Describe the bug

As of 1.7, streaming tables are always dropped when model materialized as 'streaming_table' is run, rather than simply refreshed.

Steps To Reproduce

• create a streaming table model, e.g.

{{ config(
    materialized = 'streaming_table',
)}}

SELECT *, CURRENT_TIMESTAMP() as processed_time
FROM STREAM read_files( '{{ var("my_s3_bucket") }}', format => 'json' )

Run the model multiple times. On every run after the first, dbt will output:

Dropping relation <relation name> because it is of type table
and issue a "drop table" statement, followed by a "create streaming table" statement, rather than just a "create or refresh streaming table"

Expected behavior

streaming stable model runs against previously create streaming tables should cause a refresh, not a recreate (except for changes that for a full-refresh, of course)

Screenshots and log output

If applicable, add screenshots or log output to help explain your problem.

System information

The output of dbt --version:

Various - Initially discovered with dbt-databricks and dbt-core 1.7.3,
but verified that it first occurse in dbt-databricks 1.7.0

The operating system you're using:

OSX Ventura 13.3.1

The output of python --version:
Python 3.10.11

Additional context

It appears to me the issue is in the _parse_type method introduced in PR 499, the body of which is:

    def _parse_type(self, information: str) -> str:
        type_entry = [
            entry.strip() for entry in information.split("\n") if entry.split(":")[0] == "Type"
        ]
        return type_entry[0] if type_entry else "

The return value from this method is being compared to "STREAMING_TABLE", however as written it returns "Type: STREAMING_TABLE". The return value needs to be split to solve it, though that is not particularly pretty:

        type_entry = [
            entry.split(":")[1].strip() for entry in information.split("\n") if entry.split(":")[0] == "Type"
        ]

_parse_type only seems to be called for this particular check, so there shouldn't be side effects of this change, but I have not tested for that at all.