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https://issues.apache.org/jira/browse/FLINK-5653?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15926368#comment-15926368
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ASF GitHub Bot commented on FLINK-5653:
---------------------------------------
Github user sunjincheng121 commented on a diff in the pull request:
https://github.com/apache/flink/pull/3547#discussion_r106193738
--- Diff:
flink-libraries/flink-table/src/main/scala/org/apache/flink/table/plan/nodes/datastream/DataStreamOverAggregate.scala
---
@@ -17,34 +17,38 @@
*/
package org.apache.flink.table.plan.nodes.datastream
-import org.apache.calcite.plan.{RelOptCluster, RelTraitSet}
+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.calcite.rel.{ RelNode, RelWriter, SingleRel }
import org.apache.flink.api.java.typeutils.RowTypeInfo
import org.apache.flink.streaming.api.datastream.DataStream
-import org.apache.flink.table.api.{StreamTableEnvironment, TableException}
+import org.apache.flink.table.api.{ StreamTableEnvironment, TableException
}
import org.apache.flink.table.calcite.FlinkTypeFactory
import org.apache.flink.table.runtime.aggregate._
import org.apache.flink.table.plan.nodes.OverAggregate
import org.apache.flink.types.Row
import org.apache.calcite.rel.core.Window
import org.apache.calcite.rel.core.Window.Group
-import java.util.{List => JList}
+import java.util.{ List => JList }
import org.apache.flink.table.functions.{ProcTimeType, RowTimeType}
import org.apache.flink.table.runtime.aggregate.AggregateUtil.CalcitePair
+import org.apache.calcite.sql.`type`.BasicSqlType
+import org.apache.flink.streaming.api.functions.windowing.WindowFunction
+import org.apache.flink.streaming.api.windowing.windows.GlobalWindow
+import org.apache.flink.api.java.tuple.Tuple
class DataStreamOverAggregate(
- logicWindow: Window,
- cluster: RelOptCluster,
- traitSet: RelTraitSet,
- inputNode: RelNode,
- rowRelDataType: RelDataType,
- inputType: RelDataType)
- extends SingleRel(cluster, traitSet, inputNode)
- with OverAggregate
- with DataStreamRel {
+ logicWindow: Window,
+ cluster: RelOptCluster,
+ traitSet: RelTraitSet,
+ inputNode: RelNode,
+ rowRelDataType: RelDataType,
+ inputType: RelDataType)
+ extends SingleRel(cluster, traitSet, inputNode)
--- End diff --
Indent 2 space.
> Add processing time OVER ROWS BETWEEN x PRECEDING aggregation to SQL
> --------------------------------------------------------------------
>
> Key: FLINK-5653
> URL: https://issues.apache.org/jira/browse/FLINK-5653
> Project: Flink
> Issue Type: Sub-task
> Components: Table API & SQL
> Reporter: Fabian Hueske
> Assignee: Stefano Bortoli
>
> The goal of this issue is to add support for OVER ROWS 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() ROWS BETWEEN 2 PRECEDING
> AND CURRENT ROW) AS sumB,
> MIN(b) OVER (PARTITION BY c ORDER BY procTime() ROWS BETWEEN 2 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 PARTITION BY clause is optional (no partitioning results in single
> threaded execution).
> - The ORDER BY clause may only have procTime() as parameter. procTime() is a
> parameterless scalar function that just indicates processing time mode.
> - UNBOUNDED PRECEDING is not supported (see FLINK-5656)
> - 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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