[GitHub] [spark] bogao007 commented on a diff in pull request #42035: [SPARK-42944] Streaming ForeachBatch in Python

["bogao007 (via GitHub)" <gi...@apache.org>]

bogao007 commented on code in PR #42035:
URL: https://github.com/apache/spark/pull/42035#discussion_r1265682022


##########
core/src/main/scala/org/apache/spark/api/python/PythonWorkerFactory.scala:
##########
@@ -110,6 +110,57 @@ private[spark] class PythonWorkerFactory(pythonExec: String, envVars: Map[String
     }
   }
 
+  def createStreamingWorker(): (Socket, Option[Int]) = {

Review Comment:
   Nit: Can we add some documentations for this method?



##########
connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/StreamingForeachBatchHelper.scala:
##########
@@ -57,13 +63,59 @@ object StreamingForeachBatchHelper extends Logging {
    * Handles setting up Scala remote session and other Spark Connect environment and then runs the
    * provided foreachBatch function `fn`.
    *
-   * HACK ALERT: This version does not atually set up Spark connect. Directly passes the
-   * DataFrame, so the user code actually runs with legacy DataFrame.
+   * HACK ALERT: This version does not actually set up Spark Connect session. Directly passes the
+   * DataFrame, so the user code actually runs with legacy DataFrame and session..
    */
   def scalaForeachBatchWrapper(
       fn: ForeachBatchFnType,
       sessionHolder: SessionHolder): ForeachBatchFnType = {
     // TODO: Set up Spark Connect session. Do we actually need this for the first version?
-    dataFrameCachingWrapper(fn, sessionHolder)
+    dataFrameCachingWrapper(
+      (args: FnArgsWithId) => {
+        fn(args.df, args.batchId) // dfId is not used, see hack comment above.
+      },
+      sessionHolder)
   }
+
+  def pythonForeachBatchWrapper(

Review Comment:
   Nit: Missing documentation



##########
core/src/main/scala/org/apache/spark/api/python/StreamingPythonRunner.scala:
##########
@@ -0,0 +1,86 @@
+/*
+ * 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
+
+  def init(sessionId: String): (DataOutputStream, DataInputStream) = {

Review Comment:
   Nit: Some documentations for this method would be good



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