Improve Performance of Source/Model/Exposure extraction

[kgpayne]

With ~1 year of historical manifest.json and run_results.json data, we have started experiencing timeouts running --full-refresh of dbt_artifacts.

1832 | 2021-04-15 15:43:49: 2021-04-15 15:43:49,243 - root - INFO - Database Error in model dim_dbt__sources (models/incremental/dim_dbt__sources.sql)
-- | --
2021-04-15 15:43:49: 2021-04-15 15:43:49,243 - root - INFO - 000630 (57014): Statement reached its statement or warehouse timeout of 1,200 second(s) and was canceled.

Possible solutions:

• Archive old data.
• Replace the 3 individual models that extract Sources, Models and (soon) Exposures into 1 wide table, so json extraction happens once per artefact, rather than at least 3 times.
• Snapshot the extracted json(?)
• Unpack all required fields in the COPY command executed by either the run-operation or by Snowpipe. This is probably the most performant but least flexible. What happens when we want to extract more details from previous runs? Gets a bit difficult 😬 It does however solve the case where JSON objects become too big to fit into a single VARIANT (16mb).
• Do something with the orchestration layer to avoid ever running full-refresh on these models - effectively relying on incremental models to only extract JSON values once per artefact. We'd probably use tags.

[kgpayne]

@NiallRees FYI. We had resolved to try unpacking required fields in the COPY command here, in the hope of solving our 'too much history' problem at the same time as #29 🤔 Its less flexible, but ensures that json extract happens on load, meaning the base tables are flat and therefore not a problem during full refresh.

[alanmcruickshank]

I propose that I try and fix this at the same time as #62 . Proposed approach there.