Examples of org.apache.lucene.document.NumericField

org.apache.lucene.document.NumericField
This class provides a {@link Field} that enables indexingof numeric values for efficient range filtering and sorting. Here's an example usage, adding an int value:
```
 document.add(new NumericField(name).setIntValue(value)); 
```
For optimal performance, re-use the NumericField and {@link Document} instance for more thanone document:
```
 NumericField field = new NumericField(name); Document document = new Document(); document.add(field); for(all documents) { ... field.setIntValue(value) writer.addDocument(document); ... } 
```
The java native types int, long, float and double are directly supported. However, any value that can be converted into these native types can also be indexed. For example, date/time values represented by a {@link java.util.Date} can be translated into a longvalue using the {@link java.util.Date#getTime} method. If youdon't need millisecond precision, you can quantize the value, either by dividing the result of {@link java.util.Date#getTime} or using the separate getters(for year, month, etc.) to construct an int or long value.

To perform range querying or filtering against a NumericField, use {@link NumericRangeQuery} or {@link NumericRangeFilter}. To sort according to a NumericField, use the normal numeric sort types, eg {@link SortField#INT}. NumericField values can also be loaded directly from {@link FieldCache}.

By default, a NumericField's value is not stored but is indexed for range filtering and sorting. You can use the {@link #NumericField(String,Field.Store,boolean)}constructor if you need to change these defaults.

You may add the same field name as a NumericField to the same document more than once. Range querying and filtering will be the logical OR of all values; so a range query will hit all documents that have at least one value in the range. However sort behavior is not defined. If you need to sort, you should separately index a single-valued NumericField.

A NumericField will consume somewhat more disk space in the index than an ordinary single-valued field. However, for a typical index that includes substantial textual content per document, this increase will likely be in the noise.

Within Lucene, each numeric value is indexed as a trie structure, where each term is logically assigned to larger and larger pre-defined brackets (which are simply lower-precision representations of the value). The step size between each successive bracket is called the precisionStep, measured in bits. Smaller precisionStep values result in larger number of brackets, which consumes more disk space in the index but may result in faster range search performance. The default value, 4, was selected for a reasonable tradeoff of disk space consumption versus performance. You can use the expert constructor {@link #NumericField(String,int,Field.Store,boolean)} if you'dlike to change the value. Note that you must also specify a congruent value when creating {@link NumericRangeQuery} or {@link NumericRangeFilter}. For low cardinality fields larger precision steps are good. If the cardinality is < 100, it is fair to use {@link Integer#MAX_VALUE}, which produces one term per value.
For more information on the internals of numeric trie indexing, including the precisionStep configuration, see {@link NumericRangeQuery}. The format of indexed values is described in {@link NumericUtils}.
If you only need to sort by numeric value, and never run range querying/filtering, you can index using a precisionStep of {@link Integer#MAX_VALUE}. This will minimize disk space consumed.

More advanced users can instead use {@link NumericTokenStream} directly, when indexing numbers. Thisclass is a wrapper around this token stream type for easier, more intuitive usage.

NOTE: This class is only used during indexing. When retrieving the stored field value from a {@link Document} instance after search, you will get aconventional {@link Fieldable} instance where the numericvalues are returned as {@link String}s (according to toString(value) of the used data type).
NOTE: This API is experimental and might change in incompatible ways in the next release. @since 2.9

    for (int l=0; l<5000; l++) {
      Document doc = new Document();
      for (int m=0, c=rnd.nextInt(10); m<=c; m++) {
        int value = rnd.nextInt(Integer.MAX_VALUE);
        doc.add(new Field("asc", format.format(value), Field.Store.NO, Field.Index.NOT_ANALYZED));
        doc.add(new NumericField("trie", Field.Store.NO, true).setIntValue(value));
      }
      writer.addDocument(doc);
    }  
    writer.close();

View Full Code Here

  private void buildDocument(Document document, Serializer serializer) {
    List<Fieldable> docFields = document.getFields();
    serializer.fields( docFields );
    for(Fieldable fieldable : docFields) {
      if (fieldable instanceof NumericField) {
        NumericField safeField = (NumericField) fieldable;
        LuceneNumericFieldContext context = new LuceneNumericFieldContext( (NumericField) fieldable );
        switch ( safeField.getDataType() ) {
          case INT:
            serializer.addIntNumericField(
                safeField.getNumericValue().intValue(),
                context
            );
            break;
          case LONG:
            serializer.addLongNumericField(
                safeField.getNumericValue().longValue(),
                context
            );
            break;
          case FLOAT:
            serializer.addFloatNumericField(
                safeField.getNumericValue().floatValue(),
                context
            );
            break;
          case DOUBLE:
            serializer.addDoubleNumericField(
                safeField.getNumericValue().doubleValue(),
                context
            );
            break;
          default:
            String dataType = safeField.getDataType() == null ? "null" : safeField.getDataType().toString();
            throw log.unknownNumericFieldType( dataType );
        }
      }
      else if (fieldable instanceof Field) {
        Field safeField = (Field) fieldable;
        if ( safeField.isBinary() ) {
          serializer.addFieldWithBinaryData( new LuceneFieldContext( safeField ) );
        }
        else if ( safeField.stringValue() != null )  {
          serializer.addFieldWithStringData( new LuceneFieldContext( safeField ) );
        }
        else if ( safeField.readerValue() != null && safeField.readerValue() instanceof Serializable )  {
          serializer.addFieldWithSerializableReaderData( new LuceneFieldContext( safeField ) );
        }
        else if ( safeField.readerValue() != null )  {
          throw log.conversionFromReaderToStringNotYetImplemented();
        }
        else if ( safeField.tokenStreamValue() != null )  {
          serializer.addFieldWithTokenStreamData( new LuceneFieldContext( safeField ) );
        }
        else {
          throw log.unknownFieldType( safeField.getClass() );
        }
      }
      else if (fieldable instanceof Serializable) { //Today Fieldable is Serializable but for how long?
        serializer.addFieldWithSerializableFieldable( toByteArray( fieldable ) );
      }

View Full Code Here

  public void addNumericFieldToDocument(String fieldName, Object value, Document document) {
    if ( storeType == Store.COMPRESS ) {
      throw new SearchException( "Error indexing field " + fieldName + ", @NumericField cannot be compressed" );
    }
    if ( value != null ) {
      NumericField numericField = new NumericField(
          fieldName, precisionStep, storeType != Store.NO ? Field.Store.YES : Field.Store.NO, true
      );
      NumericFieldUtils.setNumericValue( value, numericField );
      numericField.setBoost( boost );


      if ( numericField.getNumericValue() != null ) {
        document.add( numericField );
      }
    }
  }

View Full Code Here

  private void buildDocument(Document document, Serializer serializer) {
    List<Fieldable> docFields = document.getFields();
    serializer.fields( docFields );
    for ( Fieldable fieldable : docFields ) {
      if ( fieldable instanceof NumericField ) {
        NumericField safeField = (NumericField) fieldable;
        LuceneNumericFieldContext context = new LuceneNumericFieldContext( (NumericField) fieldable );
        switch ( safeField.getDataType() ) {
          case INT:
            serializer.addIntNumericField(
                safeField.getNumericValue().intValue(),
                context
            );
            break;
          case LONG:
            serializer.addLongNumericField(
                safeField.getNumericValue().longValue(),
                context
            );
            break;
          case FLOAT:
            serializer.addFloatNumericField(
                safeField.getNumericValue().floatValue(),
                context
            );
            break;
          case DOUBLE:
            serializer.addDoubleNumericField(
                safeField.getNumericValue().doubleValue(),
                context
            );
            break;
          default:
            String dataType = safeField.getDataType() == null ? "null" : safeField.getDataType().toString();
            throw log.unknownNumericFieldType( dataType );
        }
      }
      else if (fieldable instanceof Field) {
        Field safeField = (Field) fieldable;
        if ( safeField.isBinary() ) {
          serializer.addFieldWithBinaryData( new LuceneFieldContext( safeField ) );
        }
        else if ( safeField.stringValue() != null ) {
          serializer.addFieldWithStringData( new LuceneFieldContext( safeField ) );
        }
        else if ( safeField.readerValue() != null && safeField.readerValue() instanceof Serializable ) {
          serializer.addFieldWithSerializableReaderData( new LuceneFieldContext( safeField ) );
        }
        else if ( safeField.readerValue() != null ) {
          throw log.conversionFromReaderToStringNotYetImplemented();
        }
        else if ( safeField.tokenStreamValue() != null ) {
          serializer.addFieldWithTokenStreamData( new LuceneFieldContext( safeField ) );
        }
        else {
          throw log.unknownFieldType( safeField.getClass() );
        }
      }
      else if ( fieldable != null ) { //Today Fieldable is Serializable but for how long?
        serializer.addFieldWithSerializableFieldable( toByteArray( fieldable ) );
      }

View Full Code Here

        final Document doc = new Document();


        doc.add(new Field("title", docTitle, Store.YES, Index.ANALYZED));
        doc.add(new Field("author", docAuthor, Store.YES, Index.ANALYZED));
        doc.add(new Field("text", docText, Store.YES, Index.ANALYZED));
        doc.add(new NumericField("year", Store.YES, true).setIntValue(docYear));
        doc.add(new NumericField("gross", Store.YES, true)
                .setDoubleValue(docGross));


        return doc;
    }

View Full Code Here

        doc.add(new Field("title", new StringReader("Jurassic Park")));
        doc.add(new Field("author", new StringReader("Michael Crichton")));
        doc.add(new Field("text", new StringReader("It's a UNIX system! I know this!")));
        doc.add(new Field("rating", new StringReader("Good")));
        doc.add(new Field("publisher", "", Store.YES, Index.ANALYZED));
        doc.add(new NumericField("year", Store.YES, true).setIntValue(1990));
        doc.add(new NumericField("gross", Store.YES, true).setDoubleValue(900.00));


        doc.add(new NumericField("longField", Store.YES, true).setLongValue(1));
        doc.add(new NumericField("shortField", Store.YES, true).setIntValue(1));
        doc.add(new NumericField("byteField", Store.YES, true).setIntValue(1));
        doc.add(new NumericField("floatField", Store.YES, true).setFloatValue(1));


        return doc;
    }

View Full Code Here

  private void buildDocument(Document document, Serializer serializer) {
    List<Fieldable> docFields = document.getFields();
    serializer.fields( docFields );
    for(Fieldable fieldable : docFields) {
      if (fieldable instanceof NumericField) {
        NumericField safeField = (NumericField) fieldable;
        LuceneNumericFieldContext context = new LuceneNumericFieldContext( (NumericField) fieldable );
        switch ( safeField.getDataType() ) {
          case INT:
            serializer.addIntNumericField(
                safeField.getNumericValue().intValue(),
                context
            );
            break;
          case LONG:
            serializer.addLongNumericField(
                safeField.getNumericValue().longValue(),
                context
            );
            break;
          case FLOAT:
            serializer.addFloatNumericField(
                safeField.getNumericValue().floatValue(),
                context
            );
            break;
          case DOUBLE:
            serializer.addDoubleNumericField(
                safeField.getNumericValue().doubleValue(),
                context
            );
            break;
          default:
            String dataType = safeField.getDataType() == null ? "null" : safeField.getDataType().toString();
            throw log.unknownNumericFieldType( dataType );
        }
      }
      else if (fieldable instanceof Field) {
        Field safeField = (Field) fieldable;
        if ( safeField.isBinary() ) {
          serializer.addFieldWithBinaryData( new LuceneFieldContext( safeField ) );
        }
        else if ( safeField.stringValue() != null )  {
          serializer.addFieldWithStringData( new LuceneFieldContext( safeField ) );
        }
        else if ( safeField.readerValue() != null && safeField.readerValue() instanceof Serializable )  {
          serializer.addFieldWithSerializableReaderData( new LuceneFieldContext( safeField ) );
        }
        else if ( safeField.readerValue() != null )  {
          throw log.conversionFromReaderToStringNotYetImplemented();
        }
        else if ( safeField.tokenStreamValue() != null )  {
          serializer.addFieldWithTokenStreamData( new LuceneFieldContext( safeField ) );
        }
        else {
          throw log.unknownFieldType( safeField.getClass() );
        }
      }
      else if (fieldable instanceof Serializable) { //Today Fieldable is Serializable but for how long?
        serializer.addFieldWithSerializableFieldable( toByteArray( ( Serializable ) fieldable ) );
      }

View Full Code Here

    IndexWriter writer = new IndexWriter(ramDir, new StandardAnalyzer(TEST_VERSION), true, IndexWriter.MaxFieldLength.UNLIMITED);
    for (int i = 0; i < texts.length; i++) {
      addDoc(writer, texts[i]);
    }
    Document doc = new Document();
    NumericField nfield = new NumericField(NUMERIC_FIELD_NAME, Store.YES, true);
    nfield.setIntValue(1);
    doc.add(nfield);
    writer.addDocument(doc, analyzer);
    nfield = new NumericField(NUMERIC_FIELD_NAME, Store.YES, true);
    nfield.setIntValue(3);
    doc = new Document();
    doc.add(nfield);
    writer.addDocument(doc, analyzer);
    nfield = new NumericField(NUMERIC_FIELD_NAME, Store.YES, true);
    nfield.setIntValue(5);
    doc = new Document();
    doc.add(nfield);
    writer.addDocument(doc, analyzer);
    nfield = new NumericField(NUMERIC_FIELD_NAME, Store.YES, true);
    nfield.setIntValue(7);
    doc = new Document();
    doc.add(nfield);
    writer.addDocument(doc, analyzer);
    writer.optimize();
    writer.close();

View Full Code Here


  // ... has multiple jobs
  private Document makeJob(String skill, int year) {
    Document job = new Document();
    job.add(newField("skill", skill, Field.Store.YES, Field.Index.NOT_ANALYZED));
    job.add(new NumericField("year").setIntValue(year));
    return job;
  }

View Full Code Here


  // ... has multiple qualifications
  private Document makeQualification(String qualification, int year) {
    Document job = new Document();
    job.add(newField("qualification", qualification, Field.Store.YES, Field.Index.NOT_ANALYZED));
    job.add(new NumericField("year").setIntValue(year));
    return job;
  }

View Full Code Here

0 1 2 3 4 5 6 7 8 9

TOP

Related Classes of org.apache.lucene.document.NumericField

com.browseengine.bobo.test.FacetNotValuesTest

com.esri.gpt.catalog.lucene.DoubleField

com.esri.gpt.catalog.lucene.GeometryProperty

com.esri.gpt.catalog.lucene.LongField

com.esri.gpt.catalog.lucene.TimeperiodProperty

com.esri.gpt.catalog.lucene.TimestampField

com.mysema.query.lucene.LuceneQueryTest

com.mysema.query.LuceneSerializerTest

com.netflix.exhibitor.core.index.IndexBuilder

com.netflix.exhibitor.core.index.LogSearch

All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.