Github user kayousterhout commented on a diff in the pull request:
https://github.com/apache/spark/pull/900#discussion_r14033313
--- Diff:
yarn/common/src/main/scala/org/apache/spark/scheduler/cluster/YarnClusterSchedulerBackend.scala
---
@@ -0,0 +1,51 @@
+/*
+ * 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.cluster
+
+
+import org.apache.spark.{Logging, SparkContext}
+import org.apache.spark.deploy.yarn.ApplicationMasterArguments
+import org.apache.spark.scheduler.TaskSchedulerImpl
+
+import scala.collection.mutable.ArrayBuffer
+
+private[spark] class YarnClusterSchedulerBackend(
+ scheduler: TaskSchedulerImpl,
+ sc: SparkContext)
+ extends CoarseGrainedSchedulerBackend(scheduler, sc.env.actorSystem)
+ with Logging {
+
+ private[spark] def addArg(optionName: String, envVar: String, sysProp:
String,
+ arrayBuf: ArrayBuffer[String]) {
+ if (System.getenv(envVar) != null) {
+ arrayBuf += (optionName, System.getenv(envVar))
+ } else if (sc.getConf.contains(sysProp)) {
+ arrayBuf += (optionName, sc.getConf.get(sysProp))
+ }
+ }
+
+ override def start() {
+ super.start()
+ val argsArrayBuf = new ArrayBuffer[String]()
+ List(("--num-executors", "SPARK_EXECUTOR_INSTANCES",
"spark.executor.instances"),
+ ("--num-executors", "SPARK_WORKER_INSTANCES",
"spark.worker.instances"))
+ .foreach { case (optName, envVar, sysProp) => addArg(optName,
envVar, sysProp, argsArrayBuf) }
+ val args = new ApplicationMasterArguments(argsArrayBuf.toArray)
+ totalExecutors.set(args.numExecutors)
--- End diff --
I'm a little confused here -- is the point of this code just to set
CoarseGrainedSchedulerBackend.totalExecutors? Why do you check both
SPARK_WORKER_INSTANCES and SPARK_EXECUTOR_INSTANCES to set the number of
executors? Don't these mean different things?
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at [email protected] or file a JIRA ticket
with INFRA.
---
