Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/10605#discussion_r48902027
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/Window.scala ---
@@ -661,29 +719,35 @@ private[execution] final class
UnboundedFollowingWindowFunctionFrame(
lbound: BoundOrdering) extends WindowFunctionFrame {
/** Rows of the partition currently being processed. */
- private[this] var input: ArrayBuffer[InternalRow] = null
+ private[this] var input: ExternalRowBuffer = null
/** Index of the first input row with a value equal to or greater than
the lower bound of the
* current output row. */
private[this] var inputIndex = 0
- /** Index of the row we are currently writing. */
- private[this] var outputIndex = 0
-
/** Prepare the frame for calculating a new partition. */
- override def prepare(rows: ArrayBuffer[InternalRow]): Unit = {
+ override def prepare(rows: ExternalRowBuffer): Unit = {
input = rows
inputIndex = 0
- outputIndex = 0
}
/** Write the frame columns for the current row to the given target row.
*/
- override def write(): Unit = {
- var bufferUpdated = outputIndex == 0
+ override def write(index: Int, current: InternalRow): Unit = {
+ var bufferUpdated = index == 0
+
+ // Duplicate the input to have a new iterator
+ val tmp = input.copy()
// Drop all rows from the buffer for which the input row value is
smaller than
// the output row lower bound.
- while (inputIndex < input.size && lbound.compare(input, inputIndex,
outputIndex) < 0) {
+ var i = 0
+ while (i < inputIndex) {
+ tmp.next()
--- End diff --
Yes, it doubles the time. If N is large, it's kind of like double of
infinity is still infinity :-)
Actually I tried to add a `skip(n)` API for UnsafeSortIterator to improve
this a little bit, but it seems not worth that complexity, so removed.
I think the next step could be have a fast path for those functions that
has communitativity, we could reduce the complexity to `O(N * 2)`
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