Enable BigQuery CDC configuration for Python BigQuery sink

[prodriguezdefino]

Enables the configuration of CDC writes into a BigQuery table by setting the primary key columns to be used in the row mutations. This change adds the configuration of CDC usage for the BigQueryStorageWriteApiSchemaTransformProvider.

By setting configuration.setUseCDCWritesWithPrimaryKey(List.of("col1", "col2")) on the provider's config, the transform creation will create a BigQuery.Write<Row> transform that will configure the right row mutation information by checking for a Row schema like:

{
  row_mutation_info:{
    mutation_type: "..."              // can be UPSERT or DELETE
    change_sequence_number: "..."     // used for custom insert ordering
  }
  record:{...}                        // actual data to be inserted
}

The implementation also enables the possibility of setting a dynamic destination alongside with CDC usage by using this Row schema:

{
  row_mutation_info:{
    mutation_type: "..."              // can be UPSERT or DELETE
    change_sequence_number: "..."     // used for custom insert ordering
  }
  destination: "..."                  // destination table for the data
  record:{...}                        // actual data to be inserted
}

Note: In case of using dynamic destination and CDC is only supported when all the destination share the same primary key columns.

---

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[prodriguezdefino]

fixes #32527

[prodriguezdefino]

I have a question @ahmedabu98, how to make sure the xlang tests for BQ have run?

This branch test output for the test looks pretty similar to those that ran in master the last time, but in both cases it seems that the BQ StorageWrite transform is not being registered.

Am I looking at the right place or are the IT for xlang run in some other different task?

[ahmedabu98]

The test you are referencing is to generate wrappers for external transforms (unrelated here since this wrapper is handwritten).

The workflows testing GCP xlang IOs are in beam_PostCommit_Python_Xlang_Gcp_Dataflow and beam_PostCommit_Python_Xlang_Gcp_Direct. These are post commits so to trigger them you just need to modify their respective target files and push it to this branch:

• Direct runner trigger file
• Dataflow runner trigger file

[prodriguezdefino]

Run Java_GCP_IO_Direct PreCommit

[prodriguezdefino]

Run Java_Examples_Dataflow PreCommit

[ahmedabu98]

FYI @prodriguezdefino we migrated our tests from Jenkins to Github Actions, so tests aren't triggered by comments anymore. I re-ran the Java examples workflow from my side

Check out https://github.com/apache/beam/tree/master/.github/workflows#readme for more info

[prodriguezdefino]

@ahmedabu98 thanks for launching the test run.

I think I covered the previous comments on the PR, do you think is ready or it needs more work?

[ahmedabu98]

It's almost there, just a few more things.
Sorry for all the back and forth 😅

[ahmedabu98]

LGTM

Thanks for your patience and sticking this one out @prodriguezdefino, looking forward to users trying this out :)

[ahmedabu98]

Before I merge, can we add a line to CHANGES.md calling out this new feature? (make sure to mention it's specifically for storage write api's at-least-once mode)

[prodriguezdefino]

Before I merge, can we add a line to CHANGES.md calling out this new feature? (make sure to mention it's specifically for storage write api's at-least-once mode)

Added the changes here: #32788 (less tests that need to pass for the change).

Thanks for the review!

[ahmedabu98]

SGTM, merging