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[Epic] Applied State (part 2) #9425

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graciegoheen opened this issue Jan 23, 2024 · 5 comments
Open
4 of 6 tasks

[Epic] Applied State (part 2) #9425

graciegoheen opened this issue Jan 23, 2024 · 5 comments
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@graciegoheen
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graciegoheen commented Jan 23, 2024

This epic comprises the remaining work on the Applied State initiative to support better visibility into the current state of the database in a more performant way.

dbt-core 1.8

  1. High Severity backport 1.7.latest bug
    QMalcolm
  2. Impact: CA enhancement user docs
    MichelleArk
  3. enhancement
    MichelleArk QMalcolm
  4. enhancement help_wanted
    emmyoop

dbt-core 1.9

  1. enhancement
  2. enhancement freshness user docs
@adamcunnington-mlg
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@graciegoheen / @MichelleArk sorry for the direct Q on this but struggling to understand from docs / issue / PRs. Has the support for batch metadata collection been added for BQ specifically? I saw the general work in dbt-adapters and snowflake and redshift specific but I don't think BQ? Thank you

@jtcohen6
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@adamcunnington-mlg
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@jtcohen6 I think that is just the initial support and not the batch-route - which is the critical bit. Please advise - many thanks

@MichelleArk
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Hey @adamcunnington-mlg -- I've summarized some spiking done to evaluate the cost/benefit of implementing a batch-route for metadata freshness in BigQuery here: dbt-labs/dbt-bigquery#938. There are more details in the spike report, but my overall conclusion is that there isn't currently a way to implement a batch-strategy that achieves performance improvements for metadata-based source freshness given limitations of BigQuery's Python SDK.

@adamcunnington-mlg
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@MichelleArk I believe this is a missed conclusion here. I've left some details against your more comprehensive response; dbt-labs/dbt-bigquery#938 (comment)

These details are also in the original FR; #7012 (comment)

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