Updated fielddata docs to make it easier for users with old mappings

docs/reference/mapping/params/fielddata.asciidoc

@@ -2,42 +2,105 @@
 === `fielddata`
 
 Most fields are <<mapping-index,indexed>> by default, which makes them
-searchable. The inverted index allows queries to look up the search term in
-unique sorted list of terms, and from that immediately have access to the list
-of documents that contain the term.
+searchable. Sorting, aggregations, and accessing field values in scripts,
+however, requires a different access pattern from search.
 
-Sorting, aggregations, and access to field values in scripts requires a
-different data access pattern.  Instead of lookup up the term and finding
-documents, we need to be able to look up the document and find the terms that
-it has in a field.
+Search needs to answer the question _"Which documents contain this term?"_,
+while sorting and aggregations need to answer a different question: _"What is
+the value of this field for **this** document?"_.
 
-Most fields can use index-time, on-disk <<doc-values,`doc_values`>> to support
-this type of data access pattern, but `text` fields do not support `doc_values`.
+Most fields can use index-time, on-disk <<doc-values,`doc_values`>> for this
+data access pattern, but <<text,`text`>> fields do not support `doc_values`.
 
-Instead, `text` strings use a query-time data structure called
+Instead, `text` fields use a query-time *in-memory* data structure called
 `fielddata`.  This data structure is built on demand the first time that a
-field is used for aggregations, sorting, or is accessed in a script.  It is built
-by reading the entire inverted index for each segment from disk, inverting the
-term ↔︎ document relationship, and storing the result in memory, in the
-JVM heap.
-
-Loading fielddata is an expensive process so it is disabled by default. Also,
-when enabled, once it has been loaded, it remains in memory for the lifetime of
-the segment.
-
-[WARNING]
-.Fielddata can fill up your heap space
-==============================================================================
-Fielddata can consume a lot of heap space, especially when loading high
-cardinality `text` fields.  Most of the time, it doesn't make sense
-to sort or aggregate on `text` fields (with the notable exception
-of the
-<<search-aggregations-bucket-significantterms-aggregation,`significant_terms`>>
-aggregation).  Always think about whether a <<keyword,`keyword`>> field (which can
-use `doc_values`) would be  a better fit for your use case.
-==============================================================================
-
-TIP: The `fielddata.*` settings must have the same settings for fields of the
+field is used for aggregations, sorting, or in a script.  It is built by
+reading the entire inverted index for each segment from disk, inverting the
+term ↔︎ document relationship, and storing the result in memory, in the JVM
+heap.
+
+==== Fielddata is disabled on `text` fields by default
+
+Fielddata can consume a *lot* of heap space, especially when loading high
+cardinality `text` fields.  Once fielddata has been loaded into the heap, it
+remains there for the lifetime of the segment. Also, loading fielddata is an
+expensive process which can cause users to experience latency hits.  This is
+why fielddata is disabled by default.
+
+If you try to sort, aggregate, or access values from a script on a `text`
+field, you will see this exception:
+
+[quote]
+--
+Fielddata is disabled on text fields by default.  Set `fielddata=true` on
+[`your_field_name`] in order to load  fielddata in memory by uninverting the
+inverted index. Note that this can however use significant memory.
+--
+
+[[before-enabling-fielddata]]
+==== Before enabling fielddata
+
+Before you enable fielddata, consider why you are using a `text` field for
+aggregations, sorting, or in a script.  It usually doesn't make sense to do
+so.
+
+A text field is analyzed before indexing so that a value like
+`New York` can be found by searching for `new` or for `york`.  A `terms`
+aggregation on this field will return a `new` bucket and a `york` bucket, when
+you probably want a single bucket called `New York`.
+
+Instead, you should have a `text` field for full text searches, and an
+unanalyzed <<keyword,`keyword`>> field with <<doc-values,`doc_values`>>
+enabled for aggregations, as follows:
+
+[source,js]
+---------------------------------
+PUT my_index
+{
+  "mappings": {
+    "my_type": {
+      "properties": {
+        "my_field": { <1>
+          "type": "text",
+          "fields": {
+            "keyword": { <2>
+              "type": "keyword"
+            }
+          }
+        }
+      }
+    }
+  }
+}
+---------------------------------
+// CONSOLE
+<1> Use the `my_field` field for searches.
+<2> Use the `my_field.keyword` field for aggregations, sorting, or in scripts.
+
+==== Enabling fielddata on `text` fields
+
+You can enable fielddata on an existing `text` field using the
+<<indices-put-mapping,PUT mapping API>> as follows:
+
+[source,js]
+-----------------------------------
+PUT my_index/_mapping/my_type
+{
+  "properties": {
+    "my_field": { <1>
+      "type":     "text",
+      "fielddata": true
+    }
+  }
+}
+-----------------------------------
+// CONSOLE
+// TEST[continued]
+
+<1> The mapping that you specify for `my_field` should consist of the existing
+    mapping for that field, plus the `fielddata` parameter.
+
+TIP: The `fielddata.*` parameter must have the same settings for fields of the
 same name in the same index.  Its value can be updated on existing fields
 using the <<indices-put-mapping,PUT mapping API>>.
 
@@ -49,12 +112,13 @@ using the <<indices-put-mapping,PUT mapping API>>.
 Global ordinals is a data-structure on top of fielddata and doc values, that
 maintains an incremental numbering for each unique term in a lexicographic
 order. Each term has a unique number and the number of term 'A' is lower than
-the number of term 'B'. Global ordinals are only supported on string fields.
+the number of term 'B'. Global ordinals are only supported on <<text,`text`>>
+and <<keyword,`keyword`>> fields.
 
-Fielddata and doc values also have ordinals, which is a unique numbering for all terms
-in a particular segment and field. Global ordinals just build on top of this,
-by providing a mapping between the segment ordinals and the global ordinals,
-the latter being unique across the entire shard.
+Fielddata and doc values also have ordinals, which is a unique numbering for
+all terms in a particular segment and field. Global ordinals just build on top
+of this, by providing a mapping between the segment ordinals and the global
+ordinals, the latter being unique across the entire shard.
 
 Global ordinals are used for features that use segment ordinals, such as
 sorting and the terms aggregation, to improve the execution time. A terms
@@ -68,10 +132,11 @@ which is different than for field data for a specific field which is tied to a
 single segment. For this reason global ordinals need to be entirely rebuilt
 whenever a once new segment becomes visible.
 
-The loading time of global ordinals depends on the number of terms in a field, but in general
-it is low, since it source field data has already been loaded. The memory overhead of global
-ordinals is a small because it is very efficiently compressed. Eager loading of global ordinals
-can move the loading time from the first search request, to the refresh itself.
+The loading time of global ordinals depends on the number of terms in a field,
+but in general it is low, since it source field data has already been loaded.
+The memory overhead of global ordinals is a small because it is very
+efficiently compressed. Eager loading of global ordinals can move the loading
+time from the first search request, to the refresh itself.
 
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