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

Improve the error messages for cast failures in ANSI.
As mentioned in https://issues.apache.org/jira/browse/SPARK-38929, this PR targets two cast-to types: numeric types and date types.
* For numeric(`int`, `smallint`, `double`, `float`, `decimal` ..) types, it embeds the cast-to types in the error message. For example,
  ```
  Invalid input value for type INT: '1.0'. To return NULL instead, use 'try_cast'. If necessary set %s to false to bypass this error.
  ```
  It uses the `toSQLType` and `toSQLValue` to wrap the corresponding types and literals.
* For date types, it does similarly as above. For example,
  ```
  Invalid input value for type TIMESTAMP: 'a'. To return NULL instead, use 'try_cast'. If necessary set spark.sql.ansi.enabled to false to bypass this error.
  ```

### Why are the changes needed?
To improve the error message in general.

### Does this PR introduce _any_ user-facing change?
It changes the error messages.

### How was this patch tested?
The related unit tests are updated.

Authored-by: Xinyi Yu <xinyi.yudatabricks.com>
Signed-off-by: Max Gekk <max.gekkgmail.com>
(cherry picked from commit f76b3e7)

Closes #36275 from anchovYu/ansi-error-improve-3.3.

Authored-by: Xinyi Yu <xinyi.yu@databricks.com>
Signed-off-by: Max Gekk <max.gekk@gmail.com>