Microbatch strategy

[MichelleArk]

resolves #1182 docs dbt-labs/docs.getdbt.com/# N/A

Problem

dbt-snowflake needs a microbatch implementation that:

• efficiently inserts new batches of data knowing that compiled_code will be filtered down by event_time
• does not require a unique_key configuration on the model.

Solution

• Initially, this was implemented with the delete+insert strategy already defined for dbt-snowflake. However, this creates a requirement for snowflake microbatch models to specify a unique_key, which is actually not strictly necessary!
• Create a custom strategy implementation that simply:
  • Deletes the previous partition of data (using __dbt_internal_microbatch_event_time_start and __dbt_internal_microbatch_event_time_end
  • Inserts the new data from the temp table, since it is filtered-down already via compiled_code

Testing:

• override the insert_two_rows_sql fixture to use snowflake-specific syntax
• override the microbatch_model_sql fixture to demonstrate the lack of requirement of a unique_key config

Checklist

• [x] I have read the contributing guide and understand what's expected of me
• [x] I have run this code in development and it appears to resolve the stated issue
• [x] This PR includes tests, or tests are not required/relevant for this PR
• [x] This PR has no interface changes (e.g. macros, cli, logs, json artifacts, config files, adapter interface, etc) or this PR has already received feedback and approval from Product or DX

[github-actions[bot]]

Thank you for your pull request! We could not find a changelog entry for this change. For details on how to document a change, see the dbt-snowflake contributing guide.