[Bug] Ensure column name is backticked during alter

[rariyama-k]

Is this a new bug in dbt-spark?

• I believe this is a new bug in dbt-spark
• I have searched the existing issues, and I could not find an existing issue for this bug

Current Behavior

When you define a model like the following and execute dbt run, new columns will be added if there are schema changes.

version: 2
models:
  - name: table
    config:
      materialized: incremental
      on_schema_change: append_new_columns

alter table `db`.`schema`.`table`
    add columns (
        new_column string
    )

At this time, if the column name contains a hyphen, it will fail with the following error:

[INVALID_IDENTIFIER] The unquoted identifier column_name is invalid and must be back quoted as: `column_name`.
It would be helpful if you could either add an option to enclose column names with backticks when executing ALTER TABLE, or modify the SQL for ALTER TABLE itself.

Expected Behavior

When executing alter table statement, column name is backticked.

alter table `db`.`schema`.`table`
    add columns (
        `new_column` string
    )

Steps To Reproduce

1. Create table with hyphen named columns

    create table repro (
         test-c string
    )

2. Define model file as follows.

version: 2
models:
  - name: table
    config:
      materialized: incremental
      on_schema_change: append_new_columns

3. Run dbt-run and add new column

Relevant log output

NA

Environment

- OS: macOS Ventura 13.2.1 (22D68)
- Python: Python 3.12.7
- dbt-core: 1.8.5
- dbt-spark: 1.8.0

Additional Context

NA