### What changes were proposed in this pull request?
This PR adds the char/varchar type which is kind of a variant of string type:
1. Char type is fixed-length string. When comparing char type values, we need to pad the shorter one to the longer length.
2. Varchar type is string with a length limitation.
To implement the char/varchar semantic, this PR:
1. Do string length check when writing to char/varchar type columns.
2. Do string padding when reading char type columns. We don't do it at the writing side to save storage space.
3. Do string padding when comparing char type column with string literal or another char type column. (string literal is fixed length so should be treated as char type as well)
To simplify the implementation, this PR doesn't propagate char/varchar type info through functions/operators(e.g. `substring`). That said, a column can only be char/varchar type if it's a table column, not a derived column like `SELECT substring(col)`.
To be safe, this PR doesn't add char/varchar type to the query engine(expression input check, internal row framework, codegen framework, etc.). We will replace char/varchar type by string type with metadata (`Attribute.metadata` or `StructField.metadata`) that includes the original type string before it goes into the query engine. That said, the existing code will not see char/varchar type but only string type.
char/varchar type may come from several places:
1. v1 table from hive catalog.
2. v2 table from v2 catalog.
3. user-specified schema in `spark.read.schema` and `spark.readStream.schema`
4. `Column.cast`
5. schema string in places like `from_json`, pandas UDF, etc. These places use SQL parser which replaces char/varchar with string already, even before this PR.
This PR covers all the above cases, implements the length check and padding feature by looking at string type with special metadata.
### Why are the changes needed?
char and varchar are standard SQL types. varchar is widely used in other databases instead of string type.
### Does this PR introduce _any_ user-facing change?
For hive tables: now the table insertion fails if the value exceeds char/varchar length. Previously we truncate the value silently.
For other tables:
1. now char type is allowed.
2. now we have length check when inserting to varchar columns. Previously we write the value as it is.
### How was this patch tested?
new tests
Closes#30412 from cloud-fan/char.
Authored-by: Wenchen Fan <wenchen@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
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