Add conditional braching/merging to Lucene's analysis pipeline [LUCENE-2470]

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Captured from a #lucene brainstorming session with Robert Muir:

Lucene's analysis pipeline would be more flexible if it were possible to apply filter(s) to only part of an input stream's tokens, under user-specifiable conditions (e.g. when a given token attribute has a particular value) in a way that did not place that responsibility on individual filters.

Two use cases:

1. StandardAnalyzer could directly handle ideographic characters in the same way as CJKTokenizer, which generates bigrams, if it could call ShingleFilter only when the TypeAttribute=<CJK>, or if Robert's new ScriptAttribute=<Ideographic>.
2. Stemming might make sense for some stemmer/domain combinations only when token length exceeds some threshold. For example, a user could configure an analyzer to stem only when CharTermAttribute length is greater than 4 characters.

One potential way to achieve this conditional branching facility is with a new kind of filter that can be configured with one or more following filters and condition(s) under which the filter should be engaged. This could be called BranchingFilter.

I think a MergingFilter, the inverse of BranchingFilter, is necessary in the current pipeline architecture, to have a single pipeline endpoint. A MergingFilter might be useful in its own right, e.g. to collect document data from multiple sources. Perhaps a conditional merging facility would be useful as well.

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Migrated from LUCENE-2470 by Steven Rowe (@sarowe)

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Steven Rowe (@sarowe) (migrated from JIRA)

One more thing from #lucene: if a conditionally-applied filter isn't given one or more input stream tokens, it could either be reset(), or it could detect position increment gaps. Maybe both behaviors should be selectable via configuration?

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Michael McCandless (@mikemccand) (migrated from JIRA)

This is a great idea!

It'd give us much more composability in the analysis pipeline, since individual filters (Shingle, Stem) would be fully independent, ie not aware that they are being invoked from the BranchingFilter.

I think we should allow the conditional to switch between sub-pipelines? EG I could make a stage that detects proper names (say)... and if the token is not a proper name, it'll run through a LowercaseFilter then StopFilter, else it passes through. So the conditional would switch between full sub-pipelines.

We should also allow for 1 -> many sub-pipelines, eg you conditionally invoke an ngram filter. Or many -> may, eg you conditionally invoke a shingle filters.

I think upgrading the analysis pipeline to write-once attr bindings (#3524) would make this BranchingFilter easier to implement.

With write-once bindings, there's full visibility on which attrs a Stage writes to (changes). So this BranchingStage could easily introspect to see which attrs its subs write to, invoke them as the conditions require, and if none of the conditions apply, copy over the necessary attrs.

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Robert Muir (@rmuir) (migrated from JIRA)

I think we should allow the conditional to switch between sub-pipelines? EG I could make a stage that detects proper names (say)... and if the token is not a proper name, it'll run through a LowercaseFilter then StopFilter, else it passes through. So the conditional would switch between full sub-pipelines.

I really like this aspect of the idea. Besides the language issues that Steven brought up, we could start to look at the KeywordAttribute/KeywordMarker as a "hack", and this is a more generalized way to look at it.

I think the real key is, if we can make it nice to do this declaratively, for example in a Solr schema definition.

This way, someone with a multilanguage document/query could apply conditional pipelines to different parts, someone could do the 'keyword' stuff (but this might be based on length, their own custom attribute, POS, whatever they want).

In truth I think there are a lot of hardcoded 'conditions/parameters' in the analysis components right now. Something like this would allow pieces to be more general/reusable and flexible.

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Steven Rowe (@sarowe) (migrated from JIRA)

I think we should allow the conditional to switch between sub-pipelines? EG I could make a stage that detects proper names (say)... and if the token is not a proper name, it'll run through a LowercaseFilter then StopFilter, else it passes through. So the conditional would switch between full sub-pipelines.

I think one consequence of this design is that the BranchingFilter/Stage would have to do its own merging, so MergingFilter is not necessary, right?

The other uses for a MergingFilter should be put into another issue, if we go with this design and there is interest, switching this issue to cover only BranchingFilter/Stage.

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Steven Rowe (@sarowe) (migrated from JIRA)

We should also allow for 1 -> many sub-pipelines, eg you conditionally invoke an ngram filter. Or many -> may, eg you conditionally invoke a shingle filters.

Do you mean that it should be possible to configure multiple filters to process the same input token? If so, then we could e.g. remove the "outputUnigram" option from ShingleFilter, and configure both a PassThroughFilter and a ShingleFilter to operate simultaneously over the same inputs.

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Steven Rowe (@sarowe) (migrated from JIRA)

Before I forget: It's always bugged me that analysis output can only be to a single field. Could this be the place to fix that?

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Michael McCandless (@mikemccand) (migrated from JIRA)

I think one consequence of this design is that the BranchingFilter/Stage would have to do its own merging, so MergingFilter is not necessary, right?

Right.

The other uses for a MergingFilter should be put into another issue, if we go with this design and there is interest, switching this issue to cover only BranchingFilter/Stage.

These are interesting too!

Do you mean that it should be possible to configure multiple filters to process the same input token?

Actually I didn't – I meant that we should allow a sub-pipeline to process 1 token and produce (say) 3. But it is a neat idea to allow more than one sub to operate; I like the PassThroughFilter.

Before I forget: It's always bugged me that analysis output can only be to a single field. Could this be the place to fix that?

That's a biggish change :) I think we should tackle it separately – we'd have to change indexer for this (right now it visits one field at a time, processing all of its tokens).

But, I do think this write-once attr approach could be used as a document pre-processing pipeline, eg to enhance the doc, pull out additional fields, etc.

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Steven Rowe (@sarowe) (migrated from JIRA)

I think the real key is, if we can make it nice to do this declaratively, for example in a Solr schema definition.

I agree.

We could start with a BranchingStageFactory that takes in a structured conditional processing specification, but I have the feeling that it will seem like declarative specification of the entire analysis pipeline, ala Solr, is the way to go.