Updates to Docs for Fuzzy matches

docs/reference/query-dsl/queries/fuzzy-query.asciidoc

@@ -1,14 +1,22 @@
 [[query-dsl-fuzzy-query]]
 === Fuzzy Query
 
-A fuzzy query that uses similarity based on Levenshtein (edit
-distance) algorithm. This maps to Lucene's `FuzzyQuery`.
+A fuzzy query that uses similarity based on the Levenshtein (edit distance) algorithm for text,
+and ranges for numeric and date data.
+This maps to Lucene's `FuzzyQuery` when run against a text field, and maps to a range filter when run against a numeric field.
+Maximum edit distance is determined via the `min_similarity` parameter,
+which can only take the values 1 or 2 for text for performance reasons.
 
-Warning: this query is not very scalable with its default prefix length
-of 0 - in this case, *every* term will be enumerated and cause an edit
-score calculation or `max_expansions` is not set.
+Users should be warned, performance can easily degrade when using this query on an index with a
+large number of terms, especially when a `min_similarity` of 2 is set.
+Execution speed can be dramatically improved through the use of the `prefix_length` and
+`max_expansions` settings, described later in this document.
 
-Here is a simple example:
+It should also be noted that `min_similarity` can also take a `float` value, which is
+converted to an integer edit distance based based on the text's properties, but that this is deprecated.
+Please use only integer values for `min_similarity`.
+
+Here is a simple example of matching text with a `fuzzy` query:
 
 [source,js]
 --------------------------------------------------
@@ -17,8 +25,7 @@ Here is a simple example:
 }
 --------------------------------------------------
 
-More complex settings can be set (the values here are the default
-values):
+More complex settings can be seen below (the values here are the defaults):
 
 [source,js]
 --------------------------------------------------
@@ -27,20 +34,17 @@ values):
             "user" : {
                 "value" : "ki",
                 "boost" : 1.0,
-                "min_similarity" : 0.5,
+                "min_similarity" : 1,
                 "prefix_length" : 0
             }
         }
     }
 --------------------------------------------------
 
-The `max_expansions` parameter (unbounded by default) controls the
-number of terms the fuzzy query will expand to.
-
 [float]
 ==== Numeric / Date Fuzzy
 
-`fuzzy` query on a numeric field will result in a range query "around"
+A `fuzzy` query on a numeric field will result in a range query "around"
 the value using the `min_similarity` value. For example:
 
 [source,js]
@@ -77,3 +81,18 @@ For example, for dates, a fuzzy factor of "1d" will result in
 multiplying whatever fuzzy value provided in the min_similarity by it.
 Note, this is explicitly supported since query_string query only allowed
 for similarity valued between 0.0 and 1.0.
+
+==== Performance Tuning
+
+The default settings for this query prefer correct behavior over speed. Given an index
+with a large number of terms, performance can quickly degrade. The `prefix_length` and `max_expansions`
+parameters can be used to remedy performance problems in larger datasets by significantly
+reducing the search space at cost of not matching some valid documents.
+
+The `prefix_length` parameter restricts matches to those that have an an exact prefix match of the provided length with the query `value`.
+Using `prefix_length` greatly shortens the search space at the expense of not detecting edits that occur at the start of the term.
+
+The `max_expansions` parameter controls the number of alternate versions of the input term to look for.
+When the query is executed only a set number of permutations, by default 50, are actually matched.
+The lower the value of `max_expansions` the faster the query will be. The trade-off here is that some documents that
+should match may not be returned due to their specific edit not being a part of the expansion list.

docs/reference/query-dsl/queries/match-query.asciidoc

@@ -1,3 +1,4 @@
+
 [[query-dsl-match-query]]
 === Match Query
 
@@ -34,14 +35,18 @@ The `analyzer` can be set to control which analyzer will perform the
 analysis process on the text. It default to the field explicit mapping
 definition, or the default search analyzer.
 
-`fuzziness` can be set to a value (depending on the relevant type, for
-string types it should be a value between `0.0` and `1.0`) to constructs
-fuzzy queries for each term analyzed. The `prefix_length` and
-`max_expansions` can be set in this case to control the fuzzy process.
+The `fuzziness` option can be set to search for values slightly different from the query value.
+The fuzziness option controls the maximum Levenshtein distance when querying string fields 
+with distances of `1` or `2` being legal. When querying numeric fields, it can take larger values,
+and is internally converted into a range query.
+For more information on fuzzy queries see <<query-dsl-fuzzy,fuzzy>>, which documents
+this query type more fully. Note that all the options supported by the `fuzzy` query, such as
+such as `max_expansions` and `prefix_length`, are supported within a `match` query when
+`fuzziness` is specified.
+
 If the fuzzy option is set the query will use `constant_score_rewrite`
-as its <<query-dsl-multi-term-rewrite,rewrite
-method>> the `rewrite` parameter allows to control how the query will get
-rewritten.
+as its <<query-dsl-multi-term-rewrite,rewrite method>>
+the `rewrite` parameter controls how the query will get rewritten.
 
 Here is an example when providing additional parameters (note the slight
 change in structure, `message` is the field name):