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https://issues.apache.org/jira/browse/LUCENE-7526?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Timothy M. Rodriguez updated LUCENE-7526:
-----------------------------------------
Description:
This ticket improves several of the UnifiedHighlighter FieldOffsetStrategies by
reducing reliance on creating or re-creating TokenStreams.
The primary changes are as follows:
* AnalysisOffsetStrategy - split into two offset strategies
** MemoryIndexOffsetStrategy - the primary analysis mode that utilizes a
MemoryIndex for producing Offsets
** TokenStreamOffsetStrategy - an offset strategy that avoids creating a
MemoryIndex. Can only be used if the query distills down to terms and automata.
* TokenStream removal
** MemoryIndexOffsetStrategy - previously a TokenStream was created to fill
the memory index and then once consumed a new one was generated by uninverting
the MemoryIndex back into a TokenStream if there were automata (wildcard/mtq
queries) involved. Now this is avoided, which should save memory and avoid a
second pass over the data.
** TermVectorOffsetStrategy - this was refactored in a similar way to avoid
generating a TokenStream if automata are involved.
** PostingsWithTermVectorsOffsetStrategy - similar refactoring
* CompositePostingsEnum - aggregates several underlying PostingsEnums for
wildcard/mtq queries. This should improve relevancy by providing unified
metrics for a wildcard across all it's term matches
* Added a HighlightFlag for enabling the newly separated
TokenStreamOffsetStrategy since it can adversely affect passage relevancy
was:
This ticket improves several of the UnifiedHighlighter FieldOffsetStrategies by
reducing reliance on creating or re-creating TokenStreams.
The primary changes are as follows:
* AnalysisOffsetStrategy - split into two offset strategies
* MemoryIndexOffsetStrategy - the primary analysis mode that utilizes a
MemoryIndex for producing Offsets
* TokenStreamOffsetStrategy - an offset strategy that avoids creating a
MemoryIndex. Can only be used if the query distills down to terms and automata.
* TokenStream removal
* MemoryIndexOffsetStrategy - previously a TokenStream was created to fill
the memory index and then once consumed a new one was generated by uninverting
the MemoryIndex back into a TokenStream if there were automata (wildcard/mtq
queries) involved. Now this is avoided, which should save memory and avoid a
second pass over the data.
* TermVectorOffsetStrategy - this was refactored in a similar way to avoid
generating a TokenStream if automata are involved.
* PostingsWithTermVectorsOffsetStrategy - similar refactoring
* CompositePostingsEnum - aggregates several underlying PostingsEnums for
wildcard/mtq queries. This should improve relevancy by providing unified
metrics for a wildcard across all it's term matches
* Added a HighlightFlag for enabling the newly separated
TokenStreamOffsetStrategy since it can adversely affect passage relevancy
> Improvements to UnifiedHighlighter OffsetStrategies
> ---------------------------------------------------
>
> Key: LUCENE-7526
> URL: https://issues.apache.org/jira/browse/LUCENE-7526
> Project: Lucene - Core
> Issue Type: Improvement
> Reporter: Timothy M. Rodriguez
> Priority: Minor
> Labels: highlighter, unified-highlighter
>
> This ticket improves several of the UnifiedHighlighter FieldOffsetStrategies
> by reducing reliance on creating or re-creating TokenStreams.
> The primary changes are as follows:
> * AnalysisOffsetStrategy - split into two offset strategies
> ** MemoryIndexOffsetStrategy - the primary analysis mode that utilizes a
> MemoryIndex for producing Offsets
> ** TokenStreamOffsetStrategy - an offset strategy that avoids creating a
> MemoryIndex. Can only be used if the query distills down to terms and
> automata.
> * TokenStream removal
> ** MemoryIndexOffsetStrategy - previously a TokenStream was created to fill
> the memory index and then once consumed a new one was generated by
> uninverting the MemoryIndex back into a TokenStream if there were automata
> (wildcard/mtq queries) involved. Now this is avoided, which should save
> memory and avoid a second pass over the data.
> ** TermVectorOffsetStrategy - this was refactored in a similar way to avoid
> generating a TokenStream if automata are involved.
> ** PostingsWithTermVectorsOffsetStrategy - similar refactoring
> * CompositePostingsEnum - aggregates several underlying PostingsEnums for
> wildcard/mtq queries. This should improve relevancy by providing unified
> metrics for a wildcard across all it's term matches
> * Added a HighlightFlag for enabling the newly separated
> TokenStreamOffsetStrategy since it can adversely affect passage relevancy
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