[GitHub] [spark] LucaCanali commented on a change in pull request #31367: [SPARK-34265][PYTHON][SQL] Instrument Python UDF using SQL Metrics

[GitBox <gi...@apache.org>]

LucaCanali commented on a change in pull request #31367:
URL: https://github.com/apache/spark/pull/31367#discussion_r566732268



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File path: sql/core/src/main/scala/org/apache/spark/sql/execution/python/BatchEvalPythonExec.scala
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@@ -83,12 +97,19 @@ case class BatchEvalPythonExec(udfs: Seq[PythonUDF], resultAttrs: Seq[Attribute]
       val unpickledBatch = unpickle.loads(pickedResult)
       unpickledBatch.asInstanceOf[java.util.ArrayList[Any]].asScala
     }.map { result =>
+      pythonNumRowsReceived += 1
+      val startTime = System.nanoTime()
       if (udfs.length == 1) {
         // fast path for single UDF
         mutableRow(0) = fromJava(result)
+        val deltaTime = System.nanoTime() - startTime
+        pythonExecTime += deltaTime
         mutableRow
       } else {
-        fromJava(result).asInstanceOf[InternalRow]
+        val res = fromJava(result).asInstanceOf[InternalRow]
+        val deltaTime = System.nanoTime() - startTime
+        pythonExecTime += deltaTime

Review comment:
       Correct, this is just a component, actually small and could be omitted. The most important part of the execution for BatchEvalPythonExec time is measured in PythonUDFRunner.




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