Github user ifilonenko commented on a diff in the pull request:
https://github.com/apache/spark/pull/13599#discussion_r195919848
--- Diff:
core/src/main/scala/org/apache/spark/api/python/VirtualEnvFactory.scala ---
@@ -0,0 +1,164 @@
+/*
+ * 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.api.python
+
+import java.io.File
+import java.util.{Map => JMap}
+import java.util.Arrays
+import java.util.concurrent.atomic.AtomicInteger
+
+import scala.collection.JavaConverters._
+
+import com.google.common.io.Files
+
+import org.apache.spark.SparkConf
+import org.apache.spark.internal.Logging
+
+
+class VirtualEnvFactory(pythonExec: String, conf: SparkConf, isDriver:
Boolean)
+ extends Logging {
+
+ private val virtualEnvType = conf.get("spark.pyspark.virtualenv.type",
"native")
+ private val virtualEnvBinPath =
conf.get("spark.pyspark.virtualenv.bin.path", "")
+ private val initPythonPackages =
conf.getOption("spark.pyspark.virtualenv.packages")
+ private var virtualEnvName: String = _
+ private var virtualPythonExec: String = _
+ private val VIRTUALENV_ID = new AtomicInteger()
+ private var isLauncher: Boolean = false
+
+ // used by launcher when user want to use virtualenv in pyspark shell.
Launcher need this class
+ // to create virtualenv for driver.
+ def this(pythonExec: String, properties: JMap[String, String], isDriver:
java.lang.Boolean) {
+ this(pythonExec, new SparkConf().setAll(properties.asScala), isDriver)
+ this.isLauncher = true
+ }
+
+ /*
+ * Create virtualenv using native virtualenv or conda
+ *
+ */
+ def setupVirtualEnv(): String = {
+ /*
+ *
+ * Native Virtualenv:
+ * - Execute command: virtualenv -p <pythonExec> --no-site-packages
<virtualenvName>
+ * - Execute command: python -m pip --cache-dir <cache-dir> install
-r <requirement_file>
+ *
+ * Conda
+ * - Execute command: conda create --prefix <prefix> --file
<requirement_file> -y
+ *
+ */
+ logInfo("Start to setup virtualenv...")
+ logDebug("user.dir=" + System.getProperty("user.dir"))
+ logDebug("user.home=" + System.getProperty("user.home"))
+
+ require(virtualEnvType == "native" || virtualEnvType == "conda",
+ s"VirtualEnvType: $virtualEnvType is not supported." )
+ require(new File(virtualEnvBinPath).exists(),
+ s"VirtualEnvBinPath: $virtualEnvBinPath is not defined or doesn't
exist.")
+ // Two scenarios of creating virtualenv:
+ // 1. created in yarn container. Yarn will clean it up after container
is exited
+ // 2. created outside yarn container. Spark need to create temp
directory and clean it after app
+ // finish.
+ // - driver of PySpark shell
+ // - driver of yarn-client mode
+ if (isLauncher ||
+ (isDriver && conf.get("spark.submit.deployMode") == "client")) {
+ val virtualenvBasedir = Files.createTempDir()
+ virtualenvBasedir.deleteOnExit()
+ virtualEnvName = virtualenvBasedir.getAbsolutePath
+ } else if (isDriver && conf.get("spark.submit.deployMode") ==
"cluster") {
+ virtualEnvName = "virtualenv_driver"
+ } else {
+ // use the working directory of Executor
+ virtualEnvName = "virtualenv_" + conf.getAppId + "_" +
VIRTUALENV_ID.getAndIncrement()
+ }
+
+ // Use the absolute path of requirement file in the following cases
+ // 1. driver of pyspark shell
+ // 2. driver of yarn-client mode
+ // otherwise just use filename as it would be downloaded to the
working directory of Executor
--- End diff --
In Kubernetes world, I might want to use a `requirements.txt` file that is
stored locally in the base docker image, regardless of client or cluster mode.
Is that something that you think should be supported? Maybe a config variable
`spark.pyspark.virtualenv.kubernetes.localrequirements` that points to a file
stored as `local:///var/files/requirements.txt` for example.
Furthermore, when we introduce a Resource Staging Server that allows us to
stage files locally, this setting will be inter-changable between something
that is locally baked in vs. staged.
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