reader, TermListFactory listFactory, BoboSegmentReader.WorkArea workArea)
{
#if FEATURE_STRING_INTERN
string field = string.Intern(fieldName);
#else
string field = fieldName;
#endif
int maxdoc = reader.MaxDoc;
BigNestedInt32Array.BufferedLoader loader = GetBufferedLoader(maxdoc, workArea);
BigNestedInt32Array.BufferedLoader weightLoader = GetBufferedLoader(maxdoc, null);
var list = (listFactory == null ? new TermStringList() : listFactory.CreateTermList());
List <int> minIDList = new List <int>();
List <int> maxIDList = new List <int>();
List <int> freqList = new List <int>();
OpenBitSet bitset = new OpenBitSet(maxdoc + 1);
int negativeValueCount = GetNegativeValueCount(reader, field);
int t = 1; // valid term id starts from 1
list.Add(null);
minIDList.Add(-1);
maxIDList.Add(-1);
freqList.Add(0);
m_overflow = false;
string pre = null;
int df = 0;
int minID = -1;
int maxID = -1;
int docID = -1;
int valId = 0;
Terms terms = reader.GetTerms(field);
if (terms != null)
{
TermsEnum termsEnum = terms.GetIterator(null);
BytesRef text;
while ((text = termsEnum.Next()) != null)
{
string strText = text.Utf8ToString();
string val = null;
int weight = 0;
string[] split = strText.Split(new char[] { '\0' }, StringSplitOptions.RemoveEmptyEntries);
if (split.Length > 1)
{
val = split[0];
weight = int.Parse(split[split.Length - 1]);
}
else
{
continue;
}
if (pre == null || !val.Equals(pre))
{
if (pre != null)
{
freqList.Add(df);
minIDList.Add(minID);
maxIDList.Add(maxID);
}
list.Add(val);
df = 0;
minID = -1;
maxID = -1;
valId = (t - 1 < negativeValueCount) ? (negativeValueCount - t + 1) : t;
t++;
}
Term term = new Term(field, strText);
DocsEnum docsEnum = reader.GetTermDocsEnum(term);
if (docsEnum != null)
{
while ((docID = docsEnum.NextDoc()) != DocsEnum.NO_MORE_DOCS)
{
df++;
if (!loader.Add(docID, valId))
{
LogOverflow(fieldName);
}
else
{
weightLoader.Add(docID, weight);
}
if (docID < minID)
{
minID = docID;
}
bitset.FastSet(docID);
while (docsEnum.NextDoc() != DocsEnum.NO_MORE_DOCS)
{
docID = docsEnum.DocID;
df++;
if (!loader.Add(docID, valId))
{
LogOverflow(fieldName);
}
else
{
weightLoader.Add(docID, weight);
}
bitset.FastSet(docID);
}
if (docID > maxID)
{
maxID = docID;
}
}
}
pre = val;
}
if (pre != null)
{
freqList.Add(df);
minIDList.Add(minID);
maxIDList.Add(maxID);
}
}
list.Seal();
try
{
m_nestedArray.Load(maxdoc + 1, loader);
m_weightArray.Load(maxdoc + 1, weightLoader);
}
catch (Exception e)
{
throw new RuntimeException("failed to load due to " + e.ToString(), e);
}
this.m_valArray = list;
this.m_freqs = freqList.ToArray();
this.m_minIDs = minIDList.ToArray();
this.m_maxIDs = maxIDList.ToArray();
int doc = 0;
while (doc < maxdoc && !m_nestedArray.Contains(doc, 0, true))
{
++doc;
}
if (doc < maxdoc)
{
this.m_minIDs[0] = doc;
doc = maxdoc - 1;
while (doc >= 0 && !m_nestedArray.Contains(doc, 0, true))
{
--doc;
}
this.m_maxIDs[0] = doc;
}
this.m_freqs[0] = maxdoc - (int)bitset.Cardinality();
}
/// <summary>
/// loads multi-value facet data. This method uses a workarea to prepare loading.
/// </summary>
/// <param name="fieldName"></param>
/// <param name="reader"></param>
/// <param name="listFactory"></param>
/// <param name="workArea"></param>
public virtual void Load(string fieldName, IndexReader reader, TermListFactory listFactory, BoboIndexReader.WorkArea workArea)
{
long t0 = Environment.TickCount;
int maxdoc = reader.MaxDoc;
BigNestedIntArray.BufferedLoader loader = GetBufferedLoader(maxdoc, workArea);
TermEnum tenum = null;
TermDocs tdoc = null;
ITermValueList list = (listFactory == null ? (ITermValueList) new TermStringList() : listFactory.CreateTermList());
List <int> minIDList = new List <int>();
List <int> maxIDList = new List <int>();
List <int> freqList = new List <int>();
OpenBitSet bitset = new OpenBitSet();
int negativeValueCount = GetNegativeValueCount(reader, string.Intern(fieldName));
int t = 0; // current term number
list.Add(null);
minIDList.Add(-1);
maxIDList.Add(-1);
freqList.Add(0);
t++;
_overflow = false;
try
{
tdoc = reader.TermDocs();
tenum = reader.Terms(new Term(fieldName, ""));
if (tenum != null)
{
do
{
Term term = tenum.Term;
if (term == null || !fieldName.Equals(term.Field))
{
break;
}
string val = term.Text;
if (val != null)
{
list.Add(val);
tdoc.Seek(tenum);
//freqList.add(tenum.docFreq()); // removed because the df doesn't take into account the num of deletedDocs
int df = 0;
int minID = -1;
int maxID = -1;
int valId = (t - 1 < negativeValueCount) ? (negativeValueCount - t + 1) : t;
if (tdoc.Next())
{
df++;
int docid = tdoc.Doc;
if (!loader.Add(docid, valId))
{
LogOverflow(fieldName);
}
minID = docid;
bitset.Set(docid);
while (tdoc.Next())
{
df++;
docid = tdoc.Doc;
if (!loader.Add(docid, valId))
{
LogOverflow(fieldName);
}
bitset.Set(docid);
}
maxID = docid;
}
freqList.Add(df);
minIDList.Add(minID);
maxIDList.Add(maxID);
}
t++;
}while (tenum.Next());
}
}
finally
{
try
{
if (tdoc != null)
{
tdoc.Dispose();
}
}
finally
{
if (tenum != null)
{
tenum.Dispose();
}
}
}
list.Seal();
try
{
_nestedArray.Load(maxdoc + 1, loader);
}
catch (System.IO.IOException e)
{
throw e;
}
catch (Exception e)
{
throw new RuntimeException("failed to load due to " + e.ToString(), e);
}
this.valArray = list;
this.freqs = freqList.ToArray();
this.minIDs = minIDList.ToArray();
this.maxIDs = maxIDList.ToArray();
int doc = 0;
while (doc <= maxdoc && !_nestedArray.Contains(doc, 0, true))
{
++doc;
}
if (doc <= maxdoc)
{
this.minIDs[0] = doc;
doc = maxdoc;
while (doc > 0 && !_nestedArray.Contains(doc, 0, true))
{
--doc;
}
if (doc > 0)
{
this.maxIDs[0] = doc;
}
}
this.freqs[0] = maxdoc + 1 - (int)bitset.Cardinality();
}
public RangeFacetHandler(string name, TermListFactory termListFactory, IEnumerable<string> predefinedRanges)
: this(name, name, termListFactory, predefinedRanges)
{
}
