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.
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static TokenStream | GetAnyTokenStream (IndexReader reader, int docId, String field, Document doc, Analyzer analyzer) |
| A convenience method that tries to first get a TermPositionVector for the specified docId, then, falls back to using the passed in org.apache.lucene.document.Document to retrieve the TokenStream. This is useful when you already have the document, but would prefer to use the vector first.
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static TokenStream | GetAnyTokenStream (IndexReader reader, int docId, String field, Analyzer analyzer) |
| 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
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static TokenStream | GetTokenStream (TermPositionVector tpv) |
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static TokenStream | GetTokenStream (TermPositionVector tpv, bool tokenPositionsGuaranteedContiguous) |
| Low level api. Returns a token stream or null if no offset info available in index. This can be used to feed the highlighter with a pre-parsed token stream
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static TokenStream | GetTokenStream (IndexReader reader, int docId, System.String field) |
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static TokenStream | GetTokenStream (IndexReader reader, int docId, String field, Analyzer analyzer) |
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static TokenStream | GetTokenStream (Document doc, String field, Analyzer analyzer) |
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static TokenStream | GetTokenStream (String field, String contents, Analyzer analyzer) |
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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.
Definition at line 38 of file TokenSources.cs.
Low level api. Returns a token stream or null if no offset info available in index. This can be used to feed the highlighter with a pre-parsed token stream
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
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tpv | - Parameters
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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. |
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Definition at line 157 of file TokenSources.cs.