Vaishnavi-Pandey12 commented on code in PR #37108:
URL: https://github.com/apache/beam/pull/37108#discussion_r2618968148


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website/www/site/content/en/documentation/io/built-in/google-bigquery.md:
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@@ -659,6 +659,11 @@ runtime. The sharding behavior depends on the runners.
 You must use `triggering_frequency` to specify a triggering frequency for
 initiating load jobs. Be careful about setting the frequency such that your
 pipeline doesn't exceed the BigQuery load job [quota 
limit](https://cloud.google.com/bigquery/quotas#load_jobs).
+
+> **Note:** When using file load-based BigQuery writes with dynamic 
destinations and a non-zero
+> `triggering_frequency`, temporary tables may be created repeatedly and loads
+> are not finalized into destination tables. This is a known limitation (see 
BEAM-9917).

Review Comment:
   Thanks for the clarification — that makes sense.
   
   I added the documentation note to clarify the current behavior while
   investigating the issue, but I understand that the primary goal is to
   address the root cause.
   
   As a next step, I can add a failing unit test that captures the current
   behavior with dynamic destinations and triggering_frequency, or help
   with investigation into the finalization logic. Please let me know which
   direction would be preferred.
   



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