dbt_clone macros, materialization and tests to dbt-spark

[McKnight-42]

resolves #815

Description

adding the macros, and customer materialization needed on adapter side for dbt_clone and trying to design adapter zone version of Clone tests from defer_state in dbt-labs/dbt-core#7881

Checklist

• I have read the contributing guide and understand what's expected of me
• I have signed the CLA
• I have run this code in development and it appears to resolve the stated issue
• This PR includes tests, or tests are not required/relevant for this PR
• I have opened an issue to add/update docs, or docs changes are not required/relevant for this PR
• I have run changie new to create a changelog entry

[McKnight-42]

testing update 6/29: passing test_dbt_clone.py passing locally. failing in ci/cd

[McKnight-42]

@jtcohen6 Curious I know we want the shallow clone Do we also want to do deep copy as an option? I noticed it is not mentioned in updated comments on dbt-labs/dbt-core#7549 but still in the original draft pr dbt-labs/dbt-core#7258.

[jtcohen6]

@McKnight-42 IMO no need to support deep copy/clone as an option! As I understand it, this is the same as fully recreating the table (create table as select * from {other}), and loses a lot of the cost/speed/performance benefits of using clone.

[colin-rogers-dbt]

curious, why can't we do this with non-delta formats?

[McKnight-42]

this may be a misunderstanding on my part honestly will double check I know our writeup and the docs for Databricks specifies delta tables might of confused that with our delta format suggestion, we use in some other places

I know dbt-databricks uses delta tables by default but I don't believe dbt-spark does fully

[colin-rogers-dbt]

One question but LGTM