Github user szyszy commented on a diff in the pull request:
https://github.com/apache/spark/pull/20761#discussion_r189881753
--- Diff:
resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/ResourceTypeHelper.scala
---
@@ -0,0 +1,180 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.deploy.yarn
+
+import java.lang.reflect.InvocationTargetException
+
+import scala.util.control.NonFatal
+
+import org.apache.hadoop.yarn.api.records.Resource
+
+import org.apache.spark.internal.Logging
+import org.apache.spark.util.Utils
+
+/**
+ * This helper class uses some of Hadoop 3 methods from the yarn API,
+ * so we need to use reflection to avoid compile error when building
against Hadoop 2.x
+ */
+object ResourceTypeHelper extends Logging {
+ private val AMOUNT_AND_UNIT_REGEX = "([0-9]+)([A-Za-z]*)".r
+ private val resourceTypesNotAvailableErrorMessage =
+ "Ignoring updating resource with resource types because " +
+ "the version of YARN does not support it!"
+
+ def setResourceInfoFromResourceTypes(
+ resourceTypesParam: Map[String, String],
+ resource: Resource): Resource = {
+ if (resource == null) {
+ throw new IllegalArgumentException("Resource parameter should not be
null!")
+ }
+
+ if (!ResourceTypeHelper.isYarnResourceTypesAvailable()) {
+ logWarning(resourceTypesNotAvailableErrorMessage)
+ return resource
+ }
+
+ val resourceTypes = resourceTypesParam.map { case (k, v) => (
+ if (k.equals("memory")) {
+ logWarning("Trying to use 'memory' as a custom resource, converted
it to 'memory-mb'")
+ "memory-mb"
+ } else k, v)
+ }
+
+ logDebug(s"Custom resource types: $resourceTypes")
+ resourceTypes.foreach { rt =>
+ val resourceName: String = rt._1
+ val (amount, unit) = getAmountAndUnit(rt._2)
+ logDebug(s"Registering resource with name: $resourceName, amount:
$amount, unit: $unit")
+
+ try {
+ val resInfoClass = Utils.classForName(
+ "org.apache.hadoop.yarn.api.records.ResourceInformation")
+ val setResourceInformationMethod =
+ resource.getClass.getMethod("setResourceInformation",
classOf[String],
+ resInfoClass)
+
+ val resourceInformation =
+ createResourceInformation(resourceName, amount, unit,
resInfoClass)
+ setResourceInformationMethod.invoke(resource, resourceName,
resourceInformation)
+ } catch {
+ case e: InvocationTargetException =>
+ if (e.getCause != null) {
+ throw e.getCause
+ } else {
+ throw e
+ }
+ case NonFatal(e) =>
+ logWarning(resourceTypesNotAvailableErrorMessage, e)
+ }
+ }
+ resource
+ }
+
+ def getCustomResourcesAsStrings(resource: Resource): String = {
+ if (resource == null) {
+ throw new IllegalArgumentException("Resource parameter should not be
null!")
+ }
+
+ if (!ResourceTypeHelper.isYarnResourceTypesAvailable()) {
+ logWarning(resourceTypesNotAvailableErrorMessage)
+ return ""
+ }
+
+ var res: String = ""
+ try {
+ val resUtilsClass = Utils.classForName(
+ "org.apache.hadoop.yarn.util.resource.ResourceUtils")
+ val getNumberOfResourceTypesMethod =
resUtilsClass.getMethod("getNumberOfKnownResourceTypes")
+ val numberOfResourceTypes: Int =
getNumberOfResourceTypesMethod.invoke(null).asInstanceOf[Int]
+ val resourceClass = Utils.classForName(
+ "org.apache.hadoop.yarn.api.records.Resource")
+
+ // skip memory and vcores (index 0 and 1)
+ for (i <- 2 until numberOfResourceTypes) {
+ val getResourceInfoMethod =
resourceClass.getMethod("getResourceInformation",
+ classOf[Int])
+ res ++= getResourceInfoMethod.invoke(resource,
i.asInstanceOf[AnyRef]).toString()
+ }
+ } catch {
+ case e: InvocationTargetException =>
+ if (e.getCause != null) {
+ throw e.getCause
+ } else {
+ throw e
+ }
+ case NonFatal(e) =>
+ logWarning(resourceTypesNotAvailableErrorMessage, e)
+
+ }
+ res
+ }
+
+ def getAmountAndUnit(s: String): (Long, String) = {
+ try {
+ val AMOUNT_AND_UNIT_REGEX(amount, unit) = s
+ (amount.toLong, convertToYarnResourceFormat(unit))
+ } catch {
+ case _: MatchError => throw new IllegalArgumentException(
+ s"Value of resource type should match pattern
$AMOUNT_AND_UNIT_REGEX, unmatched value: $s")
+ }
+ }
+
+ def convertToYarnResourceFormat(unit: String): String = {
--- End diff --
According to the Resource Model documentation page of YARN, for every new
custom resource type, the specified units in the table are available.
I see your concern, but I don't know how to resolve this situation as Spark
uses m and M for Mega unit. How would I differentiate this from micro?
Suppose someone defines a new resource type (countable) that could have
units of mega and giga, and someone requests 2g of that resource.
If the unit is used as is, YARN cannot understand it as g is not a valid
unit.
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