viirya commented on a change in pull request #24818: [SPARK-27971[SQL][R]
MapPartitionsInRWithArrowExec.evaluate shouldn't eagerly read the first batch
URL: https://github.com/apache/spark/pull/24818#discussion_r291811780
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/execution/objects.scala
##########
@@ -243,28 +243,11 @@ case class MapPartitionsInRWithArrowExec(
// binary in a batch due to the limitation of R API. See also ARROW-4512.
val columnarBatchIter = runner.compute(batchIter, -1)
val outputProject = UnsafeProjection.create(output, output)
- new Iterator[InternalRow] {
-
- private var currentIter = if (columnarBatchIter.hasNext) {
- val batch = columnarBatchIter.next()
- val actualDataTypes = (0 until batch.numCols()).map(i =>
batch.column(i).dataType())
- assert(outputTypes == actualDataTypes, "Invalid schema from
dapply(): " +
- s"expected ${outputTypes.mkString(", ")}, got
${actualDataTypes.mkString(", ")}")
- batch.rowIterator.asScala
- } else {
- Iterator.empty
- }
-
- override def hasNext: Boolean = currentIter.hasNext || {
- if (columnarBatchIter.hasNext) {
- currentIter = columnarBatchIter.next().rowIterator.asScala
- hasNext
- } else {
- false
- }
- }
-
- override def next(): InternalRow = currentIter.next()
+ columnarBatchIter.flatMap { batch =>
+ val actualDataTypes = (0 until batch.numCols()).map(i =>
batch.column(i).dataType())
+ assert(outputTypes == actualDataTypes, "Invalid schema from dapply():
" +
+ s"expected ${outputTypes.mkString(", ")}, got
${actualDataTypes.mkString(", ")}")
+ batch.rowIterator.asScala
Review comment:
My guess is that it was wanting to check the data type at the first batch
only. I think this fix is right.
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