Github user sunjincheng121 commented on a diff in the pull request:
https://github.com/apache/flink/pull/3386#discussion_r103404131
--- Diff:
flink-libraries/flink-table/src/main/scala/org/apache/flink/table/plan/nodes/datastream/DataStreamSlideEventTimeRowAgg.scala
---
@@ -0,0 +1,179 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.flink.table.plan.nodes.datastream
+
+import org.apache.calcite.plan.{RelOptCluster, RelTraitSet}
+import org.apache.calcite.rel.`type`.RelDataType
+import org.apache.calcite.rel.core.AggregateCall
+import org.apache.calcite.rel.{RelNode, RelWriter, SingleRel}
+import org.apache.flink.api.java.tuple.Tuple
+import org.apache.flink.types.Row
+import org.apache.flink.table.calcite.{FlinkRelBuilder, FlinkTypeFactory}
+import FlinkRelBuilder.NamedWindowProperty
+import org.apache.flink.table.runtime.aggregate.AggregateUtil._
+import org.apache.flink.table.runtime.aggregate._
+import org.apache.flink.streaming.api.datastream.{AllWindowedStream,
DataStream, WindowedStream}
+import org.apache.flink.streaming.api.windowing.assigners._
+import org.apache.flink.streaming.api.windowing.windows.{Window =>
DataStreamWindow}
+import org.apache.flink.table.api.StreamTableEnvironment
+import org.apache.flink.table.plan.nodes.CommonAggregate
+
+class DataStreamSlideEventTimeRowAgg(
+ namedProperties: Seq[NamedWindowProperty],
+ cluster: RelOptCluster,
+ traitSet: RelTraitSet,
+ inputNode: RelNode,
+ namedAggregates: Seq[CalcitePair[AggregateCall, String]],
+ rowRelDataType: RelDataType,
+ inputType: RelDataType,
+ grouping: Array[Int])
+ extends SingleRel(cluster, traitSet, inputNode)
+ with CommonAggregate
+ with DataStreamRel {
+
+ override def deriveRowType(): RelDataType = rowRelDataType
+
+ override def copy(traitSet: RelTraitSet, inputs:
java.util.List[RelNode]): RelNode = {
+ new DataStreamSlideEventTimeRowAgg(
+ namedProperties,
+ cluster,
+ traitSet,
+ inputs.get(0),
+ namedAggregates,
+ getRowType,
+ inputType,
+ grouping)
--- End diff --
In fact, we can discard late events, but we must have a strategy to define
what kind of element is late.
Of course, the current implementation is also a strategy to assess the
delay event, but this strategy will lose too many events, and data calculation
results are unpredictable, not playback. This is unacceptable in the production
situation. What do you think?
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