mridulm commented on a change in pull request #34485:
URL: https://github.com/apache/spark/pull/34485#discussion_r743377519
##########
File path: docs/running-on-yarn.md
##########
@@ -205,6 +205,28 @@ To use a custom metrics.properties for the application
master and executors, upd
</td>
<td>3.0.0</td>
</tr>
+<tr>
+ <td><code>spark.yarn.resourceGpuDeviceName</code></td>
+ <td><code>yarn.io/gpu</code></td>
+ <td>
+ Specify the mapping of the Spark resource type of <code>gpu</code> to the
YARN resource
+ representing a GPU. By default YARN uses <code>yarn.io/gpu</code> but if
YARN has been
+ configured with a custom resource type, this allows remapping it.
+ Applies when using the <code>spark.{driver/executor}.resource.gpu.*</code>
configs.
+ </td>
+ <td>3.2.1</td>
+</tr>
+<tr>
+ <td><code>spark.yarn.resourceFpgaDeviceName</code></td>
+ <td><code>yarn.io/fpga</code></td>
+ <td>
+ Specify the mapping of the Spark resource type of <code>fpga</code> to the
YARN resource
+ representing a FPGA. By default YARN uses <code>yarn.io/fpga</code> but if
YARN has been
+ configured with a custom resource type, this allows remapping it.
+ Applies when using the
<code>spark.{driver/executor}.resource.fpga.*</code> configs.
+ </td>
+ <td>3.2.1</td>
Review comment:
Is this targetting 3.2.1 ? Or master ?
##########
File path:
resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocator.scala
##########
@@ -281,7 +281,7 @@ private[yarn] class YarnAllocator(
val resourcesWithDefaults =
ResourceProfile.getResourcesForClusterManager(rp.id,
rp.executorResources,
MEMORY_OVERHEAD_FACTOR, sparkConf, isPythonApp,
- ResourceRequestHelper.resourceNameMapping)
+ ResourceRequestHelper.getResourceNameMapping(sparkConf))
Review comment:
nit: Given this should not change, do we want to make it a field and
reference that here ?
##########
File path: docs/running-on-yarn.md
##########
@@ -205,6 +205,28 @@ To use a custom metrics.properties for the application
master and executors, upd
</td>
<td>3.0.0</td>
</tr>
+<tr>
+ <td><code>spark.yarn.resourceGpuDeviceName</code></td>
+ <td><code>yarn.io/gpu</code></td>
+ <td>
+ Specify the mapping of the Spark resource type of <code>gpu</code> to the
YARN resource
+ representing a GPU. By default YARN uses <code>yarn.io/gpu</code> but if
YARN has been
+ configured with a custom resource type, this allows remapping it.
+ Applies when using the <code>spark.{driver/executor}.resource.gpu.*</code>
configs.
+ </td>
+ <td>3.2.1</td>
+</tr>
+<tr>
+ <td><code>spark.yarn.resourceFpgaDeviceName</code></td>
+ <td><code>yarn.io/fpga</code></td>
+ <td>
+ Specify the mapping of the Spark resource type of <code>fpga</code> to the
YARN resource
+ representing a FPGA. By default YARN uses <code>yarn.io/fpga</code> but if
YARN has been
+ configured with a custom resource type, this allows remapping it.
+ Applies when using the
<code>spark.{driver/executor}.resource.fpga.*</code> configs.
+ </td>
+ <td>3.2.1</td>
Review comment:
Given the scope of the change, and given it is backwardly compatible, I
am fine with adding to 3.2.1 as well.
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