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

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>.
1. 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](https://issues.apache.org/jira/browse/LUCENE-2470) by Steven Rowe (@sarowe)

Start with Lucene's analysis pipeline and the migrated LUCENE-2470 discussion, then compare the proposed BranchingFilter and MergingFilter with the StandardAnalyzer, CJKTokenizer, ShingleFilter, and token-attribute use cases named here. Done should mean an agreed design and implementation scope for conditional branching and merging, with tests covering the chosen behavior.

Written by the indexing model from the issue text.