Github user mridulm commented on a diff in the pull request:
https://github.com/apache/spark/pull/19468#discussion_r147014641
--- Diff:
resource-managers/kubernetes/core/src/main/scala/org/apache/spark/scheduler/cluster/k8s/ExecutorPodFactory.scala
---
@@ -0,0 +1,229 @@
+/*
+ * 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.k8s
+
+import scala.collection.JavaConverters._
+
+import io.fabric8.kubernetes.api.model._
+
+import org.apache.spark.{SparkConf, SparkException}
+import org.apache.spark.deploy.k8s.ConfigurationUtils
+import org.apache.spark.deploy.k8s.config._
+import org.apache.spark.deploy.k8s.constants._
+import org.apache.spark.util.Utils
+
+/**
+ * Configures executor pods. Construct one of these with a SparkConf to
set up properties that are
+ * common across all executors. Then, pass in dynamic parameters into
createExecutorPod.
+ */
+private[spark] trait ExecutorPodFactory {
+ def createExecutorPod(
+ executorId: String,
+ applicationId: String,
+ driverUrl: String,
+ executorEnvs: Seq[(String, String)],
+ driverPod: Pod,
+ nodeToLocalTaskCount: Map[String, Int]): Pod
+}
+
+private[spark] class ExecutorPodFactoryImpl(sparkConf: SparkConf)
+ extends ExecutorPodFactory {
+
+ import ExecutorPodFactoryImpl._
+
+ private val executorExtraClasspath = sparkConf.get(
+ org.apache.spark.internal.config.EXECUTOR_CLASS_PATH)
+ private val executorJarsDownloadDir =
sparkConf.get(INIT_CONTAINER_JARS_DOWNLOAD_LOCATION)
+
+ private val executorLabels =
ConfigurationUtils.parsePrefixedKeyValuePairs(
+ sparkConf,
+ KUBERNETES_EXECUTOR_LABEL_PREFIX,
+ "executor label")
+ require(
+ !executorLabels.contains(SPARK_APP_ID_LABEL),
+ s"Custom executor labels cannot contain $SPARK_APP_ID_LABEL as it is
reserved for Spark.")
+ require(
+ !executorLabels.contains(SPARK_EXECUTOR_ID_LABEL),
+ s"Custom executor labels cannot contain $SPARK_EXECUTOR_ID_LABEL as it
is reserved for" +
+ s" Spark.")
+
+ private val executorAnnotations =
+ ConfigurationUtils.parsePrefixedKeyValuePairs(
+ sparkConf,
+ KUBERNETES_EXECUTOR_ANNOTATION_PREFIX,
+ "executor annotation")
+ private val nodeSelector =
+ ConfigurationUtils.parsePrefixedKeyValuePairs(
+ sparkConf,
+ KUBERNETES_NODE_SELECTOR_PREFIX,
+ "node selector")
+
+ private val executorDockerImage = sparkConf.get(EXECUTOR_DOCKER_IMAGE)
+ private val dockerImagePullPolicy =
sparkConf.get(DOCKER_IMAGE_PULL_POLICY)
+ private val executorPort = sparkConf.getInt("spark.executor.port",
DEFAULT_STATIC_PORT)
+ private val blockmanagerPort = sparkConf
+ .getInt("spark.blockmanager.port", DEFAULT_BLOCKMANAGER_PORT)
--- End diff --
Sounds good, I wanted to make sure I understood it right that we are making
the assumption about port being unbound and available for spark.
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