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

### What changes were proposed in this pull request?

This PR modifies comment for `UTF8String.trimAll` and`sql-migration-guide.mld`.
The comment for `UTF8String.trimAll` says like as follows.
```
Trims whitespaces ({literal <=} ASCII 32) from both ends of this string.
```
Similarly, `sql-migration-guide.md` mentions about the behavior of `cast` like as follows.
```
In Spark 3.0, when casting string value to integral types(tinyint, smallint, int and bigint),
datetime types(date, timestamp and interval) and boolean type,
the leading and trailing whitespaces (<= ASCII 32) will be trimmed before converted to these type values,
for example, `cast(' 1\t' as int)` results `1`, `cast(' 1\t' as boolean)` results `true`,
`cast('2019-10-10\t as date)` results the date value `2019-10-10`.
In Spark version 2.4 and below, when casting string to integrals and booleans,
it does not trim the whitespaces from both ends; the foregoing results is `null`,
while to datetimes, only the trailing spaces (= ASCII 32) are removed.
```

But SPARK-32559 (#29375) changed the behavior and only whitespace ASCII characters will be trimmed since Spark 3.0.1.

### Why are the changes needed?

To follow the previous change.

### Does this PR introduce _any_ user-facing change?

No.

### How was this patch tested?

Confirmed the document built by the following command.
```
SKIP_API=1 bundle exec jekyll build
```

Closes #33287 from sarutak/fix-utf8string-trim-issue.

Authored-by: Kousuke Saruta <sarutak@oss.nttdata.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
(cherry picked from commit 57a4f310df)
Signed-off-by: Wenchen Fan <wenchen@databricks.com>

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

@@ -562,10 +562,10 @@ public final class UTF8String implements Comparable<UTF8String>, Externalizable,
   }
 
   /**
-   * 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.
@@ -573,13 +573,13 @@ public final class UTF8String implements Comparable<UTF8String>, Externalizable,
    */
   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

@@ -159,6 +159,8 @@ 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