[GitHub] [spark] maropu commented on a change in pull request #27590: [SPARK-30703][SQL][DOCS][FollowUp] Declare the ANSI SQL compliance options as experimental

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maropu commented on a change in pull request #27590: [SPARK-30703][SQL][DOCS][FollowUp] Declare the ANSI SQL compliance options as experimental
URL: https://github.com/apache/spark/pull/27590#discussion_r379816593
 
 

 ##########
 File path: docs/sql-ref-ansi-compliance.md
 ##########
 @@ -19,19 +19,21 @@ license: |
   limitations under the License.
 ---
 
-Spark SQL has two options to comply with the SQL standard: `spark.sql.ansi.enabled` and `spark.sql.storeAssignmentPolicy` (See a table below for details).
+Since Spark 3.0, Spark SQL introduces two experimental options to comply with the SQL standard: `spark.sql.ansi.enabled` and `spark.sql.storeAssignmentPolicy` (See a table below for details).
+
 When `spark.sql.ansi.enabled` is set to `true`, Spark SQL follows the standard in basic behaviours (e.g., arithmetic operations, type conversion, and SQL parsing).
 Moreover, Spark SQL has an independent option to control implicit casting behaviours when inserting rows in a table.
 The casting behaviours are defined as store assignment rules in the standard.
-When `spark.sql.storeAssignmentPolicy` is set to `ANSI`, Spark SQL complies with the ANSI store assignment rules.
+
+When `spark.sql.storeAssignmentPolicy` is set to `ANSI`, Spark SQL complies with the ANSI store assignment rules. This is a separate configuration because its default value is `ANSI`, while the configuration `spark.sql.ansi.enabled` is disabled by default.
 
 <table class="table">
 <tr><th>Property Name</th><th>Default</th><th>Meaning</th></tr>
 <tr>
   <td><code>spark.sql.ansi.enabled</code></td>
   <td>false</td>
   <td>
-    When true, Spark tries to conform to the ANSI SQL specification:
+    (Experimental) When true, Spark tries to conform to the ANSI SQL specification:
 
 Review comment:
   What does `Experimental` mean? That is the same with the `@Experimental` annotation? Anyway, this statement is just copied from one in the SQL configuration document (https://github.com/apache/spark/pull/27459). So, instead of adding the prefix `(Experimental)` manually, I personally think its better to add this prefix automatically via `sql/gen-sql-config-docs.py`. For example, how about adding an `experimental` method in `ConfigBuilder`;
   ```
     val ANSI_ENABLED = buildConf("spark.sql.ansi.enabled")
       .experimental()
       .doc("When true, Spark tries to conform to the ANSI SQL specification: 1. Spark will " +
         "throw a runtime exception if an overflow occurs in any operation on integral/decimal " +
         "field. 2. Spark will forbid using the reserved keywords of ANSI SQL as identifiers in " +
         "the SQL parser.")
       .booleanConf
       .createWithDefault(false)
   ```
   Then, the script adds `(Experimental)` in the head of its description.

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