Class PerFieldSimilarityWrapper

java.lang.Object
org.apache.lucene.search.similarities.Similarity
org.apache.lucene.search.similarities.PerFieldSimilarityWrapper

public abstract class PerFieldSimilarityWrapper extends Similarity
Provides the ability to use a different Similarity for different fields.

Subclasses should implement get(String) to return an appropriate Similarity (for example, using field-specific parameter values) for the field.

  • Constructor Details

    • PerFieldSimilarityWrapper

      public PerFieldSimilarityWrapper()
      Sole constructor. (For invocation by subclass constructors, typically implicit.)
  • Method Details

    • computeNorm

      public final long computeNorm(FieldInvertState state)
      Description copied from class: Similarity
      Computes the normalization value for a field at index-time.

      The default implementation uses SmallFloat.intToByte4(int) to encode the number of terms as a single byte.

      WARNING: The default implementation is used by Lucene's supplied Similarity classes, which means you can change the Similarity at runtime without reindexing. If you override this method, you'll need to re-index documents for it to take effect.

      Matches in longer fields are less precise, so implementations of this method usually set smaller values when state.getLength() is large, and larger values when state.getLength() is small.

      Note that for a given term-document frequency, greater unsigned norms must produce scores that are lower or equal, ie. for two encoded norms n1 and n2 so that Long.compareUnsigned(n1, n2) > 0 then SimScorer.score(freq, n1) <= SimScorer.score(freq, n2) for any legal freq.

      0 is not a legal norm, so 1 is the norm that produces the highest scores.

      Overrides:
      computeNorm in class Similarity
      Parameters:
      state - accumulated state of term processing for this field
      Returns:
      computed norm value
    • scorer

      public final Similarity.SimScorer scorer(float boost, CollectionStatistics collectionStats, TermStatistics... termStats)
      Description copied from class: Similarity
      Compute any collection-level weight (e.g. IDF, average document length, etc) needed for scoring a query.
      Specified by:
      scorer in class Similarity
      Parameters:
      boost - a multiplicative factor to apply to the produces scores
      collectionStats - collection-level statistics, such as the number of tokens in the collection.
      termStats - term-level statistics, such as the document frequency of a term across the collection.
      Returns:
      SimWeight object with the information this Similarity needs to score a query.
    • get

      public abstract Similarity get(String name)
      Returns a Similarity for scoring a field.