LuciferYang commented on code in PR #40654:
URL: https://github.com/apache/spark/pull/40654#discussion_r1188376220


##########
connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/SparkConnectPlanner.scala:
##########
@@ -1567,6 +1613,19 @@ class SparkConnectPlanner(val session: SparkSession) {
         val expr = transformExpression(fun.getArguments(0))
         Some(transformUnregisteredUDF(MLFunctions.arrayToVectorUdf, Seq(expr)))
 
+      // Protobuf-specific functions
+      case "from_protobuf" if Seq(2, 3, 4).contains(fun.getArgumentsCount) =>
+        val children = 
fun.getArgumentsList.asScala.toSeq.map(transformExpression)
+        val (messageClassName, descFilePathOpt, options) =
+          extractArgsOfProtobufFunction("from_protobuf", 
fun.getArgumentsCount, children)
+        Some(ProtobufDataToCatalyst(children.head, messageClassName, 
descFilePathOpt, options))

Review Comment:
   like
   
   ```scala
          import org.apache.spark.sql.protobuf.{functions => pb}
           descFilePathOpt match {
             case Some(descFilePath) =>
               Some(pb.from_protobuf(Column(children.head),
                 messageClassName, descFilePath, options.asJava).expr)
             case _ =>
               Some(pb.from_protobuf(Column(children.head), messageClassName, 
options.asJava).expr)
           }
   ```?
   
   This seem not simple enough:
   
   1. We had to new a Column with `children.head` and retrieve the `.expr` of 
the return value again
   
   2. Need to pattern match `descFilePathOpt` again
   
   3. Keep the same calling way as others in `transformUnregisteredFunction` now
   
   
   So I tend to prefer the current invocation way now, do you have a simpler 
way?
   
   
   
   
   



##########
connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/SparkConnectPlanner.scala:
##########
@@ -1567,6 +1613,19 @@ class SparkConnectPlanner(val session: SparkSession) {
         val expr = transformExpression(fun.getArguments(0))
         Some(transformUnregisteredUDF(MLFunctions.arrayToVectorUdf, Seq(expr)))
 
+      // Protobuf-specific functions
+      case "from_protobuf" if Seq(2, 3, 4).contains(fun.getArgumentsCount) =>
+        val children = 
fun.getArgumentsList.asScala.toSeq.map(transformExpression)
+        val (messageClassName, descFilePathOpt, options) =
+          extractArgsOfProtobufFunction("from_protobuf", 
fun.getArgumentsCount, children)
+        Some(ProtobufDataToCatalyst(children.head, messageClassName, 
descFilePathOpt, options))

Review Comment:
   like
   
   ```scala
          import org.apache.spark.sql.protobuf.{functions => pb}
           descFilePathOpt match {
             case Some(descFilePath) =>
               Some(pb.from_protobuf(Column(children.head),
                 messageClassName, descFilePath, options.asJava).expr)
             case _ =>
               Some(pb.from_protobuf(Column(children.head), messageClassName, 
options.asJava).expr)
           }
   ```
   ?
   
   This seem not simple enough:
   
   1. We had to new a Column with `children.head` and retrieve the `.expr` of 
the return value again
   
   2. Need to pattern match `descFilePathOpt` again
   
   3. Keep the same calling way as others in `transformUnregisteredFunction` now
   
   
   So I tend to prefer the current invocation way now, do you have a simpler 
way?
   
   
   
   
   



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