Github user twalthr commented on a diff in the pull request:
https://github.com/apache/flink/pull/2282#discussion_r73290760
--- Diff:
flink-libraries/flink-table/src/main/scala/org/apache/flink/api/table/plan/nodes/dataset/DataSetSort.scala
---
@@ -71,11 +78,57 @@ class DataSetSort(
partitionedDs = partitionedDs.sortPartition(fieldCollation._1,
fieldCollation._2)
}
+ val offsetAndFetchDS = if (offset != null) {
+ val offsetIndex = RexLiteral.intValue(offset)
+ val fetchIndex = if (fetch != null) {
+ RexLiteral.intValue(fetch) + offsetIndex
+ } else {
+ Int.MaxValue
+ }
+ if (currentParallelism != 1) {
+ val partitionCount = partitionedDs.mapPartition(
+ new MapPartitionFunction[Any, Int] {
+ override def mapPartition(value: lang.Iterable[Any], out:
Collector[Int]): Unit = {
+ val iterator = value.iterator()
+ var elementCount = 0
+ while (iterator.hasNext) {
+ elementCount += 1
+ iterator -> iterator.next()
+ }
+ out.collect(elementCount)
+ }
+ }).collect().asScala
--- End diff --
I agree that the number of elements in every partition is necessary but
triggering additional jobs during a plan construction phase is not what we
want. It should be up to the user if a job plan is executed at all. Have you
thought about using a broadcast variable as a side input of your filter
function?
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