sunchao commented on code in PR #47426:
URL: https://github.com/apache/spark/pull/47426#discussion_r1702390130
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/InternalRowComparableWrapper.scala:
##########
@@ -85,22 +84,25 @@ object InternalRowComparableWrapper {
}
def mergePartitions(
- leftPartitioning: KeyGroupedPartitioning,
- rightPartitioning: KeyGroupedPartitioning,
- partitionExpression: Seq[Expression]): Seq[InternalRow] = {
+ leftPartitioning: Seq[InternalRow],
+ rightPartitioning: Seq[InternalRow],
+ partitionExpression: Seq[Expression],
+ intersect: Boolean = false): Seq[InternalRowComparableWrapper] = {
val partitionDataTypes = partitionExpression.map(_.dataType)
- val partitionsSet = new mutable.HashSet[InternalRowComparableWrapper]
- leftPartitioning.partitionValues
+ val leftPartitionSet = new mutable.HashSet[InternalRowComparableWrapper]
+ leftPartitioning
.map(new InternalRowComparableWrapper(_, partitionDataTypes))
- .foreach(partition => partitionsSet.add(partition))
- rightPartitioning.partitionValues
+ .foreach(partition => leftPartitionSet.add(partition))
+ val rightPartitionSet = new mutable.HashSet[InternalRowComparableWrapper]
+ rightPartitioning
.map(new InternalRowComparableWrapper(_, partitionDataTypes))
- .foreach(partition => partitionsSet.add(partition))
- // SPARK-41471: We keep to order of partitions to make sure the order of
- // partitions is deterministic in different case.
- val partitionOrdering: Ordering[InternalRow] = {
- RowOrdering.createNaturalAscendingOrdering(partitionDataTypes)
+ .foreach(partition => rightPartitionSet.add(partition))
+
+ val result = if (intersect) {
+ leftPartitionSet.intersect(rightPartitionSet)
+ } else {
+ leftPartitionSet.union(rightPartitionSet)
}
- partitionsSet.map(_.row).toSeq.sorted(partitionOrdering)
+ result.toSeq
Review Comment:
do we still need to sort the result partitions?
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/InternalRowComparableWrapper.scala:
##########
@@ -85,22 +84,25 @@ object InternalRowComparableWrapper {
}
def mergePartitions(
- leftPartitioning: KeyGroupedPartitioning,
- rightPartitioning: KeyGroupedPartitioning,
- partitionExpression: Seq[Expression]): Seq[InternalRow] = {
+ leftPartitioning: Seq[InternalRow],
+ rightPartitioning: Seq[InternalRow],
+ partitionExpression: Seq[Expression],
+ intersect: Boolean = false): Seq[InternalRowComparableWrapper] = {
val partitionDataTypes = partitionExpression.map(_.dataType)
- val partitionsSet = new mutable.HashSet[InternalRowComparableWrapper]
- leftPartitioning.partitionValues
+ val leftPartitionSet = new mutable.HashSet[InternalRowComparableWrapper]
+ leftPartitioning
.map(new InternalRowComparableWrapper(_, partitionDataTypes))
- .foreach(partition => partitionsSet.add(partition))
- rightPartitioning.partitionValues
+ .foreach(partition => leftPartitionSet.add(partition))
+ val rightPartitionSet = new mutable.HashSet[InternalRowComparableWrapper]
+ rightPartitioning
.map(new InternalRowComparableWrapper(_, partitionDataTypes))
- .foreach(partition => partitionsSet.add(partition))
- // SPARK-41471: We keep to order of partitions to make sure the order of
- // partitions is deterministic in different case.
- val partitionOrdering: Ordering[InternalRow] = {
- RowOrdering.createNaturalAscendingOrdering(partitionDataTypes)
+ .foreach(partition => rightPartitionSet.add(partition))
+
+ val result = if (intersect) {
+ leftPartitionSet.intersect(rightPartitionSet)
+ } else {
+ leftPartitionSet.union(rightPartitionSet)
}
- partitionsSet.map(_.row).toSeq.sorted(partitionOrdering)
+ result.toSeq
Review Comment:
ah I see it is sorted later in the other method now
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