mirror of https://github.com/apache/lucene.git
merged with trunk
git-svn-id: https://svn.apache.org/repos/asf/lucene/dev/branches/LUCENE2793@1144189 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
commit
feb9739bf7
|
@ -156,6 +156,12 @@ Changes in backwards compatibility policy
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the queries module and can be found at o.a.l.queries.function. See MIGRATE.txt
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for more information (Chris Male)
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* LUCENE-2392: Decoupled vector space scoring from Query/Weight/Scorer. If you
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extended Similarity directly before, you should extend TFIDFSimilarity instead.
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Similarity is now a lower-level API to implement other scoring algorithms.
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See MIGRATE.txt for more details.
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(David Nemeskey, Simon Willnauer, Mike Mccandless, Robert Muir)
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Changes in Runtime Behavior
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* LUCENE-2846: omitNorms now behaves like omitTermFrequencyAndPositions, if you
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@ -382,3 +382,13 @@ LUCENE-1458, LUCENE-2111: Flexible Indexing
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- o.a.l.search.function.ShortFieldSource -> o.a.l.queries.function.valuesource.ShortFieldSource
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- o.a.l.search.function.ValueSource -> o.a.l.queries.function.ValueSource
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- o.a.l.search.function.ValueSourceQuery -> o.a.l.queries.function.FunctionQuery
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* LUCENE-2392: Enable flexible scoring:
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The existing "Similarity" api is now TFIDFSimilarity, if you were extending
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Similarity before, you should likely extend this instead.
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Weight.normalize no longer takes a norm value that incorporates the top-level
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boost from outer queries such as BooleanQuery, instead it takes 2 parameters,
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the outer boost (topLevelBoost) and the norm. Weight.sumOfSquaredWeights has
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been renamed to Weight.getValueForNormalization().
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@ -331,7 +331,7 @@
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<artifact:deploy file="${build.dir}/${maven.project.build.finalName}.jar">
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<artifact-attachments/>
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<remoteRepository url="${m2.repository.url}">
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<authentication username="${m2.repository.username}" privateKey="${m2.repository.private.key}"/>
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<authentication username="${m2.repository.username}" privateKey="${m2.repository.private.key}" password="${m2.repository.password}"/>
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</remoteRepository>
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<pom refid="maven.project"/>
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</artifact:deploy>
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@ -351,7 +351,7 @@
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<artifact:pom id="maven.project" file="${maven.build.dir}/@{pom.xml}" />
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<artifact:deploy file="@{jar.file}">
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<remoteRepository url="${m2.repository.url}">
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<authentication username="${m2.repository.username}" privateKey="${m2.repository.private.key}"/>
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<authentication username="${m2.repository.username}" privateKey="${m2.repository.private.key}" password="${m2.repository.password}"/>
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</remoteRepository>
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<pom refid="maven.project"/>
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</artifact:deploy>
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|
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@ -240,8 +240,7 @@ public class InstantiatedIndexWriter implements Closeable {
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final FieldInvertState invertState = new FieldInvertState();
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invertState.setBoost(eFieldTermDocInfoFactoriesByTermText.getKey().boost * document.getDocument().getBoost());
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invertState.setLength(eFieldTermDocInfoFactoriesByTermText.getKey().fieldLength);
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final float norm = similarityProvider.get(fieldName).computeNorm(invertState);
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normsByFieldNameAndDocumentNumber.get(fieldName)[document.getDocumentNumber()] = similarityProvider.get(fieldName).encodeNormValue(norm);
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normsByFieldNameAndDocumentNumber.get(fieldName)[document.getDocumentNumber()] = similarityProvider.get(fieldName).computeNorm(invertState);
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} else {
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System.currentTimeMillis();
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}
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|
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@ -51,7 +51,6 @@ import org.apache.lucene.index.TermFreqVector;
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import org.apache.lucene.index.TermPositionVector;
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import org.apache.lucene.index.TermVectorMapper;
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import org.apache.lucene.index.FieldInvertState;
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import org.apache.lucene.index.IndexReader.ReaderContext;
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import org.apache.lucene.index.codecs.PerDocValues;
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import org.apache.lucene.search.Collector;
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import org.apache.lucene.search.IndexSearcher;
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@ -1202,15 +1201,14 @@ public class MemoryIndex {
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int numOverlapTokens = info != null ? info.numOverlapTokens : 0;
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float boost = info != null ? info.getBoost() : 1.0f;
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FieldInvertState invertState = new FieldInvertState(0, numTokens, numOverlapTokens, 0, boost);
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float n = fieldSim.computeNorm(invertState);
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byte norm = fieldSim.encodeNormValue(n);
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byte norm = fieldSim.computeNorm(invertState);
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norms = new byte[] {norm};
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// cache it for future reuse
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cachedNorms = norms;
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cachedFieldName = fieldName;
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cachedSimilarity = sim;
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if (DEBUG) System.err.println("MemoryIndexReader.norms: " + fieldName + ":" + n + ":" + norm + ":" + numTokens);
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if (DEBUG) System.err.println("MemoryIndexReader.norms: " + fieldName + ":" + norm + ":" + numTokens);
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}
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return norms;
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}
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|
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@ -147,7 +147,7 @@ public class FieldNormModifier {
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for (int d = 0; d < termCounts.length; d++) {
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if (liveDocs == null || liveDocs.get(d)) {
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invertState.setLength(termCounts[d]);
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subReader.setNorm(d, field, fieldSim.encodeNormValue(fieldSim.computeNorm(invertState)));
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subReader.setNorm(d, field, fieldSim.computeNorm(invertState));
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}
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}
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}
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@ -25,7 +25,6 @@ import org.apache.lucene.index.SegmentInfo;
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import org.apache.lucene.index.SegmentReadState;
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import org.apache.lucene.index.SegmentWriteState;
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import org.apache.lucene.index.codecs.Codec;
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import org.apache.lucene.index.codecs.DocValuesConsumer;
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import org.apache.lucene.index.codecs.DefaultDocValuesProducer;
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import org.apache.lucene.index.codecs.FieldsConsumer;
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import org.apache.lucene.index.codecs.FieldsProducer;
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@ -58,7 +57,7 @@ public class AppendingCodec extends Codec {
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public static String CODEC_NAME = "Appending";
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public AppendingCodec() {
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name = CODEC_NAME;
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super(CODEC_NAME);
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}
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@Override
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|
@ -138,22 +137,22 @@ public class AppendingCodec extends Codec {
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StandardPostingsReader.files(dir, segmentInfo, codecId, files);
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BlockTermsReader.files(dir, segmentInfo, codecId, files);
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FixedGapTermsIndexReader.files(dir, segmentInfo, codecId, files);
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DefaultDocValuesConsumer.files(dir, segmentInfo, codecId, files);
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DefaultDocValuesConsumer.files(dir, segmentInfo, codecId, files, getDocValuesUseCFS());
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}
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@Override
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public void getExtensions(Set<String> extensions) {
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StandardCodec.getStandardExtensions(extensions);
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DefaultDocValuesConsumer.getDocValuesExtensions(extensions);
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DefaultDocValuesConsumer.getDocValuesExtensions(extensions, getDocValuesUseCFS());
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}
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@Override
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public PerDocConsumer docsConsumer(PerDocWriteState state) throws IOException {
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return new DefaultDocValuesConsumer(state, BytesRef.getUTF8SortedAsUnicodeComparator());
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return new DefaultDocValuesConsumer(state, getDocValuesSortComparator(), getDocValuesUseCFS());
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}
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@Override
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public PerDocValues docsProducer(SegmentReadState state) throws IOException {
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return new DefaultDocValuesProducer(state.segmentInfo, state.dir, state.fieldInfos, state.codecId, state.context);
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return new DefaultDocValuesProducer(state.segmentInfo, state.dir, state.fieldInfos, state.codecId, getDocValuesUseCFS(), getDocValuesSortComparator(), state.context);
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}
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}
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@ -106,7 +106,7 @@ public class SweetSpotSimilarity extends DefaultSimilarity {
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* discountOverlaps is true by default or true for this
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* specific field. */
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@Override
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public float computeNorm(FieldInvertState state) {
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public byte computeNorm(FieldInvertState state) {
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final int numTokens;
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if (discountOverlaps)
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@ -114,7 +114,7 @@ public class SweetSpotSimilarity extends DefaultSimilarity {
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else
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numTokens = state.getLength();
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return state.getBoost() * computeLengthNorm(numTokens);
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return encodeNormValue(state.getBoost() * computeLengthNorm(numTokens));
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}
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/**
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|
|
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@ -70,7 +70,7 @@ public class WindowsDirectory extends FSDirectory {
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@Override
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public IndexInput openInput(String name, IOContext context) throws IOException {
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ensureOpen();
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return new WindowsIndexInput(new File(getDirectory(), name), DEFAULT_BUFFERSIZE);
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return new WindowsIndexInput(new File(getDirectory(), name), Math.max(BufferedIndexInput.bufferSize(context), DEFAULT_BUFFERSIZE));
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}
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protected static class WindowsIndexInput extends BufferedIndexInput {
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|
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@ -49,8 +49,8 @@ public class TestFieldNormModifier extends LuceneTestCase {
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public Similarity get(String field) {
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return new DefaultSimilarity() {
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@Override
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public float computeNorm(FieldInvertState state) {
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return state.getBoost() * (discountOverlaps ? state.getLength() - state.getNumOverlap() : state.getLength());
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public byte computeNorm(FieldInvertState state) {
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return encodeNormValue(state.getBoost() * (discountOverlaps ? state.getLength() - state.getNumOverlap() : state.getLength()));
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}
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};
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}
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|
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@ -21,6 +21,7 @@ package org.apache.lucene.misc;
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import org.apache.lucene.search.DefaultSimilarity;
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import org.apache.lucene.search.DefaultSimilarityProvider;
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import org.apache.lucene.search.Similarity;
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import org.apache.lucene.search.TFIDFSimilarity;
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import org.apache.lucene.search.SimilarityProvider;
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import org.apache.lucene.util.LuceneTestCase;
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import org.apache.lucene.index.FieldInvertState;
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|
@ -58,15 +59,15 @@ public class SweetSpotSimilarityTest extends LuceneTestCase {
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invertState.setLength(i);
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assertEquals("3,10: spot i="+i,
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1.0f,
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s.computeNorm(invertState),
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ss.decodeNormValue(s.computeNorm(invertState)),
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0.0f);
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}
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for (int i = 10; i < 1000; i++) {
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invertState.setLength(i-9);
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final float normD = d.computeNorm(invertState);
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final byte normD = d.computeNorm(invertState);
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invertState.setLength(i);
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final float normS = s.computeNorm(invertState);
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final byte normS = s.computeNorm(invertState);
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assertEquals("3,10: 10<x : i="+i,
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normD,
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normS,
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@ -104,14 +105,14 @@ public class SweetSpotSimilarityTest extends LuceneTestCase {
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invertState.setLength(i);
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assertEquals("f: 3,10: spot i="+i,
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1.0f,
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sp.get("foo").computeNorm(invertState),
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ss.decodeNormValue(sp.get("foo").computeNorm(invertState)),
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0.0f);
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}
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for (int i = 10; i < 1000; i++) {
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invertState.setLength(i-9);
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final float normD = d.computeNorm(invertState);
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final byte normD = d.computeNorm(invertState);
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invertState.setLength(i);
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final float normS = sp.get("foo").computeNorm(invertState);
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final byte normS = sp.get("foo").computeNorm(invertState);
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assertEquals("f: 3,10: 10<x : i="+i,
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normD,
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normS,
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|
@ -121,21 +122,21 @@ public class SweetSpotSimilarityTest extends LuceneTestCase {
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|||
invertState.setLength(i);
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assertEquals("f: 8,13: spot i="+i,
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1.0f,
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sp.get("bar").computeNorm(invertState),
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ss.decodeNormValue(sp.get("bar").computeNorm(invertState)),
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0.0f);
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}
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for (int i = 6; i <=9; i++) {
|
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invertState.setLength(i);
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||||
assertEquals("f: 6,9: spot i="+i,
|
||||
1.0f,
|
||||
sp.get("yak").computeNorm(invertState),
|
||||
ss.decodeNormValue(sp.get("yak").computeNorm(invertState)),
|
||||
0.0f);
|
||||
}
|
||||
for (int i = 13; i < 1000; i++) {
|
||||
invertState.setLength(i-12);
|
||||
final float normD = d.computeNorm(invertState);
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final byte normD = d.computeNorm(invertState);
|
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invertState.setLength(i);
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final float normS = sp.get("bar").computeNorm(invertState);
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||||
final byte normS = sp.get("bar").computeNorm(invertState);
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assertEquals("f: 8,13: 13<x : i="+i,
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||||
normD,
|
||||
normS,
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||||
|
@ -143,9 +144,9 @@ public class SweetSpotSimilarityTest extends LuceneTestCase {
|
|||
}
|
||||
for (int i = 9; i < 1000; i++) {
|
||||
invertState.setLength(i-8);
|
||||
final float normD = d.computeNorm(invertState);
|
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final byte normD = d.computeNorm(invertState);
|
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invertState.setLength(i);
|
||||
final float normS = sp.get("yak").computeNorm(invertState);
|
||||
final byte normS = sp.get("yak").computeNorm(invertState);
|
||||
assertEquals("f: 6,9: 9<x : i="+i,
|
||||
normD,
|
||||
normS,
|
||||
|
@ -157,8 +158,8 @@ public class SweetSpotSimilarityTest extends LuceneTestCase {
|
|||
|
||||
for (int i = 9; i < 1000; i++) {
|
||||
invertState.setLength(i);
|
||||
final float normSS = sp.get("a").computeNorm(invertState);
|
||||
final float normS = sp.get("b").computeNorm(invertState);
|
||||
final byte normSS = sp.get("a").computeNorm(invertState);
|
||||
final byte normS = sp.get("b").computeNorm(invertState);
|
||||
assertTrue("s: i="+i+" : a="+normSS+
|
||||
" < b="+normS,
|
||||
normSS < normS);
|
||||
|
@ -170,8 +171,8 @@ public class SweetSpotSimilarityTest extends LuceneTestCase {
|
|||
|
||||
SweetSpotSimilarity ss = new SweetSpotSimilarity();
|
||||
|
||||
Similarity d = new DefaultSimilarity();
|
||||
Similarity s = ss;
|
||||
TFIDFSimilarity d = new DefaultSimilarity();
|
||||
TFIDFSimilarity s = ss;
|
||||
|
||||
// tf equal
|
||||
|
||||
|
@ -222,7 +223,7 @@ public class SweetSpotSimilarityTest extends LuceneTestCase {
|
|||
};
|
||||
ss.setHyperbolicTfFactors(3.3f, 7.7f, Math.E, 5.0f);
|
||||
|
||||
Similarity s = ss;
|
||||
TFIDFSimilarity s = ss;
|
||||
|
||||
for (int i = 1; i <=1000; i++) {
|
||||
assertTrue("MIN tf: i="+i+" : s="+s.tf(i),
|
||||
|
|
|
@ -54,8 +54,8 @@ public class TestLengthNormModifier extends LuceneTestCase {
|
|||
public Similarity get(String field) {
|
||||
return new DefaultSimilarity() {
|
||||
@Override
|
||||
public float computeNorm(FieldInvertState state) {
|
||||
return state.getBoost() * (discountOverlaps ? state.getLength() - state.getNumOverlap() : state.getLength());
|
||||
public byte computeNorm(FieldInvertState state) {
|
||||
return encodeNormValue(state.getBoost() * (discountOverlaps ? state.getLength() - state.getNumOverlap() : state.getLength()));
|
||||
}
|
||||
};
|
||||
}
|
||||
|
@ -175,8 +175,8 @@ public class TestLengthNormModifier extends LuceneTestCase {
|
|||
public Similarity get(String field) {
|
||||
return new DefaultSimilarity() {
|
||||
@Override
|
||||
public float computeNorm(FieldInvertState state) {
|
||||
return state.getBoost() * (discountOverlaps ? state.getLength() - state.getNumOverlap() : state.getLength());
|
||||
public byte computeNorm(FieldInvertState state) {
|
||||
return encodeNormValue(state.getBoost() * (discountOverlaps ? state.getLength() - state.getNumOverlap() : state.getLength()));
|
||||
}
|
||||
};
|
||||
}
|
||||
|
|
|
@ -51,7 +51,11 @@ import org.apache.lucene.util.PriorityQueue;
|
|||
*/
|
||||
public class FuzzyLikeThisQuery extends Query
|
||||
{
|
||||
static Similarity sim=new DefaultSimilarity();
|
||||
// TODO: generalize this query (at least it should not reuse this static sim!
|
||||
// a better way might be to convert this into multitermquery rewrite methods.
|
||||
// the rewrite method can 'average' the TermContext's term statistics (docfreq,totalTermFreq)
|
||||
// provided to TermQuery, so that the general idea is agnostic to any scoring system...
|
||||
static TFIDFSimilarity sim=new DefaultSimilarity();
|
||||
Query rewrittenQuery=null;
|
||||
ArrayList<FieldVals> fieldVals=new ArrayList<FieldVals>();
|
||||
Analyzer analyzer;
|
||||
|
|
|
@ -44,6 +44,7 @@ import org.apache.lucene.search.IndexSearcher;
|
|||
import org.apache.lucene.search.Query;
|
||||
import org.apache.lucene.search.ScoreDoc;
|
||||
import org.apache.lucene.search.Similarity;
|
||||
import org.apache.lucene.search.TFIDFSimilarity;
|
||||
import org.apache.lucene.search.TermQuery;
|
||||
import org.apache.lucene.search.TopDocs;
|
||||
import org.apache.lucene.store.FSDirectory;
|
||||
|
@ -285,7 +286,7 @@ public final class MoreLikeThis {
|
|||
/**
|
||||
* For idf() calculations.
|
||||
*/
|
||||
private Similarity similarity;// = new DefaultSimilarity();
|
||||
private TFIDFSimilarity similarity;// = new DefaultSimilarity();
|
||||
|
||||
/**
|
||||
* IndexReader to use
|
||||
|
@ -320,17 +321,17 @@ public final class MoreLikeThis {
|
|||
this(ir, new DefaultSimilarity());
|
||||
}
|
||||
|
||||
public MoreLikeThis(IndexReader ir, Similarity sim){
|
||||
public MoreLikeThis(IndexReader ir, TFIDFSimilarity sim){
|
||||
this.ir = ir;
|
||||
this.similarity = sim;
|
||||
}
|
||||
|
||||
|
||||
public Similarity getSimilarity() {
|
||||
public TFIDFSimilarity getSimilarity() {
|
||||
return similarity;
|
||||
}
|
||||
|
||||
public void setSimilarity(Similarity similarity) {
|
||||
public void setSimilarity(TFIDFSimilarity similarity) {
|
||||
this.similarity = similarity;
|
||||
}
|
||||
|
||||
|
|
|
@ -81,13 +81,13 @@ public abstract class AbstractField implements Fieldable {
|
|||
* default, in the {@link
|
||||
* org.apache.lucene.search.Similarity#computeNorm(FieldInvertState)} method, the boost value is multiplied
|
||||
* by the length normalization factor and then
|
||||
* rounded by {@link org.apache.lucene.search.Similarity#encodeNormValue(float)} before it is stored in the
|
||||
* rounded by {@link org.apache.lucene.search.DefaultSimilarity#encodeNormValue(float)} before it is stored in the
|
||||
* index. One should attempt to ensure that this product does not overflow
|
||||
* the range of that encoding.
|
||||
*
|
||||
* @see org.apache.lucene.document.Document#setBoost(float)
|
||||
* @see org.apache.lucene.search.Similarity#computeNorm(FieldInvertState)
|
||||
* @see org.apache.lucene.search.Similarity#encodeNormValue(float)
|
||||
* @see org.apache.lucene.search.DefaultSimilarity#encodeNormValue(float)
|
||||
*/
|
||||
public void setBoost(float boost) {
|
||||
this.boost = boost;
|
||||
|
|
|
@ -48,13 +48,13 @@ public interface Fieldable {
|
|||
* default, in the {@link
|
||||
* org.apache.lucene.search.Similarity#computeNorm(FieldInvertState)} method, the boost value is multiplied
|
||||
* by the length normalization factor
|
||||
* and then rounded by {@link org.apache.lucene.search.Similarity#encodeNormValue(float)} before it is stored in the
|
||||
* and then rounded by {@link org.apache.lucene.search.DefaultSimilarity#encodeNormValue(float)} before it is stored in the
|
||||
* index. One should attempt to ensure that this product does not overflow
|
||||
* the range of that encoding.
|
||||
*
|
||||
* @see org.apache.lucene.document.Document#setBoost(float)
|
||||
* @see org.apache.lucene.search.Similarity#computeNorm(FieldInvertState)
|
||||
* @see org.apache.lucene.search.Similarity#encodeNormValue(float)
|
||||
* @see org.apache.lucene.search.DefaultSimilarity#encodeNormValue(float)
|
||||
*/
|
||||
void setBoost(float boost);
|
||||
|
||||
|
|
|
@ -32,7 +32,6 @@ import org.apache.lucene.search.SimilarityProvider;
|
|||
import org.apache.lucene.store.Directory;
|
||||
import org.apache.lucene.store.FlushInfo;
|
||||
import org.apache.lucene.store.IOContext;
|
||||
import org.apache.lucene.store.IOContext.Context;
|
||||
import org.apache.lucene.util.BitVector;
|
||||
import org.apache.lucene.util.ByteBlockPool.Allocator;
|
||||
import org.apache.lucene.util.ByteBlockPool.DirectTrackingAllocator;
|
||||
|
@ -546,7 +545,7 @@ public class DocumentsWriterPerThread {
|
|||
|
||||
PerDocWriteState newPerDocWriteState(int codecId) {
|
||||
assert segment != null;
|
||||
return new PerDocWriteState(infoStream, directory, segment, fieldInfos, bytesUsed, codecId);
|
||||
return new PerDocWriteState(infoStream, directory, segment, fieldInfos, bytesUsed, codecId, IOContext.DEFAULT);
|
||||
}
|
||||
|
||||
void setInfoStream(PrintStream infoStream) {
|
||||
|
|
|
@ -31,9 +31,12 @@ import org.apache.lucene.store.Directory;
|
|||
import org.apache.lucene.store.IOContext;
|
||||
import org.apache.lucene.store.IndexInput;
|
||||
import org.apache.lucene.util.CloseableThreadLocal;
|
||||
import org.apache.lucene.util.IOUtils;
|
||||
|
||||
import java.io.Closeable;
|
||||
import java.io.IOException;
|
||||
import java.io.Reader;
|
||||
import java.util.ArrayList;
|
||||
|
||||
/**
|
||||
* Class responsible for access to stored document fields.
|
||||
|
@ -42,7 +45,7 @@ import java.io.Reader;
|
|||
*
|
||||
* @lucene.internal
|
||||
*/
|
||||
public final class FieldsReader implements Cloneable {
|
||||
public final class FieldsReader implements Cloneable, Closeable {
|
||||
private final static int FORMAT_SIZE = 4;
|
||||
|
||||
private final FieldInfos fieldInfos;
|
||||
|
@ -180,21 +183,11 @@ public final class FieldsReader implements Cloneable {
|
|||
*/
|
||||
public final void close() throws IOException {
|
||||
if (!closed) {
|
||||
if (fieldsStream != null) {
|
||||
fieldsStream.close();
|
||||
}
|
||||
if (isOriginal) {
|
||||
if (cloneableFieldsStream != null) {
|
||||
cloneableFieldsStream.close();
|
||||
}
|
||||
if (cloneableIndexStream != null) {
|
||||
cloneableIndexStream.close();
|
||||
}
|
||||
IOUtils.closeSafely(false, fieldsStream, indexStream, fieldsStreamTL, cloneableFieldsStream, cloneableIndexStream);
|
||||
} else {
|
||||
IOUtils.closeSafely(false, fieldsStream, indexStream, fieldsStreamTL);
|
||||
}
|
||||
if (indexStream != null) {
|
||||
indexStream.close();
|
||||
}
|
||||
fieldsStreamTL.close();
|
||||
closed = true;
|
||||
}
|
||||
}
|
||||
|
|
|
@ -1025,7 +1025,7 @@ public abstract class IndexReader implements Cloneable,Closeable {
|
|||
public abstract byte[] norms(String field) throws IOException;
|
||||
|
||||
/** Expert: Resets the normalization factor for the named field of the named
|
||||
* document. The norm represents the product of the field's {@link
|
||||
* document. By default, The norm represents the product of the field's {@link
|
||||
* org.apache.lucene.document.Fieldable#setBoost(float) boost} and its
|
||||
* length normalization}. Thus, to preserve the length normalization
|
||||
* values when resetting this, one should base the new value upon the old.
|
||||
|
@ -1034,7 +1034,8 @@ public abstract class IndexReader implements Cloneable,Closeable {
|
|||
* this method throws {@link IllegalStateException}.
|
||||
*
|
||||
* @see #norms(String)
|
||||
* @see Similarity#decodeNormValue(byte)
|
||||
* @see Similarity#computeNorm(FieldInvertState)
|
||||
* @see org.apache.lucene.search.DefaultSimilarity#decodeNormValue(byte)
|
||||
* @throws StaleReaderException if the index has changed
|
||||
* since this reader was opened
|
||||
* @throws CorruptIndexException if the index is corrupt
|
||||
|
|
|
@ -28,6 +28,7 @@ import org.apache.lucene.index.values.IndexDocValues;
|
|||
import org.apache.lucene.index.values.MultiIndexDocValues;
|
||||
import org.apache.lucene.index.values.ValueType;
|
||||
import org.apache.lucene.index.values.MultiIndexDocValues.DocValuesIndex;
|
||||
import org.apache.lucene.util.IOUtils;
|
||||
import org.apache.lucene.util.ReaderUtil;
|
||||
import org.apache.lucene.util.ReaderUtil.Gather;
|
||||
|
||||
|
@ -151,20 +152,7 @@ public class MultiPerDocValues extends PerDocValues {
|
|||
}
|
||||
|
||||
public void close() throws IOException {
|
||||
final PerDocValues[] perDocValues = this.subs;
|
||||
IOException ex = null;
|
||||
for (PerDocValues values : perDocValues) {
|
||||
try {
|
||||
values.close();
|
||||
} catch (IOException e) {
|
||||
if (ex == null) {
|
||||
ex = e;
|
||||
}
|
||||
}
|
||||
}
|
||||
if (ex != null) {
|
||||
throw ex;
|
||||
}
|
||||
IOUtils.closeSafely(false, this.subs);
|
||||
}
|
||||
|
||||
@Override
|
||||
|
|
|
@ -72,8 +72,7 @@ final class NormsWriterPerField extends InvertedDocEndConsumerPerField implement
|
|||
assert norms.length == upto;
|
||||
norms = ArrayUtil.grow(norms, 1+upto);
|
||||
}
|
||||
final float norm = similarity.computeNorm(fieldState);
|
||||
norms[upto] = similarity.encodeNormValue(norm);
|
||||
norms[upto] = similarity.computeNorm(fieldState);
|
||||
docIDs[upto] = docState.docID;
|
||||
upto++;
|
||||
}
|
||||
|
|
|
@ -20,6 +20,7 @@ import java.util.concurrent.atomic.AtomicLong;
|
|||
|
||||
import org.apache.lucene.index.codecs.PerDocConsumer;
|
||||
import org.apache.lucene.store.Directory;
|
||||
import org.apache.lucene.store.IOContext;
|
||||
|
||||
/**
|
||||
* Encapsulates all necessary state to initiate a {@link PerDocConsumer} and
|
||||
|
@ -35,10 +36,11 @@ public class PerDocWriteState {
|
|||
public final AtomicLong bytesUsed;
|
||||
public final SegmentCodecs segmentCodecs;
|
||||
public final int codecId;
|
||||
public final IOContext context;
|
||||
|
||||
PerDocWriteState(PrintStream infoStream, Directory directory,
|
||||
String segmentName, FieldInfos fieldInfos, AtomicLong bytesUsed,
|
||||
int codecId) {
|
||||
int codecId, IOContext context) {
|
||||
this.infoStream = infoStream;
|
||||
this.directory = directory;
|
||||
this.segmentName = segmentName;
|
||||
|
@ -46,6 +48,7 @@ public class PerDocWriteState {
|
|||
this.segmentCodecs = fieldInfos.buildSegmentCodecs(false);
|
||||
this.codecId = codecId;
|
||||
this.bytesUsed = bytesUsed;
|
||||
this.context = context;
|
||||
}
|
||||
|
||||
PerDocWriteState(SegmentWriteState state) {
|
||||
|
@ -56,6 +59,7 @@ public class PerDocWriteState {
|
|||
fieldInfos = state.fieldInfos;
|
||||
codecId = state.codecId;
|
||||
bytesUsed = new AtomicLong(0);
|
||||
context = state.context;
|
||||
}
|
||||
|
||||
PerDocWriteState(PerDocWriteState state, int codecId) {
|
||||
|
@ -66,5 +70,6 @@ public class PerDocWriteState {
|
|||
this.segmentCodecs = state.segmentCodecs;
|
||||
this.codecId = codecId;
|
||||
this.bytesUsed = state.bytesUsed;
|
||||
this.context = state.context;
|
||||
}
|
||||
}
|
||||
|
|
|
@ -52,7 +52,7 @@ final class PerFieldCodecWrapper extends Codec {
|
|||
private final SegmentCodecs segmentCodecs;
|
||||
|
||||
PerFieldCodecWrapper(SegmentCodecs segmentCodecs) {
|
||||
name = "PerField";
|
||||
super("PerField");
|
||||
this.segmentCodecs = segmentCodecs;
|
||||
}
|
||||
|
||||
|
|
|
@ -26,6 +26,7 @@ import org.apache.lucene.index.codecs.PerDocValues;
|
|||
import org.apache.lucene.store.CompoundFileDirectory;
|
||||
import org.apache.lucene.store.Directory;
|
||||
import org.apache.lucene.store.IOContext;
|
||||
import org.apache.lucene.util.IOUtils;
|
||||
|
||||
/** Holds core readers that are shared (unchanged) when
|
||||
* SegmentReader is cloned or reopened */
|
||||
|
@ -120,33 +121,9 @@ final class SegmentCoreReaders {
|
|||
}
|
||||
|
||||
synchronized void decRef() throws IOException {
|
||||
|
||||
if (ref.decrementAndGet() == 0) {
|
||||
|
||||
if (fields != null) {
|
||||
fields.close();
|
||||
}
|
||||
|
||||
if (perDocProducer != null) {
|
||||
perDocProducer.close();
|
||||
}
|
||||
|
||||
if (termVectorsReaderOrig != null) {
|
||||
termVectorsReaderOrig.close();
|
||||
}
|
||||
|
||||
if (fieldsReaderOrig != null) {
|
||||
fieldsReaderOrig.close();
|
||||
}
|
||||
|
||||
if (cfsReader != null) {
|
||||
cfsReader.close();
|
||||
}
|
||||
|
||||
if (storeCFSReader != null) {
|
||||
storeCFSReader.close();
|
||||
}
|
||||
|
||||
IOUtils.closeSafely(false, fields, perDocProducer, termVectorsReaderOrig,
|
||||
fieldsReaderOrig, cfsReader, storeCFSReader);
|
||||
// Now, notify any ReaderFinished listeners:
|
||||
if (owner != null) {
|
||||
owner.notifyReaderFinishedListeners();
|
||||
|
|
|
@ -30,7 +30,6 @@ import java.util.Set;
|
|||
import org.apache.lucene.index.codecs.Codec;
|
||||
import org.apache.lucene.index.codecs.CodecProvider;
|
||||
import org.apache.lucene.index.codecs.DefaultSegmentInfosWriter;
|
||||
import org.apache.lucene.store.BufferedIndexInput;
|
||||
import org.apache.lucene.store.Directory;
|
||||
import org.apache.lucene.store.IOContext;
|
||||
import org.apache.lucene.store.IndexInput;
|
||||
|
@ -248,7 +247,7 @@ public final class SegmentInfo implements Cloneable {
|
|||
}
|
||||
final Directory dirToTest;
|
||||
if (isCompoundFile) {
|
||||
dirToTest = dir.openCompoundInput(IndexFileNames.segmentFileName(storesSegment, "", ext), IOContext.READONCE );
|
||||
dirToTest = dir.openCompoundInput(IndexFileNames.segmentFileName(storesSegment, "", ext), IOContext.READONCE);
|
||||
} else {
|
||||
dirToTest = dir;
|
||||
}
|
||||
|
|
|
@ -119,6 +119,7 @@ final class SegmentMerger {
|
|||
|
||||
mergedDocs = mergeFields();
|
||||
mergeTerms();
|
||||
mergePerDoc();
|
||||
mergeNorms();
|
||||
|
||||
if (fieldInfos.hasVectors())
|
||||
|
@ -484,17 +485,10 @@ final class SegmentMerger {
|
|||
int docBase = 0;
|
||||
|
||||
final List<Fields> fields = new ArrayList<Fields>();
|
||||
|
||||
final List<ReaderUtil.Slice> slices = new ArrayList<ReaderUtil.Slice>();
|
||||
final List<Bits> bits = new ArrayList<Bits>();
|
||||
final List<Integer> bitsStarts = new ArrayList<Integer>();
|
||||
|
||||
// TODO: move this into its own method - this merges currently only docvalues
|
||||
final List<PerDocValues> perDocProducers = new ArrayList<PerDocValues>();
|
||||
final List<ReaderUtil.Slice> perDocSlices = new ArrayList<ReaderUtil.Slice>();
|
||||
final List<Bits> perDocBits = new ArrayList<Bits>();
|
||||
final List<Integer> perDocBitsStarts = new ArrayList<Integer>();
|
||||
|
||||
for(IndexReader r : readers) {
|
||||
final Fields f = r.fields();
|
||||
final int maxDoc = r.maxDoc();
|
||||
|
@ -504,18 +498,10 @@ final class SegmentMerger {
|
|||
bits.add(r.getLiveDocs());
|
||||
bitsStarts.add(docBase);
|
||||
}
|
||||
final PerDocValues producer = r.perDocValues();
|
||||
if (producer != null) {
|
||||
perDocSlices.add(new ReaderUtil.Slice(docBase, maxDoc, fields.size()));
|
||||
perDocProducers.add(producer);
|
||||
perDocBits.add(r.getLiveDocs());
|
||||
perDocBitsStarts.add(docBase);
|
||||
}
|
||||
docBase += maxDoc;
|
||||
}
|
||||
|
||||
bitsStarts.add(docBase);
|
||||
perDocBitsStarts.add(docBase);
|
||||
|
||||
// we may gather more readers than mergeState.readerCount
|
||||
mergeState = new MergeState();
|
||||
|
@ -581,19 +567,45 @@ final class SegmentMerger {
|
|||
} finally {
|
||||
consumer.close();
|
||||
}
|
||||
}
|
||||
|
||||
private void mergePerDoc() throws IOException {
|
||||
final List<PerDocValues> perDocProducers = new ArrayList<PerDocValues>();
|
||||
final List<ReaderUtil.Slice> perDocSlices = new ArrayList<ReaderUtil.Slice>();
|
||||
final List<Bits> perDocBits = new ArrayList<Bits>();
|
||||
final List<Integer> perDocBitsStarts = new ArrayList<Integer>();
|
||||
int docBase = 0;
|
||||
for (IndexReader r : readers) {
|
||||
final int maxDoc = r.maxDoc();
|
||||
final PerDocValues producer = r.perDocValues();
|
||||
if (producer != null) {
|
||||
perDocSlices.add(new ReaderUtil.Slice(docBase, maxDoc, perDocProducers
|
||||
.size()));
|
||||
perDocProducers.add(producer);
|
||||
perDocBits.add(r.getLiveDocs());
|
||||
perDocBitsStarts.add(docBase);
|
||||
}
|
||||
docBase += maxDoc;
|
||||
}
|
||||
perDocBitsStarts.add(docBase);
|
||||
if (!perDocSlices.isEmpty()) {
|
||||
mergeState.multiLiveDocs = new MultiBits(perDocBits, perDocBitsStarts, true);
|
||||
mergeState.multiLiveDocs = new MultiBits(perDocBits, perDocBitsStarts,
|
||||
true);
|
||||
final PerDocConsumer docsConsumer = codec
|
||||
.docsConsumer(new PerDocWriteState(segmentWriteState));
|
||||
boolean success = false;
|
||||
try {
|
||||
final MultiPerDocValues multiPerDocValues = new MultiPerDocValues(perDocProducers
|
||||
.toArray(PerDocValues.EMPTY_ARRAY), perDocSlices
|
||||
.toArray(ReaderUtil.Slice.EMPTY_ARRAY));
|
||||
final MultiPerDocValues multiPerDocValues = new MultiPerDocValues(
|
||||
perDocProducers.toArray(PerDocValues.EMPTY_ARRAY),
|
||||
perDocSlices.toArray(ReaderUtil.Slice.EMPTY_ARRAY));
|
||||
docsConsumer.merge(mergeState, multiPerDocValues);
|
||||
success = true;
|
||||
} finally {
|
||||
docsConsumer.close();
|
||||
IOUtils.closeSafely(!success, docsConsumer);
|
||||
}
|
||||
}
|
||||
/* don't close the perDocProducers here since they are private segment producers
|
||||
* and will be closed once the SegmentReader goes out of scope */
|
||||
}
|
||||
|
||||
private MergeState mergeState;
|
||||
|
|
|
@ -25,11 +25,13 @@ import org.apache.lucene.store.IndexInput;
|
|||
import org.apache.lucene.store.IOContext.Context;
|
||||
import org.apache.lucene.util.ArrayUtil;
|
||||
import org.apache.lucene.util.BytesRef;
|
||||
import org.apache.lucene.util.IOUtils;
|
||||
|
||||
import java.io.Closeable;
|
||||
import java.io.IOException;
|
||||
import java.util.Arrays;
|
||||
|
||||
class TermVectorsReader implements Cloneable {
|
||||
class TermVectorsReader implements Cloneable, Closeable {
|
||||
|
||||
// NOTE: if you make a new format, it must be larger than
|
||||
// the current format
|
||||
|
@ -190,14 +192,8 @@ class TermVectorsReader implements Cloneable {
|
|||
return format;
|
||||
}
|
||||
|
||||
void close() throws IOException {
|
||||
// make all effort to close up. Keep the first exception
|
||||
// and throw it as a new one.
|
||||
IOException keep = null;
|
||||
if (tvx != null) try { tvx.close(); } catch (IOException e) { keep = e; }
|
||||
if (tvd != null) try { tvd.close(); } catch (IOException e) { if (keep == null) keep = e; }
|
||||
if (tvf != null) try { tvf.close(); } catch (IOException e) { if (keep == null) keep = e; }
|
||||
if (keep != null) throw (IOException) keep.fillInStackTrace();
|
||||
public void close() throws IOException {
|
||||
IOUtils.closeSafely(false, tvx, tvd, tvf);
|
||||
}
|
||||
|
||||
/**
|
||||
|
|
|
@ -18,6 +18,7 @@ package org.apache.lucene.index.codecs;
|
|||
*/
|
||||
|
||||
import java.io.IOException;
|
||||
import java.util.Comparator;
|
||||
import java.util.Set;
|
||||
|
||||
import org.apache.lucene.index.PerDocWriteState;
|
||||
|
@ -25,13 +26,21 @@ import org.apache.lucene.index.SegmentInfo;
|
|||
import org.apache.lucene.index.SegmentWriteState;
|
||||
import org.apache.lucene.index.SegmentReadState;
|
||||
import org.apache.lucene.store.Directory;
|
||||
import org.apache.lucene.util.BytesRef;
|
||||
|
||||
/** @lucene.experimental */
|
||||
public abstract class Codec {
|
||||
public static final Codec[] EMPTY = new Codec[0];
|
||||
/** Unique name that's used to retrieve this codec when
|
||||
* reading the index */
|
||||
public String name;
|
||||
public final String name;
|
||||
private boolean dvUseCompoundFile = true;
|
||||
private Comparator<BytesRef> docValuesSortComparator = BytesRef
|
||||
.getUTF8SortedAsUnicodeComparator();
|
||||
|
||||
protected Codec(String name) {
|
||||
this.name = name;
|
||||
}
|
||||
|
||||
/** Writes a new segment */
|
||||
public abstract FieldsConsumer fieldsConsumer(SegmentWriteState state) throws IOException;
|
||||
|
@ -69,6 +78,47 @@ public abstract class Codec {
|
|||
/** Records all file extensions this codec uses */
|
||||
public abstract void getExtensions(Set<String> extensions);
|
||||
|
||||
|
||||
/**
|
||||
* If set to <code>true</code> this codec will use a compound file for
|
||||
* IndexDocValues, otherwise each IndexDocValues field will create up to 2
|
||||
* files per segment.
|
||||
* <p>
|
||||
* NOTE: The default values is <code>true</code>.
|
||||
*/
|
||||
public void setDocValuesUseCFS(boolean docValuesUseCFS) {
|
||||
this.dvUseCompoundFile = docValuesUseCFS;
|
||||
}
|
||||
|
||||
/**
|
||||
* Returns <code>true</code> iff compound file should be used for
|
||||
* IndexDocValues, otherwise <code>false</code>.
|
||||
*
|
||||
* @see #setDocValuesUseCFS(boolean)
|
||||
* @return <code>true</code> iff compound file should be used for
|
||||
* IndexDocValues, otherwise <code>false</code>.
|
||||
*/
|
||||
public boolean getDocValuesUseCFS() {
|
||||
return dvUseCompoundFile;
|
||||
}
|
||||
|
||||
/**
|
||||
* Sets the {@link BytesRef} comparator for sorted IndexDocValue variants. The
|
||||
* default is {@link BytesRef#getUTF8SortedAsUnicodeComparator()}. *
|
||||
*/
|
||||
public void setDocValuesSortComparator(
|
||||
Comparator<BytesRef> docValuesSortComparator) {
|
||||
this.docValuesSortComparator = docValuesSortComparator;
|
||||
}
|
||||
|
||||
/**
|
||||
* Returns the {@link BytesRef} comparator for sorted IndexDocValue variants.
|
||||
* The default is {@link BytesRef#getUTF8SortedAsUnicodeComparator()}.
|
||||
*/
|
||||
public Comparator<BytesRef> getDocValuesSortComparator() {
|
||||
return docValuesSortComparator;
|
||||
}
|
||||
|
||||
@Override
|
||||
public String toString() {
|
||||
return name;
|
||||
|
|
|
@ -44,7 +44,7 @@ public class CoreCodecProvider extends CodecProvider {
|
|||
public CoreCodecProvider() {
|
||||
register(new StandardCodec());
|
||||
register(new PreFlexCodec());
|
||||
register(new PulsingCodec(1));
|
||||
register(new PulsingCodec());
|
||||
register(new SimpleTextCodec());
|
||||
register(new MemoryCodec());
|
||||
}
|
||||
|
|
|
@ -32,79 +32,106 @@ import org.apache.lucene.store.Directory;
|
|||
import org.apache.lucene.store.IOContext;
|
||||
import org.apache.lucene.util.BytesRef;
|
||||
|
||||
/**
|
||||
*
|
||||
* @lucene.experimental
|
||||
*/
|
||||
public class DefaultDocValuesConsumer extends PerDocConsumer {
|
||||
private final String segmentName;
|
||||
private final int codecId;
|
||||
private final Directory directory;
|
||||
private final AtomicLong bytesUsed;
|
||||
private final Comparator<BytesRef> comparator;
|
||||
private boolean useCompoundFile;
|
||||
private final IOContext context;
|
||||
|
||||
public DefaultDocValuesConsumer(PerDocWriteState state, Comparator<BytesRef> comparator) {
|
||||
public DefaultDocValuesConsumer(PerDocWriteState state, Comparator<BytesRef> comparator, boolean useCompoundFile) throws IOException {
|
||||
this.segmentName = state.segmentName;
|
||||
this.codecId = state.codecId;
|
||||
this.bytesUsed = state.bytesUsed;
|
||||
this.directory = state.directory;
|
||||
this.context = state.context;
|
||||
//TODO maybe we should enable a global CFS that all codecs can pull on demand to further reduce the number of files?
|
||||
this.directory = useCompoundFile ? state.directory.createCompoundOutput(
|
||||
IndexFileNames.segmentFileName(segmentName, codecId,
|
||||
IndexFileNames.COMPOUND_FILE_EXTENSION), context) : state.directory;
|
||||
this.comparator = comparator;
|
||||
this.useCompoundFile = useCompoundFile;
|
||||
}
|
||||
|
||||
public void close() throws IOException {
|
||||
if (useCompoundFile) {
|
||||
this.directory.close();
|
||||
}
|
||||
}
|
||||
|
||||
@Override
|
||||
public DocValuesConsumer addValuesField(FieldInfo field) throws IOException {
|
||||
return Writer.create(field.getDocValues(),
|
||||
docValuesId(segmentName, codecId, field.number),
|
||||
// TODO can we have a compound file per segment and codec for
|
||||
// docvalues?
|
||||
directory, comparator, bytesUsed, IOContext.DEFAULT);
|
||||
directory, comparator, bytesUsed, context);
|
||||
}
|
||||
|
||||
@SuppressWarnings("fallthrough")
|
||||
public static void files(Directory dir, SegmentInfo segmentInfo, int codecId,
|
||||
Set<String> files) throws IOException {
|
||||
Set<String> files, boolean useCompoundFile) throws IOException {
|
||||
FieldInfos fieldInfos = segmentInfo.getFieldInfos();
|
||||
for (FieldInfo fieldInfo : fieldInfos) {
|
||||
if (fieldInfo.getCodecId() == codecId && fieldInfo.hasDocValues()) {
|
||||
String filename = docValuesId(segmentInfo.name, codecId,
|
||||
fieldInfo.number);
|
||||
switch (fieldInfo.getDocValues()) {
|
||||
case BYTES_FIXED_DEREF:
|
||||
case BYTES_VAR_DEREF:
|
||||
case BYTES_VAR_SORTED:
|
||||
case BYTES_FIXED_SORTED:
|
||||
case BYTES_VAR_STRAIGHT:
|
||||
files.add(IndexFileNames.segmentFileName(filename, "",
|
||||
Writer.INDEX_EXTENSION));
|
||||
assert dir.fileExists(IndexFileNames.segmentFileName(filename, "",
|
||||
Writer.INDEX_EXTENSION));
|
||||
// until here all types use an index
|
||||
case BYTES_FIXED_STRAIGHT:
|
||||
case FLOAT_32:
|
||||
case FLOAT_64:
|
||||
case VAR_INTS:
|
||||
case FIXED_INTS_16:
|
||||
case FIXED_INTS_32:
|
||||
case FIXED_INTS_64:
|
||||
case FIXED_INTS_8:
|
||||
files.add(IndexFileNames.segmentFileName(filename, "",
|
||||
Writer.DATA_EXTENSION));
|
||||
assert dir.fileExists(IndexFileNames.segmentFileName(filename, "",
|
||||
Writer.DATA_EXTENSION));
|
||||
break;
|
||||
if (useCompoundFile) {
|
||||
files.add(IndexFileNames.segmentFileName(segmentInfo.name, codecId, IndexFileNames.COMPOUND_FILE_EXTENSION));
|
||||
files.add(IndexFileNames.segmentFileName(segmentInfo.name, codecId, IndexFileNames.COMPOUND_FILE_ENTRIES_EXTENSION));
|
||||
assert dir.fileExists(IndexFileNames.segmentFileName(segmentInfo.name, codecId, IndexFileNames.COMPOUND_FILE_ENTRIES_EXTENSION));
|
||||
assert dir.fileExists(IndexFileNames.segmentFileName(segmentInfo.name, codecId, IndexFileNames.COMPOUND_FILE_EXTENSION));
|
||||
return;
|
||||
} else {
|
||||
switch (fieldInfo.getDocValues()) {
|
||||
case BYTES_FIXED_DEREF:
|
||||
case BYTES_VAR_DEREF:
|
||||
case BYTES_VAR_SORTED:
|
||||
case BYTES_FIXED_SORTED:
|
||||
case BYTES_VAR_STRAIGHT:
|
||||
files.add(IndexFileNames.segmentFileName(filename, "",
|
||||
Writer.INDEX_EXTENSION));
|
||||
assert dir.fileExists(IndexFileNames.segmentFileName(filename, "",
|
||||
Writer.INDEX_EXTENSION));
|
||||
// until here all types use an index
|
||||
case BYTES_FIXED_STRAIGHT:
|
||||
case FLOAT_32:
|
||||
case FLOAT_64:
|
||||
case VAR_INTS:
|
||||
case FIXED_INTS_16:
|
||||
case FIXED_INTS_32:
|
||||
case FIXED_INTS_64:
|
||||
case FIXED_INTS_8:
|
||||
files.add(IndexFileNames.segmentFileName(filename, "",
|
||||
Writer.DATA_EXTENSION));
|
||||
assert dir.fileExists(IndexFileNames.segmentFileName(filename, "",
|
||||
Writer.DATA_EXTENSION));
|
||||
break;
|
||||
|
||||
default:
|
||||
assert false;
|
||||
default:
|
||||
assert false;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
static String docValuesId(String segmentsName, int codecID, int fieldId) {
|
||||
return segmentsName + "_" + codecID + "-" + fieldId;
|
||||
}
|
||||
|
||||
public static void getDocValuesExtensions(Set<String> extensions) {
|
||||
extensions.add(Writer.DATA_EXTENSION);
|
||||
extensions.add(Writer.INDEX_EXTENSION);
|
||||
public static void getDocValuesExtensions(Set<String> extensions, boolean useCompoundFile) {
|
||||
if (useCompoundFile) {
|
||||
extensions.add(IndexFileNames.COMPOUND_FILE_ENTRIES_EXTENSION);
|
||||
extensions.add(IndexFileNames.COMPOUND_FILE_EXTENSION);
|
||||
} else {
|
||||
extensions.add(Writer.DATA_EXTENSION);
|
||||
extensions.add(Writer.INDEX_EXTENSION);
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
|
|
|
@ -16,12 +16,16 @@ package org.apache.lucene.index.codecs;
|
|||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
import java.io.Closeable;
|
||||
import java.io.IOException;
|
||||
import java.util.ArrayList;
|
||||
import java.util.Collection;
|
||||
import java.util.Comparator;
|
||||
import java.util.TreeMap;
|
||||
|
||||
import org.apache.lucene.index.FieldInfo;
|
||||
import org.apache.lucene.index.FieldInfos;
|
||||
import org.apache.lucene.index.IndexFileNames;
|
||||
import org.apache.lucene.index.SegmentInfo;
|
||||
import org.apache.lucene.index.values.Bytes;
|
||||
import org.apache.lucene.index.values.IndexDocValues;
|
||||
|
@ -30,6 +34,8 @@ import org.apache.lucene.index.values.Ints;
|
|||
import org.apache.lucene.index.values.ValueType;
|
||||
import org.apache.lucene.store.Directory;
|
||||
import org.apache.lucene.store.IOContext;
|
||||
import org.apache.lucene.util.BytesRef;
|
||||
import org.apache.lucene.util.IOUtils;
|
||||
|
||||
/**
|
||||
* Abstract base class for FieldsProducer implementations supporting
|
||||
|
@ -40,8 +46,12 @@ import org.apache.lucene.store.IOContext;
|
|||
public class DefaultDocValuesProducer extends PerDocValues {
|
||||
|
||||
protected final TreeMap<String, IndexDocValues> docValues;
|
||||
private final boolean useCompoundFile;
|
||||
private final Closeable cfs;
|
||||
private final Comparator<BytesRef> sortComparator;
|
||||
|
||||
/**
|
||||
*
|
||||
* Creates a new {@link DefaultDocValuesProducer} instance and loads all
|
||||
* {@link IndexDocValues} instances for this segment and codec.
|
||||
*
|
||||
|
@ -53,12 +63,27 @@ public class DefaultDocValuesProducer extends PerDocValues {
|
|||
* the {@link FieldInfos}
|
||||
* @param codecId
|
||||
* the codec ID
|
||||
* @param useCompoundFile
|
||||
* if <code>true</code> this producer opens a compound file to read
|
||||
* IndexDocValues fields, otherwise each field defines its own set of
|
||||
* files.
|
||||
* @param sortComparator
|
||||
* defines the sort order for sorted IndexDocValues variants
|
||||
* @throws IOException
|
||||
* if an {@link IOException} occurs
|
||||
*/
|
||||
public DefaultDocValuesProducer(SegmentInfo si, Directory dir,
|
||||
FieldInfos fieldInfo, int codecId, IOContext context) throws IOException {
|
||||
docValues = load(fieldInfo, si.name, si.docCount, dir, codecId, context);
|
||||
FieldInfos fieldInfo, int codecId, boolean useCompoundFile, Comparator<BytesRef> sortComparator, IOContext context) throws IOException {
|
||||
this.useCompoundFile = useCompoundFile;
|
||||
this.sortComparator = sortComparator;
|
||||
final Directory directory;
|
||||
if (useCompoundFile) {
|
||||
cfs = directory = dir.openCompoundInput(IndexFileNames.segmentFileName(si.name, codecId, IndexFileNames.COMPOUND_FILE_EXTENSION), context);
|
||||
} else {
|
||||
cfs = null;
|
||||
directory = dir;
|
||||
}
|
||||
docValues = load(fieldInfo, si.name, si.docCount, directory, codecId, context);
|
||||
}
|
||||
|
||||
/**
|
||||
|
@ -86,14 +111,14 @@ public class DefaultDocValuesProducer extends PerDocValues {
|
|||
final String id = DefaultDocValuesConsumer.docValuesId(segment,
|
||||
codecId, fieldInfo.number);
|
||||
values.put(field,
|
||||
loadDocValues(docCount, dir, id, fieldInfo.getDocValues(), context));
|
||||
loadDocValues(docCount, dir, id, fieldInfo.getDocValues(), sortComparator, context));
|
||||
}
|
||||
}
|
||||
success = true;
|
||||
} finally {
|
||||
if (!success) {
|
||||
// if we fail we must close all opened resources if there are any
|
||||
closeDocValues(values.values());
|
||||
closeInternal(values.values());
|
||||
}
|
||||
}
|
||||
return values;
|
||||
|
@ -113,6 +138,7 @@ public class DefaultDocValuesProducer extends PerDocValues {
|
|||
* the unique file ID within the segment
|
||||
* @param type
|
||||
* the type to load
|
||||
* @param sortComparator byte comparator used by sorted variants
|
||||
* @return a {@link IndexDocValues} instance for the given type
|
||||
* @throws IOException
|
||||
* if an {@link IOException} occurs
|
||||
|
@ -120,7 +146,7 @@ public class DefaultDocValuesProducer extends PerDocValues {
|
|||
* if the given {@link ValueType} is not supported
|
||||
*/
|
||||
protected IndexDocValues loadDocValues(int docCount, Directory dir, String id,
|
||||
ValueType type, IOContext context) throws IOException {
|
||||
ValueType type, Comparator<BytesRef> sortComparator, IOContext context) throws IOException {
|
||||
switch (type) {
|
||||
case FIXED_INTS_16:
|
||||
case FIXED_INTS_32:
|
||||
|
@ -133,39 +159,36 @@ public class DefaultDocValuesProducer extends PerDocValues {
|
|||
case FLOAT_64:
|
||||
return Floats.getValues(dir, id, docCount, context);
|
||||
case BYTES_FIXED_STRAIGHT:
|
||||
return Bytes.getValues(dir, id, Bytes.Mode.STRAIGHT, true, docCount, context);
|
||||
return Bytes.getValues(dir, id, Bytes.Mode.STRAIGHT, true, docCount, sortComparator, context);
|
||||
case BYTES_FIXED_DEREF:
|
||||
return Bytes.getValues(dir, id, Bytes.Mode.DEREF, true, docCount, context);
|
||||
return Bytes.getValues(dir, id, Bytes.Mode.DEREF, true, docCount, sortComparator, context);
|
||||
case BYTES_FIXED_SORTED:
|
||||
return Bytes.getValues(dir, id, Bytes.Mode.SORTED, true, docCount, context);
|
||||
return Bytes.getValues(dir, id, Bytes.Mode.SORTED, true, docCount, sortComparator, context);
|
||||
case BYTES_VAR_STRAIGHT:
|
||||
return Bytes.getValues(dir, id, Bytes.Mode.STRAIGHT, false, docCount, context);
|
||||
return Bytes.getValues(dir, id, Bytes.Mode.STRAIGHT, false, docCount, sortComparator, context);
|
||||
case BYTES_VAR_DEREF:
|
||||
return Bytes.getValues(dir, id, Bytes.Mode.DEREF, false, docCount, context);
|
||||
return Bytes.getValues(dir, id, Bytes.Mode.DEREF, false, docCount, sortComparator, context);
|
||||
case BYTES_VAR_SORTED:
|
||||
return Bytes.getValues(dir, id, Bytes.Mode.SORTED, false, docCount, context);
|
||||
return Bytes.getValues(dir, id, Bytes.Mode.SORTED, false, docCount, sortComparator, context);
|
||||
default:
|
||||
throw new IllegalStateException("unrecognized index values mode " + type);
|
||||
}
|
||||
}
|
||||
|
||||
public void close() throws IOException {
|
||||
closeDocValues(docValues.values());
|
||||
closeInternal(docValues.values());
|
||||
}
|
||||
|
||||
private void closeDocValues(final Collection<IndexDocValues> values)
|
||||
throws IOException {
|
||||
IOException ex = null;
|
||||
for (IndexDocValues docValues : values) {
|
||||
try {
|
||||
docValues.close();
|
||||
} catch (IOException e) {
|
||||
ex = e;
|
||||
}
|
||||
}
|
||||
if (ex != null) {
|
||||
throw ex;
|
||||
private void closeInternal(Collection<? extends Closeable> closeables) throws IOException {
|
||||
final Collection<? extends Closeable> toClose;
|
||||
if (useCompoundFile) {
|
||||
final ArrayList<Closeable> list = new ArrayList<Closeable>(closeables);
|
||||
list.add(cfs);
|
||||
toClose = list;
|
||||
} else {
|
||||
toClose = closeables;
|
||||
}
|
||||
IOUtils.closeSafely(false, toClose);
|
||||
}
|
||||
|
||||
@Override
|
||||
|
|
|
@ -79,7 +79,7 @@ import org.apache.lucene.util.fst.FST;
|
|||
public class MemoryCodec extends Codec {
|
||||
|
||||
public MemoryCodec() {
|
||||
name = "Memory";
|
||||
super("Memory");
|
||||
}
|
||||
|
||||
private static final boolean VERBOSE = false;
|
||||
|
@ -779,22 +779,22 @@ public class MemoryCodec extends Codec {
|
|||
@Override
|
||||
public void files(Directory dir, SegmentInfo segmentInfo, int id, Set<String> files) throws IOException {
|
||||
files.add(IndexFileNames.segmentFileName(segmentInfo.name, id, EXTENSION));
|
||||
DefaultDocValuesConsumer.files(dir, segmentInfo, id, files);
|
||||
DefaultDocValuesConsumer.files(dir, segmentInfo, id, files, getDocValuesUseCFS());
|
||||
}
|
||||
|
||||
@Override
|
||||
public void getExtensions(Set<String> extensions) {
|
||||
extensions.add(EXTENSION);
|
||||
DefaultDocValuesConsumer.getDocValuesExtensions(extensions);
|
||||
DefaultDocValuesConsumer.getDocValuesExtensions(extensions, getDocValuesUseCFS());
|
||||
}
|
||||
|
||||
@Override
|
||||
public PerDocConsumer docsConsumer(PerDocWriteState state) throws IOException {
|
||||
return new DefaultDocValuesConsumer(state, BytesRef.getUTF8SortedAsUnicodeComparator());
|
||||
return new DefaultDocValuesConsumer(state, getDocValuesSortComparator(), getDocValuesUseCFS());
|
||||
}
|
||||
|
||||
@Override
|
||||
public PerDocValues docsProducer(SegmentReadState state) throws IOException {
|
||||
return new DefaultDocValuesProducer(state.segmentInfo, state.dir, state.fieldInfos, state.codecId, IOContext.READONCE);
|
||||
return new DefaultDocValuesProducer(state.segmentInfo, state.dir, state.fieldInfos, state.codecId, getDocValuesUseCFS(), getDocValuesSortComparator(), IOContext.READONCE);
|
||||
}
|
||||
}
|
||||
|
|
|
@ -55,7 +55,7 @@ public class PreFlexCodec extends Codec {
|
|||
public static final String PROX_EXTENSION = "prx";
|
||||
|
||||
public PreFlexCodec() {
|
||||
name = "PreFlex";
|
||||
super("PreFlex");
|
||||
}
|
||||
|
||||
@Override
|
||||
|
|
|
@ -43,7 +43,6 @@ import org.apache.lucene.index.codecs.TermsIndexReaderBase;
|
|||
import org.apache.lucene.index.codecs.TermsIndexWriterBase;
|
||||
import org.apache.lucene.index.codecs.standard.StandardCodec;
|
||||
import org.apache.lucene.store.Directory;
|
||||
import org.apache.lucene.util.BytesRef;
|
||||
import org.apache.lucene.util.IOUtils;
|
||||
|
||||
/** This codec "inlines" the postings for terms that have
|
||||
|
@ -58,10 +57,19 @@ public class PulsingCodec extends Codec {
|
|||
|
||||
private final int freqCutoff;
|
||||
|
||||
/**
|
||||
* Creates a {@link PulsingCodec} with <tt>freqCutoff = 1</tt>
|
||||
*
|
||||
* @see PulsingCodec#PulsingCodec(int)
|
||||
*/
|
||||
public PulsingCodec() {
|
||||
this(1);
|
||||
}
|
||||
|
||||
/** Terms with freq <= freqCutoff are inlined into terms
|
||||
* dict. */
|
||||
public PulsingCodec(int freqCutoff) {
|
||||
name = "Pulsing";
|
||||
super("Pulsing");
|
||||
this.freqCutoff = freqCutoff;
|
||||
}
|
||||
|
||||
|
@ -157,22 +165,22 @@ public class PulsingCodec extends Codec {
|
|||
StandardPostingsReader.files(dir, segmentInfo, id, files);
|
||||
BlockTermsReader.files(dir, segmentInfo, id, files);
|
||||
VariableGapTermsIndexReader.files(dir, segmentInfo, id, files);
|
||||
DefaultDocValuesConsumer.files(dir, segmentInfo, id, files);
|
||||
DefaultDocValuesConsumer.files(dir, segmentInfo, id, files, getDocValuesUseCFS());
|
||||
}
|
||||
|
||||
@Override
|
||||
public void getExtensions(Set<String> extensions) {
|
||||
StandardCodec.getStandardExtensions(extensions);
|
||||
DefaultDocValuesConsumer.getDocValuesExtensions(extensions);
|
||||
DefaultDocValuesConsumer.getDocValuesExtensions(extensions, getDocValuesUseCFS());
|
||||
}
|
||||
|
||||
@Override
|
||||
public PerDocConsumer docsConsumer(PerDocWriteState state) throws IOException {
|
||||
return new DefaultDocValuesConsumer(state, BytesRef.getUTF8SortedAsUnicodeComparator());
|
||||
return new DefaultDocValuesConsumer(state, getDocValuesSortComparator(), getDocValuesUseCFS());
|
||||
}
|
||||
|
||||
@Override
|
||||
public PerDocValues docsProducer(SegmentReadState state) throws IOException {
|
||||
return new DefaultDocValuesProducer(state.segmentInfo, state.dir, state.fieldInfos, state.codecId, state.context);
|
||||
return new DefaultDocValuesProducer(state.segmentInfo, state.dir, state.fieldInfos, state.codecId, getDocValuesUseCFS(), getDocValuesSortComparator(), state.context);
|
||||
}
|
||||
}
|
||||
|
|
|
@ -33,7 +33,6 @@ import org.apache.lucene.index.codecs.PerDocConsumer;
|
|||
import org.apache.lucene.index.codecs.DefaultDocValuesConsumer;
|
||||
import org.apache.lucene.index.codecs.PerDocValues;
|
||||
import org.apache.lucene.store.Directory;
|
||||
import org.apache.lucene.util.BytesRef;
|
||||
|
||||
/** For debugging, curiosity, transparency only!! Do not
|
||||
* use this codec in production.
|
||||
|
@ -46,9 +45,10 @@ import org.apache.lucene.util.BytesRef;
|
|||
public class SimpleTextCodec extends Codec {
|
||||
|
||||
public SimpleTextCodec() {
|
||||
name = "SimpleText";
|
||||
super("SimpleText");
|
||||
}
|
||||
|
||||
|
||||
@Override
|
||||
public FieldsConsumer fieldsConsumer(SegmentWriteState state) throws IOException {
|
||||
return new SimpleTextFieldsWriter(state);
|
||||
|
@ -69,23 +69,23 @@ public class SimpleTextCodec extends Codec {
|
|||
@Override
|
||||
public void files(Directory dir, SegmentInfo segmentInfo, int id, Set<String> files) throws IOException {
|
||||
files.add(getPostingsFileName(segmentInfo.name, id));
|
||||
DefaultDocValuesConsumer.files(dir, segmentInfo, id, files);
|
||||
DefaultDocValuesConsumer.files(dir, segmentInfo, id, files, getDocValuesUseCFS());
|
||||
}
|
||||
|
||||
@Override
|
||||
public void getExtensions(Set<String> extensions) {
|
||||
extensions.add(POSTINGS_EXTENSION);
|
||||
DefaultDocValuesConsumer.getDocValuesExtensions(extensions);
|
||||
DefaultDocValuesConsumer.getDocValuesExtensions(extensions, getDocValuesUseCFS());
|
||||
}
|
||||
|
||||
// TODO: would be great if these used a plain text impl
|
||||
@Override
|
||||
public PerDocConsumer docsConsumer(PerDocWriteState state) throws IOException {
|
||||
return new DefaultDocValuesConsumer(state, BytesRef.getUTF8SortedAsUnicodeComparator());
|
||||
return new DefaultDocValuesConsumer(state, getDocValuesSortComparator(), getDocValuesUseCFS());
|
||||
}
|
||||
|
||||
@Override
|
||||
public PerDocValues docsProducer(SegmentReadState state) throws IOException {
|
||||
return new DefaultDocValuesProducer(state.segmentInfo, state.dir, state.fieldInfos, state.codecId, state.context);
|
||||
return new DefaultDocValuesProducer(state.segmentInfo, state.dir, state.fieldInfos, state.codecId, getDocValuesUseCFS(), getDocValuesSortComparator(), state.context);
|
||||
}
|
||||
}
|
||||
|
|
|
@ -40,14 +40,13 @@ import org.apache.lucene.index.codecs.BlockTermsWriter;
|
|||
import org.apache.lucene.index.codecs.BlockTermsReader;
|
||||
import org.apache.lucene.index.codecs.DefaultDocValuesProducer;
|
||||
import org.apache.lucene.store.Directory;
|
||||
import org.apache.lucene.util.BytesRef;
|
||||
|
||||
/** Default codec.
|
||||
* @lucene.experimental */
|
||||
public class StandardCodec extends Codec {
|
||||
|
||||
public StandardCodec() {
|
||||
name = "Standard";
|
||||
super("Standard");
|
||||
}
|
||||
|
||||
@Override
|
||||
|
@ -140,13 +139,13 @@ public class StandardCodec extends Codec {
|
|||
StandardPostingsReader.files(dir, segmentInfo, id, files);
|
||||
BlockTermsReader.files(dir, segmentInfo, id, files);
|
||||
VariableGapTermsIndexReader.files(dir, segmentInfo, id, files);
|
||||
DefaultDocValuesConsumer.files(dir, segmentInfo, id, files);
|
||||
DefaultDocValuesConsumer.files(dir, segmentInfo, id, files, getDocValuesUseCFS());
|
||||
}
|
||||
|
||||
@Override
|
||||
public void getExtensions(Set<String> extensions) {
|
||||
getStandardExtensions(extensions);
|
||||
DefaultDocValuesConsumer.getDocValuesExtensions(extensions);
|
||||
DefaultDocValuesConsumer.getDocValuesExtensions(extensions, getDocValuesUseCFS());
|
||||
}
|
||||
|
||||
public static void getStandardExtensions(Set<String> extensions) {
|
||||
|
@ -158,11 +157,11 @@ public class StandardCodec extends Codec {
|
|||
|
||||
@Override
|
||||
public PerDocConsumer docsConsumer(PerDocWriteState state) throws IOException {
|
||||
return new DefaultDocValuesConsumer(state, BytesRef.getUTF8SortedAsUnicodeComparator());
|
||||
return new DefaultDocValuesConsumer(state, getDocValuesSortComparator(), getDocValuesUseCFS());
|
||||
}
|
||||
|
||||
@Override
|
||||
public PerDocValues docsProducer(SegmentReadState state) throws IOException {
|
||||
return new DefaultDocValuesProducer(state.segmentInfo, state.dir, state.fieldInfos, state.codecId, state.context);
|
||||
return new DefaultDocValuesProducer(state.segmentInfo, state.dir, state.fieldInfos, state.codecId, getDocValuesUseCFS(), getDocValuesSortComparator(), state.context);
|
||||
}
|
||||
}
|
||||
|
|
|
@ -153,12 +153,13 @@ public final class Bytes {
|
|||
* otherwise <code>false</code>
|
||||
* @param maxDoc
|
||||
* the number of document values stored for the given ID
|
||||
* @param sortComparator byte comparator used by sorted variants
|
||||
* @return an initialized {@link IndexDocValues} instance.
|
||||
* @throws IOException
|
||||
* if an {@link IOException} occurs
|
||||
*/
|
||||
public static IndexDocValues getValues(Directory dir, String id, Mode mode,
|
||||
boolean fixedSize, int maxDoc, IOContext context) throws IOException {
|
||||
boolean fixedSize, int maxDoc, Comparator<BytesRef> sortComparator, IOContext context) throws IOException {
|
||||
|
||||
// TODO -- I can peek @ header to determing fixed/mode?
|
||||
if (fixedSize) {
|
||||
|
@ -175,7 +176,7 @@ public final class Bytes {
|
|||
} else if (mode == Mode.DEREF) {
|
||||
return new VarDerefBytesImpl.Reader(dir, id, maxDoc, context);
|
||||
} else if (mode == Mode.SORTED) {
|
||||
return new VarSortedBytesImpl.Reader(dir, id, maxDoc, context);
|
||||
return new VarSortedBytesImpl.Reader(dir, id, maxDoc, sortComparator, context);
|
||||
}
|
||||
}
|
||||
|
||||
|
|
|
@ -131,6 +131,18 @@ public abstract class IndexDocValues implements Closeable {
|
|||
return cache.loadSorted(this, comparator);
|
||||
}
|
||||
|
||||
/**
|
||||
* Returns a {@link SortedSource} instance using a default {@link BytesRef}
|
||||
* comparator for this {@link IndexDocValues} field instance like
|
||||
* {@link #getSource()}.
|
||||
* <p>
|
||||
* This method will return null iff this {@link IndexDocValues} represent a
|
||||
* {@link Source} instead of a {@link SortedSource}.
|
||||
*/
|
||||
public SortedSource getSortedSorted() throws IOException {
|
||||
return getSortedSorted(null);
|
||||
}
|
||||
|
||||
/**
|
||||
* Loads and returns a {@link SortedSource} instance for this
|
||||
* {@link IndexDocValues} field instance like {@link #load()}.
|
||||
|
@ -143,6 +155,18 @@ public abstract class IndexDocValues implements Closeable {
|
|||
throw new UnsupportedOperationException();
|
||||
}
|
||||
|
||||
/**
|
||||
* Loads and returns a {@link SortedSource} instance using a default
|
||||
* {@link BytesRef} comparator for this {@link IndexDocValues} field instance
|
||||
* like {@link #load()}.
|
||||
* <p>
|
||||
* This method will return null iff this {@link IndexDocValues} represent a
|
||||
* {@link Source} instead of a {@link SortedSource}.
|
||||
*/
|
||||
public SortedSource loadSorted() throws IOException {
|
||||
return loadSorted(null);
|
||||
}
|
||||
|
||||
/**
|
||||
* Returns the {@link ValueType} of this {@link IndexDocValues} instance
|
||||
*/
|
||||
|
|
|
@ -168,14 +168,17 @@ class VarSortedBytesImpl {
|
|||
|
||||
public static class Reader extends BytesReaderBase {
|
||||
|
||||
Reader(Directory dir, String id, int maxDoc, IOContext context) throws IOException {
|
||||
private final Comparator<BytesRef> defaultComp;
|
||||
|
||||
Reader(Directory dir, String id, int maxDoc, Comparator<BytesRef> comparator, IOContext context) throws IOException {
|
||||
super(dir, id, CODEC_NAME, VERSION_START, true, context);
|
||||
this.defaultComp = comparator;
|
||||
}
|
||||
|
||||
@Override
|
||||
public org.apache.lucene.index.values.IndexDocValues.Source load()
|
||||
throws IOException {
|
||||
return loadSorted(null);
|
||||
return loadSorted(defaultComp);
|
||||
}
|
||||
|
||||
@Override
|
||||
|
|
|
@ -183,14 +183,11 @@ public class BooleanQuery extends Query implements Iterable<BooleanClause> {
|
|||
public Query getQuery() { return BooleanQuery.this; }
|
||||
|
||||
@Override
|
||||
public float getValue() { return getBoost(); }
|
||||
|
||||
@Override
|
||||
public float sumOfSquaredWeights() throws IOException {
|
||||
public float getValueForNormalization() throws IOException {
|
||||
float sum = 0.0f;
|
||||
for (int i = 0 ; i < weights.size(); i++) {
|
||||
// call sumOfSquaredWeights for all clauses in case of side effects
|
||||
float s = weights.get(i).sumOfSquaredWeights(); // sum sub weights
|
||||
float s = weights.get(i).getValueForNormalization(); // sum sub weights
|
||||
if (!clauses.get(i).isProhibited())
|
||||
// only add to sum for non-prohibited clauses
|
||||
sum += s;
|
||||
|
@ -206,11 +203,11 @@ public class BooleanQuery extends Query implements Iterable<BooleanClause> {
|
|||
}
|
||||
|
||||
@Override
|
||||
public void normalize(float norm) {
|
||||
norm *= getBoost(); // incorporate boost
|
||||
public void normalize(float norm, float topLevelBoost) {
|
||||
topLevelBoost *= getBoost(); // incorporate boost
|
||||
for (Weight w : weights) {
|
||||
// normalize all clauses, (even if prohibited in case of side affects)
|
||||
w.normalize(norm);
|
||||
w.normalize(norm, topLevelBoost);
|
||||
}
|
||||
}
|
||||
|
||||
|
|
|
@ -27,7 +27,7 @@ import org.apache.lucene.util.ArrayUtil;
|
|||
import org.apache.lucene.util.ByteBlockPool;
|
||||
import org.apache.lucene.util.BytesRef;
|
||||
import org.apache.lucene.util.BytesRefHash;
|
||||
import org.apache.lucene.util.PerReaderTermState;
|
||||
import org.apache.lucene.util.TermContext;
|
||||
import org.apache.lucene.util.RamUsageEstimator;
|
||||
import org.apache.lucene.util.BytesRefHash.DirectBytesStartArray;
|
||||
|
||||
|
@ -77,7 +77,7 @@ class ConstantScoreAutoRewrite extends TermCollectingRewrite<BooleanQuery> {
|
|||
}
|
||||
|
||||
@Override
|
||||
protected void addClause(BooleanQuery topLevel, Term term, int docFreq, float boost /*ignored*/, PerReaderTermState states) {
|
||||
protected void addClause(BooleanQuery topLevel, Term term, int docFreq, float boost /*ignored*/, TermContext states) {
|
||||
topLevel.add(new TermQuery(term, states), BooleanClause.Occur.SHOULD);
|
||||
}
|
||||
|
||||
|
@ -140,9 +140,9 @@ class ConstantScoreAutoRewrite extends TermCollectingRewrite<BooleanQuery> {
|
|||
assert termState != null;
|
||||
if (pos < 0) {
|
||||
pos = (-pos)-1;
|
||||
array.termState[pos].register(termState, readerContext.ord, termsEnum.docFreq());
|
||||
array.termState[pos].register(termState, readerContext.ord, termsEnum.docFreq(), termsEnum.totalTermFreq());
|
||||
} else {
|
||||
array.termState[pos] = new PerReaderTermState(topReaderContext, termState, readerContext.ord, termsEnum.docFreq());
|
||||
array.termState[pos] = new TermContext(topReaderContext, termState, readerContext.ord, termsEnum.docFreq(), termsEnum.totalTermFreq());
|
||||
}
|
||||
return true;
|
||||
}
|
||||
|
@ -183,9 +183,9 @@ class ConstantScoreAutoRewrite extends TermCollectingRewrite<BooleanQuery> {
|
|||
return true;
|
||||
}
|
||||
|
||||
/** Special implementation of BytesStartArray that keeps parallel arrays for {@link PerReaderTermState} */
|
||||
/** Special implementation of BytesStartArray that keeps parallel arrays for {@link TermContext} */
|
||||
static final class TermStateByteStart extends DirectBytesStartArray {
|
||||
PerReaderTermState[] termState;
|
||||
TermContext[] termState;
|
||||
|
||||
public TermStateByteStart(int initSize) {
|
||||
super(initSize);
|
||||
|
@ -194,7 +194,7 @@ class ConstantScoreAutoRewrite extends TermCollectingRewrite<BooleanQuery> {
|
|||
@Override
|
||||
public int[] init() {
|
||||
final int[] ord = super.init();
|
||||
termState = new PerReaderTermState[ArrayUtil.oversize(ord.length, RamUsageEstimator.NUM_BYTES_OBJECT_REF)];
|
||||
termState = new TermContext[ArrayUtil.oversize(ord.length, RamUsageEstimator.NUM_BYTES_OBJECT_REF)];
|
||||
assert termState.length >= ord.length;
|
||||
return ord;
|
||||
}
|
||||
|
@ -203,7 +203,7 @@ class ConstantScoreAutoRewrite extends TermCollectingRewrite<BooleanQuery> {
|
|||
public int[] grow() {
|
||||
final int[] ord = super.grow();
|
||||
if (termState.length < ord.length) {
|
||||
PerReaderTermState[] tmpTermState = new PerReaderTermState[ArrayUtil.oversize(ord.length, RamUsageEstimator.NUM_BYTES_OBJECT_REF)];
|
||||
TermContext[] tmpTermState = new TermContext[ArrayUtil.oversize(ord.length, RamUsageEstimator.NUM_BYTES_OBJECT_REF)];
|
||||
System.arraycopy(termState, 0, tmpTermState, 0, termState.length);
|
||||
termState = tmpTermState;
|
||||
}
|
||||
|
|
|
@ -110,24 +110,19 @@ public class ConstantScoreQuery extends Query {
|
|||
}
|
||||
|
||||
@Override
|
||||
public float getValue() {
|
||||
return queryWeight;
|
||||
}
|
||||
|
||||
@Override
|
||||
public float sumOfSquaredWeights() throws IOException {
|
||||
public float getValueForNormalization() throws IOException {
|
||||
// we calculate sumOfSquaredWeights of the inner weight, but ignore it (just to initialize everything)
|
||||
if (innerWeight != null) innerWeight.sumOfSquaredWeights();
|
||||
if (innerWeight != null) innerWeight.getValueForNormalization();
|
||||
queryWeight = getBoost();
|
||||
return queryWeight * queryWeight;
|
||||
}
|
||||
|
||||
@Override
|
||||
public void normalize(float norm) {
|
||||
this.queryNorm = norm;
|
||||
public void normalize(float norm, float topLevelBoost) {
|
||||
this.queryNorm = norm * topLevelBoost;
|
||||
queryWeight *= this.queryNorm;
|
||||
// we normalize the inner weight, but ignore it (just to initialize everything)
|
||||
if (innerWeight != null) innerWeight.normalize(norm);
|
||||
if (innerWeight != null) innerWeight.normalize(norm, topLevelBoost);
|
||||
}
|
||||
|
||||
@Override
|
||||
|
@ -148,7 +143,7 @@ public class ConstantScoreQuery extends Query {
|
|||
if (disi == null) {
|
||||
return null;
|
||||
}
|
||||
return new ConstantScorer(disi, this);
|
||||
return new ConstantScorer(disi, this, queryWeight);
|
||||
}
|
||||
|
||||
@Override
|
||||
|
@ -181,9 +176,9 @@ public class ConstantScoreQuery extends Query {
|
|||
final DocIdSetIterator docIdSetIterator;
|
||||
final float theScore;
|
||||
|
||||
public ConstantScorer(DocIdSetIterator docIdSetIterator, Weight w) throws IOException {
|
||||
public ConstantScorer(DocIdSetIterator docIdSetIterator, Weight w, float theScore) throws IOException {
|
||||
super(w);
|
||||
theScore = w.getValue();
|
||||
this.theScore = theScore;
|
||||
this.docIdSetIterator = docIdSetIterator;
|
||||
}
|
||||
|
||||
|
@ -212,7 +207,7 @@ public class ConstantScoreQuery extends Query {
|
|||
@Override
|
||||
public void setScorer(Scorer scorer) throws IOException {
|
||||
// we must wrap again here, but using the scorer passed in as parameter:
|
||||
collector.setScorer(new ConstantScorer(scorer, ConstantScorer.this.weight));
|
||||
collector.setScorer(new ConstantScorer(scorer, ConstantScorer.this.weight, ConstantScorer.this.theScore));
|
||||
}
|
||||
|
||||
@Override
|
||||
|
|
|
@ -20,7 +20,7 @@ import org.apache.lucene.index.FieldInvertState;
|
|||
*/
|
||||
|
||||
/** Expert: Default scoring implementation. */
|
||||
public class DefaultSimilarity extends Similarity {
|
||||
public class DefaultSimilarity extends TFIDFSimilarity {
|
||||
|
||||
/** Implemented as
|
||||
* <code>state.getBoost()*lengthNorm(numTerms)</code>, where
|
||||
|
@ -31,13 +31,13 @@ public class DefaultSimilarity extends Similarity {
|
|||
*
|
||||
* @lucene.experimental */
|
||||
@Override
|
||||
public float computeNorm(FieldInvertState state) {
|
||||
public byte computeNorm(FieldInvertState state) {
|
||||
final int numTerms;
|
||||
if (discountOverlaps)
|
||||
numTerms = state.getLength() - state.getNumOverlap();
|
||||
else
|
||||
numTerms = state.getLength();
|
||||
return state.getBoost() * ((float) (1.0 / Math.sqrt(numTerms)));
|
||||
return encodeNormValue(state.getBoost() * ((float) (1.0 / Math.sqrt(numTerms))));
|
||||
}
|
||||
|
||||
/** Implemented as <code>sqrt(freq)</code>. */
|
||||
|
|
|
@ -110,16 +110,12 @@ public class DisjunctionMaxQuery extends Query implements Iterable<Query> {
|
|||
@Override
|
||||
public Query getQuery() { return DisjunctionMaxQuery.this; }
|
||||
|
||||
/** Return our boost */
|
||||
@Override
|
||||
public float getValue() { return getBoost(); }
|
||||
|
||||
/** Compute the sub of squared weights of us applied to our subqueries. Used for normalization. */
|
||||
@Override
|
||||
public float sumOfSquaredWeights() throws IOException {
|
||||
public float getValueForNormalization() throws IOException {
|
||||
float max = 0.0f, sum = 0.0f;
|
||||
for (Weight currentWeight : weights) {
|
||||
float sub = currentWeight.sumOfSquaredWeights();
|
||||
float sub = currentWeight.getValueForNormalization();
|
||||
sum += sub;
|
||||
max = Math.max(max, sub);
|
||||
|
||||
|
@ -130,10 +126,10 @@ public class DisjunctionMaxQuery extends Query implements Iterable<Query> {
|
|||
|
||||
/** Apply the computed normalization factor to our subqueries */
|
||||
@Override
|
||||
public void normalize(float norm) {
|
||||
norm *= getBoost(); // Incorporate our boost
|
||||
public void normalize(float norm, float topLevelBoost) {
|
||||
topLevelBoost *= getBoost(); // Incorporate our boost
|
||||
for (Weight wt : weights) {
|
||||
wt.normalize(norm);
|
||||
wt.normalize(norm, topLevelBoost);
|
||||
}
|
||||
}
|
||||
|
||||
|
|
|
@ -23,12 +23,6 @@ import java.util.Arrays;
|
|||
import org.apache.lucene.index.*;
|
||||
|
||||
final class ExactPhraseScorer extends Scorer {
|
||||
private final byte[] norms;
|
||||
private final float value;
|
||||
|
||||
private static final int SCORE_CACHE_SIZE = 32;
|
||||
private final float[] scoreCache = new float[SCORE_CACHE_SIZE];
|
||||
|
||||
private final int endMinus1;
|
||||
|
||||
private final static int CHUNK = 4096;
|
||||
|
@ -60,14 +54,12 @@ final class ExactPhraseScorer extends Scorer {
|
|||
private int docID = -1;
|
||||
private int freq;
|
||||
|
||||
private final Similarity similarity;
|
||||
private final Similarity.ExactDocScorer docScorer;
|
||||
|
||||
ExactPhraseScorer(Weight weight, PhraseQuery.PostingsAndFreq[] postings,
|
||||
Similarity similarity, byte[] norms) throws IOException {
|
||||
Similarity.ExactDocScorer docScorer) throws IOException {
|
||||
super(weight);
|
||||
this.similarity = similarity;
|
||||
this.norms = norms;
|
||||
this.value = weight.getValue();
|
||||
this.docScorer = docScorer;
|
||||
|
||||
chunkStates = new ChunkState[postings.length];
|
||||
|
||||
|
@ -88,10 +80,6 @@ final class ExactPhraseScorer extends Scorer {
|
|||
return;
|
||||
}
|
||||
}
|
||||
|
||||
for (int i = 0; i < SCORE_CACHE_SIZE; i++) {
|
||||
scoreCache[i] = similarity.tf((float) i) * value;
|
||||
}
|
||||
}
|
||||
|
||||
@Override
|
||||
|
@ -206,13 +194,7 @@ final class ExactPhraseScorer extends Scorer {
|
|||
|
||||
@Override
|
||||
public float score() throws IOException {
|
||||
final float raw; // raw score
|
||||
if (freq < SCORE_CACHE_SIZE) {
|
||||
raw = scoreCache[freq];
|
||||
} else {
|
||||
raw = similarity.tf((float) freq) * value;
|
||||
}
|
||||
return norms == null ? raw : raw * similarity.decodeNormValue(norms[docID]); // normalize
|
||||
return docScorer.score(docID, freq);
|
||||
}
|
||||
|
||||
private int phraseFreq() throws IOException {
|
||||
|
|
|
@ -125,25 +125,4 @@ public class Explanation {
|
|||
|
||||
return buffer.toString();
|
||||
}
|
||||
|
||||
/**
|
||||
* Small Util class used to pass both an idf factor as well as an
|
||||
* explanation for that factor.
|
||||
*
|
||||
* This class will likely be held on a {@link Weight}, so be aware
|
||||
* before storing any large or un-serializable fields.
|
||||
*
|
||||
*/
|
||||
public static abstract class IDFExplanation {
|
||||
/**
|
||||
* @return the idf factor
|
||||
*/
|
||||
public abstract float getIdf();
|
||||
/**
|
||||
* This should be calculated lazily if possible.
|
||||
*
|
||||
* @return the explanation for the idf factor.
|
||||
*/
|
||||
public abstract String explain();
|
||||
}
|
||||
}
|
||||
|
|
|
@ -63,21 +63,15 @@ extends Query {
|
|||
public Weight createWeight(final IndexSearcher searcher) throws IOException {
|
||||
final Weight weight = query.createWeight (searcher);
|
||||
return new Weight() {
|
||||
private float value;
|
||||
|
||||
// pass these methods through to enclosed query's weight
|
||||
@Override
|
||||
public float getValue() { return value; }
|
||||
|
||||
@Override
|
||||
public float sumOfSquaredWeights() throws IOException {
|
||||
return weight.sumOfSquaredWeights() * getBoost() * getBoost();
|
||||
public float getValueForNormalization() throws IOException {
|
||||
return weight.getValueForNormalization() * getBoost() * getBoost();
|
||||
}
|
||||
|
||||
@Override
|
||||
public void normalize (float v) {
|
||||
weight.normalize(v);
|
||||
value = weight.getValue() * getBoost();
|
||||
public void normalize (float norm, float topLevelBoost) {
|
||||
weight.normalize(norm, topLevelBoost);
|
||||
}
|
||||
|
||||
@Override
|
||||
|
|
|
@ -674,11 +674,11 @@ public class IndexSearcher {
|
|||
public Weight createNormalizedWeight(Query query) throws IOException {
|
||||
query = rewrite(query);
|
||||
Weight weight = query.createWeight(this);
|
||||
float sum = weight.sumOfSquaredWeights();
|
||||
float norm = getSimilarityProvider().queryNorm(sum);
|
||||
float v = weight.getValueForNormalization();
|
||||
float norm = getSimilarityProvider().queryNorm(v);
|
||||
if (Float.isInfinite(norm) || Float.isNaN(norm))
|
||||
norm = 1.0f;
|
||||
weight.normalize(norm);
|
||||
weight.normalize(norm, 1.0f);
|
||||
return weight;
|
||||
}
|
||||
|
||||
|
|
|
@ -32,35 +32,17 @@ import java.io.IOException;
|
|||
*/
|
||||
public class MatchAllDocsQuery extends Query {
|
||||
|
||||
public MatchAllDocsQuery() {
|
||||
this(null);
|
||||
}
|
||||
|
||||
private final String normsField;
|
||||
|
||||
/**
|
||||
* @param normsField Field used for normalization factor (document boost). Null if nothing.
|
||||
*/
|
||||
public MatchAllDocsQuery(String normsField) {
|
||||
this.normsField = normsField;
|
||||
}
|
||||
|
||||
private class MatchAllScorer extends Scorer {
|
||||
final float score;
|
||||
final byte[] norms;
|
||||
private int doc = -1;
|
||||
private final int maxDoc;
|
||||
private final Bits liveDocs;
|
||||
private final Similarity similarity;
|
||||
|
||||
MatchAllScorer(IndexReader reader, Similarity similarity, Weight w,
|
||||
byte[] norms) throws IOException {
|
||||
MatchAllScorer(IndexReader reader, Weight w, float score) throws IOException {
|
||||
super(w);
|
||||
this.similarity = similarity;
|
||||
liveDocs = reader.getLiveDocs();
|
||||
score = w.getValue();
|
||||
this.score = score;
|
||||
maxDoc = reader.maxDoc();
|
||||
this.norms = norms;
|
||||
}
|
||||
|
||||
@Override
|
||||
|
@ -82,7 +64,7 @@ public class MatchAllDocsQuery extends Query {
|
|||
|
||||
@Override
|
||||
public float score() {
|
||||
return norms == null ? score : score * similarity.decodeNormValue(norms[docID()]);
|
||||
return score;
|
||||
}
|
||||
|
||||
@Override
|
||||
|
@ -93,12 +75,10 @@ public class MatchAllDocsQuery extends Query {
|
|||
}
|
||||
|
||||
private class MatchAllDocsWeight extends Weight {
|
||||
private Similarity similarity;
|
||||
private float queryWeight;
|
||||
private float queryNorm;
|
||||
|
||||
public MatchAllDocsWeight(IndexSearcher searcher) {
|
||||
this.similarity = normsField == null ? null : searcher.getSimilarityProvider().get(normsField);
|
||||
}
|
||||
|
||||
@Override
|
||||
|
@ -112,33 +92,27 @@ public class MatchAllDocsQuery extends Query {
|
|||
}
|
||||
|
||||
@Override
|
||||
public float getValue() {
|
||||
return queryWeight;
|
||||
}
|
||||
|
||||
@Override
|
||||
public float sumOfSquaredWeights() {
|
||||
public float getValueForNormalization() {
|
||||
queryWeight = getBoost();
|
||||
return queryWeight * queryWeight;
|
||||
}
|
||||
|
||||
@Override
|
||||
public void normalize(float queryNorm) {
|
||||
this.queryNorm = queryNorm;
|
||||
public void normalize(float queryNorm, float topLevelBoost) {
|
||||
this.queryNorm = queryNorm * topLevelBoost;
|
||||
queryWeight *= this.queryNorm;
|
||||
}
|
||||
|
||||
@Override
|
||||
public Scorer scorer(AtomicReaderContext context, ScorerContext scorerContext) throws IOException {
|
||||
return new MatchAllScorer(context.reader, similarity, this,
|
||||
normsField != null ? context.reader.norms(normsField) : null);
|
||||
return new MatchAllScorer(context.reader, this, queryWeight);
|
||||
}
|
||||
|
||||
@Override
|
||||
public Explanation explain(AtomicReaderContext context, int doc) {
|
||||
// explain query weight
|
||||
Explanation queryExpl = new ComplexExplanation
|
||||
(true, getValue(), "MatchAllDocsQuery, product of:");
|
||||
(true, queryWeight, "MatchAllDocsQuery, product of:");
|
||||
if (getBoost() != 1.0f) {
|
||||
queryExpl.addDetail(new Explanation(getBoost(),"boost"));
|
||||
}
|
||||
|
|
|
@ -22,12 +22,14 @@ import java.util.*;
|
|||
|
||||
import org.apache.lucene.index.IndexReader;
|
||||
import org.apache.lucene.index.IndexReader.AtomicReaderContext;
|
||||
import org.apache.lucene.index.IndexReader.ReaderContext;
|
||||
import org.apache.lucene.index.Term;
|
||||
import org.apache.lucene.index.DocsEnum;
|
||||
import org.apache.lucene.index.DocsAndPositionsEnum;
|
||||
import org.apache.lucene.search.Explanation.IDFExplanation;
|
||||
import org.apache.lucene.search.Similarity.SloppyDocScorer;
|
||||
import org.apache.lucene.util.ArrayUtil;
|
||||
import org.apache.lucene.util.BytesRef;
|
||||
import org.apache.lucene.util.TermContext;
|
||||
import org.apache.lucene.util.ToStringUtils;
|
||||
import org.apache.lucene.util.PriorityQueue;
|
||||
import org.apache.lucene.util.Bits;
|
||||
|
@ -129,45 +131,35 @@ public class MultiPhraseQuery extends Query {
|
|||
|
||||
|
||||
private class MultiPhraseWeight extends Weight {
|
||||
private Similarity similarity;
|
||||
private float value;
|
||||
private final IDFExplanation idfExp;
|
||||
private float idf;
|
||||
private float queryNorm;
|
||||
private float queryWeight;
|
||||
private final Similarity similarity;
|
||||
private final Similarity.Stats stats;
|
||||
|
||||
public MultiPhraseWeight(IndexSearcher searcher)
|
||||
throws IOException {
|
||||
this.similarity = searcher.getSimilarityProvider().get(field);
|
||||
final ReaderContext context = searcher.getTopReaderContext();
|
||||
|
||||
// compute idf
|
||||
ArrayList<Term> allTerms = new ArrayList<Term>();
|
||||
ArrayList<TermContext> allTerms = new ArrayList<TermContext>();
|
||||
for(final Term[] terms: termArrays) {
|
||||
for (Term term: terms) {
|
||||
allTerms.add(term);
|
||||
allTerms.add(TermContext.build(context, term, true));
|
||||
}
|
||||
}
|
||||
idfExp = similarity.idfExplain(allTerms, searcher);
|
||||
idf = idfExp.getIdf();
|
||||
stats = similarity.computeStats(searcher, field, getBoost(), allTerms.toArray(new TermContext[allTerms.size()]));
|
||||
}
|
||||
|
||||
@Override
|
||||
public Query getQuery() { return MultiPhraseQuery.this; }
|
||||
|
||||
@Override
|
||||
public float getValue() { return value; }
|
||||
|
||||
@Override
|
||||
public float sumOfSquaredWeights() {
|
||||
queryWeight = idf * getBoost(); // compute query weight
|
||||
return queryWeight * queryWeight; // square it
|
||||
public float getValueForNormalization() {
|
||||
return stats.getValueForNormalization();
|
||||
}
|
||||
|
||||
@Override
|
||||
public void normalize(float queryNorm) {
|
||||
this.queryNorm = queryNorm;
|
||||
queryWeight *= queryNorm; // normalize query weight
|
||||
value = queryWeight * idf; // idf for document
|
||||
public void normalize(float queryNorm, float topLevelBoost) {
|
||||
stats.normalize(queryNorm, topLevelBoost);
|
||||
}
|
||||
|
||||
@Override
|
||||
|
@ -222,8 +214,7 @@ public class MultiPhraseQuery extends Query {
|
|||
}
|
||||
|
||||
if (slop == 0) {
|
||||
ExactPhraseScorer s = new ExactPhraseScorer(this, postingsFreqs, similarity,
|
||||
reader.norms(field));
|
||||
ExactPhraseScorer s = new ExactPhraseScorer(this, postingsFreqs, similarity.exactDocScorer(stats, field, context));
|
||||
if (s.noDocs) {
|
||||
return null;
|
||||
} else {
|
||||
|
@ -231,84 +222,29 @@ public class MultiPhraseQuery extends Query {
|
|||
}
|
||||
} else {
|
||||
return new SloppyPhraseScorer(this, postingsFreqs, similarity,
|
||||
slop, reader.norms(field));
|
||||
slop, similarity.sloppyDocScorer(stats, field, context));
|
||||
}
|
||||
}
|
||||
|
||||
@Override
|
||||
public Explanation explain(AtomicReaderContext context, int doc)
|
||||
throws IOException {
|
||||
ComplexExplanation result = new ComplexExplanation();
|
||||
result.setDescription("weight("+getQuery()+" in "+doc+"), product of:");
|
||||
|
||||
Explanation idfExpl = new Explanation(idf, "idf(" + field + ":" + idfExp.explain() +")");
|
||||
|
||||
// explain query weight
|
||||
Explanation queryExpl = new Explanation();
|
||||
queryExpl.setDescription("queryWeight(" + getQuery() + "), product of:");
|
||||
|
||||
Explanation boostExpl = new Explanation(getBoost(), "boost");
|
||||
if (getBoost() != 1.0f)
|
||||
queryExpl.addDetail(boostExpl);
|
||||
|
||||
queryExpl.addDetail(idfExpl);
|
||||
|
||||
Explanation queryNormExpl = new Explanation(queryNorm,"queryNorm");
|
||||
queryExpl.addDetail(queryNormExpl);
|
||||
|
||||
queryExpl.setValue(boostExpl.getValue() *
|
||||
idfExpl.getValue() *
|
||||
queryNormExpl.getValue());
|
||||
|
||||
result.addDetail(queryExpl);
|
||||
|
||||
// explain field weight
|
||||
ComplexExplanation fieldExpl = new ComplexExplanation();
|
||||
fieldExpl.setDescription("fieldWeight("+getQuery()+" in "+doc+
|
||||
"), product of:");
|
||||
|
||||
public Explanation explain(AtomicReaderContext context, int doc) throws IOException {
|
||||
Scorer scorer = scorer(context, ScorerContext.def());
|
||||
if (scorer == null) {
|
||||
return new Explanation(0.0f, "no matching docs");
|
||||
if (scorer != null) {
|
||||
int newDoc = scorer.advance(doc);
|
||||
if (newDoc == doc) {
|
||||
float freq = scorer.freq();
|
||||
SloppyDocScorer docScorer = similarity.sloppyDocScorer(stats, field, context);
|
||||
ComplexExplanation result = new ComplexExplanation();
|
||||
result.setDescription("weight("+getQuery()+" in "+doc+") [" + similarity.getClass().getSimpleName() + "], result of:");
|
||||
Explanation scoreExplanation = docScorer.explain(doc, new Explanation(freq, "phraseFreq=" + freq));
|
||||
result.addDetail(scoreExplanation);
|
||||
result.setValue(scoreExplanation.getValue());
|
||||
result.setMatch(true);
|
||||
return result;
|
||||
}
|
||||
}
|
||||
|
||||
Explanation tfExplanation = new Explanation();
|
||||
int d = scorer.advance(doc);
|
||||
float phraseFreq;
|
||||
if (d == doc) {
|
||||
phraseFreq = scorer.freq();
|
||||
} else {
|
||||
phraseFreq = 0.0f;
|
||||
}
|
||||
|
||||
tfExplanation.setValue(similarity.tf(phraseFreq));
|
||||
tfExplanation.setDescription("tf(phraseFreq=" + phraseFreq + ")");
|
||||
fieldExpl.addDetail(tfExplanation);
|
||||
fieldExpl.addDetail(idfExpl);
|
||||
|
||||
Explanation fieldNormExpl = new Explanation();
|
||||
byte[] fieldNorms = context.reader.norms(field);
|
||||
float fieldNorm =
|
||||
fieldNorms!=null ? similarity.decodeNormValue(fieldNorms[doc]) : 1.0f;
|
||||
fieldNormExpl.setValue(fieldNorm);
|
||||
fieldNormExpl.setDescription("fieldNorm(field="+field+", doc="+doc+")");
|
||||
fieldExpl.addDetail(fieldNormExpl);
|
||||
|
||||
fieldExpl.setMatch(Boolean.valueOf(tfExplanation.isMatch()));
|
||||
fieldExpl.setValue(tfExplanation.getValue() *
|
||||
idfExpl.getValue() *
|
||||
fieldNormExpl.getValue());
|
||||
|
||||
result.addDetail(fieldExpl);
|
||||
result.setMatch(fieldExpl.getMatch());
|
||||
|
||||
// combine them
|
||||
result.setValue(queryExpl.getValue() * fieldExpl.getValue());
|
||||
|
||||
if (queryExpl.getValue() == 1.0f)
|
||||
return fieldExpl;
|
||||
|
||||
return result;
|
||||
return new ComplexExplanation(false, 0.0f, "no matching term");
|
||||
}
|
||||
}
|
||||
|
||||
|
|
|
@ -25,7 +25,7 @@ import org.apache.lucene.index.Terms;
|
|||
import org.apache.lucene.index.TermsEnum;
|
||||
import org.apache.lucene.queryParser.QueryParser;
|
||||
import org.apache.lucene.util.AttributeSource;
|
||||
import org.apache.lucene.util.PerReaderTermState;
|
||||
import org.apache.lucene.util.TermContext;
|
||||
|
||||
/**
|
||||
* An abstract {@link Query} that matches documents
|
||||
|
@ -154,7 +154,7 @@ public abstract class MultiTermQuery extends Query {
|
|||
}
|
||||
|
||||
@Override
|
||||
protected void addClause(BooleanQuery topLevel, Term term, int docCount, float boost, PerReaderTermState states) {
|
||||
protected void addClause(BooleanQuery topLevel, Term term, int docCount, float boost, TermContext states) {
|
||||
final TermQuery tq = new TermQuery(term, states);
|
||||
tq.setBoost(boost);
|
||||
topLevel.add(tq, BooleanClause.Occur.SHOULD);
|
||||
|
@ -195,7 +195,7 @@ public abstract class MultiTermQuery extends Query {
|
|||
}
|
||||
|
||||
@Override
|
||||
protected void addClause(BooleanQuery topLevel, Term term, int docFreq, float boost, PerReaderTermState states) {
|
||||
protected void addClause(BooleanQuery topLevel, Term term, int docFreq, float boost, TermContext states) {
|
||||
final Query q = new ConstantScoreQuery(new TermQuery(term, states));
|
||||
q.setBoost(boost);
|
||||
topLevel.add(q, BooleanClause.Occur.SHOULD);
|
||||
|
|
|
@ -22,10 +22,16 @@ import java.util.Set;
|
|||
import java.util.ArrayList;
|
||||
|
||||
import org.apache.lucene.index.IndexReader.AtomicReaderContext;
|
||||
import org.apache.lucene.index.IndexReader.ReaderContext;
|
||||
import org.apache.lucene.index.Term;
|
||||
import org.apache.lucene.index.DocsAndPositionsEnum;
|
||||
import org.apache.lucene.index.IndexReader;
|
||||
import org.apache.lucene.search.Explanation.IDFExplanation;
|
||||
import org.apache.lucene.index.TermState;
|
||||
import org.apache.lucene.index.Terms;
|
||||
import org.apache.lucene.index.TermsEnum;
|
||||
import org.apache.lucene.search.Similarity.SloppyDocScorer;
|
||||
import org.apache.lucene.util.BytesRef;
|
||||
import org.apache.lucene.util.TermContext;
|
||||
import org.apache.lucene.util.ToStringUtils;
|
||||
import org.apache.lucene.util.ArrayUtil;
|
||||
import org.apache.lucene.util.Bits;
|
||||
|
@ -171,18 +177,17 @@ public class PhraseQuery extends Query {
|
|||
|
||||
private class PhraseWeight extends Weight {
|
||||
private final Similarity similarity;
|
||||
private float value;
|
||||
private float idf;
|
||||
private float queryNorm;
|
||||
private float queryWeight;
|
||||
private IDFExplanation idfExp;
|
||||
private final Similarity.Stats stats;
|
||||
private transient TermContext states[];
|
||||
|
||||
public PhraseWeight(IndexSearcher searcher)
|
||||
throws IOException {
|
||||
this.similarity = searcher.getSimilarityProvider().get(field);
|
||||
|
||||
idfExp = similarity.idfExplain(terms, searcher);
|
||||
idf = idfExp.getIdf();
|
||||
final ReaderContext context = searcher.getTopReaderContext();
|
||||
states = new TermContext[terms.size()];
|
||||
for (int i = 0; i < terms.size(); i++)
|
||||
states[i] = TermContext.build(context, terms.get(i), true);
|
||||
stats = similarity.computeStats(searcher, field, getBoost(), states);
|
||||
}
|
||||
|
||||
@Override
|
||||
|
@ -192,19 +197,13 @@ public class PhraseQuery extends Query {
|
|||
public Query getQuery() { return PhraseQuery.this; }
|
||||
|
||||
@Override
|
||||
public float getValue() { return value; }
|
||||
|
||||
@Override
|
||||
public float sumOfSquaredWeights() {
|
||||
queryWeight = idf * getBoost(); // compute query weight
|
||||
return queryWeight * queryWeight; // square it
|
||||
public float getValueForNormalization() {
|
||||
return stats.getValueForNormalization();
|
||||
}
|
||||
|
||||
@Override
|
||||
public void normalize(float queryNorm) {
|
||||
this.queryNorm = queryNorm;
|
||||
queryWeight *= queryNorm; // normalize query weight
|
||||
value = queryWeight * idf; // idf for document
|
||||
public void normalize(float queryNorm, float topLevelBoost) {
|
||||
stats.normalize(queryNorm, topLevelBoost);
|
||||
}
|
||||
|
||||
@Override
|
||||
|
@ -216,21 +215,26 @@ public class PhraseQuery extends Query {
|
|||
PostingsAndFreq[] postingsFreqs = new PostingsAndFreq[terms.size()];
|
||||
for (int i = 0; i < terms.size(); i++) {
|
||||
final Term t = terms.get(i);
|
||||
final TermState state = states[i].get(context.ord);
|
||||
if (state == null) { /* term doesnt exist in this segment */
|
||||
assert termNotInReader(reader, field, t.bytes()) : "no termstate found but term exists in reader";
|
||||
return null;
|
||||
}
|
||||
DocsAndPositionsEnum postingsEnum = reader.termPositionsEnum(liveDocs,
|
||||
t.field(),
|
||||
t.bytes());
|
||||
t.bytes(),
|
||||
state);
|
||||
// PhraseQuery on a field that did not index
|
||||
// positions.
|
||||
if (postingsEnum == null) {
|
||||
if (reader.termDocsEnum(liveDocs, t.field(), t.bytes()) != null) {
|
||||
// term does exist, but has no positions
|
||||
throw new IllegalStateException("field \"" + t.field() + "\" was indexed with Field.omitTermFreqAndPositions=true; cannot run PhraseQuery (term=" + t.text() + ")");
|
||||
} else {
|
||||
// term does not exist
|
||||
return null;
|
||||
}
|
||||
assert (reader.termDocsEnum(liveDocs, t.field(), t.bytes(), state) != null) : "termstate found but no term exists in reader";
|
||||
// term does exist, but has no positions
|
||||
throw new IllegalStateException("field \"" + t.field() + "\" was indexed with Field.omitTermFreqAndPositions=true; cannot run PhraseQuery (term=" + t.text() + ")");
|
||||
}
|
||||
postingsFreqs[i] = new PostingsAndFreq(postingsEnum, reader.docFreq(t.field(), t.bytes()), positions.get(i).intValue(), t);
|
||||
// get the docFreq without seeking
|
||||
TermsEnum te = reader.fields().terms(field).getThreadTermsEnum();
|
||||
te.seekExact(t.bytes(), state);
|
||||
postingsFreqs[i] = new PostingsAndFreq(postingsEnum, te.docFreq(), positions.get(i).intValue(), t);
|
||||
}
|
||||
|
||||
// sort by increasing docFreq order
|
||||
|
@ -239,8 +243,7 @@ public class PhraseQuery extends Query {
|
|||
}
|
||||
|
||||
if (slop == 0) { // optimize exact case
|
||||
ExactPhraseScorer s = new ExactPhraseScorer(this, postingsFreqs, similarity,
|
||||
reader.norms(field));
|
||||
ExactPhraseScorer s = new ExactPhraseScorer(this, postingsFreqs, similarity.exactDocScorer(stats, field, context));
|
||||
if (s.noDocs) {
|
||||
return null;
|
||||
} else {
|
||||
|
@ -248,96 +251,35 @@ public class PhraseQuery extends Query {
|
|||
}
|
||||
} else {
|
||||
return
|
||||
new SloppyPhraseScorer(this, postingsFreqs, similarity, slop,
|
||||
reader.norms(field));
|
||||
new SloppyPhraseScorer(this, postingsFreqs, similarity, slop, similarity.sloppyDocScorer(stats, field, context));
|
||||
}
|
||||
}
|
||||
|
||||
private boolean termNotInReader(IndexReader reader, String field, BytesRef bytes) throws IOException {
|
||||
// only called from assert
|
||||
final Terms terms = reader.terms(field);
|
||||
return terms == null || terms.docFreq(bytes) == 0;
|
||||
}
|
||||
|
||||
@Override
|
||||
public Explanation explain(AtomicReaderContext context, int doc)
|
||||
throws IOException {
|
||||
|
||||
ComplexExplanation result = new ComplexExplanation();
|
||||
result.setDescription("weight("+getQuery()+" in "+doc+"), product of:");
|
||||
|
||||
StringBuilder docFreqs = new StringBuilder();
|
||||
StringBuilder query = new StringBuilder();
|
||||
query.append('\"');
|
||||
docFreqs.append(idfExp.explain());
|
||||
for (int i = 0; i < terms.size(); i++) {
|
||||
if (i != 0) {
|
||||
query.append(" ");
|
||||
}
|
||||
|
||||
Term term = terms.get(i);
|
||||
|
||||
query.append(term.text());
|
||||
}
|
||||
query.append('\"');
|
||||
|
||||
Explanation idfExpl =
|
||||
new Explanation(idf, "idf(" + field + ":" + docFreqs + ")");
|
||||
|
||||
// explain query weight
|
||||
Explanation queryExpl = new Explanation();
|
||||
queryExpl.setDescription("queryWeight(" + getQuery() + "), product of:");
|
||||
|
||||
Explanation boostExpl = new Explanation(getBoost(), "boost");
|
||||
if (getBoost() != 1.0f)
|
||||
queryExpl.addDetail(boostExpl);
|
||||
queryExpl.addDetail(idfExpl);
|
||||
|
||||
Explanation queryNormExpl = new Explanation(queryNorm,"queryNorm");
|
||||
queryExpl.addDetail(queryNormExpl);
|
||||
|
||||
queryExpl.setValue(boostExpl.getValue() *
|
||||
idfExpl.getValue() *
|
||||
queryNormExpl.getValue());
|
||||
|
||||
result.addDetail(queryExpl);
|
||||
|
||||
// explain field weight
|
||||
Explanation fieldExpl = new Explanation();
|
||||
fieldExpl.setDescription("fieldWeight("+field+":"+query+" in "+doc+
|
||||
"), product of:");
|
||||
|
||||
public Explanation explain(AtomicReaderContext context, int doc) throws IOException {
|
||||
Scorer scorer = scorer(context, ScorerContext.def());
|
||||
if (scorer == null) {
|
||||
return new Explanation(0.0f, "no matching docs");
|
||||
}
|
||||
Explanation tfExplanation = new Explanation();
|
||||
int d = scorer.advance(doc);
|
||||
float phraseFreq;
|
||||
if (d == doc) {
|
||||
phraseFreq = scorer.freq();
|
||||
} else {
|
||||
phraseFreq = 0.0f;
|
||||
if (scorer != null) {
|
||||
int newDoc = scorer.advance(doc);
|
||||
if (newDoc == doc) {
|
||||
float freq = scorer.freq();
|
||||
SloppyDocScorer docScorer = similarity.sloppyDocScorer(stats, field, context);
|
||||
ComplexExplanation result = new ComplexExplanation();
|
||||
result.setDescription("weight("+getQuery()+" in "+doc+") [" + similarity.getClass().getSimpleName() + "], result of:");
|
||||
Explanation scoreExplanation = docScorer.explain(doc, new Explanation(freq, "phraseFreq=" + freq));
|
||||
result.addDetail(scoreExplanation);
|
||||
result.setValue(scoreExplanation.getValue());
|
||||
result.setMatch(true);
|
||||
return result;
|
||||
}
|
||||
}
|
||||
|
||||
tfExplanation.setValue(similarity.tf(phraseFreq));
|
||||
tfExplanation.setDescription("tf(phraseFreq=" + phraseFreq + ")");
|
||||
|
||||
fieldExpl.addDetail(tfExplanation);
|
||||
fieldExpl.addDetail(idfExpl);
|
||||
|
||||
Explanation fieldNormExpl = new Explanation();
|
||||
byte[] fieldNorms = context.reader.norms(field);
|
||||
float fieldNorm =
|
||||
fieldNorms!=null ? similarity.decodeNormValue(fieldNorms[doc]) : 1.0f;
|
||||
fieldNormExpl.setValue(fieldNorm);
|
||||
fieldNormExpl.setDescription("fieldNorm(field="+field+", doc="+doc+")");
|
||||
fieldExpl.addDetail(fieldNormExpl);
|
||||
|
||||
fieldExpl.setValue(tfExplanation.getValue() *
|
||||
idfExpl.getValue() *
|
||||
fieldNormExpl.getValue());
|
||||
|
||||
result.addDetail(fieldExpl);
|
||||
|
||||
// combine them
|
||||
result.setValue(queryExpl.getValue() * fieldExpl.getValue());
|
||||
result.setMatch(tfExplanation.isMatch());
|
||||
return result;
|
||||
return new ComplexExplanation(false, 0.0f, "no matching term");
|
||||
}
|
||||
}
|
||||
|
||||
|
|
|
@ -30,9 +30,6 @@ import java.io.IOException;
|
|||
* means a match.
|
||||
*/
|
||||
abstract class PhraseScorer extends Scorer {
|
||||
protected byte[] norms;
|
||||
protected float value;
|
||||
|
||||
private boolean firstTime = true;
|
||||
private boolean more = true;
|
||||
protected PhraseQueue pq;
|
||||
|
@ -40,14 +37,12 @@ abstract class PhraseScorer extends Scorer {
|
|||
|
||||
private float freq; //phrase frequency in current doc as computed by phraseFreq().
|
||||
|
||||
protected final Similarity similarity;
|
||||
protected final Similarity.SloppyDocScorer docScorer;
|
||||
|
||||
PhraseScorer(Weight weight, PhraseQuery.PostingsAndFreq[] postings,
|
||||
Similarity similarity, byte[] norms) {
|
||||
Similarity.SloppyDocScorer docScorer) throws IOException {
|
||||
super(weight);
|
||||
this.similarity = similarity;
|
||||
this.norms = norms;
|
||||
this.value = weight.getValue();
|
||||
this.docScorer = docScorer;
|
||||
|
||||
// convert tps to a list of phrase positions.
|
||||
// note: phrase-position differs from term-position in that its position
|
||||
|
@ -107,9 +102,7 @@ abstract class PhraseScorer extends Scorer {
|
|||
|
||||
@Override
|
||||
public float score() throws IOException {
|
||||
//System.out.println("scoring " + first.doc);
|
||||
float raw = similarity.tf(freq) * value; // raw score
|
||||
return norms == null ? raw : raw * similarity.decodeNormValue(norms[first.doc]); // normalize
|
||||
return docScorer.score(first.doc, freq);
|
||||
}
|
||||
|
||||
@Override
|
||||
|
|
|
@ -28,7 +28,7 @@ import org.apache.lucene.util.ArrayUtil;
|
|||
import org.apache.lucene.util.ByteBlockPool;
|
||||
import org.apache.lucene.util.BytesRef;
|
||||
import org.apache.lucene.util.BytesRefHash;
|
||||
import org.apache.lucene.util.PerReaderTermState;
|
||||
import org.apache.lucene.util.TermContext;
|
||||
import org.apache.lucene.util.RamUsageEstimator;
|
||||
import org.apache.lucene.util.BytesRefHash.DirectBytesStartArray;
|
||||
|
||||
|
@ -56,7 +56,7 @@ public abstract class ScoringRewrite<Q extends Query> extends TermCollectingRewr
|
|||
|
||||
@Override
|
||||
protected void addClause(BooleanQuery topLevel, Term term, int docCount,
|
||||
float boost, PerReaderTermState states) {
|
||||
float boost, TermContext states) {
|
||||
final TermQuery tq = new TermQuery(term, states);
|
||||
tq.setBoost(boost);
|
||||
topLevel.add(tq, BooleanClause.Occur.SHOULD);
|
||||
|
@ -117,7 +117,7 @@ public abstract class ScoringRewrite<Q extends Query> extends TermCollectingRewr
|
|||
if (size > 0) {
|
||||
final int sort[] = col.terms.sort(col.termsEnum.getComparator());
|
||||
final float[] boost = col.array.boost;
|
||||
final PerReaderTermState[] termStates = col.array.termState;
|
||||
final TermContext[] termStates = col.array.termState;
|
||||
for (int i = 0; i < size; i++) {
|
||||
final int pos = sort[i];
|
||||
final Term term = new Term(query.getField(), col.terms.get(pos, new BytesRef()));
|
||||
|
@ -150,12 +150,12 @@ public abstract class ScoringRewrite<Q extends Query> extends TermCollectingRewr
|
|||
if (e < 0 ) {
|
||||
// duplicate term: update docFreq
|
||||
final int pos = (-e)-1;
|
||||
array.termState[pos].register(state, readerContext.ord, termsEnum.docFreq());
|
||||
array.termState[pos].register(state, readerContext.ord, termsEnum.docFreq(), termsEnum.totalTermFreq());
|
||||
assert array.boost[pos] == boostAtt.getBoost() : "boost should be equal in all segment TermsEnums";
|
||||
} else {
|
||||
// new entry: we populate the entry initially
|
||||
array.boost[e] = boostAtt.getBoost();
|
||||
array.termState[e] = new PerReaderTermState(topReaderContext, state, readerContext.ord, termsEnum.docFreq());
|
||||
array.termState[e] = new TermContext(topReaderContext, state, readerContext.ord, termsEnum.docFreq(), termsEnum.totalTermFreq());
|
||||
ScoringRewrite.this.checkMaxClauseCount(terms.size());
|
||||
}
|
||||
return true;
|
||||
|
@ -165,7 +165,7 @@ public abstract class ScoringRewrite<Q extends Query> extends TermCollectingRewr
|
|||
/** Special implementation of BytesStartArray that keeps parallel arrays for boost and docFreq */
|
||||
static final class TermFreqBoostByteStart extends DirectBytesStartArray {
|
||||
float[] boost;
|
||||
PerReaderTermState[] termState;
|
||||
TermContext[] termState;
|
||||
|
||||
public TermFreqBoostByteStart(int initSize) {
|
||||
super(initSize);
|
||||
|
@ -175,7 +175,7 @@ public abstract class ScoringRewrite<Q extends Query> extends TermCollectingRewr
|
|||
public int[] init() {
|
||||
final int[] ord = super.init();
|
||||
boost = new float[ArrayUtil.oversize(ord.length, RamUsageEstimator.NUM_BYTES_FLOAT)];
|
||||
termState = new PerReaderTermState[ArrayUtil.oversize(ord.length, RamUsageEstimator.NUM_BYTES_OBJECT_REF)];
|
||||
termState = new TermContext[ArrayUtil.oversize(ord.length, RamUsageEstimator.NUM_BYTES_OBJECT_REF)];
|
||||
assert termState.length >= ord.length && boost.length >= ord.length;
|
||||
return ord;
|
||||
}
|
||||
|
@ -185,7 +185,7 @@ public abstract class ScoringRewrite<Q extends Query> extends TermCollectingRewr
|
|||
final int[] ord = super.grow();
|
||||
boost = ArrayUtil.grow(boost, ord.length);
|
||||
if (termState.length < ord.length) {
|
||||
PerReaderTermState[] tmpTermState = new PerReaderTermState[ArrayUtil.oversize(ord.length, RamUsageEstimator.NUM_BYTES_OBJECT_REF)];
|
||||
TermContext[] tmpTermState = new TermContext[ArrayUtil.oversize(ord.length, RamUsageEstimator.NUM_BYTES_OBJECT_REF)];
|
||||
System.arraycopy(termState, 0, tmpTermState, 0, termState.length);
|
||||
termState = tmpTermState;
|
||||
}
|
||||
|
|
|
@ -19,594 +19,111 @@ package org.apache.lucene.search;
|
|||
|
||||
|
||||
import java.io.IOException;
|
||||
import java.util.Collection;
|
||||
|
||||
import org.apache.lucene.document.IndexDocValuesField; // javadoc
|
||||
import org.apache.lucene.index.FieldInvertState;
|
||||
import org.apache.lucene.index.Term;
|
||||
import org.apache.lucene.search.Explanation.IDFExplanation;
|
||||
import org.apache.lucene.util.SmallFloat;
|
||||
import org.apache.lucene.index.IndexReader; // javadoc
|
||||
import org.apache.lucene.index.IndexReader.AtomicReaderContext;
|
||||
import org.apache.lucene.index.Terms; // javadoc
|
||||
import org.apache.lucene.search.spans.SpanQuery; // javadoc
|
||||
import org.apache.lucene.util.SmallFloat; // javadoc
|
||||
import org.apache.lucene.util.TermContext;
|
||||
|
||||
|
||||
/**
|
||||
* Similarity defines the components of Lucene scoring.
|
||||
* <p>
|
||||
* Expert: Scoring API.
|
||||
*
|
||||
* <p>Similarity defines the components of Lucene scoring.
|
||||
* Overriding computation of these components is a convenient
|
||||
* way to alter Lucene scoring.
|
||||
*
|
||||
* <p>Suggested reading:
|
||||
* <a href="http://nlp.stanford.edu/IR-book/html/htmledition/queries-as-vectors-1.html">
|
||||
* Introduction To Information Retrieval, Chapter 6</a>.
|
||||
*
|
||||
* <p>The following describes how Lucene scoring evolves from
|
||||
* underlying information retrieval models to (efficient) implementation.
|
||||
* We first brief on <i>VSM Score</i>,
|
||||
* then derive from it <i>Lucene's Conceptual Scoring Formula</i>,
|
||||
* from which, finally, evolves <i>Lucene's Practical Scoring Function</i>
|
||||
* (the latter is connected directly with Lucene classes and methods).
|
||||
*
|
||||
* <p>Lucene combines
|
||||
* <a href="http://en.wikipedia.org/wiki/Standard_Boolean_model">
|
||||
* Boolean model (BM) of Information Retrieval</a>
|
||||
* with
|
||||
* <a href="http://en.wikipedia.org/wiki/Vector_Space_Model">
|
||||
* Vector Space Model (VSM) of Information Retrieval</a> -
|
||||
* documents "approved" by BM are scored by VSM.
|
||||
*
|
||||
* <p>In VSM, documents and queries are represented as
|
||||
* weighted vectors in a multi-dimensional space,
|
||||
* where each distinct index term is a dimension,
|
||||
* and weights are
|
||||
* <a href="http://en.wikipedia.org/wiki/Tfidf">Tf-idf</a> values.
|
||||
*
|
||||
* <p>VSM does not require weights to be <i>Tf-idf</i> values,
|
||||
* but <i>Tf-idf</i> values are believed to produce search results of high quality,
|
||||
* and so Lucene is using <i>Tf-idf</i>.
|
||||
* <i>Tf</i> and <i>Idf</i> are described in more detail below,
|
||||
* but for now, for completion, let's just say that
|
||||
* for given term <i>t</i> and document (or query) <i>x</i>,
|
||||
* <i>Tf(t,x)</i> varies with the number of occurrences of term <i>t</i> in <i>x</i>
|
||||
* (when one increases so does the other) and
|
||||
* <i>idf(t)</i> similarly varies with the inverse of the
|
||||
* number of index documents containing term <i>t</i>.
|
||||
*
|
||||
* <p><i>VSM score</i> of document <i>d</i> for query <i>q</i> is the
|
||||
* <a href="http://en.wikipedia.org/wiki/Cosine_similarity">
|
||||
* Cosine Similarity</a>
|
||||
* of the weighted query vectors <i>V(q)</i> and <i>V(d)</i>:
|
||||
*
|
||||
* <br> <br>
|
||||
* <table cellpadding="2" cellspacing="2" border="0" align="center">
|
||||
* <tr><td>
|
||||
* <table cellpadding="1" cellspacing="0" border="1" align="center">
|
||||
* <tr><td>
|
||||
* <table cellpadding="2" cellspacing="2" border="0" align="center">
|
||||
* <tr>
|
||||
* <td valign="middle" align="right" rowspan="1">
|
||||
* cosine-similarity(q,d) =
|
||||
* </td>
|
||||
* <td valign="middle" align="center">
|
||||
* <table>
|
||||
* <tr><td align="center"><small>V(q) · V(d)</small></td></tr>
|
||||
* <tr><td align="center">–––––––––</td></tr>
|
||||
* <tr><td align="center"><small>|V(q)| |V(d)|</small></td></tr>
|
||||
* </table>
|
||||
* </td>
|
||||
* </tr>
|
||||
* </table>
|
||||
* </td></tr>
|
||||
* </table>
|
||||
* </td></tr>
|
||||
* <tr><td>
|
||||
* <center><font=-1><u>VSM Score</u></font></center>
|
||||
* </td></tr>
|
||||
* </table>
|
||||
* <br> <br>
|
||||
*
|
||||
*
|
||||
* Where <i>V(q)</i> · <i>V(d)</i> is the
|
||||
* <a href="http://en.wikipedia.org/wiki/Dot_product">dot product</a>
|
||||
* of the weighted vectors,
|
||||
* and <i>|V(q)|</i> and <i>|V(d)|</i> are their
|
||||
* <a href="http://en.wikipedia.org/wiki/Euclidean_norm#Euclidean_norm">Euclidean norms</a>.
|
||||
*
|
||||
* <p>Note: the above equation can be viewed as the dot product of
|
||||
* the normalized weighted vectors, in the sense that dividing
|
||||
* <i>V(q)</i> by its euclidean norm is normalizing it to a unit vector.
|
||||
*
|
||||
* <p>Lucene refines <i>VSM score</i> for both search quality and usability:
|
||||
* <ul>
|
||||
* <li>Normalizing <i>V(d)</i> to the unit vector is known to be problematic in that
|
||||
* it removes all document length information.
|
||||
* For some documents removing this info is probably ok,
|
||||
* e.g. a document made by duplicating a certain paragraph <i>10</i> times,
|
||||
* especially if that paragraph is made of distinct terms.
|
||||
* But for a document which contains no duplicated paragraphs,
|
||||
* this might be wrong.
|
||||
* To avoid this problem, a different document length normalization
|
||||
* factor is used, which normalizes to a vector equal to or larger
|
||||
* than the unit vector: <i>doc-len-norm(d)</i>.
|
||||
* </li>
|
||||
*
|
||||
* <li>At indexing, users can specify that certain documents are more
|
||||
* important than others, by assigning a document boost.
|
||||
* For this, the score of each document is also multiplied by its boost value
|
||||
* <i>doc-boost(d)</i>.
|
||||
* </li>
|
||||
*
|
||||
* <li>Lucene is field based, hence each query term applies to a single
|
||||
* field, document length normalization is by the length of the certain field,
|
||||
* and in addition to document boost there are also document fields boosts.
|
||||
* </li>
|
||||
*
|
||||
* <li>The same field can be added to a document during indexing several times,
|
||||
* and so the boost of that field is the multiplication of the boosts of
|
||||
* the separate additions (or parts) of that field within the document.
|
||||
* </li>
|
||||
*
|
||||
* <li>At search time users can specify boosts to each query, sub-query, and
|
||||
* each query term, hence the contribution of a query term to the score of
|
||||
* a document is multiplied by the boost of that query term <i>query-boost(q)</i>.
|
||||
* </li>
|
||||
*
|
||||
* <li>A document may match a multi term query without containing all
|
||||
* the terms of that query (this is correct for some of the queries),
|
||||
* and users can further reward documents matching more query terms
|
||||
* through a coordination factor, which is usually larger when
|
||||
* more terms are matched: <i>coord-factor(q,d)</i>.
|
||||
* </li>
|
||||
* </ul>
|
||||
*
|
||||
* <p>Under the simplifying assumption of a single field in the index,
|
||||
* we get <i>Lucene's Conceptual scoring formula</i>:
|
||||
*
|
||||
* <br> <br>
|
||||
* <table cellpadding="2" cellspacing="2" border="0" align="center">
|
||||
* <tr><td>
|
||||
* <table cellpadding="1" cellspacing="0" border="1" align="center">
|
||||
* <tr><td>
|
||||
* <table cellpadding="2" cellspacing="2" border="0" align="center">
|
||||
* <tr>
|
||||
* <td valign="middle" align="right" rowspan="1">
|
||||
* score(q,d) =
|
||||
* <font color="#FF9933">coord-factor(q,d)</font> ·
|
||||
* <font color="#CCCC00">query-boost(q)</font> ·
|
||||
* </td>
|
||||
* <td valign="middle" align="center">
|
||||
* <table>
|
||||
* <tr><td align="center"><small><font color="#993399">V(q) · V(d)</font></small></td></tr>
|
||||
* <tr><td align="center">–––––––––</td></tr>
|
||||
* <tr><td align="center"><small><font color="#FF33CC">|V(q)|</font></small></td></tr>
|
||||
* </table>
|
||||
* </td>
|
||||
* <td valign="middle" align="right" rowspan="1">
|
||||
* · <font color="#3399FF">doc-len-norm(d)</font>
|
||||
* · <font color="#3399FF">doc-boost(d)</font>
|
||||
* </td>
|
||||
* </tr>
|
||||
* </table>
|
||||
* </td></tr>
|
||||
* </table>
|
||||
* </td></tr>
|
||||
* <tr><td>
|
||||
* <center><font=-1><u>Lucene Conceptual Scoring Formula</u></font></center>
|
||||
* </td></tr>
|
||||
* </table>
|
||||
* <br> <br>
|
||||
*
|
||||
* <p>The conceptual formula is a simplification in the sense that (1) terms and documents
|
||||
* are fielded and (2) boosts are usually per query term rather than per query.
|
||||
*
|
||||
* <p>We now describe how Lucene implements this conceptual scoring formula, and
|
||||
* derive from it <i>Lucene's Practical Scoring Function</i>.
|
||||
*
|
||||
* <p>For efficient score computation some scoring components
|
||||
* are computed and aggregated in advance:
|
||||
*
|
||||
* <ul>
|
||||
* <li><i>Query-boost</i> for the query (actually for each query term)
|
||||
* is known when search starts.
|
||||
* </li>
|
||||
*
|
||||
* <li>Query Euclidean norm <i>|V(q)|</i> can be computed when search starts,
|
||||
* as it is independent of the document being scored.
|
||||
* From search optimization perspective, it is a valid question
|
||||
* why bother to normalize the query at all, because all
|
||||
* scored documents will be multiplied by the same <i>|V(q)|</i>,
|
||||
* and hence documents ranks (their order by score) will not
|
||||
* be affected by this normalization.
|
||||
* There are two good reasons to keep this normalization:
|
||||
* <ul>
|
||||
* <li>Recall that
|
||||
* <a href="http://en.wikipedia.org/wiki/Cosine_similarity">
|
||||
* Cosine Similarity</a> can be used find how similar
|
||||
* two documents are. One can use Lucene for e.g.
|
||||
* clustering, and use a document as a query to compute
|
||||
* its similarity to other documents.
|
||||
* In this use case it is important that the score of document <i>d3</i>
|
||||
* for query <i>d1</i> is comparable to the score of document <i>d3</i>
|
||||
* for query <i>d2</i>. In other words, scores of a document for two
|
||||
* distinct queries should be comparable.
|
||||
* There are other applications that may require this.
|
||||
* And this is exactly what normalizing the query vector <i>V(q)</i>
|
||||
* provides: comparability (to a certain extent) of two or more queries.
|
||||
* </li>
|
||||
*
|
||||
* <li>Applying query normalization on the scores helps to keep the
|
||||
* scores around the unit vector, hence preventing loss of score data
|
||||
* because of floating point precision limitations.
|
||||
* </li>
|
||||
* </ul>
|
||||
* </li>
|
||||
*
|
||||
* <li>Document length norm <i>doc-len-norm(d)</i> and document
|
||||
* boost <i>doc-boost(d)</i> are known at indexing time.
|
||||
* They are computed in advance and their multiplication
|
||||
* is saved as a single value in the index: <i>norm(d)</i>.
|
||||
* (In the equations below, <i>norm(t in d)</i> means <i>norm(field(t) in doc d)</i>
|
||||
* where <i>field(t)</i> is the field associated with term <i>t</i>.)
|
||||
* </li>
|
||||
* </ul>
|
||||
*
|
||||
* <p><i>Lucene's Practical Scoring Function</i> is derived from the above.
|
||||
* The color codes demonstrate how it relates
|
||||
* to those of the <i>conceptual</i> formula:
|
||||
*
|
||||
* <P>
|
||||
* <table cellpadding="2" cellspacing="2" border="0" align="center">
|
||||
* <tr><td>
|
||||
* <table cellpadding="" cellspacing="2" border="2" align="center">
|
||||
* <tr><td>
|
||||
* <table cellpadding="2" cellspacing="2" border="0" align="center">
|
||||
* <tr>
|
||||
* <td valign="middle" align="right" rowspan="1">
|
||||
* score(q,d) =
|
||||
* <A HREF="#formula_coord"><font color="#FF9933">coord(q,d)</font></A> ·
|
||||
* <A HREF="#formula_queryNorm"><font color="#FF33CC">queryNorm(q)</font></A> ·
|
||||
* </td>
|
||||
* <td valign="bottom" align="center" rowspan="1">
|
||||
* <big><big><big>∑</big></big></big>
|
||||
* </td>
|
||||
* <td valign="middle" align="right" rowspan="1">
|
||||
* <big><big>(</big></big>
|
||||
* <A HREF="#formula_tf"><font color="#993399">tf(t in d)</font></A> ·
|
||||
* <A HREF="#formula_idf"><font color="#993399">idf(t)</font></A><sup>2</sup> ·
|
||||
* <A HREF="#formula_termBoost"><font color="#CCCC00">t.getBoost()</font></A> ·
|
||||
* <A HREF="#formula_norm"><font color="#3399FF">norm(t,d)</font></A>
|
||||
* <big><big>)</big></big>
|
||||
* </td>
|
||||
* </tr>
|
||||
* <tr valigh="top">
|
||||
* <td></td>
|
||||
* <td align="center"><small>t in q</small></td>
|
||||
* <td></td>
|
||||
* </tr>
|
||||
* </table>
|
||||
* </td></tr>
|
||||
* </table>
|
||||
* </td></tr>
|
||||
* <tr><td>
|
||||
* <center><font=-1><u>Lucene Practical Scoring Function</u></font></center>
|
||||
* </td></tr>
|
||||
* </table>
|
||||
*
|
||||
* <p> where
|
||||
* <p>
|
||||
* This is a low-level API, you should only extend this API if you want to implement
|
||||
* an information retrieval <i>model</i>. If you are instead looking for a convenient way
|
||||
* to alter Lucene's scoring, consider extending a higher-level implementation
|
||||
* such as {@link TFIDFSimilarity}, which implements the vector space model with this API, or
|
||||
* just tweaking the default implementation: {@link DefaultSimilarity}.
|
||||
* <p>
|
||||
* Similarity determines how Lucene weights terms, and Lucene interacts with
|
||||
* this class at both <a href="#indextime">index-time</a> and
|
||||
* <a href="#querytime">query-time</a>.
|
||||
* <p>
|
||||
* <a name="indextime"/>
|
||||
* At indexing time, the indexer calls {@link #computeNorm(FieldInvertState)}, allowing
|
||||
* the Similarity implementation to return a per-document byte for the field that will
|
||||
* be later accessible via {@link IndexReader#norms(String)}. Lucene makes no assumption
|
||||
* about what is in this byte, but it is most useful for encoding length normalization
|
||||
* information.
|
||||
* <p>
|
||||
* Implementations should carefully consider how the normalization byte is encoded: while
|
||||
* Lucene's classical {@link TFIDFSimilarity} encodes a combination of index-time boost
|
||||
* and length normalization information with {@link SmallFloat}, this might not be suitable
|
||||
* for all purposes.
|
||||
* <p>
|
||||
* Many formulas require the use of average document length, which can be computed via a
|
||||
* combination of {@link Terms#getSumTotalTermFreq()} and {@link IndexReader#maxDoc()},
|
||||
* <p>
|
||||
* Because index-time boost is handled entirely at the application level anyway,
|
||||
* an application can alternatively store the index-time boost separately using an
|
||||
* {@link IndexDocValuesField}, and access this at query-time with
|
||||
* {@link IndexReader#docValues(String)}.
|
||||
* <p>
|
||||
* Finally, using index-time boosts (either via folding into the normalization byte or
|
||||
* via IndexDocValues), is an inefficient way to boost the scores of different fields if the
|
||||
* boost will be the same for every document, instead the Similarity can simply take a constant
|
||||
* boost parameter <i>C</i>, and the SimilarityProvider can return different instances with
|
||||
* different boosts depending upon field name.
|
||||
* <p>
|
||||
* <a name="querytime"/>
|
||||
* At query-time, Queries interact with the Similarity via these steps:
|
||||
* <ol>
|
||||
* <li>
|
||||
* <A NAME="formula_tf"></A>
|
||||
* <b><i>tf(t in d)</i></b>
|
||||
* correlates to the term's <i>frequency</i>,
|
||||
* defined as the number of times term <i>t</i> appears in the currently scored document <i>d</i>.
|
||||
* Documents that have more occurrences of a given term receive a higher score.
|
||||
* Note that <i>tf(t in q)</i> is assumed to be <i>1</i> and therefore it does not appear in this equation,
|
||||
* However if a query contains twice the same term, there will be
|
||||
* two term-queries with that same term and hence the computation would still be correct (although
|
||||
* not very efficient).
|
||||
* The default computation for <i>tf(t in d)</i> in
|
||||
* {@link org.apache.lucene.search.DefaultSimilarity#tf(float) DefaultSimilarity} is:
|
||||
*
|
||||
* <br> <br>
|
||||
* <table cellpadding="2" cellspacing="2" border="0" align="center">
|
||||
* <tr>
|
||||
* <td valign="middle" align="right" rowspan="1">
|
||||
* {@link org.apache.lucene.search.DefaultSimilarity#tf(float) tf(t in d)} =
|
||||
* </td>
|
||||
* <td valign="top" align="center" rowspan="1">
|
||||
* frequency<sup><big>½</big></sup>
|
||||
* </td>
|
||||
* </tr>
|
||||
* </table>
|
||||
* <br> <br>
|
||||
* </li>
|
||||
*
|
||||
* <li>
|
||||
* <A NAME="formula_idf"></A>
|
||||
* <b><i>idf(t)</i></b> stands for Inverse Document Frequency. This value
|
||||
* correlates to the inverse of <i>docFreq</i>
|
||||
* (the number of documents in which the term <i>t</i> appears).
|
||||
* This means rarer terms give higher contribution to the total score.
|
||||
* <i>idf(t)</i> appears for <i>t</i> in both the query and the document,
|
||||
* hence it is squared in the equation.
|
||||
* The default computation for <i>idf(t)</i> in
|
||||
* {@link org.apache.lucene.search.DefaultSimilarity#idf(int, int) DefaultSimilarity} is:
|
||||
*
|
||||
* <br> <br>
|
||||
* <table cellpadding="2" cellspacing="2" border="0" align="center">
|
||||
* <tr>
|
||||
* <td valign="middle" align="right">
|
||||
* {@link org.apache.lucene.search.DefaultSimilarity#idf(int, int) idf(t)} =
|
||||
* </td>
|
||||
* <td valign="middle" align="center">
|
||||
* 1 + log <big>(</big>
|
||||
* </td>
|
||||
* <td valign="middle" align="center">
|
||||
* <table>
|
||||
* <tr><td align="center"><small>numDocs</small></td></tr>
|
||||
* <tr><td align="center">–––––––––</td></tr>
|
||||
* <tr><td align="center"><small>docFreq+1</small></td></tr>
|
||||
* </table>
|
||||
* </td>
|
||||
* <td valign="middle" align="center">
|
||||
* <big>)</big>
|
||||
* </td>
|
||||
* </tr>
|
||||
* </table>
|
||||
* <br> <br>
|
||||
* </li>
|
||||
*
|
||||
* <li>
|
||||
* <A NAME="formula_coord"></A>
|
||||
* <b><i>coord(q,d)</i></b>
|
||||
* is a score factor based on how many of the query terms are found in the specified document.
|
||||
* Typically, a document that contains more of the query's terms will receive a higher score
|
||||
* than another document with fewer query terms.
|
||||
* This is a search time factor computed in
|
||||
* {@link SimilarityProvider#coord(int, int) coord(q,d)}
|
||||
* by the SimilarityProvider in effect at search time.
|
||||
* <br> <br>
|
||||
* </li>
|
||||
*
|
||||
* <li><b>
|
||||
* <A NAME="formula_queryNorm"></A>
|
||||
* <i>queryNorm(q)</i>
|
||||
* </b>
|
||||
* is a normalizing factor used to make scores between queries comparable.
|
||||
* This factor does not affect document ranking (since all ranked documents are multiplied by the same factor),
|
||||
* but rather just attempts to make scores from different queries (or even different indexes) comparable.
|
||||
* This is a search time factor computed by the SimilarityProvider in effect at search time.
|
||||
*
|
||||
* The default computation in
|
||||
* {@link org.apache.lucene.search.DefaultSimilarityProvider#queryNorm(float) DefaultSimilarityProvider}
|
||||
* produces a <a href="http://en.wikipedia.org/wiki/Euclidean_norm#Euclidean_norm">Euclidean norm</a>:
|
||||
* <br> <br>
|
||||
* <table cellpadding="1" cellspacing="0" border="0" align="center">
|
||||
* <tr>
|
||||
* <td valign="middle" align="right" rowspan="1">
|
||||
* queryNorm(q) =
|
||||
* {@link org.apache.lucene.search.DefaultSimilarityProvider#queryNorm(float) queryNorm(sumOfSquaredWeights)}
|
||||
* =
|
||||
* </td>
|
||||
* <td valign="middle" align="center" rowspan="1">
|
||||
* <table>
|
||||
* <tr><td align="center"><big>1</big></td></tr>
|
||||
* <tr><td align="center"><big>
|
||||
* ––––––––––––––
|
||||
* </big></td></tr>
|
||||
* <tr><td align="center">sumOfSquaredWeights<sup><big>½</big></sup></td></tr>
|
||||
* </table>
|
||||
* </td>
|
||||
* </tr>
|
||||
* </table>
|
||||
* <br> <br>
|
||||
*
|
||||
* The sum of squared weights (of the query terms) is
|
||||
* computed by the query {@link org.apache.lucene.search.Weight} object.
|
||||
* For example, a {@link org.apache.lucene.search.BooleanQuery}
|
||||
* computes this value as:
|
||||
*
|
||||
* <br> <br>
|
||||
* <table cellpadding="1" cellspacing="0" border="0"n align="center">
|
||||
* <tr>
|
||||
* <td valign="middle" align="right" rowspan="1">
|
||||
* {@link org.apache.lucene.search.Weight#sumOfSquaredWeights() sumOfSquaredWeights} =
|
||||
* {@link org.apache.lucene.search.Query#getBoost() q.getBoost()} <sup><big>2</big></sup>
|
||||
* ·
|
||||
* </td>
|
||||
* <td valign="bottom" align="center" rowspan="1">
|
||||
* <big><big><big>∑</big></big></big>
|
||||
* </td>
|
||||
* <td valign="middle" align="right" rowspan="1">
|
||||
* <big><big>(</big></big>
|
||||
* <A HREF="#formula_idf">idf(t)</A> ·
|
||||
* <A HREF="#formula_termBoost">t.getBoost()</A>
|
||||
* <big><big>) <sup>2</sup> </big></big>
|
||||
* </td>
|
||||
* </tr>
|
||||
* <tr valigh="top">
|
||||
* <td></td>
|
||||
* <td align="center"><small>t in q</small></td>
|
||||
* <td></td>
|
||||
* </tr>
|
||||
* </table>
|
||||
* <br> <br>
|
||||
*
|
||||
* </li>
|
||||
*
|
||||
* <li>
|
||||
* <A NAME="formula_termBoost"></A>
|
||||
* <b><i>t.getBoost()</i></b>
|
||||
* is a search time boost of term <i>t</i> in the query <i>q</i> as
|
||||
* specified in the query text
|
||||
* (see <A HREF="../../../../../../queryparsersyntax.html#Boosting a Term">query syntax</A>),
|
||||
* or as set by application calls to
|
||||
* {@link org.apache.lucene.search.Query#setBoost(float) setBoost()}.
|
||||
* Notice that there is really no direct API for accessing a boost of one term in a multi term query,
|
||||
* but rather multi terms are represented in a query as multi
|
||||
* {@link org.apache.lucene.search.TermQuery TermQuery} objects,
|
||||
* and so the boost of a term in the query is accessible by calling the sub-query
|
||||
* {@link org.apache.lucene.search.Query#getBoost() getBoost()}.
|
||||
* <br> <br>
|
||||
* </li>
|
||||
*
|
||||
* <li>
|
||||
* <A NAME="formula_norm"></A>
|
||||
* <b><i>norm(t,d)</i></b> encapsulates a few (indexing time) boost and length factors:
|
||||
*
|
||||
* <ul>
|
||||
* <li><b>Document boost</b> - set by calling
|
||||
* {@link org.apache.lucene.document.Document#setBoost(float) doc.setBoost()}
|
||||
* before adding the document to the index.
|
||||
* </li>
|
||||
* <li><b>Field boost</b> - set by calling
|
||||
* {@link org.apache.lucene.document.Fieldable#setBoost(float) field.setBoost()}
|
||||
* before adding the field to a document.
|
||||
* </li>
|
||||
* <li><b>lengthNorm</b> - computed
|
||||
* when the document is added to the index in accordance with the number of tokens
|
||||
* of this field in the document, so that shorter fields contribute more to the score.
|
||||
* LengthNorm is computed by the Similarity class in effect at indexing.
|
||||
* </li>
|
||||
* </ul>
|
||||
* The {@link #computeNorm} method is responsible for
|
||||
* combining all of these factors into a single float.
|
||||
*
|
||||
* <p>
|
||||
* When a document is added to the index, all the above factors are multiplied.
|
||||
* If the document has multiple fields with the same name, all their boosts are multiplied together:
|
||||
*
|
||||
* <br> <br>
|
||||
* <table cellpadding="1" cellspacing="0" border="0"n align="center">
|
||||
* <tr>
|
||||
* <td valign="middle" align="right" rowspan="1">
|
||||
* norm(t,d) =
|
||||
* {@link org.apache.lucene.document.Document#getBoost() doc.getBoost()}
|
||||
* ·
|
||||
* lengthNorm
|
||||
* ·
|
||||
* </td>
|
||||
* <td valign="bottom" align="center" rowspan="1">
|
||||
* <big><big><big>∏</big></big></big>
|
||||
* </td>
|
||||
* <td valign="middle" align="right" rowspan="1">
|
||||
* {@link org.apache.lucene.document.Fieldable#getBoost() f.getBoost}()
|
||||
* </td>
|
||||
* </tr>
|
||||
* <tr valigh="top">
|
||||
* <td></td>
|
||||
* <td align="center"><small>field <i><b>f</b></i> in <i>d</i> named as <i><b>t</b></i></small></td>
|
||||
* <td></td>
|
||||
* </tr>
|
||||
* </table>
|
||||
* <br> <br>
|
||||
* However the resulted <i>norm</i> value is {@link #encodeNormValue(float) encoded} as a single byte
|
||||
* before being stored.
|
||||
* At search time, the norm byte value is read from the index
|
||||
* {@link org.apache.lucene.store.Directory directory} and
|
||||
* {@link #decodeNormValue(byte) decoded} back to a float <i>norm</i> value.
|
||||
* This encoding/decoding, while reducing index size, comes with the price of
|
||||
* precision loss - it is not guaranteed that <i>decode(encode(x)) = x</i>.
|
||||
* For instance, <i>decode(encode(0.89)) = 0.75</i>.
|
||||
* <br> <br>
|
||||
* Compression of norm values to a single byte saves memory at search time,
|
||||
* because once a field is referenced at search time, its norms - for
|
||||
* all documents - are maintained in memory.
|
||||
* <br> <br>
|
||||
* The rationale supporting such lossy compression of norm values is that
|
||||
* given the difficulty (and inaccuracy) of users to express their true information
|
||||
* need by a query, only big differences matter.
|
||||
* <br> <br>
|
||||
* Last, note that search time is too late to modify this <i>norm</i> part of scoring, e.g. by
|
||||
* using a different {@link Similarity} for search.
|
||||
* <br> <br>
|
||||
* </li>
|
||||
* <li>The {@link #computeStats(IndexSearcher, String, float, TermContext...)} method is called a single time,
|
||||
* allowing the implementation to compute any statistics (such as IDF, average document length, etc)
|
||||
* across <i>the entire collection</i>. The {@link TermContext}s passed in are already positioned
|
||||
* to the terms involved with the raw statistics involved, so a Similarity can freely use any combination
|
||||
* of term statistics without causing any additional I/O. Lucene makes no assumption about what is
|
||||
* stored in the returned {@link Similarity.Stats} object.
|
||||
* <li>The query normalization process occurs a single time: {@link Similarity.Stats#getValueForNormalization()}
|
||||
* is called for each query leaf node, {@link SimilarityProvider#queryNorm(float)} is called for the top-level
|
||||
* query, and finally {@link Similarity.Stats#normalize(float, float)} passes down the normalization value
|
||||
* and any top-level boosts (e.g. from enclosing {@link BooleanQuery}s).
|
||||
* <li>For each segment in the index, the Query creates a {@link #exactDocScorer(Stats, String, IndexReader.AtomicReaderContext)}
|
||||
* (for queries with exact frequencies such as TermQuerys and exact PhraseQueries) or a
|
||||
* {@link #sloppyDocScorer(Stats, String, IndexReader.AtomicReaderContext)} (for queries with sloppy frequencies such as
|
||||
* SpanQuerys and sloppy PhraseQueries). The score() method is called for each matching document.
|
||||
* </ol>
|
||||
* <p>
|
||||
* <a name="explaintime"/>
|
||||
* When {@link IndexSearcher#explain(Query, int)} is called, queries consult the Similarity's DocScorer for an
|
||||
* explanation of how it computed its score. The query passes in a the document id and an explanation of how the frequency
|
||||
* was computed.
|
||||
*
|
||||
* @see org.apache.lucene.index.IndexWriterConfig#setSimilarityProvider(SimilarityProvider)
|
||||
* @see IndexSearcher#setSimilarityProvider(SimilarityProvider)
|
||||
* @lucene.experimental
|
||||
*/
|
||||
public abstract class Similarity {
|
||||
|
||||
public static final int NO_DOC_ID_PROVIDED = -1;
|
||||
|
||||
/** Cache of decoded bytes. */
|
||||
private static final float[] NORM_TABLE = new float[256];
|
||||
|
||||
static {
|
||||
for (int i = 0; i < 256; i++)
|
||||
NORM_TABLE[i] = SmallFloat.byte315ToFloat((byte)i);
|
||||
}
|
||||
|
||||
/** Decodes a normalization factor stored in an index.
|
||||
* @see #encodeNormValue(float)
|
||||
*/
|
||||
public float decodeNormValue(byte b) {
|
||||
return NORM_TABLE[b & 0xFF]; // & 0xFF maps negative bytes to positive above 127
|
||||
}
|
||||
|
||||
/**
|
||||
* Computes the normalization value for a field, given the accumulated
|
||||
* state of term processing for this field (see {@link FieldInvertState}).
|
||||
*
|
||||
* <p>Implementations should calculate a float value based on the field
|
||||
* <p>Implementations should calculate a byte value based on the field
|
||||
* state and then return that value.
|
||||
*
|
||||
* <p>Matches in longer fields are less precise, so implementations of this
|
||||
* method usually return smaller values when <code>state.getLength()</code> is large,
|
||||
* and larger values when <code>state.getLength()</code> is small.
|
||||
*
|
||||
* <p>Note that the return values are computed under
|
||||
* {@link org.apache.lucene.index.IndexWriter#addDocument(org.apache.lucene.document.Document)}
|
||||
* and then stored using
|
||||
* {@link #encodeNormValue(float)}.
|
||||
* Thus they have limited precision, and documents
|
||||
* must be re-indexed if this method is altered.
|
||||
*
|
||||
* @lucene.experimental
|
||||
*
|
||||
* @param state current processing state for this field
|
||||
* @return the calculated float norm
|
||||
* @return the calculated byte norm
|
||||
*/
|
||||
public abstract float computeNorm(FieldInvertState state);
|
||||
|
||||
/** Encodes a normalization factor for storage in an index.
|
||||
*
|
||||
* <p>The encoding uses a three-bit mantissa, a five-bit exponent, and
|
||||
* the zero-exponent point at 15, thus
|
||||
* representing values from around 7x10^9 to 2x10^-9 with about one
|
||||
* significant decimal digit of accuracy. Zero is also represented.
|
||||
* Negative numbers are rounded up to zero. Values too large to represent
|
||||
* are rounded down to the largest representable value. Positive values too
|
||||
* small to represent are rounded up to the smallest positive representable
|
||||
* value.
|
||||
* @see org.apache.lucene.document.Field#setBoost(float)
|
||||
* @see org.apache.lucene.util.SmallFloat
|
||||
*/
|
||||
public byte encodeNormValue(float f) {
|
||||
return SmallFloat.floatToByte315(f);
|
||||
}
|
||||
|
||||
/** Computes a score factor based on a term or phrase's frequency in a
|
||||
* document. This value is multiplied by the {@link #idf(int, int)}
|
||||
* factor for each term in the query and these products are then summed to
|
||||
* form the initial score for a document.
|
||||
*
|
||||
* <p>Terms and phrases repeated in a document indicate the topic of the
|
||||
* document, so implementations of this method usually return larger values
|
||||
* when <code>freq</code> is large, and smaller values when <code>freq</code>
|
||||
* is small.
|
||||
*
|
||||
* <p>The default implementation calls {@link #tf(float)}.
|
||||
*
|
||||
* @param freq the frequency of a term within a document
|
||||
* @return a score factor based on a term's within-document frequency
|
||||
*/
|
||||
public float tf(int freq) {
|
||||
return tf((float)freq);
|
||||
}
|
||||
public abstract byte computeNorm(FieldInvertState state);
|
||||
|
||||
/** Computes the amount of a sloppy phrase match, based on an edit distance.
|
||||
* This value is summed for each sloppy phrase match in a document to form
|
||||
* the frequency that is passed to {@link #tf(float)}.
|
||||
* the frequency to be used in scoring instead of the exact term count.
|
||||
*
|
||||
* <p>A phrase match with a small edit distance to a document passage more
|
||||
* closely matches the document, so implementations of this method usually
|
||||
|
@ -619,124 +136,6 @@ public abstract class Similarity {
|
|||
*/
|
||||
public abstract float sloppyFreq(int distance);
|
||||
|
||||
/** Computes a score factor based on a term or phrase's frequency in a
|
||||
* document. This value is multiplied by the {@link #idf(int, int)}
|
||||
* factor for each term in the query and these products are then summed to
|
||||
* form the initial score for a document.
|
||||
*
|
||||
* <p>Terms and phrases repeated in a document indicate the topic of the
|
||||
* document, so implementations of this method usually return larger values
|
||||
* when <code>freq</code> is large, and smaller values when <code>freq</code>
|
||||
* is small.
|
||||
*
|
||||
* @param freq the frequency of a term within a document
|
||||
* @return a score factor based on a term's within-document frequency
|
||||
*/
|
||||
public abstract float tf(float freq);
|
||||
|
||||
/**
|
||||
* Computes a score factor for a simple term and returns an explanation
|
||||
* for that score factor.
|
||||
*
|
||||
* <p>
|
||||
* The default implementation uses:
|
||||
*
|
||||
* <pre>
|
||||
* idf(docFreq, searcher.maxDoc());
|
||||
* </pre>
|
||||
*
|
||||
* Note that {@link IndexSearcher#maxDoc()} is used instead of
|
||||
* {@link org.apache.lucene.index.IndexReader#numDocs() IndexReader#numDocs()} because also
|
||||
* {@link IndexSearcher#docFreq(Term)} is used, and when the latter
|
||||
* is inaccurate, so is {@link IndexSearcher#maxDoc()}, and in the same direction.
|
||||
* In addition, {@link IndexSearcher#maxDoc()} is more efficient to compute
|
||||
*
|
||||
* @param term the term in question
|
||||
* @param searcher the document collection being searched
|
||||
* @param docFreq externally computed docFreq for this term
|
||||
* @return an IDFExplain object that includes both an idf score factor
|
||||
and an explanation for the term.
|
||||
* @throws IOException
|
||||
*/
|
||||
public IDFExplanation idfExplain(final Term term, final IndexSearcher searcher, int docFreq) throws IOException {
|
||||
final int df = docFreq;
|
||||
final int max = searcher.maxDoc();
|
||||
final float idf = idf(df, max);
|
||||
return new IDFExplanation() {
|
||||
@Override
|
||||
public String explain() {
|
||||
return "idf(docFreq=" + df +
|
||||
", maxDocs=" + max + ")";
|
||||
}
|
||||
@Override
|
||||
public float getIdf() {
|
||||
return idf;
|
||||
}};
|
||||
}
|
||||
|
||||
/**
|
||||
* This method forwards to {@link
|
||||
* #idfExplain(Term,IndexSearcher,int)} by passing
|
||||
* <code>searcher.docFreq(term)</code> as the docFreq.
|
||||
*/
|
||||
public IDFExplanation idfExplain(final Term term, final IndexSearcher searcher) throws IOException {
|
||||
return idfExplain(term, searcher, searcher.docFreq(term));
|
||||
}
|
||||
|
||||
/**
|
||||
* Computes a score factor for a phrase.
|
||||
*
|
||||
* <p>
|
||||
* The default implementation sums the idf factor for
|
||||
* each term in the phrase.
|
||||
*
|
||||
* @param terms the terms in the phrase
|
||||
* @param searcher the document collection being searched
|
||||
* @return an IDFExplain object that includes both an idf
|
||||
* score factor for the phrase and an explanation
|
||||
* for each term.
|
||||
* @throws IOException
|
||||
*/
|
||||
public IDFExplanation idfExplain(Collection<Term> terms, IndexSearcher searcher) throws IOException {
|
||||
final int max = searcher.maxDoc();
|
||||
float idf = 0.0f;
|
||||
final StringBuilder exp = new StringBuilder();
|
||||
for (final Term term : terms ) {
|
||||
final int df = searcher.docFreq(term);
|
||||
idf += idf(df, max);
|
||||
exp.append(" ");
|
||||
exp.append(term.text());
|
||||
exp.append("=");
|
||||
exp.append(df);
|
||||
}
|
||||
final float fIdf = idf;
|
||||
return new IDFExplanation() {
|
||||
@Override
|
||||
public float getIdf() {
|
||||
return fIdf;
|
||||
}
|
||||
@Override
|
||||
public String explain() {
|
||||
return exp.toString();
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
/** Computes a score factor based on a term's document frequency (the number
|
||||
* of documents which contain the term). This value is multiplied by the
|
||||
* {@link #tf(int)} factor for each term in the query and these products are
|
||||
* then summed to form the initial score for a document.
|
||||
*
|
||||
* <p>Terms that occur in fewer documents are better indicators of topic, so
|
||||
* implementations of this method usually return larger values for rare terms,
|
||||
* and smaller values for common terms.
|
||||
*
|
||||
* @param docFreq the number of documents which contain the term
|
||||
* @param numDocs the total number of documents in the collection
|
||||
* @return a score factor based on the term's document frequency
|
||||
*/
|
||||
public abstract float idf(int docFreq, int numDocs);
|
||||
|
||||
/**
|
||||
* Calculate a scoring factor based on the data in the payload. Overriding implementations
|
||||
* are responsible for interpreting what is in the payload. Lucene makes no assumptions about
|
||||
|
@ -759,4 +158,100 @@ public abstract class Similarity {
|
|||
return 1;
|
||||
}
|
||||
|
||||
/**
|
||||
* Compute any collection-level stats (e.g. IDF, average document length, etc) needed for scoring a query.
|
||||
*/
|
||||
public abstract Stats computeStats(IndexSearcher searcher, String fieldName, float queryBoost, TermContext... termContexts) throws IOException;
|
||||
|
||||
/**
|
||||
* returns a new {@link Similarity.ExactDocScorer}.
|
||||
*/
|
||||
public abstract ExactDocScorer exactDocScorer(Stats stats, String fieldName, AtomicReaderContext context) throws IOException;
|
||||
|
||||
/**
|
||||
* returns a new {@link Similarity.SloppyDocScorer}.
|
||||
*/
|
||||
public abstract SloppyDocScorer sloppyDocScorer(Stats stats, String fieldName, AtomicReaderContext context) throws IOException;
|
||||
|
||||
/**
|
||||
* API for scoring exact queries such as {@link TermQuery} and
|
||||
* exact {@link PhraseQuery}.
|
||||
* <p>
|
||||
* Term frequencies are integers (the term or phrase's tf)
|
||||
*/
|
||||
public abstract class ExactDocScorer {
|
||||
/**
|
||||
* Score a single document
|
||||
* @param doc document id
|
||||
* @param freq term frequency
|
||||
* @return document's score
|
||||
*/
|
||||
public abstract float score(int doc, int freq);
|
||||
|
||||
/**
|
||||
* Explain the score for a single document
|
||||
* @param doc document id
|
||||
* @param freq Explanation of how the term frequency was computed
|
||||
* @return document's score
|
||||
*/
|
||||
public Explanation explain(int doc, Explanation freq) {
|
||||
Explanation result = new Explanation(score(doc, (int)freq.getValue()),
|
||||
"score(doc=" + doc + ",freq=" + freq.getValue() +"), with freq of:");
|
||||
result.addDetail(freq);
|
||||
return result;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* API for scoring "sloppy" queries such as {@link SpanQuery} and
|
||||
* sloppy {@link PhraseQuery}.
|
||||
* <p>
|
||||
* Term frequencies are floating point values.
|
||||
*/
|
||||
public abstract class SloppyDocScorer {
|
||||
/**
|
||||
* Score a single document
|
||||
* @param doc document id
|
||||
* @param freq sloppy term frequency
|
||||
* @return document's score
|
||||
*/
|
||||
public abstract float score(int doc, float freq);
|
||||
|
||||
/**
|
||||
* Explain the score for a single document
|
||||
* @param doc document id
|
||||
* @param freq Explanation of how the sloppy term frequency was computed
|
||||
* @return document's score
|
||||
*/
|
||||
public Explanation explain(int doc, Explanation freq) {
|
||||
Explanation result = new Explanation(score(doc, freq.getValue()),
|
||||
"score(doc=" + doc + ",freq=" + freq.getValue() +"), with freq of:");
|
||||
result.addDetail(freq);
|
||||
return result;
|
||||
}
|
||||
}
|
||||
|
||||
/** Stores the statistics for the indexed collection. This abstract
|
||||
* implementation is empty; descendants of {@code Similarity} should
|
||||
* subclass {@code Stats} and define the statistics they require in the
|
||||
* subclass. Examples include idf, average field length, etc.
|
||||
*/
|
||||
public static abstract class Stats {
|
||||
|
||||
/** The value for normalization of contained query clauses (e.g. sum of squared weights).
|
||||
* <p>
|
||||
* NOTE: a Similarity implementation might not use any query normalization at all,
|
||||
* its not required. However, if it wants to participate in query normalization,
|
||||
* it can return a value here.
|
||||
*/
|
||||
public abstract float getValueForNormalization();
|
||||
|
||||
/** Assigns the query normalization factor and boost from parent queries to this.
|
||||
* <p>
|
||||
* NOTE: a Similarity implementation might not use this normalized value at all,
|
||||
* its not required. However, its usually a good idea to at least incorporate
|
||||
* the topLevelBoost (e.g. from an outer BooleanQuery) into its score.
|
||||
*/
|
||||
public abstract void normalize(float queryNorm, float topLevelBoost);
|
||||
}
|
||||
}
|
||||
|
|
|
@ -25,11 +25,13 @@ final class SloppyPhraseScorer extends PhraseScorer {
|
|||
private PhrasePositions repeats[];
|
||||
private PhrasePositions tmpPos[]; // for flipping repeating pps.
|
||||
private boolean checkedRepeats;
|
||||
private final Similarity similarity;
|
||||
|
||||
SloppyPhraseScorer(Weight weight, PhraseQuery.PostingsAndFreq[] postings, Similarity similarity,
|
||||
int slop, byte[] norms) {
|
||||
super(weight, postings, similarity, norms);
|
||||
int slop, Similarity.SloppyDocScorer docScorer) throws IOException {
|
||||
super(weight, postings, docScorer);
|
||||
this.slop = slop;
|
||||
this.similarity = similarity;
|
||||
}
|
||||
|
||||
/**
|
||||
|
|
|
@ -0,0 +1,831 @@
|
|||
package org.apache.lucene.search;
|
||||
|
||||
/**
|
||||
* Licensed to the Apache Software Foundation (ASF) under one or more
|
||||
* contributor license agreements. See the NOTICE file distributed with
|
||||
* this work for additional information regarding copyright ownership.
|
||||
* The ASF licenses this file to You under the Apache License, Version 2.0
|
||||
* (the "License"); you may not use this file except in compliance with
|
||||
* the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
|
||||
|
||||
import java.io.IOException;
|
||||
|
||||
import org.apache.lucene.index.IndexReader.AtomicReaderContext;
|
||||
import org.apache.lucene.index.Term;
|
||||
import org.apache.lucene.util.TermContext;
|
||||
import org.apache.lucene.util.SmallFloat;
|
||||
|
||||
|
||||
/**
|
||||
* Implementation of {@link Similarity} with the Vector Space Model.
|
||||
* <p>
|
||||
* Expert: Scoring API.
|
||||
* <p>TFIDFSimilarity defines the components of Lucene scoring.
|
||||
* Overriding computation of these components is a convenient
|
||||
* way to alter Lucene scoring.
|
||||
*
|
||||
* <p>Suggested reading:
|
||||
* <a href="http://nlp.stanford.edu/IR-book/html/htmledition/queries-as-vectors-1.html">
|
||||
* Introduction To Information Retrieval, Chapter 6</a>.
|
||||
*
|
||||
* <p>The following describes how Lucene scoring evolves from
|
||||
* underlying information retrieval models to (efficient) implementation.
|
||||
* We first brief on <i>VSM Score</i>,
|
||||
* then derive from it <i>Lucene's Conceptual Scoring Formula</i>,
|
||||
* from which, finally, evolves <i>Lucene's Practical Scoring Function</i>
|
||||
* (the latter is connected directly with Lucene classes and methods).
|
||||
*
|
||||
* <p>Lucene combines
|
||||
* <a href="http://en.wikipedia.org/wiki/Standard_Boolean_model">
|
||||
* Boolean model (BM) of Information Retrieval</a>
|
||||
* with
|
||||
* <a href="http://en.wikipedia.org/wiki/Vector_Space_Model">
|
||||
* Vector Space Model (VSM) of Information Retrieval</a> -
|
||||
* documents "approved" by BM are scored by VSM.
|
||||
*
|
||||
* <p>In VSM, documents and queries are represented as
|
||||
* weighted vectors in a multi-dimensional space,
|
||||
* where each distinct index term is a dimension,
|
||||
* and weights are
|
||||
* <a href="http://en.wikipedia.org/wiki/Tfidf">Tf-idf</a> values.
|
||||
*
|
||||
* <p>VSM does not require weights to be <i>Tf-idf</i> values,
|
||||
* but <i>Tf-idf</i> values are believed to produce search results of high quality,
|
||||
* and so Lucene is using <i>Tf-idf</i>.
|
||||
* <i>Tf</i> and <i>Idf</i> are described in more detail below,
|
||||
* but for now, for completion, let's just say that
|
||||
* for given term <i>t</i> and document (or query) <i>x</i>,
|
||||
* <i>Tf(t,x)</i> varies with the number of occurrences of term <i>t</i> in <i>x</i>
|
||||
* (when one increases so does the other) and
|
||||
* <i>idf(t)</i> similarly varies with the inverse of the
|
||||
* number of index documents containing term <i>t</i>.
|
||||
*
|
||||
* <p><i>VSM score</i> of document <i>d</i> for query <i>q</i> is the
|
||||
* <a href="http://en.wikipedia.org/wiki/Cosine_similarity">
|
||||
* Cosine Similarity</a>
|
||||
* of the weighted query vectors <i>V(q)</i> and <i>V(d)</i>:
|
||||
*
|
||||
* <br> <br>
|
||||
* <table cellpadding="2" cellspacing="2" border="0" align="center">
|
||||
* <tr><td>
|
||||
* <table cellpadding="1" cellspacing="0" border="1" align="center">
|
||||
* <tr><td>
|
||||
* <table cellpadding="2" cellspacing="2" border="0" align="center">
|
||||
* <tr>
|
||||
* <td valign="middle" align="right" rowspan="1">
|
||||
* cosine-similarity(q,d) =
|
||||
* </td>
|
||||
* <td valign="middle" align="center">
|
||||
* <table>
|
||||
* <tr><td align="center"><small>V(q) · V(d)</small></td></tr>
|
||||
* <tr><td align="center">–––––––––</td></tr>
|
||||
* <tr><td align="center"><small>|V(q)| |V(d)|</small></td></tr>
|
||||
* </table>
|
||||
* </td>
|
||||
* </tr>
|
||||
* </table>
|
||||
* </td></tr>
|
||||
* </table>
|
||||
* </td></tr>
|
||||
* <tr><td>
|
||||
* <center><font=-1><u>VSM Score</u></font></center>
|
||||
* </td></tr>
|
||||
* </table>
|
||||
* <br> <br>
|
||||
*
|
||||
*
|
||||
* Where <i>V(q)</i> · <i>V(d)</i> is the
|
||||
* <a href="http://en.wikipedia.org/wiki/Dot_product">dot product</a>
|
||||
* of the weighted vectors,
|
||||
* and <i>|V(q)|</i> and <i>|V(d)|</i> are their
|
||||
* <a href="http://en.wikipedia.org/wiki/Euclidean_norm#Euclidean_norm">Euclidean norms</a>.
|
||||
*
|
||||
* <p>Note: the above equation can be viewed as the dot product of
|
||||
* the normalized weighted vectors, in the sense that dividing
|
||||
* <i>V(q)</i> by its euclidean norm is normalizing it to a unit vector.
|
||||
*
|
||||
* <p>Lucene refines <i>VSM score</i> for both search quality and usability:
|
||||
* <ul>
|
||||
* <li>Normalizing <i>V(d)</i> to the unit vector is known to be problematic in that
|
||||
* it removes all document length information.
|
||||
* For some documents removing this info is probably ok,
|
||||
* e.g. a document made by duplicating a certain paragraph <i>10</i> times,
|
||||
* especially if that paragraph is made of distinct terms.
|
||||
* But for a document which contains no duplicated paragraphs,
|
||||
* this might be wrong.
|
||||
* To avoid this problem, a different document length normalization
|
||||
* factor is used, which normalizes to a vector equal to or larger
|
||||
* than the unit vector: <i>doc-len-norm(d)</i>.
|
||||
* </li>
|
||||
*
|
||||
* <li>At indexing, users can specify that certain documents are more
|
||||
* important than others, by assigning a document boost.
|
||||
* For this, the score of each document is also multiplied by its boost value
|
||||
* <i>doc-boost(d)</i>.
|
||||
* </li>
|
||||
*
|
||||
* <li>Lucene is field based, hence each query term applies to a single
|
||||
* field, document length normalization is by the length of the certain field,
|
||||
* and in addition to document boost there are also document fields boosts.
|
||||
* </li>
|
||||
*
|
||||
* <li>The same field can be added to a document during indexing several times,
|
||||
* and so the boost of that field is the multiplication of the boosts of
|
||||
* the separate additions (or parts) of that field within the document.
|
||||
* </li>
|
||||
*
|
||||
* <li>At search time users can specify boosts to each query, sub-query, and
|
||||
* each query term, hence the contribution of a query term to the score of
|
||||
* a document is multiplied by the boost of that query term <i>query-boost(q)</i>.
|
||||
* </li>
|
||||
*
|
||||
* <li>A document may match a multi term query without containing all
|
||||
* the terms of that query (this is correct for some of the queries),
|
||||
* and users can further reward documents matching more query terms
|
||||
* through a coordination factor, which is usually larger when
|
||||
* more terms are matched: <i>coord-factor(q,d)</i>.
|
||||
* </li>
|
||||
* </ul>
|
||||
*
|
||||
* <p>Under the simplifying assumption of a single field in the index,
|
||||
* we get <i>Lucene's Conceptual scoring formula</i>:
|
||||
*
|
||||
* <br> <br>
|
||||
* <table cellpadding="2" cellspacing="2" border="0" align="center">
|
||||
* <tr><td>
|
||||
* <table cellpadding="1" cellspacing="0" border="1" align="center">
|
||||
* <tr><td>
|
||||
* <table cellpadding="2" cellspacing="2" border="0" align="center">
|
||||
* <tr>
|
||||
* <td valign="middle" align="right" rowspan="1">
|
||||
* score(q,d) =
|
||||
* <font color="#FF9933">coord-factor(q,d)</font> ·
|
||||
* <font color="#CCCC00">query-boost(q)</font> ·
|
||||
* </td>
|
||||
* <td valign="middle" align="center">
|
||||
* <table>
|
||||
* <tr><td align="center"><small><font color="#993399">V(q) · V(d)</font></small></td></tr>
|
||||
* <tr><td align="center">–––––––––</td></tr>
|
||||
* <tr><td align="center"><small><font color="#FF33CC">|V(q)|</font></small></td></tr>
|
||||
* </table>
|
||||
* </td>
|
||||
* <td valign="middle" align="right" rowspan="1">
|
||||
* · <font color="#3399FF">doc-len-norm(d)</font>
|
||||
* · <font color="#3399FF">doc-boost(d)</font>
|
||||
* </td>
|
||||
* </tr>
|
||||
* </table>
|
||||
* </td></tr>
|
||||
* </table>
|
||||
* </td></tr>
|
||||
* <tr><td>
|
||||
* <center><font=-1><u>Lucene Conceptual Scoring Formula</u></font></center>
|
||||
* </td></tr>
|
||||
* </table>
|
||||
* <br> <br>
|
||||
*
|
||||
* <p>The conceptual formula is a simplification in the sense that (1) terms and documents
|
||||
* are fielded and (2) boosts are usually per query term rather than per query.
|
||||
*
|
||||
* <p>We now describe how Lucene implements this conceptual scoring formula, and
|
||||
* derive from it <i>Lucene's Practical Scoring Function</i>.
|
||||
*
|
||||
* <p>For efficient score computation some scoring components
|
||||
* are computed and aggregated in advance:
|
||||
*
|
||||
* <ul>
|
||||
* <li><i>Query-boost</i> for the query (actually for each query term)
|
||||
* is known when search starts.
|
||||
* </li>
|
||||
*
|
||||
* <li>Query Euclidean norm <i>|V(q)|</i> can be computed when search starts,
|
||||
* as it is independent of the document being scored.
|
||||
* From search optimization perspective, it is a valid question
|
||||
* why bother to normalize the query at all, because all
|
||||
* scored documents will be multiplied by the same <i>|V(q)|</i>,
|
||||
* and hence documents ranks (their order by score) will not
|
||||
* be affected by this normalization.
|
||||
* There are two good reasons to keep this normalization:
|
||||
* <ul>
|
||||
* <li>Recall that
|
||||
* <a href="http://en.wikipedia.org/wiki/Cosine_similarity">
|
||||
* Cosine Similarity</a> can be used find how similar
|
||||
* two documents are. One can use Lucene for e.g.
|
||||
* clustering, and use a document as a query to compute
|
||||
* its similarity to other documents.
|
||||
* In this use case it is important that the score of document <i>d3</i>
|
||||
* for query <i>d1</i> is comparable to the score of document <i>d3</i>
|
||||
* for query <i>d2</i>. In other words, scores of a document for two
|
||||
* distinct queries should be comparable.
|
||||
* There are other applications that may require this.
|
||||
* And this is exactly what normalizing the query vector <i>V(q)</i>
|
||||
* provides: comparability (to a certain extent) of two or more queries.
|
||||
* </li>
|
||||
*
|
||||
* <li>Applying query normalization on the scores helps to keep the
|
||||
* scores around the unit vector, hence preventing loss of score data
|
||||
* because of floating point precision limitations.
|
||||
* </li>
|
||||
* </ul>
|
||||
* </li>
|
||||
*
|
||||
* <li>Document length norm <i>doc-len-norm(d)</i> and document
|
||||
* boost <i>doc-boost(d)</i> are known at indexing time.
|
||||
* They are computed in advance and their multiplication
|
||||
* is saved as a single value in the index: <i>norm(d)</i>.
|
||||
* (In the equations below, <i>norm(t in d)</i> means <i>norm(field(t) in doc d)</i>
|
||||
* where <i>field(t)</i> is the field associated with term <i>t</i>.)
|
||||
* </li>
|
||||
* </ul>
|
||||
*
|
||||
* <p><i>Lucene's Practical Scoring Function</i> is derived from the above.
|
||||
* The color codes demonstrate how it relates
|
||||
* to those of the <i>conceptual</i> formula:
|
||||
*
|
||||
* <P>
|
||||
* <table cellpadding="2" cellspacing="2" border="0" align="center">
|
||||
* <tr><td>
|
||||
* <table cellpadding="" cellspacing="2" border="2" align="center">
|
||||
* <tr><td>
|
||||
* <table cellpadding="2" cellspacing="2" border="0" align="center">
|
||||
* <tr>
|
||||
* <td valign="middle" align="right" rowspan="1">
|
||||
* score(q,d) =
|
||||
* <A HREF="#formula_coord"><font color="#FF9933">coord(q,d)</font></A> ·
|
||||
* <A HREF="#formula_queryNorm"><font color="#FF33CC">queryNorm(q)</font></A> ·
|
||||
* </td>
|
||||
* <td valign="bottom" align="center" rowspan="1">
|
||||
* <big><big><big>∑</big></big></big>
|
||||
* </td>
|
||||
* <td valign="middle" align="right" rowspan="1">
|
||||
* <big><big>(</big></big>
|
||||
* <A HREF="#formula_tf"><font color="#993399">tf(t in d)</font></A> ·
|
||||
* <A HREF="#formula_idf"><font color="#993399">idf(t)</font></A><sup>2</sup> ·
|
||||
* <A HREF="#formula_termBoost"><font color="#CCCC00">t.getBoost()</font></A> ·
|
||||
* <A HREF="#formula_norm"><font color="#3399FF">norm(t,d)</font></A>
|
||||
* <big><big>)</big></big>
|
||||
* </td>
|
||||
* </tr>
|
||||
* <tr valigh="top">
|
||||
* <td></td>
|
||||
* <td align="center"><small>t in q</small></td>
|
||||
* <td></td>
|
||||
* </tr>
|
||||
* </table>
|
||||
* </td></tr>
|
||||
* </table>
|
||||
* </td></tr>
|
||||
* <tr><td>
|
||||
* <center><font=-1><u>Lucene Practical Scoring Function</u></font></center>
|
||||
* </td></tr>
|
||||
* </table>
|
||||
*
|
||||
* <p> where
|
||||
* <ol>
|
||||
* <li>
|
||||
* <A NAME="formula_tf"></A>
|
||||
* <b><i>tf(t in d)</i></b>
|
||||
* correlates to the term's <i>frequency</i>,
|
||||
* defined as the number of times term <i>t</i> appears in the currently scored document <i>d</i>.
|
||||
* Documents that have more occurrences of a given term receive a higher score.
|
||||
* Note that <i>tf(t in q)</i> is assumed to be <i>1</i> and therefore it does not appear in this equation,
|
||||
* However if a query contains twice the same term, there will be
|
||||
* two term-queries with that same term and hence the computation would still be correct (although
|
||||
* not very efficient).
|
||||
* The default computation for <i>tf(t in d)</i> in
|
||||
* {@link org.apache.lucene.search.DefaultSimilarity#tf(float) DefaultSimilarity} is:
|
||||
*
|
||||
* <br> <br>
|
||||
* <table cellpadding="2" cellspacing="2" border="0" align="center">
|
||||
* <tr>
|
||||
* <td valign="middle" align="right" rowspan="1">
|
||||
* {@link org.apache.lucene.search.DefaultSimilarity#tf(float) tf(t in d)} =
|
||||
* </td>
|
||||
* <td valign="top" align="center" rowspan="1">
|
||||
* frequency<sup><big>½</big></sup>
|
||||
* </td>
|
||||
* </tr>
|
||||
* </table>
|
||||
* <br> <br>
|
||||
* </li>
|
||||
*
|
||||
* <li>
|
||||
* <A NAME="formula_idf"></A>
|
||||
* <b><i>idf(t)</i></b> stands for Inverse Document Frequency. This value
|
||||
* correlates to the inverse of <i>docFreq</i>
|
||||
* (the number of documents in which the term <i>t</i> appears).
|
||||
* This means rarer terms give higher contribution to the total score.
|
||||
* <i>idf(t)</i> appears for <i>t</i> in both the query and the document,
|
||||
* hence it is squared in the equation.
|
||||
* The default computation for <i>idf(t)</i> in
|
||||
* {@link org.apache.lucene.search.DefaultSimilarity#idf(int, int) DefaultSimilarity} is:
|
||||
*
|
||||
* <br> <br>
|
||||
* <table cellpadding="2" cellspacing="2" border="0" align="center">
|
||||
* <tr>
|
||||
* <td valign="middle" align="right">
|
||||
* {@link org.apache.lucene.search.DefaultSimilarity#idf(int, int) idf(t)} =
|
||||
* </td>
|
||||
* <td valign="middle" align="center">
|
||||
* 1 + log <big>(</big>
|
||||
* </td>
|
||||
* <td valign="middle" align="center">
|
||||
* <table>
|
||||
* <tr><td align="center"><small>numDocs</small></td></tr>
|
||||
* <tr><td align="center">–––––––––</td></tr>
|
||||
* <tr><td align="center"><small>docFreq+1</small></td></tr>
|
||||
* </table>
|
||||
* </td>
|
||||
* <td valign="middle" align="center">
|
||||
* <big>)</big>
|
||||
* </td>
|
||||
* </tr>
|
||||
* </table>
|
||||
* <br> <br>
|
||||
* </li>
|
||||
*
|
||||
* <li>
|
||||
* <A NAME="formula_coord"></A>
|
||||
* <b><i>coord(q,d)</i></b>
|
||||
* is a score factor based on how many of the query terms are found in the specified document.
|
||||
* Typically, a document that contains more of the query's terms will receive a higher score
|
||||
* than another document with fewer query terms.
|
||||
* This is a search time factor computed in
|
||||
* {@link SimilarityProvider#coord(int, int) coord(q,d)}
|
||||
* by the SimilarityProvider in effect at search time.
|
||||
* <br> <br>
|
||||
* </li>
|
||||
*
|
||||
* <li><b>
|
||||
* <A NAME="formula_queryNorm"></A>
|
||||
* <i>queryNorm(q)</i>
|
||||
* </b>
|
||||
* is a normalizing factor used to make scores between queries comparable.
|
||||
* This factor does not affect document ranking (since all ranked documents are multiplied by the same factor),
|
||||
* but rather just attempts to make scores from different queries (or even different indexes) comparable.
|
||||
* This is a search time factor computed by the Similarity in effect at search time.
|
||||
*
|
||||
* The default computation in
|
||||
* {@link org.apache.lucene.search.DefaultSimilarityProvider#queryNorm(float) DefaultSimilarityProvider}
|
||||
* produces a <a href="http://en.wikipedia.org/wiki/Euclidean_norm#Euclidean_norm">Euclidean norm</a>:
|
||||
* <br> <br>
|
||||
* <table cellpadding="1" cellspacing="0" border="0" align="center">
|
||||
* <tr>
|
||||
* <td valign="middle" align="right" rowspan="1">
|
||||
* queryNorm(q) =
|
||||
* {@link org.apache.lucene.search.DefaultSimilarityProvider#queryNorm(float) queryNorm(sumOfSquaredWeights)}
|
||||
* =
|
||||
* </td>
|
||||
* <td valign="middle" align="center" rowspan="1">
|
||||
* <table>
|
||||
* <tr><td align="center"><big>1</big></td></tr>
|
||||
* <tr><td align="center"><big>
|
||||
* ––––––––––––––
|
||||
* </big></td></tr>
|
||||
* <tr><td align="center">sumOfSquaredWeights<sup><big>½</big></sup></td></tr>
|
||||
* </table>
|
||||
* </td>
|
||||
* </tr>
|
||||
* </table>
|
||||
* <br> <br>
|
||||
*
|
||||
* The sum of squared weights (of the query terms) is
|
||||
* computed by the query {@link org.apache.lucene.search.Weight} object.
|
||||
* For example, a {@link org.apache.lucene.search.BooleanQuery}
|
||||
* computes this value as:
|
||||
*
|
||||
* <br> <br>
|
||||
* <table cellpadding="1" cellspacing="0" border="0"n align="center">
|
||||
* <tr>
|
||||
* <td valign="middle" align="right" rowspan="1">
|
||||
* {@link org.apache.lucene.search.Weight#getValueForNormalization() sumOfSquaredWeights} =
|
||||
* {@link org.apache.lucene.search.Query#getBoost() q.getBoost()} <sup><big>2</big></sup>
|
||||
* ·
|
||||
* </td>
|
||||
* <td valign="bottom" align="center" rowspan="1">
|
||||
* <big><big><big>∑</big></big></big>
|
||||
* </td>
|
||||
* <td valign="middle" align="right" rowspan="1">
|
||||
* <big><big>(</big></big>
|
||||
* <A HREF="#formula_idf">idf(t)</A> ·
|
||||
* <A HREF="#formula_termBoost">t.getBoost()</A>
|
||||
* <big><big>) <sup>2</sup> </big></big>
|
||||
* </td>
|
||||
* </tr>
|
||||
* <tr valigh="top">
|
||||
* <td></td>
|
||||
* <td align="center"><small>t in q</small></td>
|
||||
* <td></td>
|
||||
* </tr>
|
||||
* </table>
|
||||
* <br> <br>
|
||||
*
|
||||
* </li>
|
||||
*
|
||||
* <li>
|
||||
* <A NAME="formula_termBoost"></A>
|
||||
* <b><i>t.getBoost()</i></b>
|
||||
* is a search time boost of term <i>t</i> in the query <i>q</i> as
|
||||
* specified in the query text
|
||||
* (see <A HREF="../../../../../../queryparsersyntax.html#Boosting a Term">query syntax</A>),
|
||||
* or as set by application calls to
|
||||
* {@link org.apache.lucene.search.Query#setBoost(float) setBoost()}.
|
||||
* Notice that there is really no direct API for accessing a boost of one term in a multi term query,
|
||||
* but rather multi terms are represented in a query as multi
|
||||
* {@link org.apache.lucene.search.TermQuery TermQuery} objects,
|
||||
* and so the boost of a term in the query is accessible by calling the sub-query
|
||||
* {@link org.apache.lucene.search.Query#getBoost() getBoost()}.
|
||||
* <br> <br>
|
||||
* </li>
|
||||
*
|
||||
* <li>
|
||||
* <A NAME="formula_norm"></A>
|
||||
* <b><i>norm(t,d)</i></b> encapsulates a few (indexing time) boost and length factors:
|
||||
*
|
||||
* <ul>
|
||||
* <li><b>Document boost</b> - set by calling
|
||||
* {@link org.apache.lucene.document.Document#setBoost(float) doc.setBoost()}
|
||||
* before adding the document to the index.
|
||||
* </li>
|
||||
* <li><b>Field boost</b> - set by calling
|
||||
* {@link org.apache.lucene.document.Fieldable#setBoost(float) field.setBoost()}
|
||||
* before adding the field to a document.
|
||||
* </li>
|
||||
* <li><b>lengthNorm</b> - computed
|
||||
* when the document is added to the index in accordance with the number of tokens
|
||||
* of this field in the document, so that shorter fields contribute more to the score.
|
||||
* LengthNorm is computed by the Similarity class in effect at indexing.
|
||||
* </li>
|
||||
* </ul>
|
||||
* The {@link #computeNorm} method is responsible for
|
||||
* combining all of these factors into a single float.
|
||||
*
|
||||
* <p>
|
||||
* When a document is added to the index, all the above factors are multiplied.
|
||||
* If the document has multiple fields with the same name, all their boosts are multiplied together:
|
||||
*
|
||||
* <br> <br>
|
||||
* <table cellpadding="1" cellspacing="0" border="0"n align="center">
|
||||
* <tr>
|
||||
* <td valign="middle" align="right" rowspan="1">
|
||||
* norm(t,d) =
|
||||
* {@link org.apache.lucene.document.Document#getBoost() doc.getBoost()}
|
||||
* ·
|
||||
* lengthNorm
|
||||
* ·
|
||||
* </td>
|
||||
* <td valign="bottom" align="center" rowspan="1">
|
||||
* <big><big><big>∏</big></big></big>
|
||||
* </td>
|
||||
* <td valign="middle" align="right" rowspan="1">
|
||||
* {@link org.apache.lucene.document.Fieldable#getBoost() f.getBoost}()
|
||||
* </td>
|
||||
* </tr>
|
||||
* <tr valigh="top">
|
||||
* <td></td>
|
||||
* <td align="center"><small>field <i><b>f</b></i> in <i>d</i> named as <i><b>t</b></i></small></td>
|
||||
* <td></td>
|
||||
* </tr>
|
||||
* </table>
|
||||
* <br> <br>
|
||||
* However the resulted <i>norm</i> value is {@link #encodeNormValue(float) encoded} as a single byte
|
||||
* before being stored.
|
||||
* At search time, the norm byte value is read from the index
|
||||
* {@link org.apache.lucene.store.Directory directory} and
|
||||
* {@link #decodeNormValue(byte) decoded} back to a float <i>norm</i> value.
|
||||
* This encoding/decoding, while reducing index size, comes with the price of
|
||||
* precision loss - it is not guaranteed that <i>decode(encode(x)) = x</i>.
|
||||
* For instance, <i>decode(encode(0.89)) = 0.75</i>.
|
||||
* <br> <br>
|
||||
* Compression of norm values to a single byte saves memory at search time,
|
||||
* because once a field is referenced at search time, its norms - for
|
||||
* all documents - are maintained in memory.
|
||||
* <br> <br>
|
||||
* The rationale supporting such lossy compression of norm values is that
|
||||
* given the difficulty (and inaccuracy) of users to express their true information
|
||||
* need by a query, only big differences matter.
|
||||
* <br> <br>
|
||||
* Last, note that search time is too late to modify this <i>norm</i> part of scoring, e.g. by
|
||||
* using a different {@link Similarity} for search.
|
||||
* <br> <br>
|
||||
* </li>
|
||||
* </ol>
|
||||
*
|
||||
* @see org.apache.lucene.index.IndexWriterConfig#setSimilarityProvider(SimilarityProvider)
|
||||
* @see IndexSearcher#setSimilarityProvider(SimilarityProvider)
|
||||
*/
|
||||
public abstract class TFIDFSimilarity extends Similarity {
|
||||
|
||||
/** Computes a score factor based on a term or phrase's frequency in a
|
||||
* document. This value is multiplied by the {@link #idf(int, int)}
|
||||
* factor for each term in the query and these products are then summed to
|
||||
* form the initial score for a document.
|
||||
*
|
||||
* <p>Terms and phrases repeated in a document indicate the topic of the
|
||||
* document, so implementations of this method usually return larger values
|
||||
* when <code>freq</code> is large, and smaller values when <code>freq</code>
|
||||
* is small.
|
||||
*
|
||||
* <p>The default implementation calls {@link #tf(float)}.
|
||||
*
|
||||
* @param freq the frequency of a term within a document
|
||||
* @return a score factor based on a term's within-document frequency
|
||||
*/
|
||||
public float tf(int freq) {
|
||||
return tf((float)freq);
|
||||
}
|
||||
|
||||
/** Computes a score factor based on a term or phrase's frequency in a
|
||||
* document. This value is multiplied by the {@link #idf(int, int)}
|
||||
* factor for each term in the query and these products are then summed to
|
||||
* form the initial score for a document.
|
||||
*
|
||||
* <p>Terms and phrases repeated in a document indicate the topic of the
|
||||
* document, so implementations of this method usually return larger values
|
||||
* when <code>freq</code> is large, and smaller values when <code>freq</code>
|
||||
* is small.
|
||||
*
|
||||
* @param freq the frequency of a term within a document
|
||||
* @return a score factor based on a term's within-document frequency
|
||||
*/
|
||||
public abstract float tf(float freq);
|
||||
|
||||
/**
|
||||
* Computes a score factor for a simple term and returns an explanation
|
||||
* for that score factor.
|
||||
*
|
||||
* <p>
|
||||
* The default implementation uses:
|
||||
*
|
||||
* <pre>
|
||||
* idf(docFreq, searcher.maxDoc());
|
||||
* </pre>
|
||||
*
|
||||
* Note that {@link IndexSearcher#maxDoc()} is used instead of
|
||||
* {@link org.apache.lucene.index.IndexReader#numDocs() IndexReader#numDocs()} because also
|
||||
* {@link IndexSearcher#docFreq(Term)} is used, and when the latter
|
||||
* is inaccurate, so is {@link IndexSearcher#maxDoc()}, and in the same direction.
|
||||
* In addition, {@link IndexSearcher#maxDoc()} is more efficient to compute
|
||||
*
|
||||
* @param stats statistics of the term in question
|
||||
* @param searcher the document collection being searched
|
||||
* @return an Explain object that includes both an idf score factor
|
||||
and an explanation for the term.
|
||||
* @throws IOException
|
||||
*/
|
||||
public Explanation idfExplain(TermContext stats, final IndexSearcher searcher) throws IOException {
|
||||
final int df = stats.docFreq();
|
||||
final int max = searcher.maxDoc();
|
||||
final float idf = idf(df, max);
|
||||
return new Explanation(idf, "idf(docFreq=" + df + ", maxDocs=" + max + ")");
|
||||
}
|
||||
|
||||
/**
|
||||
* Computes a score factor for a phrase.
|
||||
*
|
||||
* <p>
|
||||
* The default implementation sums the idf factor for
|
||||
* each term in the phrase.
|
||||
*
|
||||
* @param stats statistics of the terms in the phrase
|
||||
* @param searcher the document collection being searched
|
||||
* @return an Explain object that includes both an idf
|
||||
* score factor for the phrase and an explanation
|
||||
* for each term.
|
||||
* @throws IOException
|
||||
*/
|
||||
public Explanation idfExplain(final TermContext stats[], IndexSearcher searcher) throws IOException {
|
||||
final int max = searcher.maxDoc();
|
||||
float idf = 0.0f;
|
||||
final Explanation exp = new Explanation();
|
||||
exp.setDescription("idf(), sum of:");
|
||||
for (final TermContext stat : stats ) {
|
||||
final int df = stat.docFreq();
|
||||
final float termIdf = idf(df, max);
|
||||
exp.addDetail(new Explanation(termIdf, "idf(docFreq=" + df + ", maxDocs=" + max + ")"));
|
||||
idf += termIdf;
|
||||
}
|
||||
exp.setValue(idf);
|
||||
return exp;
|
||||
}
|
||||
|
||||
/** Computes a score factor based on a term's document frequency (the number
|
||||
* of documents which contain the term). This value is multiplied by the
|
||||
* {@link #tf(int)} factor for each term in the query and these products are
|
||||
* then summed to form the initial score for a document.
|
||||
*
|
||||
* <p>Terms that occur in fewer documents are better indicators of topic, so
|
||||
* implementations of this method usually return larger values for rare terms,
|
||||
* and smaller values for common terms.
|
||||
*
|
||||
* @param docFreq the number of documents which contain the term
|
||||
* @param numDocs the total number of documents in the collection
|
||||
* @return a score factor based on the term's document frequency
|
||||
*/
|
||||
public abstract float idf(int docFreq, int numDocs);
|
||||
|
||||
/** Cache of decoded bytes. */
|
||||
private static final float[] NORM_TABLE = new float[256];
|
||||
|
||||
static {
|
||||
for (int i = 0; i < 256; i++)
|
||||
NORM_TABLE[i] = SmallFloat.byte315ToFloat((byte)i);
|
||||
}
|
||||
|
||||
/** Decodes a normalization factor stored in an index.
|
||||
* @see #encodeNormValue(float)
|
||||
*/
|
||||
public float decodeNormValue(byte b) {
|
||||
return NORM_TABLE[b & 0xFF]; // & 0xFF maps negative bytes to positive above 127
|
||||
}
|
||||
|
||||
/** Encodes a normalization factor for storage in an index.
|
||||
*
|
||||
* <p>The encoding uses a three-bit mantissa, a five-bit exponent, and
|
||||
* the zero-exponent point at 15, thus
|
||||
* representing values from around 7x10^9 to 2x10^-9 with about one
|
||||
* significant decimal digit of accuracy. Zero is also represented.
|
||||
* Negative numbers are rounded up to zero. Values too large to represent
|
||||
* are rounded down to the largest representable value. Positive values too
|
||||
* small to represent are rounded up to the smallest positive representable
|
||||
* value.
|
||||
* @see org.apache.lucene.document.Field#setBoost(float)
|
||||
* @see org.apache.lucene.util.SmallFloat
|
||||
*/
|
||||
public byte encodeNormValue(float f) {
|
||||
return SmallFloat.floatToByte315(f);
|
||||
}
|
||||
|
||||
@Override
|
||||
public final Stats computeStats(IndexSearcher searcher, String fieldName, float queryBoost,
|
||||
TermContext... termContexts) throws IOException {
|
||||
final Explanation idf = termContexts.length == 1
|
||||
? idfExplain(termContexts[0], searcher)
|
||||
: idfExplain(termContexts, searcher);
|
||||
return new IDFStats(idf, queryBoost);
|
||||
}
|
||||
|
||||
@Override
|
||||
public final ExactDocScorer exactDocScorer(Stats stats, String fieldName, AtomicReaderContext context) throws IOException {
|
||||
return new ExactTFIDFDocScorer((IDFStats)stats, context.reader.norms(fieldName));
|
||||
}
|
||||
|
||||
@Override
|
||||
public final SloppyDocScorer sloppyDocScorer(Stats stats, String fieldName, AtomicReaderContext context) throws IOException {
|
||||
return new SloppyTFIDFDocScorer((IDFStats)stats, context.reader.norms(fieldName));
|
||||
}
|
||||
|
||||
// TODO: we can specialize these for omitNorms up front, but we should test that it doesn't confuse stupid hotspot.
|
||||
|
||||
private final class ExactTFIDFDocScorer extends ExactDocScorer {
|
||||
private final IDFStats stats;
|
||||
private final float weightValue;
|
||||
private final byte[] norms;
|
||||
private static final int SCORE_CACHE_SIZE = 32;
|
||||
private float[] scoreCache = new float[SCORE_CACHE_SIZE];
|
||||
|
||||
ExactTFIDFDocScorer(IDFStats stats, byte norms[]) {
|
||||
this.stats = stats;
|
||||
this.weightValue = stats.value;
|
||||
this.norms = norms;
|
||||
for (int i = 0; i < SCORE_CACHE_SIZE; i++)
|
||||
scoreCache[i] = tf(i) * weightValue;
|
||||
}
|
||||
|
||||
@Override
|
||||
public float score(int doc, int freq) {
|
||||
final float raw = // compute tf(f)*weight
|
||||
freq < SCORE_CACHE_SIZE // check cache
|
||||
? scoreCache[freq] // cache hit
|
||||
: tf(freq)*weightValue; // cache miss
|
||||
|
||||
return norms == null ? raw : raw * decodeNormValue(norms[doc]); // normalize for field
|
||||
}
|
||||
|
||||
@Override
|
||||
public Explanation explain(int doc, Explanation freq) {
|
||||
return explainScore(doc, freq, stats, norms);
|
||||
}
|
||||
}
|
||||
|
||||
private final class SloppyTFIDFDocScorer extends SloppyDocScorer {
|
||||
private final IDFStats stats;
|
||||
private final float weightValue;
|
||||
private final byte[] norms;
|
||||
|
||||
SloppyTFIDFDocScorer(IDFStats stats, byte norms[]) {
|
||||
this.stats = stats;
|
||||
this.weightValue = stats.value;
|
||||
this.norms = norms;
|
||||
}
|
||||
|
||||
@Override
|
||||
public float score(int doc, float freq) {
|
||||
final float raw = tf(freq) * weightValue; // compute tf(f)*weight
|
||||
|
||||
return norms == null ? raw : raw * decodeNormValue(norms[doc]); // normalize for field
|
||||
}
|
||||
|
||||
@Override
|
||||
public Explanation explain(int doc, Explanation freq) {
|
||||
return explainScore(doc, freq, stats, norms);
|
||||
}
|
||||
}
|
||||
|
||||
/** Collection statistics for the TF-IDF model. The only statistic of interest
|
||||
* to this model is idf. */
|
||||
private static class IDFStats extends Stats {
|
||||
/** The idf and its explanation */
|
||||
private final Explanation idf;
|
||||
private float queryNorm;
|
||||
private float queryWeight;
|
||||
private final float queryBoost;
|
||||
private float value;
|
||||
|
||||
public IDFStats(Explanation idf, float queryBoost) {
|
||||
// TODO: Validate?
|
||||
this.idf = idf;
|
||||
this.queryBoost = queryBoost;
|
||||
this.queryWeight = idf.getValue() * queryBoost; // compute query weight
|
||||
}
|
||||
|
||||
@Override
|
||||
public float getValueForNormalization() {
|
||||
// TODO: (sorta LUCENE-1907) make non-static class and expose this squaring via a nice method to subclasses?
|
||||
return queryWeight * queryWeight; // sum of squared weights
|
||||
}
|
||||
|
||||
@Override
|
||||
public void normalize(float queryNorm, float topLevelBoost) {
|
||||
this.queryNorm = queryNorm * topLevelBoost;
|
||||
queryWeight *= this.queryNorm; // normalize query weight
|
||||
value = queryWeight * idf.getValue(); // idf for document
|
||||
}
|
||||
}
|
||||
|
||||
private Explanation explainScore(int doc, Explanation freq, IDFStats stats, byte[] norms) {
|
||||
Explanation result = new Explanation();
|
||||
result.setDescription("score(doc="+doc+",freq="+freq+"), product of:");
|
||||
|
||||
// explain query weight
|
||||
Explanation queryExpl = new Explanation();
|
||||
queryExpl.setDescription("queryWeight, product of:");
|
||||
|
||||
Explanation boostExpl = new Explanation(stats.queryBoost, "boost");
|
||||
if (stats.queryBoost != 1.0f)
|
||||
queryExpl.addDetail(boostExpl);
|
||||
queryExpl.addDetail(stats.idf);
|
||||
|
||||
Explanation queryNormExpl = new Explanation(stats.queryNorm,"queryNorm");
|
||||
queryExpl.addDetail(queryNormExpl);
|
||||
|
||||
queryExpl.setValue(boostExpl.getValue() *
|
||||
stats.idf.getValue() *
|
||||
queryNormExpl.getValue());
|
||||
|
||||
result.addDetail(queryExpl);
|
||||
|
||||
// explain field weight
|
||||
Explanation fieldExpl = new Explanation();
|
||||
fieldExpl.setDescription("fieldWeight in "+doc+
|
||||
", product of:");
|
||||
|
||||
Explanation tfExplanation = new Explanation();
|
||||
tfExplanation.setValue(tf(freq.getValue()));
|
||||
tfExplanation.setDescription("tf(freq="+freq.getValue()+"), with freq of:");
|
||||
tfExplanation.addDetail(freq);
|
||||
fieldExpl.addDetail(tfExplanation);
|
||||
fieldExpl.addDetail(stats.idf);
|
||||
|
||||
Explanation fieldNormExpl = new Explanation();
|
||||
float fieldNorm =
|
||||
norms!=null ? decodeNormValue(norms[doc]) : 1.0f;
|
||||
fieldNormExpl.setValue(fieldNorm);
|
||||
fieldNormExpl.setDescription("fieldNorm(doc="+doc+")");
|
||||
fieldExpl.addDetail(fieldNormExpl);
|
||||
|
||||
fieldExpl.setValue(tfExplanation.getValue() *
|
||||
stats.idf.getValue() *
|
||||
fieldNormExpl.getValue());
|
||||
|
||||
result.addDetail(fieldExpl);
|
||||
|
||||
// combine them
|
||||
result.setValue(queryExpl.getValue() * fieldExpl.getValue());
|
||||
|
||||
if (queryExpl.getValue() == 1.0f)
|
||||
return fieldExpl;
|
||||
|
||||
return result;
|
||||
}
|
||||
}
|
|
@ -29,7 +29,7 @@ import org.apache.lucene.index.IndexReader.AtomicReaderContext;
|
|||
import org.apache.lucene.index.IndexReader.ReaderContext;
|
||||
import org.apache.lucene.util.AttributeSource;
|
||||
import org.apache.lucene.util.BytesRef;
|
||||
import org.apache.lucene.util.PerReaderTermState;
|
||||
import org.apache.lucene.util.TermContext;
|
||||
import org.apache.lucene.util.ReaderUtil;
|
||||
|
||||
abstract class TermCollectingRewrite<Q extends Query> extends MultiTermQuery.RewriteMethod {
|
||||
|
@ -43,7 +43,7 @@ abstract class TermCollectingRewrite<Q extends Query> extends MultiTermQuery.Rew
|
|||
addClause(topLevel, term, docCount, boost, null);
|
||||
}
|
||||
|
||||
protected abstract void addClause(Q topLevel, Term term, int docCount, float boost, PerReaderTermState states) throws IOException;
|
||||
protected abstract void addClause(Q topLevel, Term term, int docCount, float boost, TermContext states) throws IOException;
|
||||
|
||||
|
||||
protected final void collectTerms(IndexReader reader, MultiTermQuery query, TermCollector collector) throws IOException {
|
||||
|
|
|
@ -27,9 +27,9 @@ import org.apache.lucene.index.Terms;
|
|||
import org.apache.lucene.index.IndexReader.AtomicReaderContext;
|
||||
import org.apache.lucene.index.IndexReader.ReaderContext;
|
||||
import org.apache.lucene.index.Term;
|
||||
import org.apache.lucene.search.Explanation.IDFExplanation;
|
||||
import org.apache.lucene.search.Similarity.ExactDocScorer;
|
||||
import org.apache.lucene.util.BytesRef;
|
||||
import org.apache.lucene.util.PerReaderTermState;
|
||||
import org.apache.lucene.util.TermContext;
|
||||
import org.apache.lucene.util.ReaderUtil;
|
||||
import org.apache.lucene.util.ToStringUtils;
|
||||
|
||||
|
@ -39,28 +39,19 @@ import org.apache.lucene.util.ToStringUtils;
|
|||
public class TermQuery extends Query {
|
||||
private final Term term;
|
||||
private int docFreq;
|
||||
private transient PerReaderTermState perReaderTermState;
|
||||
private transient TermContext perReaderTermState;
|
||||
|
||||
private class TermWeight extends Weight {
|
||||
private final Similarity similarity;
|
||||
private float value;
|
||||
private final float idf;
|
||||
private float queryNorm;
|
||||
private float queryWeight;
|
||||
private final IDFExplanation idfExp;
|
||||
private transient PerReaderTermState termStates;
|
||||
private final Similarity.Stats stats;
|
||||
private transient TermContext termStates;
|
||||
|
||||
public TermWeight(IndexSearcher searcher, PerReaderTermState termStates, int docFreq)
|
||||
public TermWeight(IndexSearcher searcher, TermContext termStates)
|
||||
throws IOException {
|
||||
assert termStates != null : "PerReaderTermState must not be null";
|
||||
assert termStates != null : "TermContext must not be null";
|
||||
this.termStates = termStates;
|
||||
this.similarity = searcher.getSimilarityProvider().get(term.field());
|
||||
if (docFreq != -1) {
|
||||
idfExp = similarity.idfExplain(term, searcher, docFreq);
|
||||
} else {
|
||||
idfExp = similarity.idfExplain(term, searcher);
|
||||
}
|
||||
idf = idfExp.getIdf();
|
||||
this.stats = similarity.computeStats(searcher, term.field(), getBoost(), termStates);
|
||||
}
|
||||
|
||||
@Override
|
||||
|
@ -70,19 +61,13 @@ public class TermQuery extends Query {
|
|||
public Query getQuery() { return TermQuery.this; }
|
||||
|
||||
@Override
|
||||
public float getValue() { return value; }
|
||||
|
||||
@Override
|
||||
public float sumOfSquaredWeights() {
|
||||
queryWeight = idf * getBoost(); // compute query weight
|
||||
return queryWeight * queryWeight; // square it
|
||||
public float getValueForNormalization() {
|
||||
return stats.getValueForNormalization();
|
||||
}
|
||||
|
||||
@Override
|
||||
public void normalize(float queryNorm) {
|
||||
this.queryNorm = queryNorm;
|
||||
queryWeight *= queryNorm; // normalize query weight
|
||||
value = queryWeight * idf; // idf for document
|
||||
public void normalize(float queryNorm, float topLevelBoost) {
|
||||
stats.normalize(queryNorm, topLevelBoost);
|
||||
}
|
||||
|
||||
@Override
|
||||
|
@ -97,7 +82,7 @@ public class TermQuery extends Query {
|
|||
}
|
||||
final DocsEnum docs = reader.termDocsEnum(reader.getLiveDocs(), field, term.bytes(), state);
|
||||
assert docs != null;
|
||||
return new TermScorer(this, docs, similarity, context.reader.norms(field));
|
||||
return new TermScorer(this, docs, similarity.exactDocScorer(stats, field, context));
|
||||
}
|
||||
|
||||
private boolean termNotInReader(IndexReader reader, String field, BytesRef bytes) throws IOException {
|
||||
|
@ -107,79 +92,25 @@ public class TermQuery extends Query {
|
|||
}
|
||||
|
||||
@Override
|
||||
public Explanation explain(AtomicReaderContext context, int doc)
|
||||
throws IOException {
|
||||
final IndexReader reader = context.reader;
|
||||
|
||||
ComplexExplanation result = new ComplexExplanation();
|
||||
result.setDescription("weight("+getQuery()+" in "+doc+"), product of:");
|
||||
|
||||
Explanation expl = new Explanation(idf, idfExp.explain());
|
||||
|
||||
// explain query weight
|
||||
Explanation queryExpl = new Explanation();
|
||||
queryExpl.setDescription("queryWeight(" + getQuery() + "), product of:");
|
||||
|
||||
Explanation boostExpl = new Explanation(getBoost(), "boost");
|
||||
if (getBoost() != 1.0f)
|
||||
queryExpl.addDetail(boostExpl);
|
||||
queryExpl.addDetail(expl);
|
||||
|
||||
Explanation queryNormExpl = new Explanation(queryNorm,"queryNorm");
|
||||
queryExpl.addDetail(queryNormExpl);
|
||||
|
||||
queryExpl.setValue(boostExpl.getValue() *
|
||||
expl.getValue() *
|
||||
queryNormExpl.getValue());
|
||||
|
||||
result.addDetail(queryExpl);
|
||||
|
||||
// explain field weight
|
||||
String field = term.field();
|
||||
ComplexExplanation fieldExpl = new ComplexExplanation();
|
||||
fieldExpl.setDescription("fieldWeight("+term+" in "+doc+
|
||||
"), product of:");
|
||||
|
||||
Explanation tfExplanation = new Explanation();
|
||||
int tf = 0;
|
||||
public Explanation explain(AtomicReaderContext context, int doc) throws IOException {
|
||||
IndexReader reader = context.reader;
|
||||
DocsEnum docs = reader.termDocsEnum(context.reader.getLiveDocs(), term.field(), term.bytes());
|
||||
if (docs != null) {
|
||||
int newDoc = docs.advance(doc);
|
||||
if (newDoc == doc) {
|
||||
tf = docs.freq();
|
||||
}
|
||||
tfExplanation.setValue(similarity.tf(tf));
|
||||
tfExplanation.setDescription("tf(termFreq("+term+")="+tf+")");
|
||||
} else {
|
||||
tfExplanation.setValue(0.0f);
|
||||
tfExplanation.setDescription("no matching term");
|
||||
int newDoc = docs.advance(doc);
|
||||
if (newDoc == doc) {
|
||||
int freq = docs.freq();
|
||||
ExactDocScorer docScorer = similarity.exactDocScorer(stats, term.field(), context);
|
||||
ComplexExplanation result = new ComplexExplanation();
|
||||
result.setDescription("weight("+getQuery()+" in "+doc+") [" + similarity.getClass().getSimpleName() + "], result of:");
|
||||
Explanation scoreExplanation = docScorer.explain(doc, new Explanation(freq, "termFreq=" + freq));
|
||||
result.addDetail(scoreExplanation);
|
||||
result.setValue(scoreExplanation.getValue());
|
||||
result.setMatch(true);
|
||||
return result;
|
||||
}
|
||||
}
|
||||
fieldExpl.addDetail(tfExplanation);
|
||||
fieldExpl.addDetail(expl);
|
||||
|
||||
Explanation fieldNormExpl = new Explanation();
|
||||
final byte[] fieldNorms = reader.norms(field);
|
||||
float fieldNorm =
|
||||
fieldNorms!=null ? similarity.decodeNormValue(fieldNorms[doc]) : 1.0f;
|
||||
fieldNormExpl.setValue(fieldNorm);
|
||||
fieldNormExpl.setDescription("fieldNorm(field="+field+", doc="+doc+")");
|
||||
fieldExpl.addDetail(fieldNormExpl);
|
||||
|
||||
fieldExpl.setMatch(Boolean.valueOf(tfExplanation.isMatch()));
|
||||
fieldExpl.setValue(tfExplanation.getValue() *
|
||||
expl.getValue() *
|
||||
fieldNormExpl.getValue());
|
||||
|
||||
result.addDetail(fieldExpl);
|
||||
result.setMatch(fieldExpl.getMatch());
|
||||
|
||||
// combine them
|
||||
result.setValue(queryExpl.getValue() * fieldExpl.getValue());
|
||||
|
||||
if (queryExpl.getValue() == 1.0f)
|
||||
return fieldExpl;
|
||||
|
||||
return result;
|
||||
return new ComplexExplanation(false, 0.0f, "no matching term");
|
||||
}
|
||||
}
|
||||
|
||||
|
@ -200,7 +131,7 @@ public class TermQuery extends Query {
|
|||
/** Expert: constructs a TermQuery that will use the
|
||||
* provided docFreq instead of looking up the docFreq
|
||||
* against the searcher. */
|
||||
public TermQuery(Term t, PerReaderTermState states) {
|
||||
public TermQuery(Term t, TermContext states) {
|
||||
assert states != null;
|
||||
term = t;
|
||||
docFreq = states.docFreq();
|
||||
|
@ -213,20 +144,20 @@ public class TermQuery extends Query {
|
|||
@Override
|
||||
public Weight createWeight(IndexSearcher searcher) throws IOException {
|
||||
final ReaderContext context = searcher.getTopReaderContext();
|
||||
final int weightDocFreq;
|
||||
final PerReaderTermState termState;
|
||||
final TermContext termState;
|
||||
if (perReaderTermState == null || perReaderTermState.topReaderContext != context) {
|
||||
// make TermQuery single-pass if we don't have a PRTS or if the context differs!
|
||||
termState = PerReaderTermState.build(context, term, true); // cache term lookups!
|
||||
// we must not ignore the given docFreq - if set use the given value
|
||||
weightDocFreq = docFreq == -1 ? termState.docFreq() : docFreq;
|
||||
termState = TermContext.build(context, term, true); // cache term lookups!
|
||||
} else {
|
||||
// PRTS was pre-build for this IS
|
||||
termState = this.perReaderTermState;
|
||||
weightDocFreq = docFreq;
|
||||
}
|
||||
|
||||
return new TermWeight(searcher, termState, weightDocFreq);
|
||||
// we must not ignore the given docFreq - if set use the given value (lie)
|
||||
if (docFreq != -1)
|
||||
termState.setDocFreq(docFreq);
|
||||
|
||||
return new TermWeight(searcher, termState);
|
||||
}
|
||||
|
||||
@Override
|
||||
|
|
|
@ -25,20 +25,16 @@ import org.apache.lucene.index.DocsEnum;
|
|||
*/
|
||||
final class TermScorer extends Scorer {
|
||||
private DocsEnum docsEnum;
|
||||
private byte[] norms;
|
||||
private float weightValue;
|
||||
private int doc = -1;
|
||||
private int freq;
|
||||
|
||||
private int pointer;
|
||||
private int pointerMax;
|
||||
|
||||
private static final int SCORE_CACHE_SIZE = 32;
|
||||
private float[] scoreCache = new float[SCORE_CACHE_SIZE];
|
||||
private int[] docs;
|
||||
private int[] freqs;
|
||||
private final DocsEnum.BulkReadResult bulkResult;
|
||||
private final Similarity similarity;
|
||||
private final Similarity.ExactDocScorer docScorer;
|
||||
|
||||
/**
|
||||
* Construct a <code>TermScorer</code>.
|
||||
|
@ -47,22 +43,15 @@ final class TermScorer extends Scorer {
|
|||
* The weight of the <code>Term</code> in the query.
|
||||
* @param td
|
||||
* An iterator over the documents matching the <code>Term</code>.
|
||||
* @param similarity
|
||||
* The </code>Similarity</code> implementation to be used for score
|
||||
* computations.
|
||||
* @param norms
|
||||
* The field norms of the document fields for the <code>Term</code>.
|
||||
* @param docScorer
|
||||
* The </code>Similarity.ExactDocScorer</code> implementation
|
||||
* to be used for score computations.
|
||||
*/
|
||||
TermScorer(Weight weight, DocsEnum td, Similarity similarity, byte[] norms) {
|
||||
TermScorer(Weight weight, DocsEnum td, Similarity.ExactDocScorer docScorer) throws IOException {
|
||||
super(weight);
|
||||
this.similarity = similarity;
|
||||
this.docScorer = docScorer;
|
||||
this.docsEnum = td;
|
||||
this.norms = norms;
|
||||
this.weightValue = weight.getValue();
|
||||
bulkResult = td.getBulkResult();
|
||||
|
||||
for (int i = 0; i < SCORE_CACHE_SIZE; i++)
|
||||
scoreCache[i] = similarity.tf(i) * weightValue;
|
||||
}
|
||||
|
||||
@Override
|
||||
|
@ -134,12 +123,7 @@ final class TermScorer extends Scorer {
|
|||
@Override
|
||||
public float score() {
|
||||
assert doc != NO_MORE_DOCS;
|
||||
float raw = // compute tf(f)*weight
|
||||
freq < SCORE_CACHE_SIZE // check cache
|
||||
? scoreCache[freq] // cache hit
|
||||
: similarity.tf(freq)*weightValue; // cache miss
|
||||
|
||||
return norms == null ? raw : raw * similarity.decodeNormValue(norms[doc]); // normalize for field
|
||||
return docScorer.score(doc, freq);
|
||||
}
|
||||
|
||||
/**
|
||||
|
|
|
@ -29,7 +29,7 @@ import org.apache.lucene.index.TermState;
|
|||
import org.apache.lucene.index.TermsEnum;
|
||||
import org.apache.lucene.util.ArrayUtil;
|
||||
import org.apache.lucene.util.BytesRef;
|
||||
import org.apache.lucene.util.PerReaderTermState;
|
||||
import org.apache.lucene.util.TermContext;
|
||||
|
||||
/**
|
||||
* Base rewrite method for collecting only the top terms
|
||||
|
@ -80,7 +80,7 @@ public abstract class TopTermsRewrite<Q extends Query> extends TermCollectingRew
|
|||
this.termComp = termsEnum.getComparator();
|
||||
// lazy init the initial ScoreTerm because comparator is not known on ctor:
|
||||
if (st == null)
|
||||
st = new ScoreTerm(this.termComp, new PerReaderTermState(topReaderContext));
|
||||
st = new ScoreTerm(this.termComp, new TermContext(topReaderContext));
|
||||
boostAtt = termsEnum.attributes().addAttribute(BoostAttribute.class);
|
||||
}
|
||||
|
||||
|
@ -101,14 +101,14 @@ public abstract class TopTermsRewrite<Q extends Query> extends TermCollectingRew
|
|||
if (t != null) {
|
||||
// if the term is already in the PQ, only update docFreq of term in PQ
|
||||
assert t.boost == boost : "boost should be equal in all segment TermsEnums";
|
||||
t.termState.register(state, readerContext.ord, termsEnum.docFreq());
|
||||
t.termState.register(state, readerContext.ord, termsEnum.docFreq(), termsEnum.totalTermFreq());
|
||||
} else {
|
||||
// add new entry in PQ, we must clone the term, else it may get overwritten!
|
||||
st.bytes.copy(bytes);
|
||||
st.boost = boost;
|
||||
visitedTerms.put(st.bytes, st);
|
||||
assert st.termState.docFreq() == 0;
|
||||
st.termState.register(state, readerContext.ord, termsEnum.docFreq());
|
||||
st.termState.register(state, readerContext.ord, termsEnum.docFreq(), termsEnum.totalTermFreq());
|
||||
stQueue.offer(st);
|
||||
// possibly drop entries from queue
|
||||
if (stQueue.size() > maxSize) {
|
||||
|
@ -116,7 +116,7 @@ public abstract class TopTermsRewrite<Q extends Query> extends TermCollectingRew
|
|||
visitedTerms.remove(st.bytes);
|
||||
st.termState.clear(); // reset the termstate!
|
||||
} else {
|
||||
st = new ScoreTerm(termComp, new PerReaderTermState(topReaderContext));
|
||||
st = new ScoreTerm(termComp, new TermContext(topReaderContext));
|
||||
}
|
||||
assert stQueue.size() <= maxSize : "the PQ size must be limited to maxSize";
|
||||
// set maxBoostAtt with values to help FuzzyTermsEnum to optimize
|
||||
|
@ -171,8 +171,8 @@ public abstract class TopTermsRewrite<Q extends Query> extends TermCollectingRew
|
|||
public final Comparator<BytesRef> termComp;
|
||||
public final BytesRef bytes = new BytesRef();
|
||||
public float boost;
|
||||
public final PerReaderTermState termState;
|
||||
public ScoreTerm(Comparator<BytesRef> termComp, PerReaderTermState termState) {
|
||||
public final TermContext termState;
|
||||
public ScoreTerm(Comparator<BytesRef> termComp, TermContext termState) {
|
||||
this.termComp = termComp;
|
||||
this.termState = termState;
|
||||
}
|
||||
|
|
|
@ -41,11 +41,11 @@ import org.apache.lucene.index.IndexReader.ReaderContext;
|
|||
* <ol>
|
||||
* <li>A <code>Weight</code> is constructed by a top-level query, given a
|
||||
* <code>IndexSearcher</code> ({@link Query#createWeight(IndexSearcher)}).
|
||||
* <li>The {@link #sumOfSquaredWeights()} method is called on the
|
||||
* <li>The {@link #getValueForNormalization()} method is called on the
|
||||
* <code>Weight</code> to compute the query normalization factor
|
||||
* {@link SimilarityProvider#queryNorm(float)} of the query clauses contained in the
|
||||
* query.
|
||||
* <li>The query normalization factor is passed to {@link #normalize(float)}. At
|
||||
* <li>The query normalization factor is passed to {@link #normalize(float, float)}. At
|
||||
* this point the weighting is complete.
|
||||
* <li>A <code>Scorer</code> is constructed by
|
||||
* {@link #scorer(IndexReader.AtomicReaderContext, ScorerContext)}.
|
||||
|
@ -68,11 +68,11 @@ public abstract class Weight {
|
|||
/** The query that this concerns. */
|
||||
public abstract Query getQuery();
|
||||
|
||||
/** The weight for this query. */
|
||||
public abstract float getValue();
|
||||
/** The value for normalization of contained query clauses (e.g. sum of squared weights). */
|
||||
public abstract float getValueForNormalization() throws IOException;
|
||||
|
||||
/** Assigns the query normalization factor to this. */
|
||||
public abstract void normalize(float norm);
|
||||
/** Assigns the query normalization factor and boost from parent queries to this. */
|
||||
public abstract void normalize(float norm, float topLevelBoost);
|
||||
|
||||
/**
|
||||
* Returns a {@link Scorer} which scores documents in/out-of order according
|
||||
|
@ -94,9 +94,6 @@ public abstract class Weight {
|
|||
*/
|
||||
public abstract Scorer scorer(AtomicReaderContext context, ScorerContext scorerContext) throws IOException;
|
||||
|
||||
/** The sum of squared weights of contained query clauses. */
|
||||
public abstract float sumOfSquaredWeights() throws IOException;
|
||||
|
||||
/**
|
||||
* Returns true iff this implementation scores docs only out of order. This
|
||||
* method is used in conjunction with {@link Collector}'s
|
||||
|
|
|
@ -18,11 +18,13 @@ package org.apache.lucene.search.payloads;
|
|||
*/
|
||||
|
||||
import org.apache.lucene.index.IndexReader.AtomicReaderContext;
|
||||
import org.apache.lucene.search.ComplexExplanation;
|
||||
import org.apache.lucene.search.Explanation;
|
||||
import org.apache.lucene.search.Scorer;
|
||||
import org.apache.lucene.search.IndexSearcher;
|
||||
import org.apache.lucene.search.Similarity;
|
||||
import org.apache.lucene.search.Weight;
|
||||
import org.apache.lucene.search.Similarity.SloppyDocScorer;
|
||||
import org.apache.lucene.search.spans.NearSpansOrdered;
|
||||
import org.apache.lucene.search.spans.NearSpansUnordered;
|
||||
import org.apache.lucene.search.spans.SpanNearQuery;
|
||||
|
@ -145,7 +147,35 @@ public class PayloadNearQuery extends SpanNearQuery {
|
|||
@Override
|
||||
public Scorer scorer(AtomicReaderContext context, ScorerContext scorerContext) throws IOException {
|
||||
return new PayloadNearSpanScorer(query.getSpans(context), this,
|
||||
similarity, context.reader.norms(query.getField()));
|
||||
similarity, similarity.sloppyDocScorer(stats, query.getField(), context));
|
||||
}
|
||||
|
||||
@Override
|
||||
public Explanation explain(AtomicReaderContext context, int doc) throws IOException {
|
||||
PayloadNearSpanScorer scorer = (PayloadNearSpanScorer) scorer(context, ScorerContext.def());
|
||||
if (scorer != null) {
|
||||
int newDoc = scorer.advance(doc);
|
||||
if (newDoc == doc) {
|
||||
float freq = scorer.freq();
|
||||
SloppyDocScorer docScorer = similarity.sloppyDocScorer(stats, query.getField(), context);
|
||||
Explanation expl = new Explanation();
|
||||
expl.setDescription("weight("+getQuery()+" in "+doc+") [" + similarity.getClass().getSimpleName() + "], result of:");
|
||||
Explanation scoreExplanation = docScorer.explain(doc, new Explanation(freq, "phraseFreq=" + freq));
|
||||
expl.addDetail(scoreExplanation);
|
||||
expl.setValue(scoreExplanation.getValue());
|
||||
// now the payloads part
|
||||
Explanation payloadExpl = function.explain(doc, scorer.payloadsSeen, scorer.payloadScore);
|
||||
// combined
|
||||
ComplexExplanation result = new ComplexExplanation();
|
||||
result.addDetail(expl);
|
||||
result.addDetail(payloadExpl);
|
||||
result.setValue(expl.getValue() * payloadExpl.getValue());
|
||||
result.setDescription("PayloadNearQuery, product of:");
|
||||
return result;
|
||||
}
|
||||
}
|
||||
|
||||
return new ComplexExplanation(false, 0.0f, "no matching term");
|
||||
}
|
||||
}
|
||||
|
||||
|
@ -155,8 +185,8 @@ public class PayloadNearQuery extends SpanNearQuery {
|
|||
private int payloadsSeen;
|
||||
|
||||
protected PayloadNearSpanScorer(Spans spans, Weight weight,
|
||||
Similarity similarity, byte[] norms) throws IOException {
|
||||
super(spans, weight, similarity, norms);
|
||||
Similarity similarity, Similarity.SloppyDocScorer docScorer) throws IOException {
|
||||
super(spans, weight, similarity, docScorer);
|
||||
this.spans = spans;
|
||||
}
|
||||
|
||||
|
@ -225,20 +255,6 @@ public class PayloadNearQuery extends SpanNearQuery {
|
|||
return super.score()
|
||||
* function.docScore(doc, fieldName, payloadsSeen, payloadScore);
|
||||
}
|
||||
|
||||
@Override
|
||||
protected Explanation explain(int doc) throws IOException {
|
||||
Explanation result = new Explanation();
|
||||
// Add detail about tf/idf...
|
||||
Explanation nonPayloadExpl = super.explain(doc);
|
||||
result.addDetail(nonPayloadExpl);
|
||||
// Add detail about payload
|
||||
Explanation payloadExpl = function.explain(doc, payloadsSeen, payloadScore);
|
||||
result.addDetail(payloadExpl);
|
||||
result.setValue(nonPayloadExpl.getValue() * payloadExpl.getValue());
|
||||
result.setDescription("PayloadNearQuery, product of:");
|
||||
return result;
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
|
|
|
@ -26,6 +26,9 @@ import org.apache.lucene.search.Weight;
|
|||
import org.apache.lucene.search.Similarity;
|
||||
import org.apache.lucene.search.Explanation;
|
||||
import org.apache.lucene.search.ComplexExplanation;
|
||||
import org.apache.lucene.search.Similarity.SloppyDocScorer;
|
||||
import org.apache.lucene.search.Weight.ScorerContext;
|
||||
import org.apache.lucene.search.payloads.PayloadNearQuery.PayloadNearSpanScorer;
|
||||
import org.apache.lucene.search.spans.TermSpans;
|
||||
import org.apache.lucene.search.spans.SpanTermQuery;
|
||||
import org.apache.lucene.search.spans.SpanWeight;
|
||||
|
@ -76,7 +79,7 @@ public class PayloadTermQuery extends SpanTermQuery {
|
|||
@Override
|
||||
public Scorer scorer(AtomicReaderContext context, ScorerContext scorerContext) throws IOException {
|
||||
return new PayloadTermSpanScorer((TermSpans) query.getSpans(context),
|
||||
this, similarity, context.reader.norms(query.getField()));
|
||||
this, similarity, similarity.sloppyDocScorer(stats, query.getField(), context));
|
||||
}
|
||||
|
||||
protected class PayloadTermSpanScorer extends SpanScorer {
|
||||
|
@ -86,8 +89,8 @@ public class PayloadTermQuery extends SpanTermQuery {
|
|||
private final TermSpans termSpans;
|
||||
|
||||
public PayloadTermSpanScorer(TermSpans spans, Weight weight,
|
||||
Similarity similarity, byte[] norms) throws IOException {
|
||||
super(spans, weight, similarity, norms);
|
||||
Similarity similarity, Similarity.SloppyDocScorer docScorer) throws IOException {
|
||||
super(spans, weight, similarity, docScorer);
|
||||
termSpans = spans;
|
||||
}
|
||||
|
||||
|
@ -173,29 +176,40 @@ public class PayloadTermQuery extends SpanTermQuery {
|
|||
protected float getPayloadScore() {
|
||||
return function.docScore(doc, term.field(), payloadsSeen, payloadScore);
|
||||
}
|
||||
}
|
||||
|
||||
@Override
|
||||
protected Explanation explain(final int doc) throws IOException {
|
||||
ComplexExplanation result = new ComplexExplanation();
|
||||
Explanation nonPayloadExpl = super.explain(doc);
|
||||
result.addDetail(nonPayloadExpl);
|
||||
// QUESTION: Is there a way to avoid this skipTo call? We need to know
|
||||
// whether to load the payload or not
|
||||
Explanation payloadBoost = new Explanation();
|
||||
result.addDetail(payloadBoost);
|
||||
|
||||
float payloadScore = getPayloadScore();
|
||||
payloadBoost.setValue(payloadScore);
|
||||
// GSI: I suppose we could toString the payload, but I don't think that
|
||||
// would be a good idea
|
||||
payloadBoost.setDescription("scorePayload(...)");
|
||||
result.setValue(nonPayloadExpl.getValue() * payloadScore);
|
||||
result.setDescription("btq, product of:");
|
||||
result.setMatch(nonPayloadExpl.getValue() == 0 ? Boolean.FALSE
|
||||
: Boolean.TRUE); // LUCENE-1303
|
||||
return result;
|
||||
@Override
|
||||
public Explanation explain(AtomicReaderContext context, int doc) throws IOException {
|
||||
PayloadTermSpanScorer scorer = (PayloadTermSpanScorer) scorer(context, ScorerContext.def());
|
||||
if (scorer != null) {
|
||||
int newDoc = scorer.advance(doc);
|
||||
if (newDoc == doc) {
|
||||
float freq = scorer.freq();
|
||||
SloppyDocScorer docScorer = similarity.sloppyDocScorer(stats, query.getField(), context);
|
||||
Explanation expl = new Explanation();
|
||||
expl.setDescription("weight("+getQuery()+" in "+doc+") [" + similarity.getClass().getSimpleName() + "], result of:");
|
||||
Explanation scoreExplanation = docScorer.explain(doc, new Explanation(freq, "phraseFreq=" + freq));
|
||||
expl.addDetail(scoreExplanation);
|
||||
expl.setValue(scoreExplanation.getValue());
|
||||
// now the payloads part
|
||||
// QUESTION: Is there a way to avoid this skipTo call? We need to know
|
||||
// whether to load the payload or not
|
||||
// GSI: I suppose we could toString the payload, but I don't think that
|
||||
// would be a good idea
|
||||
Explanation payloadExpl = new Explanation(scorer.getPayloadScore(), "scorePayload(...)");
|
||||
payloadExpl.setValue(scorer.getPayloadScore());
|
||||
// combined
|
||||
ComplexExplanation result = new ComplexExplanation();
|
||||
result.addDetail(expl);
|
||||
result.addDetail(payloadExpl);
|
||||
result.setValue(expl.getValue() * payloadExpl.getValue());
|
||||
result.setDescription("btq, product of:");
|
||||
result.setMatch(expl.getValue() == 0 ? Boolean.FALSE : Boolean.TRUE); // LUCENE-1303
|
||||
return result;
|
||||
}
|
||||
}
|
||||
|
||||
return new ComplexExplanation(false, 0.0f, "no matching term");
|
||||
}
|
||||
}
|
||||
|
||||
|
|
|
@ -27,7 +27,7 @@ import org.apache.lucene.search.Query;
|
|||
import org.apache.lucene.search.TopTermsRewrite;
|
||||
import org.apache.lucene.search.ScoringRewrite;
|
||||
import org.apache.lucene.search.BooleanClause.Occur; // javadocs only
|
||||
import org.apache.lucene.util.PerReaderTermState;
|
||||
import org.apache.lucene.util.TermContext;
|
||||
|
||||
/**
|
||||
* Wraps any {@link MultiTermQuery} as a {@link SpanQuery},
|
||||
|
@ -155,7 +155,7 @@ public class SpanMultiTermQueryWrapper<Q extends MultiTermQuery> extends SpanQue
|
|||
}
|
||||
|
||||
@Override
|
||||
protected void addClause(SpanOrQuery topLevel, Term term, int docCount, float boost, PerReaderTermState states) {
|
||||
protected void addClause(SpanOrQuery topLevel, Term term, int docCount, float boost, TermContext states) {
|
||||
final SpanTermQuery q = new SpanTermQuery(term);
|
||||
q.setBoost(boost);
|
||||
topLevel.addClause(q);
|
||||
|
@ -204,7 +204,7 @@ public class SpanMultiTermQueryWrapper<Q extends MultiTermQuery> extends SpanQue
|
|||
}
|
||||
|
||||
@Override
|
||||
protected void addClause(SpanOrQuery topLevel, Term term, int docFreq, float boost, PerReaderTermState states) {
|
||||
protected void addClause(SpanOrQuery topLevel, Term term, int docFreq, float boost, TermContext states) {
|
||||
final SpanTermQuery q = new SpanTermQuery(term);
|
||||
q.setBoost(boost);
|
||||
topLevel.addClause(q);
|
||||
|
|
|
@ -20,6 +20,7 @@ package org.apache.lucene.search.spans;
|
|||
import java.io.IOException;
|
||||
|
||||
import org.apache.lucene.search.Explanation;
|
||||
import org.apache.lucene.search.TFIDFSimilarity;
|
||||
import org.apache.lucene.search.Weight;
|
||||
import org.apache.lucene.search.Scorer;
|
||||
import org.apache.lucene.search.Similarity;
|
||||
|
@ -29,22 +30,21 @@ import org.apache.lucene.search.Similarity;
|
|||
*/
|
||||
public class SpanScorer extends Scorer {
|
||||
protected Spans spans;
|
||||
protected byte[] norms;
|
||||
protected float value;
|
||||
|
||||
protected boolean more = true;
|
||||
|
||||
protected int doc;
|
||||
protected float freq;
|
||||
protected final Similarity similarity;
|
||||
protected final Similarity.SloppyDocScorer docScorer;
|
||||
|
||||
protected SpanScorer(Spans spans, Weight weight, Similarity similarity, byte[] norms)
|
||||
protected SpanScorer(Spans spans, Weight weight, Similarity similarity, Similarity.SloppyDocScorer docScorer)
|
||||
throws IOException {
|
||||
super(weight);
|
||||
this.similarity = similarity;
|
||||
this.docScorer = docScorer;
|
||||
this.spans = spans;
|
||||
this.norms = norms;
|
||||
this.value = weight.getValue();
|
||||
|
||||
if (this.spans.next()) {
|
||||
doc = -1;
|
||||
} else {
|
||||
|
@ -94,27 +94,11 @@ public class SpanScorer extends Scorer {
|
|||
|
||||
@Override
|
||||
public float score() throws IOException {
|
||||
float raw = similarity.tf(freq) * value; // raw score
|
||||
return norms == null? raw : raw * similarity.decodeNormValue(norms[doc]); // normalize
|
||||
return docScorer.score(doc, freq);
|
||||
}
|
||||
|
||||
@Override
|
||||
public float freq() throws IOException {
|
||||
return freq;
|
||||
}
|
||||
|
||||
/** This method is no longer an official member of {@link Scorer},
|
||||
* but it is needed by SpanWeight to build an explanation. */
|
||||
protected Explanation explain(final int doc) throws IOException {
|
||||
Explanation tfExplanation = new Explanation();
|
||||
|
||||
int expDoc = advance(doc);
|
||||
|
||||
float phraseFreq = (expDoc == doc) ? freq : 0.0f;
|
||||
tfExplanation.setValue(similarity.tf(phraseFreq));
|
||||
tfExplanation.setDescription("tf(phraseFreq=" + phraseFreq + ")");
|
||||
|
||||
return tfExplanation;
|
||||
}
|
||||
|
||||
}
|
||||
|
|
|
@ -18,125 +18,76 @@ package org.apache.lucene.search.spans;
|
|||
*/
|
||||
|
||||
import org.apache.lucene.index.IndexReader.AtomicReaderContext;
|
||||
import org.apache.lucene.index.IndexReader.ReaderContext;
|
||||
import org.apache.lucene.index.Term;
|
||||
import org.apache.lucene.search.*;
|
||||
import org.apache.lucene.search.Explanation.IDFExplanation;
|
||||
import org.apache.lucene.search.Similarity.SloppyDocScorer;
|
||||
import org.apache.lucene.util.TermContext;
|
||||
|
||||
import java.io.IOException;
|
||||
import java.util.HashSet;
|
||||
import java.util.Set;
|
||||
import java.util.TreeSet;
|
||||
|
||||
/**
|
||||
* Expert-only. Public for use by other weight implementations
|
||||
*/
|
||||
public class SpanWeight extends Weight {
|
||||
protected Similarity similarity;
|
||||
protected float value;
|
||||
protected float idf;
|
||||
protected float queryNorm;
|
||||
protected float queryWeight;
|
||||
|
||||
protected Set<Term> terms;
|
||||
protected SpanQuery query;
|
||||
private IDFExplanation idfExp;
|
||||
protected Similarity.Stats stats;
|
||||
|
||||
public SpanWeight(SpanQuery query, IndexSearcher searcher)
|
||||
throws IOException {
|
||||
this.similarity = searcher.getSimilarityProvider().get(query.getField());
|
||||
this.query = query;
|
||||
|
||||
terms=new HashSet<Term>();
|
||||
terms=new TreeSet<Term>();
|
||||
query.extractTerms(terms);
|
||||
|
||||
idfExp = similarity.idfExplain(terms, searcher);
|
||||
idf = idfExp.getIdf();
|
||||
final ReaderContext context = searcher.getTopReaderContext();
|
||||
final TermContext states[] = new TermContext[terms.size()];
|
||||
int i = 0;
|
||||
for (Term term : terms)
|
||||
states[i++] = TermContext.build(context, term, true);
|
||||
stats = similarity.computeStats(searcher, query.getField(), query.getBoost(), states);
|
||||
}
|
||||
|
||||
@Override
|
||||
public Query getQuery() { return query; }
|
||||
|
||||
@Override
|
||||
public float getValue() { return value; }
|
||||
|
||||
@Override
|
||||
public float sumOfSquaredWeights() throws IOException {
|
||||
queryWeight = idf * query.getBoost(); // compute query weight
|
||||
return queryWeight * queryWeight; // square it
|
||||
public float getValueForNormalization() throws IOException {
|
||||
return stats.getValueForNormalization();
|
||||
}
|
||||
|
||||
@Override
|
||||
public void normalize(float queryNorm) {
|
||||
this.queryNorm = queryNorm;
|
||||
queryWeight *= queryNorm; // normalize query weight
|
||||
value = queryWeight * idf; // idf for document
|
||||
public void normalize(float queryNorm, float topLevelBoost) {
|
||||
stats.normalize(queryNorm, topLevelBoost);
|
||||
}
|
||||
|
||||
@Override
|
||||
public Scorer scorer(AtomicReaderContext context, ScorerContext scorerContext) throws IOException {
|
||||
return new SpanScorer(query.getSpans(context), this, similarity, context.reader
|
||||
.norms(query.getField()));
|
||||
return new SpanScorer(query.getSpans(context), this, similarity, similarity.sloppyDocScorer(stats, query.getField(), context));
|
||||
}
|
||||
|
||||
@Override
|
||||
public Explanation explain(AtomicReaderContext context, int doc)
|
||||
throws IOException {
|
||||
public Explanation explain(AtomicReaderContext context, int doc) throws IOException {
|
||||
Scorer scorer = scorer(context, ScorerContext.def());
|
||||
if (scorer != null) {
|
||||
int newDoc = scorer.advance(doc);
|
||||
if (newDoc == doc) {
|
||||
float freq = scorer.freq();
|
||||
SloppyDocScorer docScorer = similarity.sloppyDocScorer(stats, query.getField(), context);
|
||||
ComplexExplanation result = new ComplexExplanation();
|
||||
result.setDescription("weight("+getQuery()+" in "+doc+") [" + similarity.getClass().getSimpleName() + "], result of:");
|
||||
Explanation scoreExplanation = docScorer.explain(doc, new Explanation(freq, "phraseFreq=" + freq));
|
||||
result.addDetail(scoreExplanation);
|
||||
result.setValue(scoreExplanation.getValue());
|
||||
result.setMatch(true);
|
||||
return result;
|
||||
}
|
||||
}
|
||||
|
||||
ComplexExplanation result = new ComplexExplanation();
|
||||
result.setDescription("weight("+getQuery()+" in "+doc+"), product of:");
|
||||
String field = ((SpanQuery)getQuery()).getField();
|
||||
|
||||
Explanation idfExpl =
|
||||
new Explanation(idf, "idf(" + field + ": " + idfExp.explain() + ")");
|
||||
|
||||
// explain query weight
|
||||
Explanation queryExpl = new Explanation();
|
||||
queryExpl.setDescription("queryWeight(" + getQuery() + "), product of:");
|
||||
|
||||
Explanation boostExpl = new Explanation(getQuery().getBoost(), "boost");
|
||||
if (getQuery().getBoost() != 1.0f)
|
||||
queryExpl.addDetail(boostExpl);
|
||||
queryExpl.addDetail(idfExpl);
|
||||
|
||||
Explanation queryNormExpl = new Explanation(queryNorm,"queryNorm");
|
||||
queryExpl.addDetail(queryNormExpl);
|
||||
|
||||
queryExpl.setValue(boostExpl.getValue() *
|
||||
idfExpl.getValue() *
|
||||
queryNormExpl.getValue());
|
||||
|
||||
result.addDetail(queryExpl);
|
||||
|
||||
// explain field weight
|
||||
ComplexExplanation fieldExpl = new ComplexExplanation();
|
||||
fieldExpl.setDescription("fieldWeight("+field+":"+query.toString(field)+
|
||||
" in "+doc+"), product of:");
|
||||
|
||||
Explanation tfExpl = ((SpanScorer)scorer(context, ScorerContext.def())).explain(doc);
|
||||
fieldExpl.addDetail(tfExpl);
|
||||
fieldExpl.addDetail(idfExpl);
|
||||
|
||||
Explanation fieldNormExpl = new Explanation();
|
||||
byte[] fieldNorms = context.reader.norms(field);
|
||||
float fieldNorm =
|
||||
fieldNorms!=null ? similarity.decodeNormValue(fieldNorms[doc]) : 1.0f;
|
||||
fieldNormExpl.setValue(fieldNorm);
|
||||
fieldNormExpl.setDescription("fieldNorm(field="+field+", doc="+doc+")");
|
||||
fieldExpl.addDetail(fieldNormExpl);
|
||||
|
||||
fieldExpl.setMatch(Boolean.valueOf(tfExpl.isMatch()));
|
||||
fieldExpl.setValue(tfExpl.getValue() *
|
||||
idfExpl.getValue() *
|
||||
fieldNormExpl.getValue());
|
||||
|
||||
result.addDetail(fieldExpl);
|
||||
result.setMatch(fieldExpl.getMatch());
|
||||
|
||||
// combine them
|
||||
result.setValue(queryExpl.getValue() * fieldExpl.getValue());
|
||||
|
||||
if (queryExpl.getValue() == 1.0f)
|
||||
return fieldExpl;
|
||||
|
||||
return result;
|
||||
return new ComplexExplanation(false, 0.0f, "no matching term");
|
||||
}
|
||||
}
|
||||
|
|
|
@ -60,7 +60,7 @@ public abstract class CompoundFileDirectory extends Directory {
|
|||
* NOTE: subclasses must call {@link #initForRead(Map)} before the directory can be used.
|
||||
*/
|
||||
public CompoundFileDirectory(Directory directory, String fileName, IOContext context) throws IOException {
|
||||
assert !(directory instanceof CompoundFileDirectory) : "compound file inside of compound file: " + fileName;
|
||||
|
||||
this.directory = directory;
|
||||
this.fileName = fileName;
|
||||
this.readBufferSize = BufferedIndexInput.bufferSize(context);
|
||||
|
@ -75,9 +75,11 @@ public abstract class CompoundFileDirectory extends Directory {
|
|||
}
|
||||
|
||||
protected final void initForWrite() {
|
||||
assert !(directory instanceof CompoundFileDirectory) : "compound file inside of compound file: " + fileName;
|
||||
this.entries = SENTINEL;
|
||||
this.openForWrite = true;
|
||||
this.isOpen = true;
|
||||
writer = new CompoundFileWriter(directory, fileName);
|
||||
}
|
||||
|
||||
/** Helper method that reads CFS entries from an input stream */
|
||||
|
@ -173,7 +175,11 @@ public abstract class CompoundFileDirectory extends Directory {
|
|||
|
||||
@Override
|
||||
public synchronized void close() throws IOException {
|
||||
ensureOpen();
|
||||
if (!isOpen) {
|
||||
// allow double close - usually to be consistent with other closeables
|
||||
assert entries == null;
|
||||
return; // already closed
|
||||
}
|
||||
entries = null;
|
||||
isOpen = false;
|
||||
if (writer != null) {
|
||||
|
@ -263,7 +269,6 @@ public abstract class CompoundFileDirectory extends Directory {
|
|||
@Override
|
||||
public IndexOutput createOutput(String name, IOContext context) throws IOException {
|
||||
ensureOpen();
|
||||
initWriter();
|
||||
return writer.createOutput(name, context);
|
||||
}
|
||||
|
||||
|
@ -279,12 +284,13 @@ public abstract class CompoundFileDirectory extends Directory {
|
|||
throw new UnsupportedOperationException();
|
||||
}
|
||||
|
||||
/** Not implemented
|
||||
* @throws UnsupportedOperationException */
|
||||
@Override
|
||||
public final CompoundFileDirectory openCompoundInput(String name, IOContext context) throws IOException {
|
||||
// NOTE: final to make nested compounding impossible.
|
||||
throw new UnsupportedOperationException();
|
||||
public CompoundFileDirectory openCompoundInput(String name, IOContext context) throws IOException {
|
||||
FileEntry fileEntry = this.entries.get(IndexFileNames.stripSegmentName(name));
|
||||
if (fileEntry == null) {
|
||||
throw new FileNotFoundException("file " + name + " does not exists in this CFS");
|
||||
}
|
||||
return new NestedCompoundFileDirectory(name, context, fileEntry.offset, fileEntry.length);
|
||||
}
|
||||
|
||||
/** Not implemented
|
||||
|
@ -292,16 +298,36 @@ public abstract class CompoundFileDirectory extends Directory {
|
|||
@Override
|
||||
public CompoundFileDirectory createCompoundOutput(String name, IOContext context)
|
||||
throws IOException {
|
||||
// NOTE: final to make nested compounding impossible.
|
||||
throw new UnsupportedOperationException();
|
||||
throw new UnsupportedOperationException("can not create nested CFS, create seperately and use Directory.copy instead");
|
||||
}
|
||||
|
||||
private final void initWriter() {
|
||||
assert openForWrite;
|
||||
assert entries == SENTINEL;
|
||||
if (writer == null) {
|
||||
writer = new CompoundFileWriter(directory, fileName);
|
||||
private class NestedCompoundFileDirectory extends CompoundFileDirectory {
|
||||
|
||||
private final long cfsOffset;
|
||||
private final long cfsLength;
|
||||
|
||||
public NestedCompoundFileDirectory(String fileName, IOContext context, long offset, long length)
|
||||
throws IOException {
|
||||
super(directory, fileName, context);
|
||||
this.cfsOffset = offset;
|
||||
this.cfsLength = length;
|
||||
IndexInput input = null;
|
||||
try {
|
||||
input = CompoundFileDirectory.this.openInput(fileName, IOContext.READONCE);
|
||||
initForRead(CompoundFileDirectory.readEntries(input,
|
||||
CompoundFileDirectory.this, fileName));
|
||||
} finally {
|
||||
IOUtils.closeSafely(false, input);
|
||||
}
|
||||
}
|
||||
|
||||
@Override
|
||||
public IndexInput openInputSlice(String id, long offset, long length,
|
||||
int readBufferSize) throws IOException {
|
||||
assert offset + length <= cfsLength;
|
||||
return CompoundFileDirectory.this.openInputSlice(id, cfsOffset + offset, length, readBufferSize);
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
}
|
||||
|
|
|
@ -17,6 +17,7 @@ package org.apache.lucene.store;
|
|||
* limitations under the License.
|
||||
*/
|
||||
|
||||
import java.io.Closeable;
|
||||
import java.io.FileNotFoundException;
|
||||
import java.io.IOException;
|
||||
import java.util.Collection;
|
||||
|
@ -55,7 +56,7 @@ import org.apache.lucene.util.IOUtils;
|
|||
*
|
||||
* @lucene.internal
|
||||
*/
|
||||
final class CompoundFileWriter {
|
||||
final class CompoundFileWriter implements Closeable{
|
||||
|
||||
private static final class FileEntry {
|
||||
/** source file */
|
||||
|
@ -89,8 +90,8 @@ final class CompoundFileWriter {
|
|||
private boolean closed = false;
|
||||
private volatile IndexOutput dataOut;
|
||||
private final AtomicBoolean outputTaken = new AtomicBoolean(false);
|
||||
private final String entryTableName;
|
||||
private final String dataFileName;
|
||||
final String entryTableName;
|
||||
final String dataFileName;
|
||||
|
||||
/**
|
||||
* Create the compound stream in the specified file. The file name is the
|
||||
|
@ -128,17 +129,14 @@ final class CompoundFileWriter {
|
|||
* if close() had been called before or if no file has been added to
|
||||
* this object
|
||||
*/
|
||||
void close() throws IOException {
|
||||
public void close() throws IOException {
|
||||
if (closed) {
|
||||
throw new IllegalStateException("already closed");
|
||||
}
|
||||
IOException priorException = null;
|
||||
IndexOutput entryTableOut = null;
|
||||
try {
|
||||
if (entries.isEmpty()) {
|
||||
throw new IllegalStateException("CFS has no entries");
|
||||
}
|
||||
|
||||
initDataOut(IOContext.DEFAULT);
|
||||
if (!pendingEntries.isEmpty() || outputTaken.get()) {
|
||||
throw new IllegalStateException("CFS has pending open files");
|
||||
}
|
||||
|
@ -147,12 +145,18 @@ final class CompoundFileWriter {
|
|||
assert dataOut != null;
|
||||
long finalLength = dataOut.getFilePointer();
|
||||
assert assertFileLength(finalLength, dataOut);
|
||||
} catch (IOException e) {
|
||||
priorException = e;
|
||||
} finally {
|
||||
IOUtils.closeSafely(priorException, dataOut);
|
||||
}
|
||||
try {
|
||||
entryTableOut = directory.createOutput(entryTableName, IOContext.DEFAULT);
|
||||
writeEntryTable(entries.values(), entryTableOut);
|
||||
} catch (IOException e) {
|
||||
priorException = e;
|
||||
} finally {
|
||||
IOUtils.closeSafely(priorException, dataOut, entryTableOut);
|
||||
IOUtils.closeSafely(priorException, entryTableOut);
|
||||
}
|
||||
}
|
||||
|
||||
|
@ -321,6 +325,7 @@ final class CompoundFileWriter {
|
|||
closed = true;
|
||||
entry.length = writtenBytes;
|
||||
if (isSeparate) {
|
||||
delegate.close();
|
||||
// we are a separate file - push into the pending entries
|
||||
pendingEntries.add(entry);
|
||||
} else {
|
||||
|
|
|
@ -28,25 +28,27 @@ import org.apache.lucene.index.Terms;
|
|||
import org.apache.lucene.index.TermsEnum;
|
||||
import org.apache.lucene.index.IndexReader.AtomicReaderContext;
|
||||
import org.apache.lucene.index.IndexReader.ReaderContext;
|
||||
import org.apache.lucene.index.TermsEnum.SeekStatus;
|
||||
|
||||
/**
|
||||
* Maintains a {@link IndexReader} {@link TermState} view over
|
||||
* {@link IndexReader} instances containing a single term. The
|
||||
* {@link PerReaderTermState} doesn't track if the given {@link TermState}
|
||||
* {@link TermContext} doesn't track if the given {@link TermState}
|
||||
* objects are valid, neither if the {@link TermState} instances refer to the
|
||||
* same terms in the associated readers.
|
||||
*
|
||||
* @lucene.experimental
|
||||
*/
|
||||
public final class PerReaderTermState {
|
||||
public final class TermContext {
|
||||
public final ReaderContext topReaderContext; // for asserting!
|
||||
private final TermState[] states;
|
||||
private int docFreq;
|
||||
private long totalTermFreq;
|
||||
|
||||
/**
|
||||
* Creates an empty {@link PerReaderTermState} from a {@link ReaderContext}
|
||||
* Creates an empty {@link TermContext} from a {@link ReaderContext}
|
||||
*/
|
||||
public PerReaderTermState(ReaderContext context) {
|
||||
public TermContext(ReaderContext context) {
|
||||
assert context != null && context.isTopLevel;
|
||||
topReaderContext = context;
|
||||
docFreq = 0;
|
||||
|
@ -60,28 +62,28 @@ public final class PerReaderTermState {
|
|||
}
|
||||
|
||||
/**
|
||||
* Creates a {@link PerReaderTermState} with an initial {@link TermState},
|
||||
* Creates a {@link TermContext} with an initial {@link TermState},
|
||||
* {@link IndexReader} pair.
|
||||
*/
|
||||
public PerReaderTermState(ReaderContext context, TermState state, int ord, int docFreq) {
|
||||
public TermContext(ReaderContext context, TermState state, int ord, int docFreq, long totalTermFreq) {
|
||||
this(context);
|
||||
register(state, ord, docFreq);
|
||||
register(state, ord, docFreq, totalTermFreq);
|
||||
}
|
||||
|
||||
/**
|
||||
* Creates a {@link PerReaderTermState} from a top-level {@link ReaderContext} and the
|
||||
* Creates a {@link TermContext} from a top-level {@link ReaderContext} and the
|
||||
* given {@link Term}. This method will lookup the given term in all context's leaf readers
|
||||
* and register each of the readers containing the term in the returned {@link PerReaderTermState}
|
||||
* and register each of the readers containing the term in the returned {@link TermContext}
|
||||
* using the leaf reader's ordinal.
|
||||
* <p>
|
||||
* Note: the given context must be a top-level context.
|
||||
*/
|
||||
public static PerReaderTermState build(ReaderContext context, Term term, boolean cache)
|
||||
public static TermContext build(ReaderContext context, Term term, boolean cache)
|
||||
throws IOException {
|
||||
assert context != null && context.isTopLevel;
|
||||
final String field = term.field();
|
||||
final BytesRef bytes = term.bytes();
|
||||
final PerReaderTermState perReaderTermState = new PerReaderTermState(context);
|
||||
final TermContext perReaderTermState = new TermContext(context);
|
||||
final AtomicReaderContext[] leaves = ReaderUtil.leaves(context);
|
||||
for (int i = 0; i < leaves.length; i++) {
|
||||
final Fields fields = leaves[i].reader.fields();
|
||||
|
@ -91,7 +93,7 @@ public final class PerReaderTermState {
|
|||
final TermsEnum termsEnum = terms.getThreadTermsEnum(); // thread-private don't share!
|
||||
if (termsEnum.seekExact(bytes, cache)) {
|
||||
final TermState termState = termsEnum.termState();
|
||||
perReaderTermState.register(termState, leaves[i].ord, termsEnum.docFreq());
|
||||
perReaderTermState.register(termState, leaves[i].ord, termsEnum.docFreq(), termsEnum.totalTermFreq());
|
||||
}
|
||||
}
|
||||
}
|
||||
|
@ -100,7 +102,7 @@ public final class PerReaderTermState {
|
|||
}
|
||||
|
||||
/**
|
||||
* Clears the {@link PerReaderTermState} internal state and removes all
|
||||
* Clears the {@link TermContext} internal state and removes all
|
||||
* registered {@link TermState}s
|
||||
*/
|
||||
public void clear() {
|
||||
|
@ -112,12 +114,16 @@ public final class PerReaderTermState {
|
|||
* Registers and associates a {@link TermState} with an leaf ordinal. The leaf ordinal
|
||||
* should be derived from a {@link ReaderContext}'s leaf ord.
|
||||
*/
|
||||
public void register(TermState state, final int ord, final int docFreq) {
|
||||
public void register(TermState state, final int ord, final int docFreq, final long totalTermFreq) {
|
||||
assert state != null : "state must not be null";
|
||||
assert ord >= 0 && ord < states.length;
|
||||
assert states[ord] == null : "state for ord: " + ord
|
||||
+ " already registered";
|
||||
this.docFreq += docFreq;
|
||||
if (this.totalTermFreq >= 0 && totalTermFreq >= 0)
|
||||
this.totalTermFreq += totalTermFreq;
|
||||
else
|
||||
this.totalTermFreq = -1;
|
||||
states[ord] = state;
|
||||
}
|
||||
|
||||
|
@ -137,11 +143,27 @@ public final class PerReaderTermState {
|
|||
|
||||
/**
|
||||
* Returns the accumulated document frequency of all {@link TermState}
|
||||
* instances passed to {@link #register(TermState, int, int)}.
|
||||
* instances passed to {@link #register(TermState, int, int, long)}.
|
||||
* @return the accumulated document frequency of all {@link TermState}
|
||||
* instances passed to {@link #register(TermState, int, int)}.
|
||||
* instances passed to {@link #register(TermState, int, int, long)}.
|
||||
*/
|
||||
public int docFreq() {
|
||||
return docFreq;
|
||||
}
|
||||
|
||||
/**
|
||||
* Returns the accumulated term frequency of all {@link TermState}
|
||||
* instances passed to {@link #register(TermState, int, int, long)}.
|
||||
* @return the accumulated term frequency of all {@link TermState}
|
||||
* instances passed to {@link #register(TermState, int, int, long)}.
|
||||
*/
|
||||
public long totalTermFreq() {
|
||||
return totalTermFreq;
|
||||
}
|
||||
|
||||
/** expert: only available for queries that want to lie about docfreq
|
||||
* @lucene.internal */
|
||||
public void setDocFreq(int docFreq) {
|
||||
this.docFreq = docFreq;
|
||||
}
|
||||
}
|
|
@ -32,6 +32,7 @@ import org.apache.lucene.index.codecs.sep.IntIndexInput;
|
|||
import org.apache.lucene.index.codecs.sep.IntIndexOutput;
|
||||
import org.apache.lucene.index.codecs.sep.SepPostingsReaderImpl;
|
||||
import org.apache.lucene.index.codecs.sep.SepPostingsWriterImpl;
|
||||
import org.apache.lucene.index.codecs.standard.StandardCodec;
|
||||
import org.apache.lucene.index.codecs.intblock.FixedIntBlockIndexInput;
|
||||
import org.apache.lucene.index.codecs.intblock.FixedIntBlockIndexOutput;
|
||||
import org.apache.lucene.index.codecs.DefaultDocValuesProducer;
|
||||
|
@ -46,7 +47,6 @@ import org.apache.lucene.index.codecs.BlockTermsReader;
|
|||
import org.apache.lucene.index.codecs.BlockTermsWriter;
|
||||
import org.apache.lucene.index.codecs.TermsIndexReaderBase;
|
||||
import org.apache.lucene.index.codecs.TermsIndexWriterBase;
|
||||
import org.apache.lucene.index.codecs.standard.StandardCodec;
|
||||
import org.apache.lucene.store.*;
|
||||
import org.apache.lucene.util.BytesRef;
|
||||
import org.apache.lucene.util.IOUtils;
|
||||
|
@ -62,8 +62,8 @@ public class MockFixedIntBlockCodec extends Codec {
|
|||
private final int blockSize;
|
||||
|
||||
public MockFixedIntBlockCodec(int blockSize) {
|
||||
super("MockFixedIntBlock");
|
||||
this.blockSize = blockSize;
|
||||
name = "MockFixedIntBlock";
|
||||
}
|
||||
|
||||
@Override
|
||||
|
@ -207,7 +207,7 @@ public class MockFixedIntBlockCodec extends Codec {
|
|||
SepPostingsReaderImpl.files(segmentInfo, codecId, files);
|
||||
BlockTermsReader.files(dir, segmentInfo, codecId, files);
|
||||
FixedGapTermsIndexReader.files(dir, segmentInfo, codecId, files);
|
||||
DefaultDocValuesConsumer.files(dir, segmentInfo, codecId, files);
|
||||
DefaultDocValuesConsumer.files(dir, segmentInfo, codecId, files, getDocValuesUseCFS());
|
||||
}
|
||||
|
||||
@Override
|
||||
|
@ -215,16 +215,16 @@ public class MockFixedIntBlockCodec extends Codec {
|
|||
SepPostingsWriterImpl.getExtensions(extensions);
|
||||
BlockTermsReader.getExtensions(extensions);
|
||||
FixedGapTermsIndexReader.getIndexExtensions(extensions);
|
||||
DefaultDocValuesConsumer.getDocValuesExtensions(extensions);
|
||||
DefaultDocValuesConsumer.getDocValuesExtensions(extensions, getDocValuesUseCFS());
|
||||
}
|
||||
|
||||
@Override
|
||||
public PerDocConsumer docsConsumer(PerDocWriteState state) throws IOException {
|
||||
return new DefaultDocValuesConsumer(state, BytesRef.getUTF8SortedAsUnicodeComparator());
|
||||
return new DefaultDocValuesConsumer(state, getDocValuesSortComparator(), getDocValuesUseCFS());
|
||||
}
|
||||
|
||||
@Override
|
||||
public PerDocValues docsProducer(SegmentReadState state) throws IOException {
|
||||
return new DefaultDocValuesProducer(state.segmentInfo, state.dir, state.fieldInfos, state.codecId, state.context);
|
||||
return new DefaultDocValuesProducer(state.segmentInfo, state.dir, state.fieldInfos, state.codecId, getDocValuesUseCFS(), getDocValuesSortComparator(), state.context);
|
||||
}
|
||||
}
|
||||
|
|
|
@ -32,6 +32,7 @@ import org.apache.lucene.index.codecs.sep.IntIndexInput;
|
|||
import org.apache.lucene.index.codecs.sep.IntIndexOutput;
|
||||
import org.apache.lucene.index.codecs.sep.SepPostingsReaderImpl;
|
||||
import org.apache.lucene.index.codecs.sep.SepPostingsWriterImpl;
|
||||
import org.apache.lucene.index.codecs.standard.StandardCodec;
|
||||
import org.apache.lucene.index.codecs.intblock.VariableIntBlockIndexInput;
|
||||
import org.apache.lucene.index.codecs.intblock.VariableIntBlockIndexOutput;
|
||||
import org.apache.lucene.index.codecs.DefaultDocValuesProducer;
|
||||
|
@ -46,7 +47,6 @@ import org.apache.lucene.index.codecs.BlockTermsReader;
|
|||
import org.apache.lucene.index.codecs.BlockTermsWriter;
|
||||
import org.apache.lucene.index.codecs.TermsIndexReaderBase;
|
||||
import org.apache.lucene.index.codecs.TermsIndexWriterBase;
|
||||
import org.apache.lucene.index.codecs.standard.StandardCodec;
|
||||
import org.apache.lucene.store.Directory;
|
||||
import org.apache.lucene.store.IOContext;
|
||||
import org.apache.lucene.store.IndexInput;
|
||||
|
@ -65,7 +65,7 @@ public class MockVariableIntBlockCodec extends Codec {
|
|||
private final int baseBlockSize;
|
||||
|
||||
public MockVariableIntBlockCodec(int baseBlockSize) {
|
||||
name = "MockVariableIntBlock";
|
||||
super("MockVariableIntBlock");
|
||||
this.baseBlockSize = baseBlockSize;
|
||||
}
|
||||
|
||||
|
@ -230,7 +230,7 @@ public class MockVariableIntBlockCodec extends Codec {
|
|||
SepPostingsReaderImpl.files(segmentInfo, codecId, files);
|
||||
BlockTermsReader.files(dir, segmentInfo, codecId, files);
|
||||
FixedGapTermsIndexReader.files(dir, segmentInfo, codecId, files);
|
||||
DefaultDocValuesConsumer.files(dir, segmentInfo, codecId, files);
|
||||
DefaultDocValuesConsumer.files(dir, segmentInfo, codecId, files, getDocValuesUseCFS());
|
||||
}
|
||||
|
||||
@Override
|
||||
|
@ -238,16 +238,16 @@ public class MockVariableIntBlockCodec extends Codec {
|
|||
SepPostingsWriterImpl.getExtensions(extensions);
|
||||
BlockTermsReader.getExtensions(extensions);
|
||||
FixedGapTermsIndexReader.getIndexExtensions(extensions);
|
||||
DefaultDocValuesConsumer.getDocValuesExtensions(extensions);
|
||||
DefaultDocValuesConsumer.getDocValuesExtensions(extensions, getDocValuesUseCFS());
|
||||
}
|
||||
|
||||
@Override
|
||||
public PerDocConsumer docsConsumer(PerDocWriteState state) throws IOException {
|
||||
return new DefaultDocValuesConsumer(state, BytesRef.getUTF8SortedAsUnicodeComparator());
|
||||
return new DefaultDocValuesConsumer(state, getDocValuesSortComparator(), getDocValuesUseCFS());
|
||||
}
|
||||
|
||||
@Override
|
||||
public PerDocValues docsProducer(SegmentReadState state) throws IOException {
|
||||
return new DefaultDocValuesProducer(state.segmentInfo, state.dir, state.fieldInfos, state.codecId, state.context);
|
||||
return new DefaultDocValuesProducer(state.segmentInfo, state.dir, state.fieldInfos, state.codecId, getDocValuesUseCFS(), getDocValuesSortComparator(), state.context);
|
||||
}
|
||||
}
|
||||
|
|
|
@ -78,7 +78,7 @@ public class MockRandomCodec extends Codec {
|
|||
private final String SEED_EXT = "sd";
|
||||
|
||||
public MockRandomCodec(Random random) {
|
||||
name = "MockRandom";
|
||||
super("MockRandom");
|
||||
this.seedRandom = new Random(random.nextLong());
|
||||
}
|
||||
|
||||
|
@ -355,7 +355,7 @@ public class MockRandomCodec extends Codec {
|
|||
BlockTermsReader.files(dir, segmentInfo, codecId, files);
|
||||
FixedGapTermsIndexReader.files(dir, segmentInfo, codecId, files);
|
||||
VariableGapTermsIndexReader.files(dir, segmentInfo, codecId, files);
|
||||
DefaultDocValuesConsumer.files(dir, segmentInfo, codecId, files);
|
||||
DefaultDocValuesConsumer.files(dir, segmentInfo, codecId, files, getDocValuesUseCFS());
|
||||
// hackish!
|
||||
Iterator<String> it = files.iterator();
|
||||
while(it.hasNext()) {
|
||||
|
@ -373,7 +373,7 @@ public class MockRandomCodec extends Codec {
|
|||
BlockTermsReader.getExtensions(extensions);
|
||||
FixedGapTermsIndexReader.getIndexExtensions(extensions);
|
||||
VariableGapTermsIndexReader.getIndexExtensions(extensions);
|
||||
DefaultDocValuesConsumer.getDocValuesExtensions(extensions);
|
||||
DefaultDocValuesConsumer.getDocValuesExtensions(extensions, getDocValuesUseCFS());
|
||||
extensions.add(SEED_EXT);
|
||||
//System.out.println("MockRandom.getExtensions return " + extensions);
|
||||
}
|
||||
|
@ -381,11 +381,11 @@ public class MockRandomCodec extends Codec {
|
|||
// can we make this more evil?
|
||||
@Override
|
||||
public PerDocConsumer docsConsumer(PerDocWriteState state) throws IOException {
|
||||
return new DefaultDocValuesConsumer(state, BytesRef.getUTF8SortedAsUnicodeComparator());
|
||||
return new DefaultDocValuesConsumer(state, getDocValuesSortComparator(), getDocValuesUseCFS());
|
||||
}
|
||||
|
||||
@Override
|
||||
public PerDocValues docsProducer(SegmentReadState state) throws IOException {
|
||||
return new DefaultDocValuesProducer(state.segmentInfo, state.dir, state.fieldInfos, state.codecId, state.context);
|
||||
return new DefaultDocValuesProducer(state.segmentInfo, state.dir, state.fieldInfos, state.codecId, getDocValuesUseCFS(), getDocValuesSortComparator(), state.context);
|
||||
}
|
||||
}
|
||||
|
|
|
@ -54,7 +54,7 @@ import org.apache.lucene.util.BytesRef;
|
|||
public class MockSepCodec extends Codec {
|
||||
|
||||
public MockSepCodec() {
|
||||
name = "MockSep";
|
||||
super("MockSep");
|
||||
}
|
||||
|
||||
@Override
|
||||
|
@ -139,13 +139,13 @@ public class MockSepCodec extends Codec {
|
|||
SepPostingsReaderImpl.files(segmentInfo, codecId, files);
|
||||
BlockTermsReader.files(dir, segmentInfo, codecId, files);
|
||||
FixedGapTermsIndexReader.files(dir, segmentInfo, codecId, files);
|
||||
DefaultDocValuesConsumer.files(dir, segmentInfo, codecId, files);
|
||||
DefaultDocValuesConsumer.files(dir, segmentInfo, codecId, files, getDocValuesUseCFS());
|
||||
}
|
||||
|
||||
@Override
|
||||
public void getExtensions(Set<String> extensions) {
|
||||
getSepExtensions(extensions);
|
||||
DefaultDocValuesConsumer.getDocValuesExtensions(extensions);
|
||||
DefaultDocValuesConsumer.getDocValuesExtensions(extensions, getDocValuesUseCFS());
|
||||
}
|
||||
|
||||
public static void getSepExtensions(Set<String> extensions) {
|
||||
|
@ -156,11 +156,11 @@ public class MockSepCodec extends Codec {
|
|||
|
||||
@Override
|
||||
public PerDocConsumer docsConsumer(PerDocWriteState state) throws IOException {
|
||||
return new DefaultDocValuesConsumer(state, BytesRef.getUTF8SortedAsUnicodeComparator());
|
||||
return new DefaultDocValuesConsumer(state, getDocValuesSortComparator(), getDocValuesUseCFS());
|
||||
}
|
||||
|
||||
@Override
|
||||
public PerDocValues docsProducer(SegmentReadState state) throws IOException {
|
||||
return new DefaultDocValuesProducer(state.segmentInfo, state.dir, state.fieldInfos, state.codecId, state.context);
|
||||
return new DefaultDocValuesProducer(state.segmentInfo, state.dir, state.fieldInfos, state.codecId, getDocValuesUseCFS(), getDocValuesSortComparator(), state.context);
|
||||
}
|
||||
}
|
||||
|
|
|
@ -37,7 +37,6 @@ public class PreFlexRWCodec extends PreFlexCodec {
|
|||
public PreFlexRWCodec() {
|
||||
// NOTE: we impersonate the PreFlex codec so that it can
|
||||
// read the segments we write!
|
||||
super();
|
||||
}
|
||||
|
||||
@Override
|
||||
|
|
|
@ -62,12 +62,7 @@ public class AssertingIndexSearcher extends IndexSearcher {
|
|||
}
|
||||
|
||||
@Override
|
||||
public float getValue() {
|
||||
return w.getValue();
|
||||
}
|
||||
|
||||
@Override
|
||||
public void normalize(float norm) {
|
||||
public void normalize(float norm, float topLevelBoost) {
|
||||
throw new IllegalStateException("Weight already normalized.");
|
||||
}
|
||||
|
||||
|
@ -77,7 +72,7 @@ public class AssertingIndexSearcher extends IndexSearcher {
|
|||
}
|
||||
|
||||
@Override
|
||||
public float sumOfSquaredWeights() throws IOException {
|
||||
public float getValueForNormalization() throws IOException {
|
||||
throw new IllegalStateException("Weight already normalized.");
|
||||
}
|
||||
|
||||
|
|
|
@ -329,9 +329,10 @@ public class CheckHits {
|
|||
Explanation detail[] = expl.getDetails();
|
||||
if (detail!=null) {
|
||||
if (detail.length==1) {
|
||||
// simple containment, no matter what the description says,
|
||||
// simple containment, unless its a freq of: (which lets a query explain how the freq is calculated),
|
||||
// just verify contained expl has same score
|
||||
verifyExplanation(q,doc,score,deep,detail[0]);
|
||||
if (!expl.getDescription().endsWith("with freq of:"))
|
||||
verifyExplanation(q,doc,score,deep,detail[0]);
|
||||
} else {
|
||||
// explanation must either:
|
||||
// - end with one of: "product of:", "sum of:", "max of:", or
|
||||
|
@ -357,6 +358,7 @@ public class CheckHits {
|
|||
}
|
||||
}
|
||||
}
|
||||
// TODO: this is a TERRIBLE assertion!!!!
|
||||
Assert.assertTrue(
|
||||
q+": multi valued explanation description=\""+descr
|
||||
+"\" must be 'max of plus x times others' or end with 'product of'"
|
||||
|
|
|
@ -19,7 +19,6 @@ package org.apache.lucene.store;
|
|||
|
||||
import java.io.IOException;
|
||||
import java.util.Collection;
|
||||
import java.util.Collections;
|
||||
|
||||
public class MockCompoundFileDirectoryWrapper extends CompoundFileDirectory {
|
||||
private final MockDirectoryWrapper parent;
|
||||
|
@ -31,11 +30,7 @@ public class MockCompoundFileDirectoryWrapper extends CompoundFileDirectory {
|
|||
this.name = name;
|
||||
this.parent = parent;
|
||||
this.delegate = delegate;
|
||||
if (forWrite) {
|
||||
super.initForWrite();
|
||||
} else {
|
||||
super.initForRead(Collections.<String,FileEntry>emptyMap());
|
||||
}
|
||||
// don't initialize here since we delegate everything - if not initialized a direct call will cause an assert to fail!
|
||||
parent.addFileHandle(this, name, !forWrite);
|
||||
}
|
||||
|
||||
|
@ -51,12 +46,8 @@ public class MockCompoundFileDirectoryWrapper extends CompoundFileDirectory {
|
|||
|
||||
@Override
|
||||
public synchronized void close() throws IOException {
|
||||
try {
|
||||
delegate.close();
|
||||
parent.removeOpenFile(this, name);
|
||||
} finally {
|
||||
super.close();
|
||||
}
|
||||
delegate.close();
|
||||
parent.removeOpenFile(this, name);
|
||||
}
|
||||
|
||||
@Override
|
||||
|
@ -148,4 +139,11 @@ public class MockCompoundFileDirectoryWrapper extends CompoundFileDirectory {
|
|||
public CompoundFileDirectory createCompoundOutput(String name, IOContext context) throws IOException {
|
||||
return delegate.createCompoundOutput(name, context);
|
||||
}
|
||||
|
||||
@Override
|
||||
public CompoundFileDirectory openCompoundInput(String name, IOContext context)
|
||||
throws IOException {
|
||||
return delegate.openCompoundInput(name, context);
|
||||
}
|
||||
|
||||
}
|
||||
|
|
|
@ -242,7 +242,7 @@ public abstract class LuceneTestCase extends Assert {
|
|||
if (prior != null) {
|
||||
cp.unregister(prior);
|
||||
}
|
||||
cp.register(c);
|
||||
cp.register(randomizCodec(random, c));
|
||||
}
|
||||
|
||||
// returns current default codec
|
||||
|
@ -280,7 +280,7 @@ public abstract class LuceneTestCase extends Assert {
|
|||
}
|
||||
|
||||
swapCodec(new MockSepCodec(), cp);
|
||||
swapCodec(new PulsingCodec(codecHasParam && "Pulsing".equals(codec) ? codecParam : _TestUtil.nextInt(random, 1, 20)), cp);
|
||||
swapCodec(new PulsingCodec(codecHasParam && "Pulsing".equals(codec) ? codecParam : 1 + random.nextInt(20)), cp);
|
||||
swapCodec(new MockFixedIntBlockCodec(codecHasParam && "MockFixedIntBlock".equals(codec) ? codecParam : _TestUtil.nextInt(random, 1, 2000)), cp);
|
||||
// baseBlockSize cannot be over 127:
|
||||
swapCodec(new MockVariableIntBlockCodec(codecHasParam && "MockVariableIntBlock".equals(codec) ? codecParam : _TestUtil.nextInt(random, 1, 127)), cp);
|
||||
|
@ -289,6 +289,11 @@ public abstract class LuceneTestCase extends Assert {
|
|||
return cp.lookup(codec);
|
||||
}
|
||||
|
||||
public static Codec randomizCodec(Random random, Codec codec) {
|
||||
codec.setDocValuesUseCFS(random.nextBoolean());
|
||||
return codec;
|
||||
}
|
||||
|
||||
// returns current PreFlex codec
|
||||
static void removeTestCodecs(Codec codec, CodecProvider cp) {
|
||||
if (codec.name.equals("PreFlex")) {
|
||||
|
@ -1493,11 +1498,11 @@ public abstract class LuceneTestCase extends Assert {
|
|||
|
||||
RandomCodecProvider(Random random) {
|
||||
this.perFieldSeed = random.nextInt();
|
||||
register(new StandardCodec());
|
||||
register(new PreFlexCodec());
|
||||
register(new PulsingCodec(1));
|
||||
register(new SimpleTextCodec());
|
||||
register(new MemoryCodec());
|
||||
register(randomizCodec(random, new StandardCodec()));
|
||||
register(randomizCodec(random, new PreFlexCodec()));
|
||||
register(randomizCodec(random, new PulsingCodec( 1 + random.nextInt(20))));
|
||||
register(randomizCodec(random, new SimpleTextCodec()));
|
||||
register(randomizCodec(random, new MemoryCodec()));
|
||||
Collections.shuffle(knownCodecs, random);
|
||||
}
|
||||
|
||||
|
|
|
@ -24,8 +24,6 @@ import org.apache.lucene.document.*;
|
|||
import org.apache.lucene.search.*;
|
||||
import org.apache.lucene.analysis.*;
|
||||
import org.apache.lucene.index.codecs.*;
|
||||
import org.apache.lucene.index.codecs.standard.*;
|
||||
import org.apache.lucene.index.codecs.pulsing.*;
|
||||
import org.apache.lucene.store.*;
|
||||
import java.util.*;
|
||||
import java.io.*;
|
||||
|
@ -75,7 +73,7 @@ public class TestExternalCodecs extends LuceneTestCase {
|
|||
public static class RAMOnlyCodec extends Codec {
|
||||
|
||||
public RAMOnlyCodec() {
|
||||
name = "RamOnly";
|
||||
super("RamOnly");
|
||||
}
|
||||
// Postings state:
|
||||
static class RAMPostings extends FieldsProducer {
|
||||
|
|
|
@ -1161,7 +1161,7 @@ public class TestAddIndexes extends LuceneTestCase {
|
|||
IndexWriterConfig conf = newIndexWriterConfig(TEST_VERSION_CURRENT,
|
||||
new MockAnalyzer(random));
|
||||
CodecProvider provider = new CodecProvider();
|
||||
provider.register(new PulsingCodec(1 + random.nextInt(10)));
|
||||
provider.register(new PulsingCodec(1 + random.nextInt(20)));
|
||||
conf.setCodecProvider(provider);
|
||||
IndexWriter w = new IndexWriter(dir, conf);
|
||||
try {
|
||||
|
@ -1182,7 +1182,7 @@ public class TestAddIndexes extends LuceneTestCase {
|
|||
IndexWriterConfig conf = newIndexWriterConfig(TEST_VERSION_CURRENT,
|
||||
new MockAnalyzer(random));
|
||||
CodecProvider provider = new CodecProvider();
|
||||
provider.register(new PulsingCodec(1 + random.nextInt(10)));
|
||||
provider.register(new PulsingCodec(1 + random.nextInt(20)));
|
||||
conf.setCodecProvider(provider);
|
||||
IndexWriter w = new IndexWriter(dir, conf);
|
||||
IndexReader indexReader = IndexReader.open(toAdd);
|
||||
|
|
|
@ -38,7 +38,6 @@ import org.apache.lucene.search.FieldCache;
|
|||
import org.apache.lucene.search.IndexSearcher;
|
||||
import org.apache.lucene.search.NumericRangeQuery;
|
||||
import org.apache.lucene.search.ScoreDoc;
|
||||
import org.apache.lucene.search.Similarity;
|
||||
import org.apache.lucene.search.TermQuery;
|
||||
import org.apache.lucene.store.CompoundFileDirectory;
|
||||
import org.apache.lucene.store.Directory;
|
||||
|
@ -375,7 +374,8 @@ public class TestBackwardsCompatibility extends LuceneTestCase {
|
|||
Term searchTerm = new Term("id", "6");
|
||||
int delCount = reader.deleteDocuments(searchTerm);
|
||||
assertEquals("wrong delete count", 1, delCount);
|
||||
reader.setNorm(searcher.search(new TermQuery(new Term("id", "22")), 10).scoreDocs[0].doc, "content", searcher.getSimilarityProvider().get("content").encodeNormValue(2.0f));
|
||||
DefaultSimilarity sim = new DefaultSimilarity();
|
||||
reader.setNorm(searcher.search(new TermQuery(new Term("id", "22")), 10).scoreDocs[0].doc, "content", sim.encodeNormValue(2.0f));
|
||||
reader.close();
|
||||
searcher.close();
|
||||
|
||||
|
@ -421,7 +421,8 @@ public class TestBackwardsCompatibility extends LuceneTestCase {
|
|||
Term searchTerm = new Term("id", "6");
|
||||
int delCount = reader.deleteDocuments(searchTerm);
|
||||
assertEquals("wrong delete count", 1, delCount);
|
||||
reader.setNorm(22, "content", searcher.getSimilarityProvider().get("content").encodeNormValue(2.0f));
|
||||
DefaultSimilarity sim = new DefaultSimilarity();
|
||||
reader.setNorm(22, "content", sim.encodeNormValue(2.0f));
|
||||
reader.close();
|
||||
|
||||
// make sure they "took":
|
||||
|
@ -483,7 +484,8 @@ public class TestBackwardsCompatibility extends LuceneTestCase {
|
|||
assertEquals("didn't delete the right number of documents", 1, delCount);
|
||||
|
||||
// Set one norm so we get a .s0 file:
|
||||
reader.setNorm(21, "content", conf.getSimilarityProvider().get("content").encodeNormValue(1.5f));
|
||||
DefaultSimilarity sim = new DefaultSimilarity();
|
||||
reader.setNorm(21, "content", sim.encodeNormValue(1.5f));
|
||||
reader.close();
|
||||
}
|
||||
|
||||
|
@ -526,7 +528,7 @@ public class TestBackwardsCompatibility extends LuceneTestCase {
|
|||
assertEquals("didn't delete the right number of documents", 1, delCount);
|
||||
|
||||
// Set one norm so we get a .s0 file:
|
||||
Similarity sim = new DefaultSimilarity();
|
||||
DefaultSimilarity sim = new DefaultSimilarity();
|
||||
reader.setNorm(21, "content", sim.encodeNormValue(1.5f));
|
||||
reader.close();
|
||||
|
||||
|
|
|
@ -21,10 +21,9 @@ import java.io.IOException;
|
|||
import java.io.File;
|
||||
|
||||
import org.apache.lucene.util.LuceneTestCase;
|
||||
import junit.framework.TestSuite;
|
||||
import junit.textui.TestRunner;
|
||||
|
||||
import org.apache.lucene.store.CompoundFileDirectory;
|
||||
import org.apache.lucene.store.IOContext;
|
||||
import org.apache.lucene.store.IndexOutput;
|
||||
import org.apache.lucene.store.Directory;
|
||||
import org.apache.lucene.store.IndexInput;
|
||||
|
@ -35,27 +34,8 @@ import org.apache.lucene.util._TestUtil;
|
|||
|
||||
public class TestCompoundFile extends LuceneTestCase
|
||||
{
|
||||
/** Main for running test case by itself. */
|
||||
public static void main(String args[]) {
|
||||
TestRunner.run (new TestSuite(TestCompoundFile.class));
|
||||
// TestRunner.run (new TestCompoundFile("testSingleFile"));
|
||||
// TestRunner.run (new TestCompoundFile("testTwoFiles"));
|
||||
// TestRunner.run (new TestCompoundFile("testRandomFiles"));
|
||||
// TestRunner.run (new TestCompoundFile("testClonedStreamsClosing"));
|
||||
// TestRunner.run (new TestCompoundFile("testReadAfterClose"));
|
||||
// TestRunner.run (new TestCompoundFile("testRandomAccess"));
|
||||
// TestRunner.run (new TestCompoundFile("testRandomAccessClones"));
|
||||
// TestRunner.run (new TestCompoundFile("testFileNotFound"));
|
||||
// TestRunner.run (new TestCompoundFile("testReadPastEOF"));
|
||||
|
||||
// TestRunner.run (new TestCompoundFile("testIWCreate"));
|
||||
|
||||
}
|
||||
|
||||
|
||||
private Directory dir;
|
||||
|
||||
|
||||
@Override
|
||||
public void setUp() throws Exception {
|
||||
super.setUp();
|
||||
|
@ -323,13 +303,13 @@ public class TestCompoundFile extends LuceneTestCase
|
|||
throws IOException
|
||||
{
|
||||
// Setup the test file - we need more than 1024 bytes
|
||||
IndexOutput os = fsdir.createOutput(file, newIOContext(random));
|
||||
IndexOutput os = fsdir.createOutput(file, IOContext.DEFAULT);
|
||||
for(int i=0; i<2000; i++) {
|
||||
os.writeByte((byte) i);
|
||||
}
|
||||
os.close();
|
||||
|
||||
IndexInput in = fsdir.openInput(file, newIOContext(random));
|
||||
IndexInput in = fsdir.openInput(file, IOContext.DEFAULT);
|
||||
|
||||
// This read primes the buffer in IndexInput
|
||||
in.readByte();
|
||||
|
@ -718,4 +698,73 @@ public class TestCompoundFile extends LuceneTestCase
|
|||
newDir.close();
|
||||
}
|
||||
|
||||
public void testEmptyCFS() throws IOException {
|
||||
Directory newDir = newDirectory();
|
||||
CompoundFileDirectory csw = newDir.createCompoundOutput("d.cfs", newIOContext(random));
|
||||
csw.close();
|
||||
|
||||
CompoundFileDirectory csr = newDir.openCompoundInput("d.cfs", newIOContext(random));
|
||||
assertEquals(0, csr.listAll().length);
|
||||
csr.close();
|
||||
|
||||
newDir.close();
|
||||
}
|
||||
|
||||
public void testReadNestedCFP() throws IOException {
|
||||
Directory newDir = newDirectory();
|
||||
CompoundFileDirectory csw = newDir.createCompoundOutput("d.cfs", newIOContext(random));
|
||||
CompoundFileDirectory nested = newDir.createCompoundOutput("b.cfs", newIOContext(random));
|
||||
IndexOutput out = nested.createOutput("b.xyz", newIOContext(random));
|
||||
IndexOutput out1 = nested.createOutput("b_1.xyz", newIOContext(random));
|
||||
out.writeInt(0);
|
||||
out1.writeInt(1);
|
||||
out.close();
|
||||
out1.close();
|
||||
nested.close();
|
||||
newDir.copy(csw, "b.cfs", "b.cfs", newIOContext(random));
|
||||
newDir.copy(csw, "b.cfe", "b.cfe", newIOContext(random));
|
||||
newDir.deleteFile("b.cfs");
|
||||
newDir.deleteFile("b.cfe");
|
||||
csw.close();
|
||||
|
||||
assertEquals(2, newDir.listAll().length);
|
||||
csw = newDir.openCompoundInput("d.cfs", newIOContext(random));
|
||||
|
||||
assertEquals(2, csw.listAll().length);
|
||||
nested = csw.openCompoundInput("b.cfs", newIOContext(random));
|
||||
|
||||
assertEquals(2, nested.listAll().length);
|
||||
IndexInput openInput = nested.openInput("b.xyz", newIOContext(random));
|
||||
assertEquals(0, openInput.readInt());
|
||||
openInput.close();
|
||||
openInput = nested.openInput("b_1.xyz", newIOContext(random));
|
||||
assertEquals(1, openInput.readInt());
|
||||
openInput.close();
|
||||
nested.close();
|
||||
csw.close();
|
||||
newDir.close();
|
||||
}
|
||||
|
||||
public void testDoubleClose() throws IOException {
|
||||
Directory newDir = newDirectory();
|
||||
CompoundFileDirectory csw = newDir.createCompoundOutput("d.cfs", newIOContext(random));
|
||||
IndexOutput out = csw.createOutput("d.xyz", newIOContext(random));
|
||||
out.writeInt(0);
|
||||
out.close();
|
||||
|
||||
csw.close();
|
||||
// close a second time - must have no effect according to Closeable
|
||||
csw.close();
|
||||
|
||||
csw = newDir.openCompoundInput("d.cfs", newIOContext(random));
|
||||
IndexInput openInput = csw.openInput("d.xyz", newIOContext(random));
|
||||
assertEquals(0, openInput.readInt());
|
||||
openInput.close();
|
||||
csw.close();
|
||||
// close a second time - must have no effect according to Closeable
|
||||
csw.close();
|
||||
|
||||
newDir.close();
|
||||
|
||||
}
|
||||
}
|
||||
|
|
|
@ -27,6 +27,7 @@ import org.apache.lucene.analysis.MockAnalyzer;
|
|||
import org.apache.lucene.document.Document;
|
||||
import org.apache.lucene.document.Field;
|
||||
import org.apache.lucene.index.IndexWriterConfig.OpenMode;
|
||||
import org.apache.lucene.search.DefaultSimilarity;
|
||||
import org.apache.lucene.search.IndexSearcher;
|
||||
import org.apache.lucene.search.Query;
|
||||
import org.apache.lucene.search.ScoreDoc;
|
||||
|
@ -655,7 +656,8 @@ public class TestDeletionPolicy extends LuceneTestCase {
|
|||
writer.close();
|
||||
IndexReader reader = IndexReader.open(dir, policy, false);
|
||||
reader.deleteDocument(3*i+1);
|
||||
reader.setNorm(4*i+1, "content", conf.getSimilarityProvider().get("content").encodeNormValue(2.0F));
|
||||
DefaultSimilarity sim = new DefaultSimilarity();
|
||||
reader.setNorm(4*i+1, "content", sim.encodeNormValue(2.0F));
|
||||
IndexSearcher searcher = newSearcher(reader);
|
||||
ScoreDoc[] hits = searcher.search(query, null, 1000).scoreDocs;
|
||||
assertEquals(16*(1+i), hits.length);
|
||||
|
@ -781,7 +783,8 @@ public class TestDeletionPolicy extends LuceneTestCase {
|
|||
writer.close();
|
||||
IndexReader reader = IndexReader.open(dir, policy, false);
|
||||
reader.deleteDocument(3);
|
||||
reader.setNorm(5, "content", conf.getSimilarityProvider().get("content").encodeNormValue(2.0F));
|
||||
DefaultSimilarity sim = new DefaultSimilarity();
|
||||
reader.setNorm(5, "content", sim.encodeNormValue(2.0F));
|
||||
IndexSearcher searcher = newSearcher(reader);
|
||||
ScoreDoc[] hits = searcher.search(query, null, 1000).scoreDocs;
|
||||
assertEquals(16, hits.length);
|
||||
|
|
|
@ -105,8 +105,9 @@ public class TestDocTermOrds extends LuceneTestCase {
|
|||
}
|
||||
|
||||
private static class StandardCodecWithOrds extends Codec {
|
||||
|
||||
public StandardCodecWithOrds() {
|
||||
name = "StandardOrds";
|
||||
super("StandardOrds");
|
||||
}
|
||||
|
||||
@Override
|
||||
|
@ -200,13 +201,13 @@ public class TestDocTermOrds extends LuceneTestCase {
|
|||
StandardPostingsReader.files(dir, segmentInfo, id, files);
|
||||
BlockTermsReader.files(dir, segmentInfo, id, files);
|
||||
FixedGapTermsIndexReader.files(dir, segmentInfo, id, files);
|
||||
DefaultDocValuesConsumer.files(dir, segmentInfo, id, files);
|
||||
DefaultDocValuesConsumer.files(dir, segmentInfo, id, files, getDocValuesUseCFS());
|
||||
}
|
||||
|
||||
@Override
|
||||
public void getExtensions(Set<String> extensions) {
|
||||
getStandardExtensions(extensions);
|
||||
DefaultDocValuesConsumer.getDocValuesExtensions(extensions);
|
||||
DefaultDocValuesConsumer.getDocValuesExtensions(extensions, getDocValuesUseCFS());
|
||||
}
|
||||
|
||||
public static void getStandardExtensions(Set<String> extensions) {
|
||||
|
@ -218,12 +219,12 @@ public class TestDocTermOrds extends LuceneTestCase {
|
|||
|
||||
@Override
|
||||
public PerDocConsumer docsConsumer(PerDocWriteState state) throws IOException {
|
||||
return new DefaultDocValuesConsumer(state, BytesRef.getUTF8SortedAsUnicodeComparator());
|
||||
return new DefaultDocValuesConsumer(state, getDocValuesSortComparator(), getDocValuesUseCFS());
|
||||
}
|
||||
|
||||
@Override
|
||||
public PerDocValues docsProducer(SegmentReadState state) throws IOException {
|
||||
return new DefaultDocValuesProducer(state.segmentInfo, state.dir, state.fieldInfos, state.codecId, state.context);
|
||||
return new DefaultDocValuesProducer(state.segmentInfo, state.dir, state.fieldInfos, state.codecId, getDocValuesUseCFS(), getDocValuesSortComparator(), state.context);
|
||||
}
|
||||
}
|
||||
|
||||
|
|
|
@ -71,7 +71,7 @@ public class TestIndexFileDeleter extends LuceneTestCase {
|
|||
Term searchTerm = new Term("id", "7");
|
||||
int delCount = reader.deleteDocuments(searchTerm);
|
||||
assertEquals("didn't delete the right number of documents", 1, delCount);
|
||||
Similarity sim = new DefaultSimilarity();
|
||||
DefaultSimilarity sim = new DefaultSimilarity();
|
||||
// Set one norm so we get a .s0 file:
|
||||
reader.setNorm(21, "content", sim.encodeNormValue(1.5f));
|
||||
reader.close();
|
||||
|
|
|
@ -421,7 +421,7 @@ public class TestIndexReader extends LuceneTestCase
|
|||
// expected
|
||||
}
|
||||
|
||||
Similarity sim = new DefaultSimilarity();
|
||||
DefaultSimilarity sim = new DefaultSimilarity();
|
||||
try {
|
||||
reader.setNorm(5, "aaa", sim.encodeNormValue(2.0f));
|
||||
fail("setNorm after close failed to throw IOException");
|
||||
|
@ -462,7 +462,7 @@ public class TestIndexReader extends LuceneTestCase
|
|||
// expected
|
||||
}
|
||||
|
||||
Similarity sim = new DefaultSimilarity();
|
||||
DefaultSimilarity sim = new DefaultSimilarity();
|
||||
try {
|
||||
reader.setNorm(5, "aaa", sim.encodeNormValue(2.0f));
|
||||
fail("setNorm should have hit LockObtainFailedException");
|
||||
|
@ -494,7 +494,7 @@ public class TestIndexReader extends LuceneTestCase
|
|||
|
||||
// now open reader & set norm for doc 0
|
||||
IndexReader reader = IndexReader.open(dir, false);
|
||||
Similarity sim = new DefaultSimilarity();
|
||||
DefaultSimilarity sim = new DefaultSimilarity();
|
||||
reader.setNorm(0, "content", sim.encodeNormValue(2.0f));
|
||||
|
||||
// we should be holding the write lock now:
|
||||
|
@ -539,7 +539,7 @@ public class TestIndexReader extends LuceneTestCase
|
|||
addDoc(writer, searchTerm.text());
|
||||
writer.close();
|
||||
|
||||
Similarity sim = new DefaultSimilarity();
|
||||
DefaultSimilarity sim = new DefaultSimilarity();
|
||||
// now open reader & set norm for doc 0 (writes to
|
||||
// _0_1.s0)
|
||||
reader = IndexReader.open(dir, false);
|
||||
|
@ -738,7 +738,7 @@ public class TestIndexReader extends LuceneTestCase
|
|||
}
|
||||
|
||||
reader = IndexReader.open(dir, false);
|
||||
Similarity sim = new DefaultSimilarity();
|
||||
DefaultSimilarity sim = new DefaultSimilarity();
|
||||
try {
|
||||
reader.setNorm(1, "content", sim.encodeNormValue(2.0f));
|
||||
fail("did not hit exception when calling setNorm on an invalid doc number");
|
||||
|
|
|
@ -273,7 +273,7 @@ public class TestIndexReaderClone extends LuceneTestCase {
|
|||
* @throws Exception
|
||||
*/
|
||||
private void performDefaultTests(IndexReader r1) throws Exception {
|
||||
Similarity sim = new DefaultSimilarity();
|
||||
DefaultSimilarity sim = new DefaultSimilarity();
|
||||
float norm1 = sim.decodeNormValue(MultiNorms.norms(r1, "field1")[4]);
|
||||
|
||||
IndexReader pr1Clone = (IndexReader) r1.clone();
|
||||
|
@ -329,7 +329,7 @@ public class TestIndexReaderClone extends LuceneTestCase {
|
|||
TestIndexReaderReopen.createIndex(random, dir1, false);
|
||||
SegmentReader origSegmentReader = getOnlySegmentReader(IndexReader.open(dir1, false));
|
||||
origSegmentReader.deleteDocument(1);
|
||||
Similarity sim = new DefaultSimilarity();
|
||||
DefaultSimilarity sim = new DefaultSimilarity();
|
||||
origSegmentReader.setNorm(4, "field1", sim.encodeNormValue(0.5f));
|
||||
|
||||
SegmentReader clonedSegmentReader = (SegmentReader) origSegmentReader
|
||||
|
@ -429,7 +429,7 @@ public class TestIndexReaderClone extends LuceneTestCase {
|
|||
final Directory dir1 = newDirectory();
|
||||
TestIndexReaderReopen.createIndex(random, dir1, false);
|
||||
IndexReader orig = IndexReader.open(dir1, false);
|
||||
Similarity sim = new DefaultSimilarity();
|
||||
DefaultSimilarity sim = new DefaultSimilarity();
|
||||
orig.setNorm(1, "field1", sim.encodeNormValue(17.0f));
|
||||
final byte encoded = sim.encodeNormValue(17.0f);
|
||||
assertEquals(encoded, MultiNorms.norms(orig, "field1")[1]);
|
||||
|
|
|
@ -47,9 +47,9 @@ public class TestIndexReaderCloneNorms extends LuceneTestCase {
|
|||
public Similarity get(String field) {
|
||||
return new DefaultSimilarity() {
|
||||
@Override
|
||||
public float computeNorm(FieldInvertState state) {
|
||||
public byte computeNorm(FieldInvertState state) {
|
||||
// diable length norm
|
||||
return state.getBoost();
|
||||
return encodeNormValue(state.getBoost());
|
||||
}
|
||||
};
|
||||
}
|
||||
|
@ -217,7 +217,7 @@ public class TestIndexReaderCloneNorms extends LuceneTestCase {
|
|||
IndexReader reader4C = (IndexReader) reader3C.clone();
|
||||
SegmentReader segmentReader4C = getOnlySegmentReader(reader4C);
|
||||
assertEquals(4, reader3CCNorm.bytesRef().get());
|
||||
Similarity sim = new DefaultSimilarity();
|
||||
DefaultSimilarity sim = new DefaultSimilarity();
|
||||
reader4C.setNorm(5, "field1", sim.encodeNormValue(0.33f));
|
||||
|
||||
// generate a cannot update exception in reader1
|
||||
|
@ -278,7 +278,7 @@ public class TestIndexReaderCloneNorms extends LuceneTestCase {
|
|||
// System.out.println(" and: for "+k+" from "+newNorm+" to "+origNorm);
|
||||
modifiedNorms.set(i, Float.valueOf(newNorm));
|
||||
modifiedNorms.set(k, Float.valueOf(origNorm));
|
||||
Similarity sim = new DefaultSimilarity();
|
||||
DefaultSimilarity sim = new DefaultSimilarity();
|
||||
ir.setNorm(i, "f" + 1, sim.encodeNormValue(newNorm));
|
||||
ir.setNorm(k, "f" + 1, sim.encodeNormValue(origNorm));
|
||||
// System.out.println("setNorm i: "+i);
|
||||
|
@ -300,7 +300,7 @@ public class TestIndexReaderCloneNorms extends LuceneTestCase {
|
|||
assertEquals("number of norms mismatches", numDocNorms, b.length);
|
||||
ArrayList<Float> storedNorms = (i == 1 ? modifiedNorms : norms);
|
||||
for (int j = 0; j < b.length; j++) {
|
||||
Similarity sim = new DefaultSimilarity();
|
||||
DefaultSimilarity sim = new DefaultSimilarity();
|
||||
float norm = sim.decodeNormValue(b[j]);
|
||||
float norm1 = storedNorms.get(j).floatValue();
|
||||
assertEquals("stored norm value of " + field + " for doc " + j + " is "
|
||||
|
@ -340,7 +340,7 @@ public class TestIndexReaderCloneNorms extends LuceneTestCase {
|
|||
// return unique norm values that are unchanged by encoding/decoding
|
||||
private float nextNorm(String fname) {
|
||||
float norm = lastNorm + normDelta;
|
||||
Similarity sim = new DefaultSimilarity();
|
||||
DefaultSimilarity sim = new DefaultSimilarity();
|
||||
do {
|
||||
float norm1 = sim.decodeNormValue(
|
||||
sim.encodeNormValue(norm));
|
||||
|
|
|
@ -131,7 +131,7 @@ public class TestIndexReaderOnDiskFull extends LuceneTestCase {
|
|||
|
||||
dir.setMaxSizeInBytes(thisDiskFree);
|
||||
dir.setRandomIOExceptionRate(rate);
|
||||
Similarity sim = new DefaultSimilarity();
|
||||
DefaultSimilarity sim = new DefaultSimilarity();
|
||||
try {
|
||||
if (0 == x) {
|
||||
int docId = 12;
|
||||
|
|
|
@ -606,7 +606,7 @@ public class TestIndexReaderReopen extends LuceneTestCase {
|
|||
|
||||
IndexReader reader2 = reader1.reopen();
|
||||
modifier = IndexReader.open(dir1, false);
|
||||
Similarity sim = new DefaultSimilarity();
|
||||
DefaultSimilarity sim = new DefaultSimilarity();
|
||||
modifier.setNorm(1, "field1", sim.encodeNormValue(50f));
|
||||
modifier.setNorm(1, "field2", sim.encodeNormValue(50f));
|
||||
modifier.close();
|
||||
|
@ -702,7 +702,7 @@ public class TestIndexReaderReopen extends LuceneTestCase {
|
|||
protected void modifyIndex(int i) throws IOException {
|
||||
if (i % 3 == 0) {
|
||||
IndexReader modifier = IndexReader.open(dir, false);
|
||||
Similarity sim = new DefaultSimilarity();
|
||||
DefaultSimilarity sim = new DefaultSimilarity();
|
||||
modifier.setNorm(i, "field1", sim.encodeNormValue(50f));
|
||||
modifier.close();
|
||||
} else if (i % 3 == 1) {
|
||||
|
@ -983,7 +983,7 @@ public class TestIndexReaderReopen extends LuceneTestCase {
|
|||
}
|
||||
case 1: {
|
||||
IndexReader reader = IndexReader.open(dir, false);
|
||||
Similarity sim = new DefaultSimilarity();
|
||||
DefaultSimilarity sim = new DefaultSimilarity();
|
||||
reader.setNorm(4, "field1", sim.encodeNormValue(123f));
|
||||
reader.setNorm(44, "field2", sim.encodeNormValue(222f));
|
||||
reader.setNorm(44, "field4", sim.encodeNormValue(22f));
|
||||
|
@ -1007,7 +1007,7 @@ public class TestIndexReaderReopen extends LuceneTestCase {
|
|||
}
|
||||
case 4: {
|
||||
IndexReader reader = IndexReader.open(dir, false);
|
||||
Similarity sim = new DefaultSimilarity();
|
||||
DefaultSimilarity sim = new DefaultSimilarity();
|
||||
reader.setNorm(5, "field1", sim.encodeNormValue(123f));
|
||||
reader.setNorm(55, "field2", sim.encodeNormValue(222f));
|
||||
reader.close();
|
||||
|
|
|
@ -116,8 +116,8 @@ public class TestMaxTermFrequency extends LuceneTestCase {
|
|||
}
|
||||
|
||||
@Override
|
||||
public float computeNorm(FieldInvertState state) {
|
||||
return (float) state.getMaxTermFrequency();
|
||||
public byte computeNorm(FieldInvertState state) {
|
||||
return encodeNormValue((float) state.getMaxTermFrequency());
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
|
@ -46,9 +46,9 @@ public class TestNorms extends LuceneTestCase {
|
|||
public Similarity get(String field) {
|
||||
return new DefaultSimilarity() {
|
||||
@Override
|
||||
public float computeNorm(FieldInvertState state) {
|
||||
public byte computeNorm(FieldInvertState state) {
|
||||
// diable length norm
|
||||
return state.getBoost();
|
||||
return encodeNormValue(state.getBoost());
|
||||
}
|
||||
};
|
||||
}
|
||||
|
@ -177,7 +177,7 @@ public class TestNorms extends LuceneTestCase {
|
|||
//System.out.println(" and: for "+k+" from "+newNorm+" to "+origNorm);
|
||||
modifiedNorms.set(i, Float.valueOf(newNorm));
|
||||
modifiedNorms.set(k, Float.valueOf(origNorm));
|
||||
Similarity sim = new DefaultSimilarity();
|
||||
DefaultSimilarity sim = new DefaultSimilarity();
|
||||
ir.setNorm(i, "f"+1, sim.encodeNormValue(newNorm));
|
||||
ir.setNorm(k, "f"+1, sim.encodeNormValue(origNorm));
|
||||
}
|
||||
|
@ -192,8 +192,9 @@ public class TestNorms extends LuceneTestCase {
|
|||
byte b[] = MultiNorms.norms(ir, field);
|
||||
assertEquals("number of norms mismatches",numDocNorms,b.length);
|
||||
ArrayList<Float> storedNorms = (i==1 ? modifiedNorms : norms);
|
||||
DefaultSimilarity sim = (DefaultSimilarity) similarityProviderOne.get(field);
|
||||
for (int j = 0; j < b.length; j++) {
|
||||
float norm = similarityProviderOne.get(field).decodeNormValue(b[j]);
|
||||
float norm = sim.decodeNormValue(b[j]);
|
||||
float norm1 = storedNorms.get(j).floatValue();
|
||||
assertEquals("stored norm value of "+field+" for doc "+j+" is "+norm+" - a mismatch!", norm, norm1, 0.000001);
|
||||
}
|
||||
|
@ -229,7 +230,7 @@ public class TestNorms extends LuceneTestCase {
|
|||
// return unique norm values that are unchanged by encoding/decoding
|
||||
private float nextNorm(String fname) {
|
||||
float norm = lastNorm + normDelta;
|
||||
Similarity similarity = similarityProviderOne.get(fname);
|
||||
DefaultSimilarity similarity = (DefaultSimilarity) similarityProviderOne.get(fname);
|
||||
do {
|
||||
float norm1 = similarity.decodeNormValue(similarity.encodeNormValue(norm));
|
||||
if (norm1 > lastNorm) {
|
||||
|
@ -259,8 +260,8 @@ public class TestNorms extends LuceneTestCase {
|
|||
}
|
||||
|
||||
@Override
|
||||
public float computeNorm(FieldInvertState state) {
|
||||
return (float) state.getLength();
|
||||
public byte computeNorm(FieldInvertState state) {
|
||||
return encodeNormValue((float) state.getLength());
|
||||
}
|
||||
}
|
||||
|
||||
|
|
|
@ -18,9 +18,9 @@ package org.apache.lucene.index;
|
|||
*/
|
||||
|
||||
import java.io.IOException;
|
||||
import java.util.Collection;
|
||||
|
||||
import org.apache.lucene.util.LuceneTestCase;
|
||||
import org.apache.lucene.util.TermContext;
|
||||
import org.apache.lucene.util._TestUtil;
|
||||
import org.apache.lucene.analysis.Analyzer;
|
||||
import org.apache.lucene.analysis.MockAnalyzer;
|
||||
|
@ -30,7 +30,6 @@ import org.apache.lucene.index.IndexReader.AtomicReaderContext;
|
|||
import org.apache.lucene.search.*;
|
||||
import org.apache.lucene.search.BooleanClause.Occur;
|
||||
import org.apache.lucene.store.Directory;
|
||||
import org.apache.lucene.search.Explanation.IDFExplanation;
|
||||
|
||||
|
||||
public class TestOmitTf extends LuceneTestCase {
|
||||
|
@ -39,23 +38,14 @@ public class TestOmitTf extends LuceneTestCase {
|
|||
public float queryNorm(float sumOfSquaredWeights) { return 1.0f; }
|
||||
public float coord(int overlap, int maxOverlap) { return 1.0f; }
|
||||
public Similarity get(String field) {
|
||||
return new Similarity() {
|
||||
return new TFIDFSimilarity() {
|
||||
|
||||
@Override public float computeNorm(FieldInvertState state) { return state.getBoost(); }
|
||||
@Override public byte computeNorm(FieldInvertState state) { return encodeNormValue(state.getBoost()); }
|
||||
@Override public float tf(float freq) { return freq; }
|
||||
@Override public float sloppyFreq(int distance) { return 2.0f; }
|
||||
@Override public float idf(int docFreq, int numDocs) { return 1.0f; }
|
||||
@Override public IDFExplanation idfExplain(Collection<Term> terms, IndexSearcher searcher) throws IOException {
|
||||
return new IDFExplanation() {
|
||||
@Override
|
||||
public float getIdf() {
|
||||
return 1.0f;
|
||||
}
|
||||
@Override
|
||||
public String explain() {
|
||||
return "Inexplicable";
|
||||
}
|
||||
};
|
||||
@Override public Explanation idfExplain(TermContext[] terms, IndexSearcher searcher) throws IOException {
|
||||
return new Explanation(1.0f, "Inexplicable");
|
||||
}
|
||||
};
|
||||
}
|
||||
|
|
|
@ -149,7 +149,7 @@ public class TestParallelReader extends LuceneTestCase {
|
|||
|
||||
assertTrue(pr.isCurrent());
|
||||
IndexReader modifier = IndexReader.open(dir1, false);
|
||||
Similarity sim = new DefaultSimilarity();
|
||||
DefaultSimilarity sim = new DefaultSimilarity();
|
||||
modifier.setNorm(0, "f1", sim.encodeNormValue(100f));
|
||||
modifier.close();
|
||||
|
||||
|
|
|
@ -279,7 +279,7 @@ public class TestPerFieldCodecSupport extends LuceneTestCase {
|
|||
CodecProvider provider = new CodecProvider();
|
||||
Codec[] codecs = new Codec[] { new StandardCodec(),
|
||||
new SimpleTextCodec(), new MockSepCodec(),
|
||||
new PulsingCodec(1 + random.nextInt(10)),
|
||||
new PulsingCodec(1 + random.nextInt(20)),
|
||||
new MockVariableIntBlockCodec(1 + random.nextInt(10)),
|
||||
new MockFixedIntBlockCodec(1 + random.nextInt(10)) };
|
||||
for (Codec codec : codecs) {
|
||||
|
|
|
@ -81,7 +81,7 @@ public class TestDocValues extends LuceneTestCase {
|
|||
w.finish(maxDoc);
|
||||
assertEquals(0, trackBytes.get());
|
||||
|
||||
IndexDocValues r = Bytes.getValues(dir, "test", mode, fixedSize, maxDoc, newIOContext(random));
|
||||
IndexDocValues r = Bytes.getValues(dir, "test", mode, fixedSize, maxDoc, comp, newIOContext(random));
|
||||
for (int iter = 0; iter < 2; iter++) {
|
||||
ValuesEnum bytesEnum = getEnum(r);
|
||||
assertNotNull("enum is null", bytesEnum);
|
||||
|
@ -105,7 +105,8 @@ public class TestDocValues extends LuceneTestCase {
|
|||
Source s;
|
||||
IndexDocValues.SortedSource ss;
|
||||
if (mode == Bytes.Mode.SORTED) {
|
||||
s = ss = getSortedSource(r, comp);
|
||||
// default is unicode so we can simply pass null here
|
||||
s = ss = getSortedSource(r, random.nextBoolean() ? comp : null);
|
||||
} else {
|
||||
s = getSource(r);
|
||||
ss = null;
|
||||
|
|
|
@ -20,7 +20,11 @@ package org.apache.lucene.search;
|
|||
import java.io.IOException;
|
||||
|
||||
import org.apache.lucene.index.IndexReader.AtomicReaderContext;
|
||||
import org.apache.lucene.search.Similarity.ExactDocScorer;
|
||||
import org.apache.lucene.search.Similarity.SloppyDocScorer;
|
||||
import org.apache.lucene.search.Similarity.Stats;
|
||||
import org.apache.lucene.util.BytesRef;
|
||||
import org.apache.lucene.util.TermContext;
|
||||
import org.apache.lucene.index.FieldInvertState;
|
||||
import org.apache.lucene.util.PriorityQueue;
|
||||
|
||||
|
@ -187,8 +191,8 @@ final class JustCompileSearch {
|
|||
static final class JustCompilePhraseScorer extends PhraseScorer {
|
||||
|
||||
JustCompilePhraseScorer(Weight weight, PhraseQuery.PostingsAndFreq[] postings,
|
||||
Similarity similarity, byte[] norms) {
|
||||
super(weight, postings, similarity, norms);
|
||||
Similarity.SloppyDocScorer docScorer) throws IOException {
|
||||
super(weight, postings, docScorer);
|
||||
}
|
||||
|
||||
@Override
|
||||
|
@ -243,12 +247,22 @@ final class JustCompileSearch {
|
|||
static final class JustCompileSimilarity extends Similarity {
|
||||
|
||||
@Override
|
||||
public float idf(int docFreq, int numDocs) {
|
||||
public Stats computeStats(IndexSearcher searcher, String fieldName, float queryBoost, TermContext... termContexts) throws IOException {
|
||||
throw new UnsupportedOperationException(UNSUPPORTED_MSG);
|
||||
}
|
||||
|
||||
@Override
|
||||
public float computeNorm(FieldInvertState state) {
|
||||
public ExactDocScorer exactDocScorer(Stats stats, String fieldName, AtomicReaderContext context) throws IOException {
|
||||
throw new UnsupportedOperationException(UNSUPPORTED_MSG);
|
||||
}
|
||||
|
||||
@Override
|
||||
public SloppyDocScorer sloppyDocScorer(Stats stats, String fieldName, AtomicReaderContext context) throws IOException {
|
||||
throw new UnsupportedOperationException(UNSUPPORTED_MSG);
|
||||
}
|
||||
|
||||
@Override
|
||||
public byte computeNorm(FieldInvertState state) {
|
||||
throw new UnsupportedOperationException(UNSUPPORTED_MSG);
|
||||
}
|
||||
|
||||
|
@ -256,11 +270,6 @@ final class JustCompileSearch {
|
|||
public float sloppyFreq(int distance) {
|
||||
throw new UnsupportedOperationException(UNSUPPORTED_MSG);
|
||||
}
|
||||
|
||||
@Override
|
||||
public float tf(float freq) {
|
||||
throw new UnsupportedOperationException(UNSUPPORTED_MSG);
|
||||
}
|
||||
}
|
||||
|
||||
static final class JustCompileSimilarityProvider implements SimilarityProvider {
|
||||
|
@ -348,17 +357,12 @@ final class JustCompileSearch {
|
|||
}
|
||||
|
||||
@Override
|
||||
public float getValue() {
|
||||
public void normalize(float norm, float topLevelBoost) {
|
||||
throw new UnsupportedOperationException(UNSUPPORTED_MSG);
|
||||
}
|
||||
|
||||
@Override
|
||||
public void normalize(float norm) {
|
||||
throw new UnsupportedOperationException(UNSUPPORTED_MSG);
|
||||
}
|
||||
|
||||
@Override
|
||||
public float sumOfSquaredWeights() throws IOException {
|
||||
public float getValueForNormalization() throws IOException {
|
||||
throw new UnsupportedOperationException(UNSUPPORTED_MSG);
|
||||
}
|
||||
|
||||
|
|
|
@ -62,9 +62,9 @@ public class TestDisjunctionMaxQuery extends LuceneTestCase {
|
|||
}
|
||||
|
||||
@Override
|
||||
public float computeNorm(FieldInvertState state) {
|
||||
public byte computeNorm(FieldInvertState state) {
|
||||
// Disable length norm
|
||||
return state.getBoost();
|
||||
return encodeNormValue(state.getBoost());
|
||||
}
|
||||
|
||||
@Override
|
||||
|
|
|
@ -0,0 +1,203 @@
|
|||
package org.apache.lucene.search;
|
||||
|
||||
/**
|
||||
* Licensed to the Apache Software Foundation (ASF) under one or more
|
||||
* contributor license agreements. See the NOTICE file distributed with
|
||||
* this work for additional information regarding copyright ownership.
|
||||
* The ASF licenses this file to You under the Apache License, Version 2.0
|
||||
* (the "License"); you may not use this file except in compliance with
|
||||
* the License. You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
|
||||
import java.io.IOException;
|
||||
|
||||
import org.apache.lucene.document.Document;
|
||||
import org.apache.lucene.document.Field;
|
||||
import org.apache.lucene.document.IndexDocValuesField;
|
||||
import org.apache.lucene.index.FieldInvertState;
|
||||
import org.apache.lucene.index.IndexReader;
|
||||
import org.apache.lucene.index.RandomIndexWriter;
|
||||
import org.apache.lucene.index.Term;
|
||||
import org.apache.lucene.index.IndexReader.AtomicReaderContext;
|
||||
import org.apache.lucene.index.codecs.CodecProvider;
|
||||
import org.apache.lucene.index.values.IndexDocValues.Source;
|
||||
import org.apache.lucene.store.Directory;
|
||||
import org.apache.lucene.util.LuceneTestCase;
|
||||
import org.apache.lucene.util.TermContext;
|
||||
|
||||
/**
|
||||
* Tests the use of indexdocvalues in scoring.
|
||||
*
|
||||
* In the example, a docvalues field is used as a per-document boost (separate from the norm)
|
||||
* @lucene.experimental
|
||||
*/
|
||||
public class TestDocValuesScoring extends LuceneTestCase {
|
||||
private static final float SCORE_EPSILON = 0.001f; /* for comparing floats */
|
||||
|
||||
public void testSimple() throws Exception {
|
||||
assumeFalse("PreFlex codec cannot work with IndexDocValues!",
|
||||
"PreFlex".equals(CodecProvider.getDefault().getDefaultFieldCodec()));
|
||||
|
||||
Directory dir = newDirectory();
|
||||
RandomIndexWriter iw = new RandomIndexWriter(random, dir);
|
||||
Document doc = new Document();
|
||||
Field field = newField("foo", "", Field.Store.NO, Field.Index.ANALYZED);
|
||||
doc.add(field);
|
||||
IndexDocValuesField dvField = new IndexDocValuesField("foo_boost");
|
||||
doc.add(dvField);
|
||||
Field field2 = newField("bar", "", Field.Store.NO, Field.Index.ANALYZED);
|
||||
doc.add(field2);
|
||||
|
||||
field.setValue("quick brown fox");
|
||||
field2.setValue("quick brown fox");
|
||||
dvField.setFloat(2f); // boost x2
|
||||
iw.addDocument(doc);
|
||||
field.setValue("jumps over lazy brown dog");
|
||||
field2.setValue("jumps over lazy brown dog");
|
||||
dvField.setFloat(4f); // boost x4
|
||||
iw.addDocument(doc);
|
||||
IndexReader ir = iw.getReader();
|
||||
iw.close();
|
||||
|
||||
// no boosting
|
||||
IndexSearcher searcher1 = newSearcher(ir);
|
||||
// boosting
|
||||
IndexSearcher searcher2 = newSearcher(ir);
|
||||
searcher2.setSimilarityProvider(new DefaultSimilarityProvider() {
|
||||
final Similarity fooSim = new BoostingSimilarity(super.get("foo"), "foo_boost");
|
||||
|
||||
public Similarity get(String field) {
|
||||
return "foo".equals(field) ? fooSim : super.get(field);
|
||||
}
|
||||
});
|
||||
|
||||
// in this case, we searched on field "foo". first document should have 2x the score.
|
||||
TermQuery tq = new TermQuery(new Term("foo", "quick"));
|
||||
QueryUtils.check(random, tq, searcher1);
|
||||
QueryUtils.check(random, tq, searcher2);
|
||||
|
||||
TopDocs noboost = searcher1.search(tq, 10);
|
||||
TopDocs boost = searcher2.search(tq, 10);
|
||||
assertEquals(1, noboost.totalHits);
|
||||
assertEquals(1, boost.totalHits);
|
||||
|
||||
//System.out.println(searcher2.explain(tq, boost.scoreDocs[0].doc));
|
||||
assertEquals(boost.scoreDocs[0].score, noboost.scoreDocs[0].score*2f, SCORE_EPSILON);
|
||||
|
||||
// this query matches only the second document, which should have 4x the score.
|
||||
tq = new TermQuery(new Term("foo", "jumps"));
|
||||
QueryUtils.check(random, tq, searcher1);
|
||||
QueryUtils.check(random, tq, searcher2);
|
||||
|
||||
noboost = searcher1.search(tq, 10);
|
||||
boost = searcher2.search(tq, 10);
|
||||
assertEquals(1, noboost.totalHits);
|
||||
assertEquals(1, boost.totalHits);
|
||||
|
||||
assertEquals(boost.scoreDocs[0].score, noboost.scoreDocs[0].score*4f, SCORE_EPSILON);
|
||||
|
||||
// search on on field bar just for kicks, nothing should happen, since we setup
|
||||
// our sim provider to only use foo_boost for field foo.
|
||||
tq = new TermQuery(new Term("bar", "quick"));
|
||||
QueryUtils.check(random, tq, searcher1);
|
||||
QueryUtils.check(random, tq, searcher2);
|
||||
|
||||
noboost = searcher1.search(tq, 10);
|
||||
boost = searcher2.search(tq, 10);
|
||||
assertEquals(1, noboost.totalHits);
|
||||
assertEquals(1, boost.totalHits);
|
||||
|
||||
assertEquals(boost.scoreDocs[0].score, noboost.scoreDocs[0].score, SCORE_EPSILON);
|
||||
|
||||
|
||||
searcher1.close();
|
||||
searcher2.close();
|
||||
ir.close();
|
||||
dir.close();
|
||||
}
|
||||
|
||||
/**
|
||||
* Similarity that wraps another similarity and boosts the final score
|
||||
* according to whats in a docvalues field.
|
||||
*
|
||||
* @lucene.experimental
|
||||
*/
|
||||
static class BoostingSimilarity extends Similarity {
|
||||
private final Similarity sim;
|
||||
private final String boostField;
|
||||
|
||||
public BoostingSimilarity(Similarity sim, String boostField) {
|
||||
this.sim = sim;
|
||||
this.boostField = boostField;
|
||||
}
|
||||
|
||||
@Override
|
||||
public byte computeNorm(FieldInvertState state) {
|
||||
return sim.computeNorm(state);
|
||||
}
|
||||
|
||||
@Override
|
||||
public float sloppyFreq(int distance) {
|
||||
return sim.sloppyFreq(distance);
|
||||
}
|
||||
|
||||
@Override
|
||||
public Stats computeStats(IndexSearcher searcher, String fieldName, float queryBoost, TermContext... termContexts) throws IOException {
|
||||
return sim.computeStats(searcher, fieldName, queryBoost, termContexts);
|
||||
}
|
||||
|
||||
@Override
|
||||
public ExactDocScorer exactDocScorer(Stats stats, String fieldName, AtomicReaderContext context) throws IOException {
|
||||
final ExactDocScorer sub = sim.exactDocScorer(stats, fieldName, context);
|
||||
final Source values = context.reader.docValues(boostField).getSource();
|
||||
|
||||
return new ExactDocScorer() {
|
||||
@Override
|
||||
public float score(int doc, int freq) {
|
||||
return (float) values.getFloat(doc) * sub.score(doc, freq);
|
||||
}
|
||||
|
||||
@Override
|
||||
public Explanation explain(int doc, Explanation freq) {
|
||||
Explanation boostExplanation = new Explanation((float) values.getFloat(doc), "indexDocValue(" + boostField + ")");
|
||||
Explanation simExplanation = sub.explain(doc, freq);
|
||||
Explanation expl = new Explanation(boostExplanation.getValue() * simExplanation.getValue(), "product of:");
|
||||
expl.addDetail(boostExplanation);
|
||||
expl.addDetail(simExplanation);
|
||||
return expl;
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
@Override
|
||||
public SloppyDocScorer sloppyDocScorer(Stats stats, String fieldName, AtomicReaderContext context) throws IOException {
|
||||
final SloppyDocScorer sub = sim.sloppyDocScorer(stats, fieldName, context);
|
||||
final Source values = context.reader.docValues(boostField).getSource();
|
||||
|
||||
return new SloppyDocScorer() {
|
||||
@Override
|
||||
public float score(int doc, float freq) {
|
||||
return (float) values.getFloat(doc) * sub.score(doc, freq);
|
||||
}
|
||||
|
||||
@Override
|
||||
public Explanation explain(int doc, Explanation freq) {
|
||||
Explanation boostExplanation = new Explanation((float) values.getFloat(doc), "indexDocValue(" + boostField + ")");
|
||||
Explanation simExplanation = sub.explain(doc, freq);
|
||||
Explanation expl = new Explanation(boostExplanation.getValue() * simExplanation.getValue(), "product of:");
|
||||
expl.addDetail(boostExplanation);
|
||||
expl.addDetail(simExplanation);
|
||||
return expl;
|
||||
}
|
||||
};
|
||||
}
|
||||
}
|
||||
}
|
Some files were not shown because too many files have changed in this diff Show More
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Reference in New Issue