/// <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, 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 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 FacetDataCache Load(BoboIndexReader reader)
{
int maxDoc = reader.MaxDoc;
BigIntArray order = new BigIntArray(maxDoc);
ITermValueList mterms = _termListFactory == null ? new TermStringList() : _termListFactory.CreateTermList();
List <int> minIDList = new List <int>();
List <int> maxIDList = new List <int>();
List <int> freqList = new List <int>();
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.Dispose();
}
}
finally
{
if (termEnum != null)
{
termEnum.Dispose();
}
}
}
mterms.Seal();
return(new FacetDataCache(order, mterms, freqList.ToArray(), minIDList.ToArray(), maxIDList.ToArray(), TermCountSize.Large));
}