Examples with RandomIndexWriter org.apache.lucene.index.RandomIndexWriter used on opensource projects

Example 96 with RandomIndexWriter

use of org.apache.lucene.index.RandomIndexWriter in project lucene-solr by apache.

the class BaseGeoPointTestCase method verifyRandomPolygons.

protected void verifyRandomPolygons(double[] lats, double[] lons) throws Exception {
    IndexWriterConfig iwc = newIndexWriterConfig();
    // Else seeds may not reproduce:
    iwc.setMergeScheduler(new SerialMergeScheduler());
    // Else we can get O(N^2) merging:
    int mbd = iwc.getMaxBufferedDocs();
    if (mbd != -1 && mbd < lats.length / 100) {
        iwc.setMaxBufferedDocs(lats.length / 100);
    }
    Directory dir;
    if (lats.length > 100000) {
        dir = newFSDirectory(createTempDir(getClass().getSimpleName()));
    } else {
        dir = newDirectory();
    }
    Set<Integer> deleted = new HashSet<>();
    // RandomIndexWriter is too slow here:
    IndexWriter w = new IndexWriter(dir, iwc);
    for (int id = 0; id < lats.length; id++) {
        Document doc = new Document();
        doc.add(newStringField("id", "" + id, Field.Store.NO));
        doc.add(new NumericDocValuesField("id", id));
        if (Double.isNaN(lats[id]) == false) {
            addPointToDoc(FIELD_NAME, doc, lats[id], lons[id]);
        }
        w.addDocument(doc);
        if (id > 0 && random().nextInt(100) == 42) {
            int idToDelete = random().nextInt(id);
            w.deleteDocuments(new Term("id", "" + idToDelete));
            deleted.add(idToDelete);
            if (VERBOSE) {
                System.out.println("  delete id=" + idToDelete);
            }
        }
    }
    if (random().nextBoolean()) {
        w.forceMerge(1);
    }
    final IndexReader r = DirectoryReader.open(w);
    w.close();
    // We can't wrap with "exotic" readers because points needs to work:
    IndexSearcher s = newSearcher(r);
    final int iters = atLeast(75);
    Bits liveDocs = MultiFields.getLiveDocs(s.getIndexReader());
    int maxDoc = s.getIndexReader().maxDoc();
    for (int iter = 0; iter < iters; iter++) {
        if (VERBOSE) {
            System.out.println("\nTEST: iter=" + iter + " s=" + s);
        }
        // Polygon
        Polygon polygon = nextPolygon();
        Query query = newPolygonQuery(FIELD_NAME, polygon);
        if (VERBOSE) {
            System.out.println("  query=" + query);
        }
        final FixedBitSet hits = new FixedBitSet(maxDoc);
        s.search(query, new SimpleCollector() {

            private int docBase;

            @Override
            public boolean needsScores() {
                return false;
            }

            @Override
            protected void doSetNextReader(LeafReaderContext context) throws IOException {
                docBase = context.docBase;
            }

            @Override
            public void collect(int doc) {
                hits.set(docBase + doc);
            }
        });
        boolean fail = false;
        NumericDocValues docIDToID = MultiDocValues.getNumericValues(r, "id");
        for (int docID = 0; docID < maxDoc; docID++) {
            assertEquals(docID, docIDToID.nextDoc());
            int id = (int) docIDToID.longValue();
            boolean expected;
            if (liveDocs != null && liveDocs.get(docID) == false) {
                // document is deleted
                expected = false;
            } else if (Double.isNaN(lats[id])) {
                expected = false;
            } else {
                expected = GeoTestUtil.containsSlowly(polygon, lats[id], lons[id]);
            }
            if (hits.get(docID) != expected) {
                StringBuilder b = new StringBuilder();
                if (expected) {
                    b.append("FAIL: id=" + id + " should match but did not\n");
                } else {
                    b.append("FAIL: id=" + id + " should not match but did\n");
                }
                b.append("  query=" + query + " docID=" + docID + "\n");
                b.append("  lat=" + lats[id] + " lon=" + lons[id] + "\n");
                b.append("  deleted?=" + (liveDocs != null && liveDocs.get(docID) == false));
                b.append("  polygon=" + polygon);
                if (true) {
                    fail("wrong hit (first of possibly more):\n\n" + b);
                } else {
                    System.out.println(b.toString());
                    fail = true;
                }
            }
        }
        if (fail) {
            fail("some hits were wrong");
        }
    }
    IOUtils.close(r, dir);
}

Example 97 with RandomIndexWriter

use of org.apache.lucene.index.RandomIndexWriter in project lucene-solr by apache.

the class TestLTRScoringQuery method testLTRScoringQuery.

@Test
public void testLTRScoringQuery() throws IOException, ModelException {
    final Directory dir = newDirectory();
    final RandomIndexWriter w = new RandomIndexWriter(random(), dir);
    Document doc = new Document();
    doc.add(newStringField("id", "0", Field.Store.YES));
    doc.add(newTextField("field", "wizard the the the the the oz", Field.Store.NO));
    doc.add(new FloatDocValuesField("final-score", 1.0f));
    w.addDocument(doc);
    doc = new Document();
    doc.add(newStringField("id", "1", Field.Store.YES));
    // 1 extra token, but wizard and oz are close;
    doc.add(newTextField("field", "wizard oz the the the the the the", Field.Store.NO));
    doc.add(new FloatDocValuesField("final-score", 2.0f));
    w.addDocument(doc);
    final IndexReader r = w.getReader();
    w.close();
    // Do ordinary BooleanQuery:
    final BooleanQuery.Builder bqBuilder = new BooleanQuery.Builder();
    bqBuilder.add(new TermQuery(new Term("field", "wizard")), BooleanClause.Occur.SHOULD);
    bqBuilder.add(new TermQuery(new Term("field", "oz")), BooleanClause.Occur.SHOULD);
    final IndexSearcher searcher = getSearcher(r);
    // first run the standard query
    final TopDocs hits = searcher.search(bqBuilder.build(), 10);
    assertEquals(2, hits.totalHits);
    assertEquals("0", searcher.doc(hits.scoreDocs[0].doc).get("id"));
    assertEquals("1", searcher.doc(hits.scoreDocs[1].doc).get("id"));
    List<Feature> features = makeFeatures(new int[] { 0, 1, 2 });
    final List<Feature> allFeatures = makeFeatures(new int[] { 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 });
    List<Normalizer> norms = new ArrayList<Normalizer>(Collections.nCopies(features.size(), IdentityNormalizer.INSTANCE));
    LTRScoringModel ltrScoringModel = TestLinearModel.createLinearModel("test", features, norms, "test", allFeatures, makeFeatureWeights(features));
    LTRScoringQuery.ModelWeight modelWeight = performQuery(hits, searcher, hits.scoreDocs[0].doc, new LTRScoringQuery(ltrScoringModel));
    assertEquals(3, modelWeight.getModelFeatureValuesNormalized().length);
    for (int i = 0; i < 3; i++) {
        assertEquals(i, modelWeight.getModelFeatureValuesNormalized()[i], 0.0001);
    }
    int[] posVals = new int[] { 0, 1, 2 };
    int pos = 0;
    for (LTRScoringQuery.FeatureInfo fInfo : modelWeight.getFeaturesInfo()) {
        if (fInfo == null) {
            continue;
        }
        assertEquals(posVals[pos], fInfo.getValue(), 0.0001);
        assertEquals("f" + posVals[pos], fInfo.getName());
        pos++;
    }
    final int[] mixPositions = new int[] { 8, 2, 4, 9, 0 };
    features = makeFeatures(mixPositions);
    norms = new ArrayList<Normalizer>(Collections.nCopies(features.size(), IdentityNormalizer.INSTANCE));
    ltrScoringModel = TestLinearModel.createLinearModel("test", features, norms, "test", allFeatures, makeFeatureWeights(features));
    modelWeight = performQuery(hits, searcher, hits.scoreDocs[0].doc, new LTRScoringQuery(ltrScoringModel));
    assertEquals(mixPositions.length, modelWeight.getModelFeatureWeights().length);
    for (int i = 0; i < mixPositions.length; i++) {
        assertEquals(mixPositions[i], modelWeight.getModelFeatureValuesNormalized()[i], 0.0001);
    }
    final ModelException expectedModelException = new ModelException("no features declared for model test");
    final int[] noPositions = new int[] {};
    features = makeFeatures(noPositions);
    norms = new ArrayList<Normalizer>(Collections.nCopies(features.size(), IdentityNormalizer.INSTANCE));
    try {
        ltrScoringModel = TestLinearModel.createLinearModel("test", features, norms, "test", allFeatures, makeFeatureWeights(features));
        fail("unexpectedly got here instead of catching " + expectedModelException);
        modelWeight = performQuery(hits, searcher, hits.scoreDocs[0].doc, new LTRScoringQuery(ltrScoringModel));
        assertEquals(0, modelWeight.getModelFeatureWeights().length);
    } catch (ModelException actualModelException) {
        assertEquals(expectedModelException.toString(), actualModelException.toString());
    }
    // test normalizers
    features = makeFilterFeatures(mixPositions);
    final Normalizer norm = new Normalizer() {

        @Override
        public float normalize(float value) {
            return 42.42f;
        }

        @Override
        public LinkedHashMap<String, Object> paramsToMap() {
            return null;
        }

        @Override
        protected void validate() throws NormalizerException {
        }
    };
    norms = new ArrayList<Normalizer>(Collections.nCopies(features.size(), norm));
    final LTRScoringModel normMeta = TestLinearModel.createLinearModel("test", features, norms, "test", allFeatures, makeFeatureWeights(features));
    modelWeight = performQuery(hits, searcher, hits.scoreDocs[0].doc, new LTRScoringQuery(normMeta));
    normMeta.normalizeFeaturesInPlace(modelWeight.getModelFeatureValuesNormalized());
    assertEquals(mixPositions.length, modelWeight.getModelFeatureWeights().length);
    for (int i = 0; i < mixPositions.length; i++) {
        assertEquals(42.42f, modelWeight.getModelFeatureValuesNormalized()[i], 0.0001);
    }
    r.close();
    dir.close();
}

Example 98 with RandomIndexWriter

use of org.apache.lucene.index.RandomIndexWriter in project lucene-solr by apache.

the class TestLTRReRankingPipeline method testDifferentTopN.

@Ignore
@Test
public void testDifferentTopN() throws IOException {
    final Directory dir = newDirectory();
    final RandomIndexWriter w = new RandomIndexWriter(random(), dir);
    Document doc = new Document();
    doc.add(newStringField("id", "0", Field.Store.YES));
    doc.add(newTextField("field", "wizard oz oz oz oz oz", Field.Store.NO));
    doc.add(new FloatDocValuesField("final-score", 1.0f));
    w.addDocument(doc);
    doc = new Document();
    doc.add(newStringField("id", "1", Field.Store.YES));
    doc.add(newTextField("field", "wizard oz oz oz oz the", Field.Store.NO));
    doc.add(new FloatDocValuesField("final-score", 2.0f));
    w.addDocument(doc);
    doc = new Document();
    doc.add(newStringField("id", "2", Field.Store.YES));
    doc.add(newTextField("field", "wizard oz oz oz the the ", Field.Store.NO));
    doc.add(new FloatDocValuesField("final-score", 3.0f));
    w.addDocument(doc);
    doc = new Document();
    doc.add(newStringField("id", "3", Field.Store.YES));
    doc.add(newTextField("field", "wizard oz oz the the the the ", Field.Store.NO));
    doc.add(new FloatDocValuesField("final-score", 4.0f));
    w.addDocument(doc);
    doc = new Document();
    doc.add(newStringField("id", "4", Field.Store.YES));
    doc.add(newTextField("field", "wizard oz the the the the the the", Field.Store.NO));
    doc.add(new FloatDocValuesField("final-score", 5.0f));
    w.addDocument(doc);
    final IndexReader r = w.getReader();
    w.close();
    // Do ordinary BooleanQuery:
    final BooleanQuery.Builder bqBuilder = new BooleanQuery.Builder();
    bqBuilder.add(new TermQuery(new Term("field", "wizard")), BooleanClause.Occur.SHOULD);
    bqBuilder.add(new TermQuery(new Term("field", "oz")), BooleanClause.Occur.SHOULD);
    final IndexSearcher searcher = getSearcher(r);
    // first run the standard query
    TopDocs hits = searcher.search(bqBuilder.build(), 10);
    assertEquals(5, hits.totalHits);
    assertEquals("0", searcher.doc(hits.scoreDocs[0].doc).get("id"));
    assertEquals("1", searcher.doc(hits.scoreDocs[1].doc).get("id"));
    assertEquals("2", searcher.doc(hits.scoreDocs[2].doc).get("id"));
    assertEquals("3", searcher.doc(hits.scoreDocs[3].doc).get("id"));
    assertEquals("4", searcher.doc(hits.scoreDocs[4].doc).get("id"));
    final List<Feature> features = makeFieldValueFeatures(new int[] { 0, 1, 2 }, "final-score");
    final List<Normalizer> norms = new ArrayList<Normalizer>(Collections.nCopies(features.size(), IdentityNormalizer.INSTANCE));
    final List<Feature> allFeatures = makeFieldValueFeatures(new int[] { 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 }, "final-score");
    final LTRScoringModel ltrScoringModel = TestLinearModel.createLinearModel("test", features, norms, "test", allFeatures, null);
    final LTRRescorer rescorer = new LTRRescorer(new LTRScoringQuery(ltrScoringModel));
    // rerank @ 0 should not change the order
    hits = rescorer.rescore(searcher, hits, 0);
    assertEquals("0", searcher.doc(hits.scoreDocs[0].doc).get("id"));
    assertEquals("1", searcher.doc(hits.scoreDocs[1].doc).get("id"));
    assertEquals("2", searcher.doc(hits.scoreDocs[2].doc).get("id"));
    assertEquals("3", searcher.doc(hits.scoreDocs[3].doc).get("id"));
    assertEquals("4", searcher.doc(hits.scoreDocs[4].doc).get("id"));
    for (int topN = 1; topN <= 5; topN++) {
        log.info("rerank {} documents ", topN);
        hits = searcher.search(bqBuilder.build(), 10);
        final ScoreDoc[] slice = new ScoreDoc[topN];
        System.arraycopy(hits.scoreDocs, 0, slice, 0, topN);
        hits = new TopDocs(hits.totalHits, slice, hits.getMaxScore());
        hits = rescorer.rescore(searcher, hits, topN);
        for (int i = topN - 1, j = 0; i >= 0; i--, j++) {
            log.info("doc {} in pos {}", searcher.doc(hits.scoreDocs[j].doc).get("id"), j);
            assertEquals(i, Integer.parseInt(searcher.doc(hits.scoreDocs[j].doc).get("id")));
            assertEquals(i + 1, hits.scoreDocs[j].score, 0.00001);
        }
    }
    r.close();
    dir.close();
}

Example 99 with RandomIndexWriter

use of org.apache.lucene.index.RandomIndexWriter in project lucene-solr by apache.

the class TestBooleanSimilarity method testPhraseScoreIsEqualToBoost.

public void testPhraseScoreIsEqualToBoost() throws IOException {
    Directory dir = newDirectory();
    RandomIndexWriter w = new RandomIndexWriter(random(), dir, newIndexWriterConfig().setSimilarity(new BooleanSimilarity()));
    Document doc = new Document();
    doc.add(new TextField("foo", "bar baz quux", Store.NO));
    w.addDocument(doc);
    DirectoryReader reader = w.getReader();
    w.close();
    IndexSearcher searcher = newSearcher(reader);
    searcher.setSimilarity(new BooleanSimilarity());
    PhraseQuery query = new PhraseQuery(2, "foo", "bar", "quux");
    TopDocs topDocs = searcher.search(query, 2);
    assertEquals(1, topDocs.totalHits);
    assertEquals(1f, topDocs.scoreDocs[0].score, 0f);
    topDocs = searcher.search(new BoostQuery(query, 7), 2);
    assertEquals(1, topDocs.totalHits);
    assertEquals(7f, topDocs.scoreDocs[0].score, 0f);
    reader.close();
    dir.close();
}

Example 100 with RandomIndexWriter

use of org.apache.lucene.index.RandomIndexWriter in project lucene-solr by apache.

the class TestDrillSideways method testBasic.

public void testBasic() throws Exception {
    Directory dir = newDirectory();
    Directory taxoDir = newDirectory();
    // Writes facet ords to a separate directory from the
    // main index:
    DirectoryTaxonomyWriter taxoWriter = new DirectoryTaxonomyWriter(taxoDir, IndexWriterConfig.OpenMode.CREATE);
    FacetsConfig config = new FacetsConfig();
    config.setHierarchical("Publish Date", true);
    RandomIndexWriter writer = new RandomIndexWriter(random(), dir);
    Document doc = new Document();
    doc.add(new FacetField("Author", "Bob"));
    doc.add(new FacetField("Publish Date", "2010", "10", "15"));
    writer.addDocument(config.build(taxoWriter, doc));
    doc = new Document();
    doc.add(new FacetField("Author", "Lisa"));
    doc.add(new FacetField("Publish Date", "2010", "10", "20"));
    writer.addDocument(config.build(taxoWriter, doc));
    doc = new Document();
    doc.add(new FacetField("Author", "Lisa"));
    doc.add(new FacetField("Publish Date", "2012", "1", "1"));
    writer.addDocument(config.build(taxoWriter, doc));
    doc = new Document();
    doc.add(new FacetField("Author", "Susan"));
    doc.add(new FacetField("Publish Date", "2012", "1", "7"));
    writer.addDocument(config.build(taxoWriter, doc));
    doc = new Document();
    doc.add(new FacetField("Author", "Frank"));
    doc.add(new FacetField("Publish Date", "1999", "5", "5"));
    writer.addDocument(config.build(taxoWriter, doc));
    // NRT open
    IndexSearcher searcher = newSearcher(writer.getReader());
    //System.out.println("searcher=" + searcher);
    // NRT open
    TaxonomyReader taxoReader = new DirectoryTaxonomyReader(taxoWriter);
    DrillSideways ds = getNewDrillSideways(searcher, config, taxoReader);
    //  case: drill-down on a single field; in this
    // case the drill-sideways + drill-down counts ==
    // drill-down of just the query:
    DrillDownQuery ddq = new DrillDownQuery(config);
    ddq.add("Author", "Lisa");
    DrillSidewaysResult r = ds.search(null, ddq, 10);
    assertEquals(2, r.hits.totalHits);
    // Publish Date is only drill-down, and Lisa published
    // one in 2012 and one in 2010:
    assertEquals("dim=Publish Date path=[] value=2 childCount=2\n  2010 (1)\n  2012 (1)\n", r.facets.getTopChildren(10, "Publish Date").toString());
    // Author is drill-sideways + drill-down: Lisa
    // (drill-down) published twice, and Frank/Susan/Bob
    // published once:
    assertEquals("dim=Author path=[] value=5 childCount=4\n  Lisa (2)\n  Bob (1)\n  Susan (1)\n  Frank (1)\n", r.facets.getTopChildren(10, "Author").toString());
    // Same simple case, but no baseQuery (pure browse):
    // drill-down on a single field; in this case the
    // drill-sideways + drill-down counts == drill-down of
    // just the query:
    ddq = new DrillDownQuery(config);
    ddq.add("Author", "Lisa");
    r = ds.search(null, ddq, 10);
    assertEquals(2, r.hits.totalHits);
    // Publish Date is only drill-down, and Lisa published
    // one in 2012 and one in 2010:
    assertEquals("dim=Publish Date path=[] value=2 childCount=2\n  2010 (1)\n  2012 (1)\n", r.facets.getTopChildren(10, "Publish Date").toString());
    // Author is drill-sideways + drill-down: Lisa
    // (drill-down) published twice, and Frank/Susan/Bob
    // published once:
    assertEquals("dim=Author path=[] value=5 childCount=4\n  Lisa (2)\n  Bob (1)\n  Susan (1)\n  Frank (1)\n", r.facets.getTopChildren(10, "Author").toString());
    // Another simple case: drill-down on single fields
    // but OR of two values
    ddq = new DrillDownQuery(config);
    ddq.add("Author", "Lisa");
    ddq.add("Author", "Bob");
    r = ds.search(null, ddq, 10);
    assertEquals(3, r.hits.totalHits);
    // Publish Date is only drill-down: Lisa and Bob
    // (drill-down) published twice in 2010 and once in 2012:
    assertEquals("dim=Publish Date path=[] value=3 childCount=2\n  2010 (2)\n  2012 (1)\n", r.facets.getTopChildren(10, "Publish Date").toString());
    // Author is drill-sideways + drill-down: Lisa
    // (drill-down) published twice, and Frank/Susan/Bob
    // published once:
    assertEquals("dim=Author path=[] value=5 childCount=4\n  Lisa (2)\n  Bob (1)\n  Susan (1)\n  Frank (1)\n", r.facets.getTopChildren(10, "Author").toString());
    assertTrue(r.facets instanceof MultiFacets);
    List<FacetResult> allResults = r.facets.getAllDims(10);
    assertEquals(2, allResults.size());
    assertEquals("dim=Author path=[] value=5 childCount=4\n  Lisa (2)\n  Bob (1)\n  Susan (1)\n  Frank (1)\n", allResults.get(0).toString());
    assertEquals("dim=Publish Date path=[] value=3 childCount=2\n  2010 (2)\n  2012 (1)\n", allResults.get(1).toString());
    // More interesting case: drill-down on two fields
    ddq = new DrillDownQuery(config);
    ddq.add("Author", "Lisa");
    ddq.add("Publish Date", "2010");
    r = ds.search(null, ddq, 10);
    assertEquals(1, r.hits.totalHits);
    // Publish Date is drill-sideways + drill-down: Lisa
    // (drill-down) published once in 2010 and once in 2012:
    assertEquals("dim=Publish Date path=[] value=2 childCount=2\n  2010 (1)\n  2012 (1)\n", r.facets.getTopChildren(10, "Publish Date").toString());
    // Author is drill-sideways + drill-down:
    // only Lisa & Bob published (once each) in 2010:
    assertEquals("dim=Author path=[] value=2 childCount=2\n  Bob (1)\n  Lisa (1)\n", r.facets.getTopChildren(10, "Author").toString());
    // Even more interesting case: drill down on two fields,
    // but one of them is OR
    ddq = new DrillDownQuery(config);
    // Drill down on Lisa or Bob:
    ddq.add("Author", "Lisa");
    ddq.add("Publish Date", "2010");
    ddq.add("Author", "Bob");
    r = ds.search(null, ddq, 10);
    assertEquals(2, r.hits.totalHits);
    // Publish Date is both drill-sideways + drill-down:
    // Lisa or Bob published twice in 2010 and once in 2012:
    assertEquals("dim=Publish Date path=[] value=3 childCount=2\n  2010 (2)\n  2012 (1)\n", r.facets.getTopChildren(10, "Publish Date").toString());
    // Author is drill-sideways + drill-down:
    // only Lisa & Bob published (once each) in 2010:
    assertEquals("dim=Author path=[] value=2 childCount=2\n  Bob (1)\n  Lisa (1)\n", r.facets.getTopChildren(10, "Author").toString());
    // Test drilling down on invalid field:
    ddq = new DrillDownQuery(config);
    ddq.add("Foobar", "Baz");
    r = ds.search(null, ddq, 10);
    assertEquals(0, r.hits.totalHits);
    assertNull(r.facets.getTopChildren(10, "Publish Date"));
    assertNull(r.facets.getTopChildren(10, "Foobar"));
    // Test drilling down on valid term or'd with invalid term:
    ddq = new DrillDownQuery(config);
    ddq.add("Author", "Lisa");
    ddq.add("Author", "Tom");
    r = ds.search(null, ddq, 10);
    assertEquals(2, r.hits.totalHits);
    // Publish Date is only drill-down, and Lisa published
    // one in 2012 and one in 2010:
    assertEquals("dim=Publish Date path=[] value=2 childCount=2\n  2010 (1)\n  2012 (1)\n", r.facets.getTopChildren(10, "Publish Date").toString());
    // Author is drill-sideways + drill-down: Lisa
    // (drill-down) published twice, and Frank/Susan/Bob
    // published once:
    assertEquals("dim=Author path=[] value=5 childCount=4\n  Lisa (2)\n  Bob (1)\n  Susan (1)\n  Frank (1)\n", r.facets.getTopChildren(10, "Author").toString());
    // LUCENE-4915: test drilling down on a dimension but
    // NOT facet counting it:
    ddq = new DrillDownQuery(config);
    ddq.add("Author", "Lisa");
    ddq.add("Author", "Tom");
    r = ds.search(null, ddq, 10);
    assertEquals(2, r.hits.totalHits);
    // Publish Date is only drill-down, and Lisa published
    // one in 2012 and one in 2010:
    assertEquals("dim=Publish Date path=[] value=2 childCount=2\n  2010 (1)\n  2012 (1)\n", r.facets.getTopChildren(10, "Publish Date").toString());
    // Test main query gets null scorer:
    ddq = new DrillDownQuery(config, new TermQuery(new Term("foobar", "baz")));
    ddq.add("Author", "Lisa");
    r = ds.search(null, ddq, 10);
    assertEquals(0, r.hits.totalHits);
    assertNull(r.facets.getTopChildren(10, "Publish Date"));
    assertNull(r.facets.getTopChildren(10, "Author"));
    writer.close();
    IOUtils.close(searcher.getIndexReader(), taxoReader, taxoWriter, dir, taxoDir);
}