[GitHub] [spark] yym1995 commented on a change in pull request #35038: [SPARK-37728][SQL][3.2] Reading nested columns with ORC vectorized reader can cause ArrayIndexOutOfBoundsException

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yym1995 commented on a change in pull request #35038:
URL: https://github.com/apache/spark/pull/35038#discussion_r777804429



##########
File path: sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/orc/OrcQuerySuite.scala
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@@ -713,6 +715,27 @@ abstract class OrcQuerySuite extends OrcQueryTest with SharedSparkSession {
       }
     }
   }
+
+  test("SPARK-37728: Reading nested columns with ORC vectorized reader should not " +
+    "cause ArrayIndexOutOfBoundsException") {
+    withTempPath { dir =>
+      val path = dir.getCanonicalPath
+      val df = spark.range(100).map { _ =>
+        val arrayColumn = (0 until 50).map(_ => (0 until 1000).map(k => k.toString))
+        arrayColumn
+      }.toDF("record").repartition(1)
+      df.write.format("orc").save(path)
+
+      withSQLConf(SQLConf.ORC_VECTORIZED_READER_NESTED_COLUMN_ENABLED.key -> "true") {
+        val readDf = spark.read.orc(path)
+        val vectorizationEnabled = readDf.queryExecution.executedPlan.find {
+          case scan @ (_: FileSourceScanExec | _: BatchScanExec) => scan.supportsColumnar
+          case _ => false
+        }.isDefined

Review comment:
       Because when testing with OrcV2QuerySuite, method supportColumnarReads in
   https://github.com/apache/spark/blob/branch-3.2/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/orc/OrcPartitionReaderFactory.scala will be  called. `resultSchema.forall(_.dataType.isInstanceOf[AtomicType])` is false in that case. Therefore, I removed `assert(vectorizationEnabled)`.




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