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In Lucid Imagination “ Erste Schritte mit Payloads habe ich die Grundlagen von Payloads vorgestellt, aber dieser Artikel ist jetzt etwas veraltet, wenn Sie Lucene 3.x verwenden, also dachte ich, ich würde ein Update geben. Die größte Änderung betrifft die Abfrageseite. Die BoostingTermQuery (BTQ) wurde zugunsten der PayloadTermQuery (veraltet und) entfernt (wir waren der Meinung, dass der Name besser wiedergibt, was sie tut). Wir haben auch die Similarity.scorePayload-Signatur leicht geändert, um mehr Informationen zu liefern.

Schließlich wird die BoostingTermQuery verwendet, um alle Payloads eines übereinstimmenden Dokuments zu summieren und dann den Durchschnitt zu bilden. Wir haben dies nun durch die Einführung des Begriffs PayloadFunction und verschiedener Implementierungen anpassbar gemacht: AveragePayloadFunction (was die BTQ früher tat), MinPayloadFunction, MaxPayloadFunction. Wenn Sie natürlich eine eigene Implementierung wünschen, erweitern Sie einfach die PayloadFunction und übergeben Sie sie.

Der neue Code sollte wie folgt aussehen:

package com.lucidimagination.noodles;

import junit.framework.TestCase;
import org.apache.lucene.analysis.Analyzer;
import org.apache.lucene.analysis.LowerCaseFilter;
import org.apache.lucene.analysis.TokenStream;
import org.apache.lucene.analysis.WhitespaceTokenizer;
import org.apache.lucene.analysis.payloads.DelimitedPayloadTokenFilter;
import org.apache.lucene.analysis.payloads.FloatEncoder;
import org.apache.lucene.analysis.payloads.PayloadEncoder;
import org.apache.lucene.analysis.payloads.PayloadHelper;
import org.apache.lucene.document.Document;
import org.apache.lucene.document.Field;
import org.apache.lucene.index.IndexWriter;
import org.apache.lucene.index.Term;
import org.apache.lucene.search.DefaultSimilarity;
import org.apache.lucene.search.IndexSearcher;
import org.apache.lucene.search.Query;
import org.apache.lucene.search.ScoreDoc;
import org.apache.lucene.search.TermQuery;
import org.apache.lucene.search.TopDocs;
import org.apache.lucene.search.payloads.AveragePayloadFunction;
import org.apache.lucene.search.payloads.PayloadTermQuery;
import org.apache.lucene.store.Directory;
import org.apache.lucene.store.RAMDirectory;

import java.io.IOException;
import java.io.Reader;

/**
 *
 *
 **/
public class PayloadTest extends TestCase {
  Directory dir;

  public static String[] DOCS = {
          "The quick|2.0 red|2.0 fox|10.0 jumped|5.0 over the lazy|2.0 brown|2.0 dogs|10.0",
          "The quick red fox jumped over the lazy brown dogs",//no boosts
          "The quick|2.0 red|2.0 fox|10.0 jumped|5.0 over the old|2.0 brown|2.0 box|10.0",
          "Mary|10.0 had a little|2.0 lamb|10.0 whose fleece|10.0 was|5.0 white|2.0 as snow|10.0",
          "Mary had a little lamb whose fleece was white as snow",
          "Mary|10.0 takes on Wolf|10.0 Restoration|10.0 project|10.0 despite ties|10.0 to sheep|10.0 farming|10.0",
          "Mary|10.0 who lives|5.0 on a farm|10.0 is|5.0 happy|2.0 that she|10.0 takes|5.0 a walk|10.0 every day|10.0",
          "Moby|10.0 Dick|10.0 is|5.0 a story|10.0 of a whale|10.0 and a man|10.0 obsessed|10.0",
          "The robber|10.0 wore|5.0 a black|2.0 fleece|10.0 jacket|10.0 and a baseball|10.0 cap|10.0",
          "The English|10.0 Springer|10.0 Spaniel|10.0 is|5.0 the best|2.0 of all dogs|10.0"
  };
  protected PayloadSimilarity payloadSimilarity;

  @Override
  protected void setUp() throws Exception {
    dir = new RAMDirectory();

    PayloadEncoder encoder = new FloatEncoder();
    IndexWriter writer = new IndexWriter(dir, new PayloadAnalyzer(encoder), true, IndexWriter.MaxFieldLength.UNLIMITED);
    payloadSimilarity = new PayloadSimilarity();
    writer.setSimilarity(payloadSimilarity);
    for (int i = 0; i < DOCS.length; i++) {
      Document doc = new Document();
      Field id = new Field("id", "doc_" + i, Field.Store.YES, Field.Index.NOT_ANALYZED_NO_NORMS);
      doc.add(id);
      //Store both position and offset information
      Field text = new Field("body", DOCS[i], Field.Store.NO, Field.Index.ANALYZED);
      doc.add(text);
      writer.addDocument(doc);
    }
    writer.close();
  }

  public void testPayloads() throws Exception {
    IndexSearcher searcher = new IndexSearcher(dir, true);
    searcher.setSimilarity(payloadSimilarity);//set the similarity.  Very important
    PayloadTermQuery btq = new PayloadTermQuery(new Term("body", "fox"), new AveragePayloadFunction());// was BoostingTermQuery(new Term("body", "fox"));
    TopDocs topDocs = searcher.search(btq, 10);
    printResults(searcher, btq, topDocs);

    TermQuery tq = new TermQuery(new Term("body", "fox"));
    topDocs = searcher.search(tq, 10);
    printResults(searcher, tq, topDocs);
  }

  private void printResults(IndexSearcher searcher, Query query, TopDocs topDocs) throws IOException {
    System.out.println("-----------");
    System.out.println("Results for " + query + " of type: " + query.getClass().getName());
    for (int i = 0; i < topDocs.scoreDocs.length; i++) {
      ScoreDoc doc = topDocs.scoreDocs[i];
      System.out.println("Doc: " + doc.toString());
      System.out.println("Explain: " + searcher.explain(query, doc.doc));
    }
  }

  class PayloadSimilarity extends DefaultSimilarity {
    //Note the new similarity signature, giving much more information about the field name, etc.
    @Override
    public float scorePayload(int docId, String fieldName, int start, int end, byte[] payload, int offset, int length) {
      return PayloadHelper.decodeFloat(payload, offset);//we can ignore length here, because we know it is encoded as 4 bytes
    }

  }

  class PayloadAnalyzer extends Analyzer {
    private PayloadEncoder encoder;

    PayloadAnalyzer(PayloadEncoder encoder) {
      this.encoder = encoder;
    }

    public TokenStream tokenStream(String fieldName, Reader reader) {
      TokenStream result = new WhitespaceTokenizer(reader);
      result = new LowerCaseFilter(result);
      result = new DelimitedPayloadTokenFilter(result, '|', encoder);
      return result;
    }
  }
}