Github user fhueske commented on a diff in the pull request:
https://github.com/apache/flink/pull/3641#discussion_r108722685
--- Diff:
flink-libraries/flink-table/src/main/scala/org/apache/flink/table/runtime/aggregate/AggregateUtil.scala
---
@@ -1208,5 +1208,40 @@ object AggregateUtil {
private def gcd(a: Long, b: Long): Long = {
if (b == 0) a else gcd(b, a % b)
}
-}
+
+ /**
+ * Create an
[[org.apache.flink.streaming.api.functions.ProcessFunction]] to evaluate final
+ * aggregate value over a window with processing time boundaries.
+ *
+ * @param namedAggregates List of calls to aggregate functions and their
output field names
+ * @param inputType Input row type
+ * @param timeBoundary time limit of the window boundary expressed in
milliseconds
+ * @param isPartitioned Flag to indicate whether the input is
partitioned or not
+ * @return [[org.apache.flink.streaming.api.functions.ProcessFunction]]
+ */
+ private[flink] def createTimeBoundedProcessingOverProcessFunction(
+ namedAggregates: Seq[CalcitePair[AggregateCall, String]],
+ inputType: RelDataType,
+ timeBoundary: Long,
+ isPartitioned: Boolean = true): ProcessFunction[Row, Row] = {
+
+ val (aggFields, aggregates) =
+ transformToAggregateFunctions(
+ namedAggregates.map(_.getKey),
+ inputType,
+ needRetraction = false)
--- End diff --
`needRetraction` must be `true`. This is probably not caught by the tests,
because the agg functions in the test are always retractable. You could use a
`min` or `max` aggregation which have dedicated implementation for retraction.
Actually, we should check if the over window tests have `min` and `max` agg
functions as well. I'll do that once all over windows have been merged.
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