[SPARK-19261][SQL] Alter add columns for Hive serde and some datasource tables

## What changes were proposed in this pull request?
Support` ALTER TABLE ADD COLUMNS (...) `syntax for Hive serde and some datasource tables.
In this PR, we consider a few aspects:

1. View is not supported for `ALTER ADD COLUMNS`

2. Since tables created in SparkSQL with Hive DDL syntax will populate table properties with schema information, we need make sure the consistency of the schema before and after ALTER operation in order for future use.

3. For embedded-schema type of format, such as `parquet`, we need to make sure that the predicate on the newly-added columns can be evaluated properly, or pushed down properly. In case of the data file does not have the columns for the newly-added columns, such predicates should return as if the column values are NULLs.

4. For datasource table, this feature does not support the following:
4.1 TEXT format, since there is only one default column `value` is inferred for text format data.
4.2 ORC format, since SparkSQL native ORC reader does not support the difference between user-specified-schema and inferred schema from ORC files.
4.3 Third party datasource types that implements RelationProvider, including the built-in JDBC format, since different implementations by the vendors may have different ways to dealing with schema.
4.4 Other datasource types, such as `parquet`, `json`, `csv`, `hive` are supported.

5. Column names being added can not be duplicate of any existing data column or partition column names. Case sensitivity is taken into consideration according to the sql configuration.

6. This feature also supports In-Memory catalog, while Hive support is turned off.
## How was this patch tested?
Add new test cases

Author: Xin Wu <xinwu@us.ibm.com>

Closes #16626 from xwu0226/alter_add_columns.