[SPARK-20888][SQL][DOCS] Document change of default setting of spark.sql.hive.caseSensitiveInferenceMode

(Link to Jira: https://issues.apache.org/jira/browse/SPARK-20888)

## What changes were proposed in this pull request?

Document change of default setting of spark.sql.hive.caseSensitiveInferenceMode configuration key from NEVER_INFO to INFER_AND_SAVE in the Spark SQL 2.1 to 2.2 migration notes.

Author: Michael Allman <[email protected]>

Closes #18112 from mallman/spark-20888-document_infer_and_save.

(cherry picked from commit c1e7989)
Signed-off-by: Wenchen Fan <[email protected]>

Author: Michael Allman

docs/sql-programming-guide.md

@@ -1223,7 +1223,7 @@ the following case-insensitive options:
      This is a JDBC writer related option. If specified, this option allows setting of database-specific table and partition options when creating a table (e.g., <code>CREATE TABLE t (name string) ENGINE=InnoDB.</code>). This option applies only to writing.
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     <td><code>createTableColumnTypes</code></td>
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@@ -1444,6 +1444,10 @@ options.
 
 # Migration Guide
 
+## Upgrading From Spark SQL 2.1 to 2.2
+
+  - Spark 2.1.1 introduced a new configuration key: `spark.sql.hive.caseSensitiveInferenceMode`. It had a default setting of `NEVER_INFER`, which kept behavior identical to 2.1.0. However, Spark 2.2.0 changes this setting's default value to `INFER_AND_SAVE` to restore compatibility with reading Hive metastore tables whose underlying file schema have mixed-case column names. With the `INFER_AND_SAVE` configuration value, on first access Spark will perform schema inference on any Hive metastore table for which it has not already saved an inferred schema. Note that schema inference can be a very time consuming operation for tables with thousands of partitions. If compatibility with mixed-case column names is not a concern, you can safely set `spark.sql.hive.caseSensitiveInferenceMode` to `NEVER_INFER` to avoid the initial overhead of schema inference. Note that with the new default `INFER_AND_SAVE` setting, the results of the schema inference are saved as a metastore key for future use. Therefore, the initial schema inference occurs only at a table's first access.
+
 ## Upgrading From Spark SQL 2.0 to 2.1
 
  - Datasource tables now store partition metadata in the Hive metastore. This means that Hive DDLs such as `ALTER TABLE PARTITION ... SET LOCATION` are now available for tables created with the Datasource API.