[GitHub] [spark] rangadi commented on a diff in pull request #42035: [SPARK-42944][SS][PYTHON] Streaming ForeachBatch in Python

["rangadi (via GitHub)" <gi...@apache.org>]

rangadi commented on code in PR #42035:
URL: https://github.com/apache/spark/pull/42035#discussion_r1266009168


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core/src/main/scala/org/apache/spark/api/python/StreamingPythonRunner.scala:
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@@ -0,0 +1,88 @@
+/*
+ * 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.{BufferedInputStream, BufferedOutputStream, DataInputStream, DataOutputStream}
+import java.net.Socket
+
+import scala.collection.JavaConverters._
+
+import org.apache.spark.SparkEnv
+import org.apache.spark.internal.Logging
+import org.apache.spark.internal.config.BUFFER_SIZE
+import org.apache.spark.internal.config.Python.{PYTHON_AUTH_SOCKET_TIMEOUT, PYTHON_USE_DAEMON}
+
+
+private[spark] object StreamingPythonRunner {
+  def apply(func: PythonFunction, connectUrl: String): StreamingPythonRunner = {
+    new StreamingPythonRunner(func, connectUrl)
+  }
+}
+
+private[spark] class StreamingPythonRunner(func: PythonFunction, connectUrl: String)
+  extends Logging {
+  private val conf = SparkEnv.get.conf
+  protected val bufferSize: Int = conf.get(BUFFER_SIZE)
+  protected val authSocketTimeout = conf.get(PYTHON_AUTH_SOCKET_TIMEOUT)
+
+  private val envVars: java.util.Map[String, String] = func.envVars
+  private val pythonExec: String = func.pythonExec
+  protected val pythonVer: String = func.pythonVer
+
+  /**
+   * Initializes the Python worker for streaming functions. Sets up Spark Connect session
+   * to be used with the functions.
+   */
+  def init(sessionId: String): (DataOutputStream, DataInputStream) = {
+    log.info(s"Initializing Python runner (session: $sessionId ,pythonExec: $pythonExec")
+
+    val env = SparkEnv.get
+
+    val localdir = env.blockManager.diskBlockManager.localDirs.map(f => f.getPath()).mkString(",")
+    envVars.put("SPARK_LOCAL_DIRS", localdir)
+
+    envVars.put("SPARK_AUTH_SOCKET_TIMEOUT", authSocketTimeout.toString)
+    envVars.put("SPARK_BUFFER_SIZE", bufferSize.toString)
+    conf.set(PYTHON_USE_DAEMON, false)
+    envVars.put("SPARK_CONNECT_LOCAL_URL", connectUrl)
+
+    val pythonWorkerFactory = new PythonWorkerFactory(pythonExec, envVars.asScala.toMap)
+    val (worker: Socket, _) = pythonWorkerFactory.createStreamingWorker()

Review Comment:
   Yeah, we can share. From my first look #41948 does not seem to initialize a session. Also, it is not a long running process with multiple iterations like here.



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