Implement Andrew's suggestion (import foo.config._).

A little bit noisier since package objects cannot be `private[foo]`,
apparently.

core/src/main/scala/org/apache/spark/config/package.scala

@@ -0,0 +1,79 @@
+/*
+ * 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
+
+import org.apache.spark.launcher.SparkLauncher
+
+package object config {
+  import ConfigEntry._
+
+  private[spark] val DRIVER_CLASS_PATH = stringConf(SparkLauncher.DRIVER_EXTRA_CLASSPATH)
+    .optional
+
+  private[spark] val DRIVER_JAVA_OPTIONS = stringConf(SparkLauncher.DRIVER_EXTRA_JAVA_OPTIONS)
+    .optional
+
+  private[spark] val DRIVER_LIBRARY_PATH = stringConf(SparkLauncher.DRIVER_EXTRA_LIBRARY_PATH)
+    .optional
+
+  private[spark] val DRIVER_USER_CLASS_PATH_FIRST = booleanConf("spark.driver.userClassPathFirst",
+    defaultValue = Some(false))
+
+  private[spark] val EXECUTOR_CLASS_PATH = stringConf(SparkLauncher.EXECUTOR_EXTRA_CLASSPATH)
+    .optional
+
+  private[spark] val EXECUTOR_JAVA_OPTIONS = stringConf(SparkLauncher.EXECUTOR_EXTRA_JAVA_OPTIONS)
+    .optional
+
+  private[spark] val EXECUTOR_LIBRARY_PATH = stringConf(SparkLauncher.EXECUTOR_EXTRA_LIBRARY_PATH)
+    .optional
+
+  private[spark] val EXECUTOR_USER_CLASS_PATH_FIRST =
+    booleanConf("spark.executor.userClassPathFirst", defaultValue = Some(false))
+
+  private[spark] val IS_PYTHON_APP = booleanConf("spark.yarn.isPython",
+    defaultValue = Some(false),
+    isPublic = false)
+
+  private[spark] val CPUS_PER_TASK = intConf("spark.task.cpus",
+    defaultValue = Some(1))
+
+  private[spark] val DYN_ALLOCATION_MIN_EXECUTORS = intConf("spark.dynamicAllocation.minExecutors",
+    defaultValue = Some(0))
+
+  private[spark] val DYN_ALLOCATION_INITIAL_EXECUTORS =
+    fallbackConf("spark.dynamicAllocation.initialExecutors",
+      fallback = DYN_ALLOCATION_MIN_EXECUTORS)
+
+  private[spark] val DYN_ALLOCATION_MAX_EXECUTORS = intConf("spark.dynamicAllocation.maxExecutors",
+    defaultValue = Some(Int.MaxValue))
+
+  private[spark] val SHUFFLE_SERVICE_ENABLED = booleanConf("spark.shuffle.service.enabled",
+    defaultValue = Some(false))
+
+  private[spark] val KEYTAB = stringConf("spark.yarn.keytab",
+    doc = "Location of user's keytab.")
+    .optional
+
+  private[spark] val PRINCIPAL = stringConf("spark.yarn.principal",
+    doc = "Name of the Kerberos principal.")
+    .optional
+
+  private[spark] val EXECUTOR_INSTANCES = intConf("spark.executor.instances").optional
+
+}

yarn/src/main/scala/org/apache/spark/deploy/yarn/AMDelegationTokenRenewer.scala

@@ -27,7 +27,8 @@ import org.apache.hadoop.security.UserGroupInformation
 import org.apache.spark.deploy.SparkHadoopUtil
 
 import org.apache.spark.{Logging, SparkConf}
-import org.apache.spark.config.CoreConfigKeys._
+import org.apache.spark.config._
+import org.apache.spark.deploy.yarn.config._
 import org.apache.spark.util.ThreadUtils
 
 /*
@@ -53,8 +54,6 @@ private[yarn] class AMDelegationTokenRenewer(
     sparkConf: SparkConf,
     hadoopConf: Configuration) extends Logging {
 
-  import YarnConfigKeys._
-
   private var lastCredentialsFileSuffix = 0
 
   private val delegationTokenRenewer =

yarn/src/main/scala/org/apache/spark/deploy/yarn/ApplicationMaster.scala

@@ -32,9 +32,10 @@ import org.apache.hadoop.yarn.conf.YarnConfiguration
 import org.apache.spark.rpc._
 import org.apache.spark.{Logging, SecurityManager, SparkConf, SparkContext, SparkEnv,
   SparkException, SparkUserAppException}
-import org.apache.spark.config.CoreConfigKeys._
+import org.apache.spark.config._
 import org.apache.spark.deploy.SparkHadoopUtil
 import org.apache.spark.deploy.history.HistoryServer
+import org.apache.spark.deploy.yarn.config._
 import org.apache.spark.scheduler.cluster.{CoarseGrainedSchedulerBackend, YarnSchedulerBackend}
 import org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages._
 import org.apache.spark.util._
@@ -47,8 +48,6 @@ private[spark] class ApplicationMaster(
     client: YarnRMClient)
   extends Logging {
 
-  import YarnConfigKeys._
-
   // Load the properties file with the Spark configuration and set entries as system properties,
   // so that user code run inside the AM also has access to them.
   if (args.propertiesFile != null) {

yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala

@@ -55,9 +55,10 @@ import org.apache.hadoop.yarn.exceptions.ApplicationNotFoundException
 import org.apache.hadoop.yarn.util.Records
 
 import org.apache.spark.{Logging, SecurityManager, SparkConf, SparkContext, SparkException}
-import org.apache.spark.config.CoreConfigKeys._
-import org.apache.spark.launcher.{LauncherBackend, SparkAppHandle, YarnCommandBuilderUtils}
+import org.apache.spark.config._
 import org.apache.spark.deploy.SparkHadoopUtil
+import org.apache.spark.deploy.yarn.config._
+import org.apache.spark.launcher.{LauncherBackend, SparkAppHandle, YarnCommandBuilderUtils}
 import org.apache.spark.util.Utils
 
 private[spark] class Client(
@@ -67,7 +68,6 @@ private[spark] class Client(
   extends Logging {
 
   import Client._
-  import YarnConfigKeys._
 
   def this(clientArgs: ClientArguments, spConf: SparkConf) =
     this(clientArgs, SparkHadoopUtil.get.newConfiguration(spConf), spConf)
@@ -1043,8 +1043,6 @@ private[spark] class Client(
 
 object Client extends Logging {
 
-  import YarnConfigKeys._
-
   def main(argStrings: Array[String]) {
     if (!sys.props.contains("SPARK_SUBMIT")) {
       logWarning("WARNING: This client is deprecated and will be removed in a " +

yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala

@@ -20,17 +20,16 @@ package org.apache.spark.deploy.yarn
 import scala.collection.mutable.ArrayBuffer
 
 import org.apache.spark.{SparkConf, SparkException}
-import org.apache.spark.config.CoreConfigKeys._
+import org.apache.spark.config._
 import org.apache.spark.deploy.yarn.YarnSparkHadoopUtil._
+import org.apache.spark.deploy.yarn.config._
 import org.apache.spark.util.{IntParam, MemoryParam, Utils}
 
 // TODO: Add code and support for ensuring that yarn resource 'tasks' are location aware !
 private[spark] class ClientArguments(
     args: Array[String],
     sparkConf: SparkConf) {
 
-  import YarnConfigKeys._
-
   var addJars: String = null
   var files: String = null
   var archives: String = null

yarn/src/main/scala/org/apache/spark/deploy/yarn/ExecutorDelegationTokenUpdater.scala

@@ -24,6 +24,7 @@ import org.apache.hadoop.security.{Credentials, UserGroupInformation}
 
 import org.apache.spark.deploy.SparkHadoopUtil
 import org.apache.spark.{Logging, SparkConf}
+import org.apache.spark.deploy.yarn.config._
 import org.apache.spark.util.{ThreadUtils, Utils}
 
 import scala.util.control.NonFatal
@@ -34,7 +35,7 @@ private[spark] class ExecutorDelegationTokenUpdater(
 
   @volatile private var lastCredentialsFileSuffix = 0
 
-  private val credentialsFile = sparkConf.get(YarnConfigKeys.CREDENTIALS_FILE_PATH)
+  private val credentialsFile = sparkConf.get(CREDENTIALS_FILE_PATH)
   private val freshHadoopConf =
     SparkHadoopUtil.get.getConfBypassingFSCache(
       hadoopConf, new Path(credentialsFile).toUri.getScheme)

yarn/src/main/scala/org/apache/spark/deploy/yarn/ExecutorRunnable.scala

@@ -38,7 +38,8 @@ import org.apache.hadoop.yarn.ipc.YarnRPC
 import org.apache.hadoop.yarn.util.{ConverterUtils, Records}
 
 import org.apache.spark.{Logging, SecurityManager, SparkConf, SparkException}
-import org.apache.spark.config.CoreConfigKeys._
+import org.apache.spark.config._
+import org.apache.spark.deploy.yarn.config._
 import org.apache.spark.launcher.YarnCommandBuilderUtils
 import org.apache.spark.network.util.JavaUtils
 import org.apache.spark.util.Utils
@@ -56,8 +57,6 @@ private[yarn] class ExecutorRunnable(
     securityMgr: SecurityManager)
   extends Runnable with Logging {
 
-  import YarnConfigKeys._
-
   var rpc: YarnRPC = YarnRPC.create(conf)
   var nmClient: NMClient = _
   val yarnConf: YarnConfiguration = new YarnConfiguration(conf)

yarn/src/main/scala/org/apache/spark/deploy/yarn/LocalityPreferredContainerPlacementStrategy.scala

@@ -26,7 +26,7 @@ import org.apache.hadoop.yarn.client.api.AMRMClient.ContainerRequest
 import org.apache.hadoop.yarn.util.RackResolver
 
 import org.apache.spark.SparkConf
-import org.apache.spark.config.CoreConfigKeys
+import org.apache.spark.config._
 
 private[yarn] case class ContainerLocalityPreferences(nodes: Array[String], racks: Array[String])
 
@@ -85,9 +85,6 @@ private[yarn] class LocalityPreferredContainerPlacementStrategy(
     val yarnConf: Configuration,
     val resource: Resource) {
 
-  // Number of CPUs per task
-  private val CPUS_PER_TASK = sparkConf.get(CoreConfigKeys.CPUS_PER_TASK)
-
   /**
    * Calculate each container's node locality and rack locality
    * @param numContainer number of containers to calculate
@@ -160,7 +157,7 @@ private[yarn] class LocalityPreferredContainerPlacementStrategy(
    */
   private def numExecutorsPending(numTasksPending: Int): Int = {
     val coresPerExecutor = resource.getVirtualCores
-    (numTasksPending * CPUS_PER_TASK + coresPerExecutor - 1) / coresPerExecutor
+    (numTasksPending * sparkConf.get(CPUS_PER_TASK) + coresPerExecutor - 1) / coresPerExecutor
   }
 
   /**

yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocator.scala

@@ -35,6 +35,7 @@ import org.apache.log4j.{Level, Logger}
 
 import org.apache.spark.{Logging, SecurityManager, SparkConf, SparkException}
 import org.apache.spark.deploy.yarn.YarnSparkHadoopUtil._
+import org.apache.spark.deploy.yarn.config._
 import org.apache.spark.rpc.{RpcCallContext, RpcEndpointRef}
 import org.apache.spark.scheduler.{ExecutorExited, ExecutorLossReason}
 import org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RemoveExecutor
@@ -65,7 +66,6 @@ private[yarn] class YarnAllocator(
   extends Logging {
 
   import YarnAllocator._
-  import YarnConfigKeys._
 
   // RackResolver logs an INFO message whenever it resolves a rack, which is way too often.
   if (Logger.getLogger(classOf[RackResolver]).getLevel == null) {