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Posted to github@datafusion.apache.org by "comphead (via GitHub)" <gi...@apache.org> on 2026/06/04 23:43:17 UTC

[PR] chore: document programmatic access to Comet fallback reasons [datafusion-comet]

comphead opened a new pull request, #4597:
URL: https://github.com/apache/datafusion-comet/pull/4597

   ## Which issue does this PR close?
   
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   ## Rationale for this change
   
   The Understanding Comet Plans guide covers the four configs that route fallback reasons to logs or the SQL UI, but it does not mention that `org.apache.comet.ExtendedExplainInfo` can be called directly. 
   That API is the only way to read fallback reasons as data - needed for tests asserting on fallback behavior, custom diagnostics. This adds a short section showing getFallbackReasons and generateExtendedInfo with the gotchas (must use executedPlan; empty result means accelerated, not failed).
     
   
   
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Re: [PR] chore: document programmatic access to Comet fallback reasons [datafusion-comet]

Posted by "comphead (via GitHub)" <gi...@apache.org>.
comphead merged PR #4597:
URL: https://github.com/apache/datafusion-comet/pull/4597


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Re: [PR] chore: document programmatic access to Comet fallback reasons [datafusion-comet]

Posted by "mbutrovich (via GitHub)" <gi...@apache.org>.
mbutrovich commented on code in PR #4597:
URL: https://github.com/apache/datafusion-comet/pull/4597#discussion_r3363085583


##########
docs/source/user-guide/latest/understanding-comet-plans.md:
##########
@@ -138,6 +138,51 @@ operators were arranged after Comet's serialization). See the
 [Metrics Guide](metrics.md) for details on the native metrics that appear in
 this output.
 
+## Programmatic Access to Fallback Reasons
+
+The configs above route fallback reasons to logs or the SQL UI. If you want
+the reasons for a specific query as data — for example, to assert in a test
+or to drive a custom report — use `org.apache.comet.ExtendedExplainInfo`
+directly. It is the same class that backs `spark.comet.explain.format`, and
+it works on any Spark version because it does not rely on the Spark 4.0

Review Comment:
   ```suggestion
   it works on any supported Spark version because it does not rely on the Spark 4.0+
   ```



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