Is this your first time submitting a feature request?

• I have read the expectations for open source contributors
• I have searched the existing issues, and I could not find an existing issue for this feature
• I am requesting a straightforward extension of existing dbt-bigquery functionality, rather than a Big Idea better suited to a discussion

Describe the feature

Python BigQuery Client supports asynchronous copy jobs while the dbt-bigquery adapter sends BigQuery requests one by one (using incremental_strategy = 'insert_overwrite' with copy_partitions=true).

We can achieve a better performance if we start sending requests in small batches of partitions.

dbt-bigquery already supports parallel execution in the copy_bq_table function.
But in the bq_copy_partitions macro partitions are sent one at a time.

We can probably implement this feature by introducing a batch_size argument to the configs:

{{ config(
    materialized = 'incremental',
    incremental_strategy = 'insert_overwrite',
    partition_by = {
      "field": "day",
      "data_type": "date",
      "copy_partitions": true,
      "batch_size": 5
    }
) }}

Default value will be 1. And bq_copy_partitions macro will send a list of partitions to the copy_bq_table, where the size of list = batch_size.

Describe alternatives you've considered

No response

Who will this benefit?

Anyone who has high amount of heavy BigQuery partitions.

Are you interested in contributing this feature?

Definitely, just need a green light to proceed

Anything else?

No response