FuzzySuggester should boost terms with minimal Levenshtein Distance [LUCENE-5172]

For my use case I need both suggesters: AnalyzingSuggester and FuzzySuggester because FuzzySuggester does not boost terms with minimal Levenshtein distance.
Post processing of FuzzySuggester results is somewhat heavy if only one wants to find direct prefix suggestions. So I first use AnalyzingSuggester to find prefix suggestions and optionally FuzzySuggester afterwards if AnaylzingSuggester did not yield appropriate results.

It would be really useful if FuzzySuggester could boost/sort suggestion results in order of Levenshtein distances. Then I only would need FuzzySuggester.

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Migrated from [LUCENE-5172](https://issues.apache.org/jira/browse/LUCENE-5172) by Anna Björk Nikulásdóttir, updated Jul 19 2019

Start by reading the FuzzySuggester and AnalyzingSuggester entry points to understand how each ranks suggestions and where Levenshtein distance is available. Define how FuzzySuggester should boost or sort terms with minimal distance, then verify that direct prefix suggestions are preferred without losing fuzzy matches.

Written by the indexing model from the issue text.