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.

public static TokenStream GetTokenStream(
	TermPositionVector tpv,
	bool tokenPositionsGuaranteedContiguous
)

Public Shared Function GetTokenStream ( _
	tpv As TermPositionVector, _
	tokenPositionsGuaranteedContiguous As Boolean _
) As TokenStream

public:
static TokenStream^ GetTokenStream(
	TermPositionVector^ tpv, 
	bool tokenPositionsGuaranteedContiguous
)