public virtual void TestAddSameDocTwice()
{
// LUCENE-5367: this was a problem with the previous code, making sure it
// works with the new code.
Directory indexDir = NewDirectory(), taxoDir = NewDirectory();
IndexWriter indexWriter = new IndexWriter(indexDir, NewIndexWriterConfig(TEST_VERSION_CURRENT, new MockAnalyzer(Random())));
DirectoryTaxonomyWriter taxoWriter = new DirectoryTaxonomyWriter(taxoDir);
FacetsConfig facetsConfig = new FacetsConfig();
Document doc = new Document();
doc.Add(new FacetField("a", "b"));
doc = facetsConfig.Build(taxoWriter, doc);
// these two addDocument() used to fail
indexWriter.AddDocument(doc);
indexWriter.AddDocument(doc);
IOUtils.Close(indexWriter, taxoWriter);
DirectoryReader indexReader = DirectoryReader.Open(indexDir);
DirectoryTaxonomyReader taxoReader = new DirectoryTaxonomyReader(taxoDir);
IndexSearcher searcher = NewSearcher(indexReader);
FacetsCollector fc = new FacetsCollector();
searcher.Search(new MatchAllDocsQuery(), fc);
Facets facets = GetTaxonomyFacetCounts(taxoReader, facetsConfig, fc);
FacetResult res = facets.GetTopChildren(10, "a");
Assert.AreEqual(1, res.LabelValues.Length);
Assert.AreEqual(2, res.LabelValues[0].value);
IOUtils.Close(indexReader, taxoReader);
IOUtils.Close(indexDir, taxoDir);
}
public static void BeforeClassDrillDownQueryTest()
{
dir = NewDirectory();
Random r = Random();
RandomIndexWriter writer = new RandomIndexWriter(r, dir, NewIndexWriterConfig(TEST_VERSION_CURRENT, new MockAnalyzer(r, MockTokenizer.KEYWORD, false)));
taxoDir = NewDirectory();
TaxonomyWriter taxoWriter = new DirectoryTaxonomyWriter(taxoDir);
config = new FacetsConfig();
// Randomize the per-dim config:
config.SetHierarchical("a", Random().NextBoolean());
config.SetMultiValued("a", Random().NextBoolean());
if (Random().NextBoolean())
{
config.SetIndexFieldName("a", "$a");
}
config.SetRequireDimCount("a", true);
config.SetHierarchical("b", Random().NextBoolean());
config.SetMultiValued("b", Random().NextBoolean());
if (Random().NextBoolean())
{
config.SetIndexFieldName("b", "$b");
}
config.SetRequireDimCount("b", true);
for (int i = 0; i < 100; i++)
{
Document doc = new Document();
if (i % 2 == 0) // 50
{
doc.Add(new TextField("content", "foo", Field.Store.NO));
}
if (i % 3 == 0) // 33
{
doc.Add(new TextField("content", "bar", Field.Store.NO));
}
if (i % 4 == 0) // 25
{
if (r.NextBoolean())
{
doc.Add(new FacetField("a", "1"));
}
else
{
doc.Add(new FacetField("a", "2"));
}
}
if (i % 5 == 0) // 20
{
doc.Add(new FacetField("b", "1"));
}
writer.AddDocument(config.Build(taxoWriter, doc));
}
taxoWriter.Dispose();
reader = writer.Reader;
writer.Dispose();
taxo = new DirectoryTaxonomyReader(taxoDir);
}
public virtual void TestRandomSampling()
{
Directory dir = NewDirectory();
Directory taxoDir = NewDirectory();
DirectoryTaxonomyWriter taxoWriter = new DirectoryTaxonomyWriter(taxoDir);
RandomIndexWriter writer = new RandomIndexWriter(
#if FEATURE_INSTANCE_TESTDATA_INITIALIZATION
this,
#endif
Random, dir);
FacetsConfig config = new FacetsConfig();
int numDocs = AtLeast(10000);
for (int i = 0; i < numDocs; i++)
{
Document doc = new Document();
doc.Add(new StringField("EvenOdd", (i % 2 == 0) ? "even" : "odd", Store.NO));
doc.Add(new FacetField("iMod10", Convert.ToString(i % 10, CultureInfo.InvariantCulture)));
writer.AddDocument(config.Build(taxoWriter, doc));
}
Random random = Random;
// NRT open
IndexSearcher searcher = NewSearcher(writer.GetReader());
var taxoReader = new DirectoryTaxonomyReader(taxoWriter);
IOUtils.Dispose(writer, taxoWriter);
// Test empty results
RandomSamplingFacetsCollector collectRandomZeroResults = new RandomSamplingFacetsCollector(numDocs / 10, random.NextInt64());
// There should be no divisions by zero
searcher.Search(new TermQuery(new Term("EvenOdd", "NeverMatches")), collectRandomZeroResults);
// There should be no divisions by zero and no null result
Assert.IsNotNull(collectRandomZeroResults.GetMatchingDocs());
// There should be no results at all
foreach (MatchingDocs doc in collectRandomZeroResults.GetMatchingDocs())
{
Assert.AreEqual(0, doc.TotalHits);
}
// Now start searching and retrieve results.
// Use a query to select half of the documents.
TermQuery query = new TermQuery(new Term("EvenOdd", "even"));
// there will be 5 facet values (0, 2, 4, 6 and 8), as only the even (i %
// 10) are hits.
// there is a REAL small chance that one of the 5 values will be missed when
// sampling.
// but is that 0.8 (chance not to take a value) ^ 2000 * 5 (any can be
// missing) ~ 10^-193
// so that is probably not going to happen.
int maxNumChildren = 5;
RandomSamplingFacetsCollector random100Percent = new RandomSamplingFacetsCollector(numDocs, random.NextInt64()); // no sampling
RandomSamplingFacetsCollector random10Percent = new RandomSamplingFacetsCollector(numDocs / 10, random.NextInt64()); // 10 % of total docs, 20% of the hits
FacetsCollector fc = new FacetsCollector();
searcher.Search(query, MultiCollector.Wrap(fc, random100Percent, random10Percent));
FastTaxonomyFacetCounts random10FacetCounts = new FastTaxonomyFacetCounts(taxoReader, config, random10Percent);
FastTaxonomyFacetCounts random100FacetCounts = new FastTaxonomyFacetCounts(taxoReader, config, random100Percent);
FastTaxonomyFacetCounts exactFacetCounts = new FastTaxonomyFacetCounts(taxoReader, config, fc);
FacetResult random10Result = random10Percent.AmortizeFacetCounts(random10FacetCounts.GetTopChildren(10, "iMod10"), config, searcher);
FacetResult random100Result = random100FacetCounts.GetTopChildren(10, "iMod10");
FacetResult exactResult = exactFacetCounts.GetTopChildren(10, "iMod10");
Assert.AreEqual(random100Result, exactResult);
// we should have five children, but there is a small chance we have less.
// (see above).
Assert.IsTrue(random10Result.ChildCount <= maxNumChildren);
// there should be one child at least.
Assert.IsTrue(random10Result.ChildCount >= 1);
// now calculate some statistics to determine if the sampled result is 'ok'.
// because random sampling is used, the results will vary each time.
int sum = 0;
foreach (LabelAndValue lav in random10Result.LabelValues)
{
sum += (int)lav.Value;
}
float mu = (float)sum / (float)maxNumChildren;
float variance = 0;
foreach (LabelAndValue lav in random10Result.LabelValues)
{
variance += (float)Math.Pow((mu - (int)lav.Value), 2);
}
variance = variance / maxNumChildren;
float sigma = (float)Math.Sqrt(variance);
// we query only half the documents and have 5 categories. The average
// number of docs in a category will thus be the total divided by 5*2
float targetMu = numDocs / (5.0f * 2.0f);
// the average should be in the range and the standard deviation should not
// be too great
Assert.IsTrue(sigma < 200);
Assert.IsTrue(targetMu - 3 * sigma < mu && mu < targetMu + 3 * sigma);
IOUtils.Dispose(searcher.IndexReader, taxoReader, dir, taxoDir);
}
public virtual void TestRandomSampling()
{
Directory dir = NewDirectory();
Directory taxoDir = NewDirectory();
DirectoryTaxonomyWriter taxoWriter = new DirectoryTaxonomyWriter(taxoDir);
RandomIndexWriter writer = new RandomIndexWriter(Random(), dir);
FacetsConfig config = new FacetsConfig();
int numDocs = AtLeast(10000);
for (int i = 0; i < numDocs; i++)
{
Document doc = new Document();
doc.Add(new StringField("EvenOdd", (i % 2 == 0) ? "even" : "odd", Store.NO));
doc.Add(new FacetField("iMod10", Convert.ToString(i % 10)));
writer.AddDocument(config.Build(taxoWriter, doc));
}
Random random = Random();
// NRT open
IndexSearcher searcher = NewSearcher(writer.Reader);
var taxoReader = new DirectoryTaxonomyReader(taxoWriter);
IOUtils.Close(writer, taxoWriter);
// Test empty results
RandomSamplingFacetsCollector collectRandomZeroResults = new RandomSamplingFacetsCollector(numDocs / 10, random.NextLong());
// There should be no divisions by zero
searcher.Search(new TermQuery(new Term("EvenOdd", "NeverMatches")), collectRandomZeroResults);
// There should be no divisions by zero and no null result
Assert.NotNull(collectRandomZeroResults.GetMatchingDocs);
// There should be no results at all
foreach (MatchingDocs doc in collectRandomZeroResults.GetMatchingDocs)
{
Assert.AreEqual(0, doc.totalHits);
}
// Now start searching and retrieve results.
// Use a query to select half of the documents.
TermQuery query = new TermQuery(new Term("EvenOdd", "even"));
// there will be 5 facet values (0, 2, 4, 6 and 8), as only the even (i %
// 10) are hits.
// there is a REAL small chance that one of the 5 values will be missed when
// sampling.
// but is that 0.8 (chance not to take a value) ^ 2000 * 5 (any can be
// missing) ~ 10^-193
// so that is probably not going to happen.
int maxNumChildren = 5;
RandomSamplingFacetsCollector random100Percent = new RandomSamplingFacetsCollector(numDocs, random.NextLong()); // no sampling
RandomSamplingFacetsCollector random10Percent = new RandomSamplingFacetsCollector(numDocs / 10, random.NextLong()); // 10 % of total docs, 20% of the hits
FacetsCollector fc = new FacetsCollector();
searcher.Search(query, MultiCollector.Wrap(fc, random100Percent, random10Percent));
FastTaxonomyFacetCounts random10FacetCounts = new FastTaxonomyFacetCounts(taxoReader, config, random10Percent);
FastTaxonomyFacetCounts random100FacetCounts = new FastTaxonomyFacetCounts(taxoReader, config, random100Percent);
FastTaxonomyFacetCounts exactFacetCounts = new FastTaxonomyFacetCounts(taxoReader, config, fc);
FacetResult random10Result = random10Percent.AmortizeFacetCounts(random10FacetCounts.GetTopChildren(10, "iMod10"), config, searcher);
FacetResult random100Result = random100FacetCounts.GetTopChildren(10, "iMod10");
FacetResult exactResult = exactFacetCounts.GetTopChildren(10, "iMod10");
Assert.AreEqual(random100Result, exactResult);
// we should have five children, but there is a small chance we have less.
// (see above).
Assert.True(random10Result.ChildCount <= maxNumChildren);
// there should be one child at least.
Assert.True(random10Result.ChildCount >= 1);
// now calculate some statistics to determine if the sampled result is 'ok'.
// because random sampling is used, the results will vary each time.
int sum = 0;
foreach (LabelAndValue lav in random10Result.LabelValues)
{
sum += (int)lav.value;
}
float mu = (float)sum / (float)maxNumChildren;
float variance = 0;
foreach (LabelAndValue lav in random10Result.LabelValues)
{
variance += (float)Math.Pow((mu - (int)lav.value), 2);
}
variance = variance / maxNumChildren;
float sigma = (float)Math.Sqrt(variance);
// we query only half the documents and have 5 categories. The average
// number of docs in a category will thus be the total divided by 5*2
float targetMu = numDocs / (5.0f * 2.0f);
// the average should be in the range and the standard deviation should not
// be too great
Assert.True(sigma < 200);
Assert.True(targetMu - 3 * sigma < mu && mu < targetMu + 3 * sigma);
IOUtils.Close(searcher.IndexReader, taxoReader, dir, taxoDir);
}
public override void BeforeClass() // LUCENENET specific - renamed from BeforeClassDrillDownQueryTest() to ensure calling order
{
base.BeforeClass();
dir = NewDirectory();
Random r = Random;
RandomIndexWriter writer = new RandomIndexWriter(r, dir, NewIndexWriterConfig(TEST_VERSION_CURRENT, new MockAnalyzer(r, MockTokenizer.KEYWORD, false)));
taxoDir = NewDirectory();
ITaxonomyWriter taxoWriter = new DirectoryTaxonomyWriter(taxoDir);
config = new FacetsConfig();
// Randomize the per-dim config:
config.SetHierarchical("a", Random.NextBoolean());
config.SetMultiValued("a", Random.NextBoolean());
if (Random.NextBoolean())
{
config.SetIndexFieldName("a", "$a");
}
config.SetRequireDimCount("a", true);
config.SetHierarchical("b", Random.NextBoolean());
config.SetMultiValued("b", Random.NextBoolean());
if (Random.NextBoolean())
{
config.SetIndexFieldName("b", "$b");
}
config.SetRequireDimCount("b", true);
for (int i = 0; i < 100; i++)
{
Document doc = new Document();
if (i % 2 == 0) // 50
{
doc.Add(new TextField("content", "foo", Field.Store.NO));
}
if (i % 3 == 0) // 33
{
doc.Add(new TextField("content", "bar", Field.Store.NO));
}
if (i % 4 == 0) // 25
{
if (r.NextBoolean())
{
doc.Add(new FacetField("a", "1"));
}
else
{
doc.Add(new FacetField("a", "2"));
}
}
if (i % 5 == 0) // 20
{
doc.Add(new FacetField("b", "1"));
}
writer.AddDocument(config.Build(taxoWriter, doc));
}
taxoWriter.Dispose();
reader = writer.GetReader();
writer.Dispose();
taxo = new DirectoryTaxonomyReader(taxoDir);
}
private static void seedIndex(TaxonomyWriter tw, RandomIndexWriter iw, FacetsConfig config)
{
foreach (FacetField ff in CATEGORIES)
{
Document doc = new Document();
doc.Add(ff);
doc.Add(new TextField("content", "alpha", Field.Store.YES));
iw.AddDocument(config.Build(tw, doc));
}
}
