Github user liyinan926 commented on a diff in the pull request:

    https://github.com/apache/spark/pull/19954#discussion_r157351657
  
    --- Diff: 
resource-managers/kubernetes/core/src/main/scala/org/apache/spark/deploy/rest/k8s/KubernetesSparkDependencyDownloadInitContainer.scala
 ---
    @@ -0,0 +1,129 @@
    +/*
    + * 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.rest.k8s
    +
    +import java.io.File
    +import java.util.concurrent.TimeUnit
    +
    +import scala.concurrent.{ExecutionContext, Future}
    +import scala.concurrent.duration.Duration
    +
    +import org.apache.spark.{SecurityManager => SparkSecurityManager, 
SparkConf}
    +import org.apache.spark.deploy.SparkHadoopUtil
    +import org.apache.spark.deploy.k8s.Config._
    +import org.apache.spark.internal.Logging
    +import org.apache.spark.util.{ThreadUtils, Utils}
    +
    +/**
    + * Process that fetches files from a resource staging server and/or 
arbitrary remote locations.
    + *
    + * The init-container can handle fetching files from any of those sources, 
but not all of the
    + * sources need to be specified. This allows for composing multiple 
instances of this container
    + * with different configurations for different download sources, or using 
the same container to
    + * download everything at once.
    + */
    +private[spark] class KubernetesSparkDependencyDownloadInitContainer(
    +    sparkConf: SparkConf,
    +    fileFetcher: FileFetcher) extends Logging {
    +
    +  private implicit val downloadExecutor = 
ExecutionContext.fromExecutorService(
    +    ThreadUtils.newDaemonCachedThreadPool("download-executor"))
    +
    +  private val jarsDownloadDir = new File(
    +    sparkConf.get(JARS_DOWNLOAD_LOCATION))
    +  private val filesDownloadDir = new File(
    +    sparkConf.get(FILES_DOWNLOAD_LOCATION))
    +
    +  private val remoteJars = sparkConf.get(INIT_CONTAINER_REMOTE_JARS)
    +  private val remoteFiles = sparkConf.get(INIT_CONTAINER_REMOTE_FILES)
    +
    +  private val downloadTimeoutMinutes = 
sparkConf.get(INIT_CONTAINER_MOUNT_TIMEOUT)
    +
    +  def run(): Unit = {
    +    val remoteJarsDownload = Future[Unit] {
    +      logInfo(s"Downloading remote jars: $remoteJars")
    +      downloadFiles(
    +        remoteJars,
    +        jarsDownloadDir,
    +        s"Remote jars download directory specified at $jarsDownloadDir 
does not exist " +
    +          "or is not a directory.")
    +    }
    +    val remoteFilesDownload = Future[Unit] {
    +      logInfo(s"Downloading remote files: $remoteFiles")
    +      downloadFiles(
    +        remoteFiles,
    +        filesDownloadDir,
    +        s"Remote files download directory specified at $filesDownloadDir 
does not exist " +
    +          "or is not a directory.")
    +    }
    +    waitForFutures(
    --- End diff --
    
    Updated to create one task per file/jar to download. Regarding the type of 
thread pool, we are using a `CachedThreadPool`, which I think makes sense as it 
can be expected that the tasks are not long-lived.  


---

---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org
For additional commands, e-mail: reviews-h...@spark.apache.org

Reply via email to