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[SPARK-59458][YARN] Fix 'propogate' typos in YarnAllocator comments #58757

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[SPARK-59458][YARN] Fix 'propogate' typos in YarnAllocator comments #58757

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6 changes: 3 additions & 3 deletions resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocator.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -329,21 +329,21 @@ private[yarn] class YarnAllocator(
// to request YARN containers with extra resources without Spark scheduling on
// them, the user can specify resources via the <code>spark.yarn.executor.resource.</code>
// config. Those configs are only used in the base default profile though and do
// not get propogated into any other custom ResourceProfiles. This is because
// not get propagated into any other custom ResourceProfiles. This is because
// there would be no way to remove them if you wanted a stage to not have them.
// This results in your default profile getting custom resources defined in
// <code>spark.yarn.executor.resource.</code> plus spark defined resources of
// GPU or FPGA. Spark converts GPU and FPGA resources into the YARN built in
// types <code>yarn.io/gpu</code>) and <code>yarn.io/fpga</code>, but does not

@dongjoon-hyun dongjoon-hyun Sep 14, 2026

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nit. There is an unmatched ) here.

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// types <code>yarn.io/gpu</code>) and <code>yarn.io/fpga</code>, but does not
// types <code>yarn.io/gpu</code> and <code>yarn.io/fpga</code>, but does not

// know the mapping of any other resources. Any other Spark custom resources
// are not propogated to YARN for the default profile. So if you want Spark
// are not propagated to YARN for the default profile. So if you want Spark
// to schedule based off a custom resource and have it requested from YARN, you
// must specify it in both YARN (<code>spark.yarn.{driver/executor}.resource.</code>)
// and Spark (<code>spark.{driver/executor}.resource.</code>) configs. Leave the Spark
// config off if you only want YARN containers with the extra resources but Spark not to
// schedule using them. Now for custom ResourceProfiles, it doesn't currently have a way
// to only specify YARN resources without Spark scheduling off of them. This means for
// custom ResourceProfiles we propogate all the resources defined in the ResourceProfile
// custom ResourceProfiles we propagate all the resources defined in the ResourceProfile
// to YARN. We still convert GPU and FPGA to the YARN build in types as well. This requires

@dongjoon-hyun dongjoon-hyun Sep 14, 2026

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nit. build in -> built in (like line 336)

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// to YARN. We still convert GPU and FPGA to the YARN build in types as well. This requires
// to YARN. We still convert GPU and FPGA to the YARN built in types as well. This requires

// that the name of any custom resources you specify match what they are defined as in YARN.
val customResources = if (rp.id == DEFAULT_RESOURCE_PROFILE_ID) {
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