feat(incremental): optimize 'insert_overwrite' strategy (#1409)

[AxelThevenot]

resolves #1409 docs "N/A"

Problem

The MERGE statement is sub-optimized in BigQuery when it comes to only replace partitions in the 'insert_overwrite' strategy for incremental models

Solution

For the insert_overwrite strategy where we are looking to replace rows at the partition-level, there is a better solution and here is why:

• a DELETE or INSERT statement is cheapest than a MERGE statement.
• incremental tables are the most expensive tables in real-world projects.
• The DELETE statement in BigQuery is free at the partition-level.

This has been tested at Carrefour which is my company.

• On this replacement of the MERGE statement it reduces the cost by 50.4% and the elapsed time by 35.2% (slot based and not on demand)
• On the overall procedure it reduces the cost by 26.1% and the elapsed time by 23.1%

This is wrapped in a transaction to avoid deleting rows if any error occurs.

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 --> (using the same existing tests for 'insert_overwrite')
• [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