Package org.apache.lucene.search.highlight

Class TokenSources

  • public class TokenSources
extends java.lang.Object
    Hides implementation issues associated with obtaining a TokenStream for use with the higlighter - can obtain from TermFreqVectors with offsets and (optionally) positions or from Analyzer class reparsing the stored content.

    • Constructor Detail

      • TokenSources

        public TokenSources()

    • Method Detail

      • getAnyTokenStream

        public static TokenStream getAnyTokenStream​(IndexReader reader,
                                            int docId,
                                            java.lang.String field,
                                            Document doc,
                                            Analyzer analyzer)
                                     throws java.io.IOException
        A convenience method that tries to first get a TermPositionVector for the specified docId, then, falls back to using the passed in Document to retrieve the TokenStream. This is useful when you already have the document, but would prefer to use the vector first.
        Parameters:
        reader - The IndexReader to use to try and get the vector from
        docId - The docId to retrieve.
        field - The field to retrieve on the document
        doc - The document to fall back on
        analyzer - The analyzer to use for creating the TokenStream if the vector doesn't exist
        Returns:
        The TokenStream for the IndexableField on the Document
        Throws:
        java.io.IOException - if there was an error loading

      • getAnyTokenStream

        public static TokenStream getAnyTokenStream​(IndexReader reader,
                                            int docId,
                                            java.lang.String field,
                                            Analyzer analyzer)
                                     throws java.io.IOException
        A convenience method that tries a number of approaches to getting a token stream. The cost of finding there are no termVectors in the index is minimal (1000 invocations still registers 0 ms). So this "lazy" (flexible?) approach to coding is probably acceptable
        Returns:
        null if field not stored correctly
        Throws:
        java.io.IOException - If there is a low-level I/O error

      • getTokenStream

        public static TokenStream getTokenStream​(Terms vector)
                                  throws java.io.IOException
        Throws:
        java.io.IOException

      • getTokenStream

        public static TokenStream getTokenStream​(Terms tpv,
                                         boolean tokenPositionsGuaranteedContiguous)
                                  throws java.io.IOException
        Low level api. Returns a token stream generated from a Terms. This can be used to feed the highlighter with a pre-parsed token stream. The Terms must have offsets available. In my tests the speeds to recreate 1000 token streams using this method are: - with TermVector offset only data stored - 420 milliseconds - with TermVector offset AND position data stored - 271 milliseconds (nb timings for TermVector with position data are based on a tokenizer with contiguous positions - no overlaps or gaps) The cost of not using TermPositionVector to store pre-parsed content and using an analyzer to re-parse the original content: - reanalyzing the original content - 980 milliseconds The re-analyze timings will typically vary depending on - 1) The complexity of the analyzer code (timings above were using a stemmer/lowercaser/stopword combo) 2) The number of other fields (Lucene reads ALL fields off the disk when accessing just one document field - can cost dear!) 3) Use of compression on field storage - could be faster due to compression (less disk IO) or slower (more CPU burn) depending on the content.
        Parameters:
        tokenPositionsGuaranteedContiguous - true if the token position numbers have no overlaps or gaps. If looking to eek out the last drops of performance, set to true. If in doubt, set to false.
        Throws:
        java.lang.IllegalArgumentException - if no offsets are available
        java.io.IOException

      • getTokenStreamWithOffsets

        public static TokenStream getTokenStreamWithOffsets​(IndexReader reader,
                                                    int docId,
                                                    java.lang.String field)
                                             throws java.io.IOException
        Returns a TokenStream with positions and offsets constructed from field termvectors. If the field has no termvectors, or positions or offsets are not included in the termvector, return null.
        Parameters:
        reader - the IndexReader to retrieve term vectors from
        docId - the document to retrieve termvectors for
        field - the field to retrieve termvectors for
        Returns:
        a TokenStream, or null if positions and offsets are not available
        Throws:
        java.io.IOException - If there is a low-level I/O error

      • getTokenStream

        public static TokenStream getTokenStream​(IndexReader reader,
                                         int docId,
                                         java.lang.String field,
                                         Analyzer analyzer)
                                  throws java.io.IOException
        Throws:
        java.io.IOException

      • getTokenStream

        public static TokenStream getTokenStream​(java.lang.String field,
                                         java.lang.String contents,
                                         Analyzer analyzer)