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https://issues.apache.org/jira/browse/FLINK-5803?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15882986#comment-15882986
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ASF GitHub Bot commented on FLINK-5803:
---------------------------------------
Github user fhueske commented on a diff in the pull request:
https://github.com/apache/flink/pull/3397#discussion_r102946820
--- Diff:
flink-libraries/flink-table/src/main/scala/org/apache/flink/table/plan/rules/datastream/DataStreamOverAggregateRule.scala
---
@@ -0,0 +1,64 @@
+/*
+ * 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.rules.datastream
+
+import org.apache.calcite.plan.volcano.RelSubset
+import org.apache.calcite.plan.{Convention, RelOptRule, RelTraitSet}
+import org.apache.calcite.rel.RelNode
+import org.apache.calcite.rel.convert.ConverterRule
+import org.apache.calcite.rel.logical.LogicalWindow
+import org.apache.flink.table.calcite.FlinkRelBuilder.NamedWindowProperty
+import org.apache.flink.table.plan.nodes.datastream.DataStreamConvention
+import org.apache.flink.table.plan.nodes.datastream.DataStreamOverAggregate
+
+import scala.collection.JavaConversions._
+
+/**
+ * Rule to convert a LogicalWindow into a DataStreamOverAggregate.
+ */
+class DataStreamOverAggregateRule
+ extends ConverterRule(
+ classOf[LogicalWindow],
+ Convention.NONE,
+ DataStreamConvention.INSTANCE,
+ "DataStreamOverAggregateRule") {
+
+ override def convert(rel: RelNode): RelNode = {
--- End diff --
We need to check that ORDER BY is on `proctime()`.
Currently any attribute can be used in the ORDER BY clause and the query is
executed without issues.
> Add [partitioned] processing time OVER RANGE BETWEEN UNBOUNDED PRECEDING
> aggregation to SQL
> -------------------------------------------------------------------------------------------
>
> Key: FLINK-5803
> URL: https://issues.apache.org/jira/browse/FLINK-5803
> Project: Flink
> Issue Type: Sub-task
> Components: Table API & SQL
> Reporter: sunjincheng
> Assignee: sunjincheng
>
> The goal of this issue is to add support for OVER RANGE aggregations on
> processing time streams to the SQL interface.
> Queries similar to the following should be supported:
> {code}
> SELECT
> a,
> SUM(b) OVER (PARTITION BY c ORDER BY procTime() RANGE BETWEEN UNBOUNDED
> PRECEDING AND CURRENT ROW) AS sumB,
> MIN(b) OVER (PARTITION BY c ORDER BY procTime() RANGE BETWEEN UNBOUNDED
> PRECEDING AND CURRENT ROW) AS minB
> FROM myStream
> {code}
> The following restrictions should initially apply:
> - All OVER clauses in the same SELECT clause must be exactly the same.
> - The ORDER BY clause may only have procTime() as parameter. procTime() is a
> parameterless scalar function that just indicates processing time mode.
> - bounded PRECEDING is not supported (see FLINK-5654)
> - FOLLOWING is not supported.
> The restrictions will be resolved in follow up issues. If we find that some
> of the restrictions are trivial to address, we can add the functionality in
> this issue as well.
> This issue includes:
> - Design of the DataStream operator to compute OVER ROW aggregates
> - Translation from Calcite's RelNode representation (LogicalProject with
> RexOver expression).
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