[SPARK-36081][SPARK-36066][SQL] Update the document about the behavior change of trimming characters for cast

common/unsafe/src/main/java/org/apache/spark/unsafe/types/UTF8String.java

@@ -562,24 +562,24 @@ public UTF8String trim() {
   }
 
   /**
-   * Trims whitespaces ({@literal <=} ASCII 32) from both ends of this string.
+   * Trims whitespace ASCII characters from both ends of this string.
    *
-   * Note that, this method is the same as java's {@link String#trim}, and different from
-   * {@link UTF8String#trim()} which remove only spaces(= ASCII 32) from both ends.
+   * Note that, this method is different from {@link UTF8String#trim()} which removes
+   * only spaces(= ASCII 32) from both ends.
    *
    * @return A UTF8String whose value is this UTF8String, with any leading and trailing white
    * space removed, or this UTF8String if it has no leading or trailing whitespace.
    *
    */
   public UTF8String trimAll() {
     int s = 0;
-    // skip all of the whitespaces (<=0x20) in the left side
+    // skip all of the whitespaces in the left side
     while (s < this.numBytes && Character.isWhitespace(getByte(s))) s++;
     if (s == this.numBytes) {
       // Everything trimmed
       return EMPTY_UTF8;
     }
-    // skip all of the whitespaces (<=0x20) in the right side
+    // skip all of the whitespaces in the right side
     int e = this.numBytes - 1;
     while (e > s && Character.isWhitespace(getByte(e))) e--;
     if (s == 0 && e == numBytes - 1) {

docs/sql-migration-guide.md

@@ -157,6 +157,8 @@ license: |
 
 - In Spark 3.0, JSON datasource and JSON function `schema_of_json` infer TimestampType from string values if they match to the pattern defined by the JSON option `timestampFormat`. Since version 3.0.1, the timestamp type inference is disabled by default. Set the JSON option `inferTimestamp` to `true` to enable such type inference.
 
+- In Spark 3.0, when casting string to integral types(tinyint, smallint, int and bigint), datetime types(date, timestamp and interval) and boolean type, the leading and trailing characters (<= ASCII 32) will be trimmed. For example, `cast('\b1\b' as int)` results `1`. Since Spark 3.0.1, only the leading and trailing whitespace ASCII characters will be trimmed. For example, `cast('\t1\t' as int)` results `1` but `cast('\b1\b' as int)` results `NULL`.
+
 ## Upgrading from Spark SQL 2.4 to 3.0
 
 ### Dataset/DataFrame APIs