create barcode image c# Applying individual analyzers in Java

Painting ECC200 in Java Applying individual analyzers

Listing 7.4
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Applying individual analyzers
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public class TestAnalyzerWrapper extends SearchTestCase { @Test public void testScopedAnalyzer() throws Exception { FullTextSession session = Search.getFullTextSession( openSession() ); Transaction tx = session.beginTransaction(); buildIndex(session, tx); try { SearchFactory searchFactory = session.getSearchFactory(); FullTextQuery hibQuery = buildQuery(searchFactory, "field2", session); List<ScopedEntity> results = hibQuery.list(); assert result.size() == 0: "incorrect result count";
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B Zero results after field2 search C First generated query string
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assert hibQuery.toString().equals( "FullTextQueryImpl(+field2:TEST)"): "incorrect query";
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hibQuery = buildQuery(searchFactory, "field1", session);
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Writing a Lucene query Two results after
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results = hibQuery.list(); assert result.size() == 0: "incorrect result count";
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D field1 search
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assert hibQuery.toString().equals( "FullTextQueryImpl(+field1:TEST)"): "incorrect query";
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generated E Secondstring query
for (Object element : session.createQuery("from " + ScopedEntity.class.getName()).list()) session.delete(element); tx.commit(); } finally { session.close(); } } private FullTextQuery buildQuery(SearchFactory factory, field, FullTextSession session) throws IOException { Reader reader = new StringReader( TEST ); TokenStream stream = factory.getAnalyzer( ScopedEntity.class ) .tokenStream( field, reader); BooleanQuery bq = new BooleanQuery(); Token token = new Token(); token = stream.next( token );
String
F TokenStream from ScopedAnalyzer
G Get the first token
while (token != null) { if ( token.termLength() != 0) { String term = new String( token.termBuffer(), 0, token.termLength() );
H Extract the term I Add the term to
the BooleanQuery
bq.add( new TermQuery( new Term(field, term)), BooleanClause.Occur.MUST ); } token = stream.next( token );
} next token return session.createFullTextQuery(bq, ScopedEntity.class); Return the } complete query
Loop for the
private void buildIndex() { tx = session.beginTransaction(); ScopedEntity entity = new ScopedEntity(); entity.setField1("test field1"); entity.setField2("test field2"); session.save(entity); entity = new ScopedEntity(); entity.setField1("test field3"); entity.setField2("test field4");
Tokenization and fields
session.save(entity); tx.commit(); } }
The results of our first query B of TEST on field2 returned zero results. Looking at C we see that the generated query string was +field2:TEST. According to listing 7.2 the ScopedAnalyzer should have applied a WhitespaceAnalyzer to the field during indexing and during the query. The WhitespaceAnalyzer does not pass its tokens through a LowercaseFilter, so the query of TEST would have remained uppercase and therefore would not have found any results. That is exactly what happened; so far, so good. Now the second query D illustrates that the query returned two results for the query string +field1:test E. The query in this case was lowercased. Examining listing 7.2 again we see that no explicit analyzer was applied to the field1 field. Therefore, the ScopedAnalyzer would have applied the global analyzer, which is by definition the StandardAnalyzer. This analyzer does lowercase its tokens, so ScopedAnalyzer works exactly as we expected. It applied a WhitespaceAnalyzer to field2 and a StandardAnalyzer to field1. Let s examine how the query was built. A TokenStream is obtained from the ScopedAnalyzer F. Since the name of the field being analyzed is passed as a parameter, it allows the ScopedAnalyzer to determine the appropriate context and return the appropriate analyzer. The first token is retrieved from the stream at G. We use the next(Token token) method in lieu of the next() method because it is faster. Read the Javadoc for the org.apache.lucene.analysis.TokenStream.next(Token result). We extract the term from the token via the char[] buffer in the token H and copy it to a new string, so it s safe to reuse the token. We start building the query I and loop for more tokens J. Once the tokens are exhausted, we return the completed query 1). As you can see, this requires a fair amount of additional programming, but it guarantees that the analyzer used at query time is the same as the one used at index time. For a thorough treatment of the ScopedAnalyzer API, we recommend that you spend some time examining the testScopedAnalyzerAPI unit test in org.hibernate. search.test.analyzer.AnalyzerTest. Next we re going to talk about programmatic custom query generation. This is the real power of full-text searching. The sky is basically the limit here. You can clean up user queries before they ever make it to your application s search engine. You can split queries in any manner you wish across any number of fields. In short, use your imagination. We re going to discuss the API version of the queries. When we arrive at the BooleanQuery you ll finally see how to put these many different types together to form custom queries exactly as you want them.
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