Examples of org.apache.lucene.document.DoubleField

org.apache.lucene.document.DoubleField
Field that indexes double values for efficient range filtering and sorting. Here's an example usage:
```
 document.add(new DoubleField(name, 6.0, Field.Store.NO)); 
```
For optimal performance, re-use the DoubleField and {@link Document} instance for more than one document:
```
 DoubleField field = new DoubleField(name, 0.0, Field.Store.NO); Document document = new Document(); document.add(field); for(all documents) { ... field.setDoubleValue(value) writer.addDocument(document); ... } 
```
See also {@link IntField}, {@link LongField}, {@link FloatField}.
To perform range querying or filtering against a DoubleField, use {@link NumericRangeQuery} or {@link NumericRangeFilter}. To sort according to a DoubleField, use the normal numeric sort types, eg {@link org.apache.lucene.search.SortField.Type#DOUBLE}. DoubleField values can also be loaded directly from {@link FieldCache}.

You may add the same field name as an DoubleField 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 DoubleField.

A DoubleField 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 create a custom {@link FieldType} and invoke the {@link FieldType#setNumericPrecisionStep} method 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.
@since 2.9

    doc.add( field );
    field = new Field( "id", "1", Field.Store.YES, Field.Index.NOT_ANALYZED );
    doc.add( field );
    field = new Field( "logo", shirt.getLogo(), Field.Store.NO, Field.Index.ANALYZED );
    doc.add( field );
    DoubleField numField = new DoubleField( "length", shirt.getLength(), Field.Store.NO );
    doc.add( numField );
    LuceneWork luceneWork = new AddLuceneWork(
        shirt.getId(), String.valueOf( shirt.getId() ), shirt.getClass(), doc
    );
    List<LuceneWork> queue = new ArrayList<LuceneWork>();

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    getLuceneDocument().add( numField );
  }


  @Override
  public void addDoubleNumericField(double value, String name, int precisionStep, SerializableStore store, boolean indexed, float boost, boolean omitNorms, boolean omitTermFreqAndPositions) {
    final DoubleField numField = new DoubleField( name, value, getStore( store ) );
    numField.setBoost( boost );
    getLuceneDocument().add( numField );
  }

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            RemoteEntity.class
        )
    );


    Document doc = new Document();
    Field numField = new DoubleField( "double", 23d, Store.NO );
    //numField.setBoost( 3f );
    //numField.setOmitNorms( true );
    //numField.setOmitTermFreqAndPositions( true );
    doc.add( numField );
    numField = new IntField( "int", 23, Store.NO );

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            RemoteEntity.class
        )
    );


    Document doc = new Document();
    Field numField = new DoubleField( "double", 23d, Store.NO );
    doc.add( numField );
    numField = new IntField( "int", 23, Store.NO );
    doc.add( numField );
    numField = new FloatField( "float", 2.3f, Store.NO );
    doc.add( numField );

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    doc.add( field );
    field = new Field( "id", "1", Field.Store.YES, Field.Index.NOT_ANALYZED );
    doc.add( field );
    field = new Field( "logo", shirt.getLogo(), Field.Store.NO, Field.Index.ANALYZED );
    doc.add( field );
    DoubleField numField = new DoubleField( "length", shirt.getLength(), Field.Store.NO );
    doc.add( numField );
    LuceneWork luceneWork = new AddLuceneWork(
        shirt.getId(), String.valueOf( shirt.getId() ), shirt.getClass(), doc
    );
    List<LuceneWork> queue = new ArrayList<LuceneWork>();

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    for(int i=0;i<numDocs;i++) {
      Document doc = new Document();
      double v = random().nextDouble();
      values[i] = v;
      doc.add(new DoubleDocValuesField("field", v));
      doc.add(new DoubleField("field", v, Field.Store.NO));
      w.addDocument(doc);
      minValue = Math.min(minValue, v);
      maxValue = Math.max(maxValue, v);
    }
    IndexReader r = w.getReader();

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      fields.add(newStringField("short", "" + ((short) random().nextInt()), Field.Store.NO));
      fields.add(new IntField("int", random().nextInt(), Field.Store.NO));
      fields.add(new LongField("long", random().nextLong(), Field.Store.NO));


      fields.add(new FloatField("float", random().nextFloat(), Field.Store.NO));
      fields.add(new DoubleField("double", random().nextDouble(), Field.Store.NO));
      fields.add(newStringField("bytes", TestUtil.randomRealisticUnicodeString(random()), Field.Store.NO));
      fields.add(newStringField("bytesval", TestUtil.randomRealisticUnicodeString(random()), Field.Store.NO));
      fields.add(new DoubleField("double", random().nextDouble(), Field.Store.NO));


      if (supportsDocValues) {
        fields.add(new NumericDocValuesField("intdocvalues", random().nextInt()));
        fields.add(new FloatDocValuesField("floatdocvalues", random().nextFloat()));
        fields.add(new SortedDocValuesField("sortedbytesdocvalues", new BytesRef(TestUtil.randomRealisticUnicodeString(random()))));

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    // TODO: we could index in radians instead ... saves all the conversions in getBoundingBoxFilter


    // Add documents with latitude/longitude location:
    Document doc = new Document();
    doc.add(new DoubleField("latitude", 40.759011, Field.Store.NO));
    doc.add(new DoubleField("longitude", -73.9844722, Field.Store.NO));
    writer.addDocument(doc);
    
    doc = new Document();
    doc.add(new DoubleField("latitude", 40.718266, Field.Store.NO));
    doc.add(new DoubleField("longitude", -74.007819, Field.Store.NO));
    writer.addDocument(doc);
    
    doc = new Document();
    doc.add(new DoubleField("latitude", 40.7051157, Field.Store.NO));
    doc.add(new DoubleField("longitude", -74.0088305, Field.Store.NO));
    writer.addDocument(doc);


    // Open near-real-time searcher
    searcher = new IndexSearcher(DirectoryReader.open(writer, true));
    writer.close();

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  public void testInfiniteValues() throws Exception {
    Directory dir = newDirectory();
    RandomIndexWriter writer = new RandomIndexWriter(random(), dir,
      newIndexWriterConfig(TEST_VERSION_CURRENT, new MockAnalyzer(random())));
    Document doc = new Document();
    doc.add(new DoubleField("double", Double.NEGATIVE_INFINITY, Field.Store.NO));
    doc.add(new LongField("long", Long.MIN_VALUE, Field.Store.NO));
    writer.addDocument(doc);
    
    doc = new Document();
    doc.add(new DoubleField("double", Double.POSITIVE_INFINITY, Field.Store.NO));
    doc.add(new LongField("long", Long.MAX_VALUE, Field.Store.NO));
    writer.addDocument(doc);
    
    doc = new Document();
    doc.add(new DoubleField("double", 0.0, Field.Store.NO));
    doc.add(new LongField("long", 0L, Field.Store.NO));
    writer.addDocument(doc);
    
    for (double d : TestNumericUtils.DOUBLE_NANs) {
      doc = new Document();
      doc.add(new DoubleField("double", d, Field.Store.NO));
      writer.addDocument(doc);
    }
    
    writer.close();

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  /** @see #createIndexableFields(com.spatial4j.core.shape.Shape) */
  public Field[] createIndexableFields(Point point) {
    FieldType doubleFieldType = new FieldType(DoubleField.TYPE_NOT_STORED);
    doubleFieldType.setNumericPrecisionStep(precisionStep);
    Field[] f = new Field[2];
    f[0] = new DoubleField(fieldNameX, point.getX(), doubleFieldType);
    f[1] = new DoubleField(fieldNameY, point.getY(), doubleFieldType);
    return f;
  }

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