wbo4958 commented on code in PR #43494: URL: https://github.com/apache/spark/pull/43494#discussion_r1369478240
########## core/src/main/scala/org/apache/spark/scheduler/ExecutorResourcesAmounts.scala: ########## @@ -0,0 +1,199 @@ +/* + * 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.scheduler + +import scala.collection.mutable.HashMap + +import org.apache.spark.SparkException +import org.apache.spark.resource.{ResourceInformation, ResourceProfile} +import org.apache.spark.resource.ResourceAmountUtils.RESOURCE_TOTAL_AMOUNT + +/** + * Class to hold information about a series of resources belonging to an executor. + * A resource could be a GPU, FPGA, etc. And it is used as a temporary + * class to calculate the resources amounts when offering resources to + * the tasks in the [[TaskSchedulerImpl]] + * + * One example is GPUs, where the addresses would be the indices of the GPUs + * + * @param resources The executor available resources and amount. eg, + * Map("gpu" -> mutable.Map("0" -> 0.2, "1" -> 1.0), + * "fpga" -> mutable.Map("a" -> 0.3, "b" -> 0.9) + * ) + */ +private[spark] class ExecutorResourcesAmounts( + private val resources: Map[String, Map[String, Double]]) extends Serializable { + + resources.foreach { case (_, addressMount) => + addressMount.foreach { case (_, amount) => assert(amount <= 1.0)}} + + // multiply the RESOURCE_TOTAL_AMOUNT to avoid using double directly. + // and convert the addressesAmounts to be mutable.HashMap + private val internalResources: Map[String, HashMap[String, Long]] = { + resources.map { case (rName, addressAmounts) => + rName -> HashMap(addressAmounts.map { case (address, amount) => + address -> (amount * RESOURCE_TOTAL_AMOUNT).toLong + }.toSeq: _*) + } + } + + // It maps from the resource name to its amount. + lazy val resourceAmount: Map[String, Int] = internalResources.map { case (rName, addressMap) => + rName -> addressMap.size + } + + // convert internal resources back to the public. + def availableResources: Map[String, Map[String, Double]] = { + internalResources.map { case (rName, addressMap) => + rName -> addressMap.map { case (address, amount) => + address -> amount.toDouble / RESOURCE_TOTAL_AMOUNT + }.toMap + } + } + + // Acquire the resource and update the resource + def acquire(assignedResource: Map[String, Map[String, Double]]): Unit = { + assignedResource.foreach { case (rName, taskResAmounts) => + val availableResourceAmounts = internalResources.getOrElse(rName, + throw new SparkException(s"Try to acquire an address from $rName that doesn't exist")) + taskResAmounts.foreach { case (address, amount) => + val prevInternalTotalAmount = availableResourceAmounts.getOrElse(address, + throw new SparkException(s"Try to acquire an address that doesn't exist. $rName " + + s"address $address doesn't exist.")) + + val internalTaskAmount = (amount * RESOURCE_TOTAL_AMOUNT).toLong + val internalLeft = prevInternalTotalAmount - internalTaskAmount + val realLeft = internalLeft.toDouble / RESOURCE_TOTAL_AMOUNT + if (realLeft < 0) { + throw new SparkException(s"The total amount ${realLeft} " + + s"after acquiring $rName address $address should be >= 0") + } + internalResources(rName)(address) = internalLeft + // scalastyle:off println Review Comment: I will remove the debug log in the next commit ########## core/src/main/scala/org/apache/spark/scheduler/ExecutorResourcesAmounts.scala: ########## @@ -0,0 +1,199 @@ +/* + * 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.scheduler + +import scala.collection.mutable.HashMap + +import org.apache.spark.SparkException +import org.apache.spark.resource.{ResourceInformation, ResourceProfile} +import org.apache.spark.resource.ResourceAmountUtils.RESOURCE_TOTAL_AMOUNT + +/** + * Class to hold information about a series of resources belonging to an executor. + * A resource could be a GPU, FPGA, etc. And it is used as a temporary + * class to calculate the resources amounts when offering resources to + * the tasks in the [[TaskSchedulerImpl]] + * + * One example is GPUs, where the addresses would be the indices of the GPUs + * + * @param resources The executor available resources and amount. eg, + * Map("gpu" -> mutable.Map("0" -> 0.2, "1" -> 1.0), + * "fpga" -> mutable.Map("a" -> 0.3, "b" -> 0.9) + * ) + */ +private[spark] class ExecutorResourcesAmounts( + private val resources: Map[String, Map[String, Double]]) extends Serializable { + + resources.foreach { case (_, addressMount) => + addressMount.foreach { case (_, amount) => assert(amount <= 1.0)}} + + // multiply the RESOURCE_TOTAL_AMOUNT to avoid using double directly. + // and convert the addressesAmounts to be mutable.HashMap + private val internalResources: Map[String, HashMap[String, Long]] = { + resources.map { case (rName, addressAmounts) => + rName -> HashMap(addressAmounts.map { case (address, amount) => + address -> (amount * RESOURCE_TOTAL_AMOUNT).toLong + }.toSeq: _*) + } + } + + // It maps from the resource name to its amount. + lazy val resourceAmount: Map[String, Int] = internalResources.map { case (rName, addressMap) => + rName -> addressMap.size + } + + // convert internal resources back to the public. + def availableResources: Map[String, Map[String, Double]] = { + internalResources.map { case (rName, addressMap) => + rName -> addressMap.map { case (address, amount) => + address -> amount.toDouble / RESOURCE_TOTAL_AMOUNT + }.toMap + } + } + + // Acquire the resource and update the resource + def acquire(assignedResource: Map[String, Map[String, Double]]): Unit = { + assignedResource.foreach { case (rName, taskResAmounts) => + val availableResourceAmounts = internalResources.getOrElse(rName, + throw new SparkException(s"Try to acquire an address from $rName that doesn't exist")) + taskResAmounts.foreach { case (address, amount) => + val prevInternalTotalAmount = availableResourceAmounts.getOrElse(address, + throw new SparkException(s"Try to acquire an address that doesn't exist. $rName " + + s"address $address doesn't exist.")) + + val internalTaskAmount = (amount * RESOURCE_TOTAL_AMOUNT).toLong + val internalLeft = prevInternalTotalAmount - internalTaskAmount + val realLeft = internalLeft.toDouble / RESOURCE_TOTAL_AMOUNT + if (realLeft < 0) { + throw new SparkException(s"The total amount ${realLeft} " + + s"after acquiring $rName address $address should be >= 0") + } + internalResources(rName)(address) = internalLeft + // scalastyle:off println + println(s"Acquired. left ${realLeft}") + // scalastyle:on println + } + } + } + + // release the resources and update the values + def release(assignedResource: Map[String, Map[String, Double]]): Unit = { + assignedResource.foreach { case (rName, taskResAmounts) => + val availableResourceAmounts = internalResources.getOrElse(rName, + throw new SparkException(s"Try to release an address from $rName that doesn't exist")) + taskResAmounts.foreach { case (address, amount) => + val prevInternalTotalAmount = availableResourceAmounts.getOrElse(address, + throw new SparkException(s"Try to release an address that is not assigned. $rName " + + s"address $address is not assigned.")) + val internalTaskAmount = (amount * RESOURCE_TOTAL_AMOUNT).toLong + val internalTotal = prevInternalTotalAmount + internalTaskAmount + if (internalTotal > RESOURCE_TOTAL_AMOUNT) { + throw new SparkException(s"The total amount " + + s"${internalTotal.toDouble / RESOURCE_TOTAL_AMOUNT} " + + s"after releasing $rName address $address should be <= 1.0") + } + internalResources(rName)(address) = internalTotal + // scalastyle:off println Review Comment: I will remove the debug log in the next commit -- This is an automated message from the Apache Git Service. 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