You are viewing a plain text version of this content. The canonical link for it is here.
Posted to reviews@spark.apache.org by vanzin <gi...@git.apache.org> on 2018/08/21 19:40:08 UTC
[GitHub] spark pull request #20761: [SPARK-20327][CORE][YARN] Add CLI support for YAR...
Github user vanzin commented on a diff in the pull request:
https://github.com/apache/spark/pull/20761#discussion_r211733592
--- Diff: resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/ResourceTypeValidator.scala ---
@@ -0,0 +1,185 @@
+/*
+ * 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 scala.collection.mutable
+
+import org.apache.spark.{SparkConf, SparkException}
+import org.apache.spark.deploy.yarn.ProcessType.{am, driver, executor, ProcessType}
+import org.apache.spark.deploy.yarn.ResourceType.{cores, memory, ResourceType}
+import org.apache.spark.deploy.yarn.RunMode.{client, cluster, RunMode}
+import org.apache.spark.deploy.yarn.config._
+import org.apache.spark.internal.config._
+
+private[spark] object ProcessType extends Enumeration {
+ type ProcessType = Value
+ val driver, executor, am = Value
+}
+
+private[spark] object RunMode extends Enumeration {
+ type RunMode = Value
+ val client, cluster = Value
+}
+
+private[spark] object ResourceType extends Enumeration {
+ type ResourceType = Value
+ val cores, memory = Value
+}
+
+private object ResourceTypeValidator {
+ private val ERROR_PREFIX: String = "Error: "
+ private val POSSIBLE_RESOURCE_DEFINITIONS = Seq[ResourceConfigProperties](
+ new ResourceConfigProperties(am, client, memory),
+ new ResourceConfigProperties(am, client, cores),
+ new ResourceConfigProperties(driver, cluster, memory),
+ new ResourceConfigProperties(driver, cluster, cores),
+ new ResourceConfigProperties(processType = executor, resourceType = memory),
+ new ResourceConfigProperties(processType = executor, resourceType = cores))
+
+ /**
+ * Validates sparkConf and throws a SparkException if a standard resource (memory or cores)
+ * is defined with the property spark.yarn.x.resource.y<br>
+ *
+ * Example of an invalid config:<br>
+ * - spark.yarn.driver.resource.memory=2g<br>
+ *
+ * Please note that if multiple resources are defined like described above,
+ * the error messages will be concatenated.<br>
+ * Example of such a config:<br>
+ * - spark.yarn.driver.resource.memory=2g<br>
+ * - spark.yarn.executor.resource.cores=2<br>
+ * Then the following two error messages will be printed:<br>
+ * - "memory cannot be requested with config spark.yarn.driver.resource.memory,
+ * please use config spark.driver.memory instead!<br>
+ * - "cores cannot be requested with config spark.yarn.executor.resource.cores,
+ * please use config spark.executor.cores instead!<br>
+ *
+ * @param sparkConf
+ */
+ def validateResources(sparkConf: SparkConf): Unit = {
--- End diff --
You said:
> the error message points you to the right direction, explicitly printing the right config to use instead.
So does my code above, it just need to be changed a little to be more parameterized. And it's an order of magnitude smaller and simpler than your validation code.
So, same question: what else is your validator checking that those two asserts (properly parameterized to check for driver, am, or executor) do not cover?
---
---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscribe@spark.apache.org
For additional commands, e-mail: reviews-help@spark.apache.org