address comments

Author: cloud-fan

docs/sql-migration-guide.md

@@ -113,7 +113,7 @@ license: |
 
 ### UDFs and Built-in Functions
 
-  - Since Spark 3.0, the `date_add` and `date_sub` functions only accepts int, smallint, tinyint as the 2nd argument, fractional and string types are not valid anymore, e.g. `date_add(cast('1964-05-23' as date), '12.34')` will cause `AnalysisException`. Note that, string literals are still allowed, but Spark will throw Analysis Exception if the string is not a valid integer. In Spark version 2.4 and earlier, if the 2nd argument is fractional or string value, it will be coerced to int value, and the result will be a date value of `1964-06-04`.
+  - Since Spark 3.0, the `date_add` and `date_sub` functions only accept int, smallint, tinyint as the 2nd argument, fractional and non-literal string are not valid anymore, e.g. `date_add(cast('1964-05-23' as date), 12.34)` will cause `AnalysisException`. Note that, string literals are still allowed, but Spark will throw Analysis Exception if the string content is not a valid integer. In Spark version 2.4 and earlier, if the 2nd argument is fractional or string value, it will be coerced to int value, and the result will be a date value of `1964-06-04`.
 
   - Since Spark 3.0, the function `percentile_approx` and its alias `approx_percentile` only accept integral value with range in `[1, 2147483647]` as its 3rd argument `accuracy`, fractional and string types are disallowed, e.g. `percentile_approx(10.0, 0.2, 1.8D)` will cause `AnalysisException`. In Spark version 2.4 and earlier, if `accuracy` is fractional or string value, it will be coerced to an int value, `percentile_approx(10.0, 0.2, 1.8D)` is operated as `percentile_approx(10.0, 0.2, 1)` which results in `10.0`.
 

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/TypeCoercion.scala

@@ -1049,7 +1049,7 @@ object TypeCoercion {
   /**
    * A special rule to support string literal as the second argument of date_add/date_sub functions,
    * to keep backward compatibility as a temporary workaround.
-   * TODO: revisit the type coercion rules for string.
+   * TODO(SPARK-28589): implement ANSI type type coercion and handle string literals.
    */
   object StringLiteralCoercion extends TypeCoercionRule {
     override protected def coerceTypes(plan: LogicalPlan): LogicalPlan = plan resolveExpressions {