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 cos of compression (less disk IO) or slower (more CPU burn) depending on the content.

Parameters

tpv

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.

See Also

TokenSources Class | Lucene.Net.Highlight Namespace | TokenSources.GetTokenStream Overload List