Github user dongjoon-hyun commented on a diff in the pull request: https://github.com/apache/spark/pull/20511#discussion_r168834997 --- Diff: sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/orc/OrcSourceSuite.scala --- @@ -160,6 +160,15 @@ abstract class OrcSuite extends OrcTest with BeforeAndAfterAll { } } } + + test("SPARK-23340 Empty float/double array columns raise EOFException") { + Seq(Seq(Array.empty[Float]).toDF(), Seq(Array.empty[Double]).toDF()).foreach { df => + withTempPath { path => --- End diff -- It's not about ORC issue. Spark doesn't allow complex type vectorization. Please see `def supportBatch`. > When we write these test cases, we should do our best to cover all the scenarios even if it is not supported now. This is like black-box testing.
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