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https://issues.apache.org/jira/browse/FLINK-7797?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16311794#comment-16311794
]
ASF GitHub Bot commented on FLINK-7797:
---------------------------------------
Github user fhueske commented on a diff in the pull request:
https://github.com/apache/flink/pull/5140#discussion_r159719430
--- Diff:
flink-libraries/flink-table/src/main/scala/org/apache/flink/table/plan/nodes/datastream/DataStreamWindowJoin.scala
---
@@ -183,23 +190,48 @@ class DataStreamWindowJoin(
}
}
- def createEmptyJoin(
+ def createNegativeWindowSizeJoin(
--- End diff --
I think we can make this even more efficient if we implement this as:
```
def createNegativeWindowSizeJoin(
joinType: JoinType,
leftInput: DataStream[CRow],
rightInput: DataStream[CRow],
leftArity: Int,
rightArity: Int,
returnType: TypeInformation[CRow]): DataStream[CRow] = {
// we filter all records instead of adding an empty source to preserve
the watermarks
val allFilter = new FlatMapFunction[CRow, CRow] with
ResultTypeQueryable[CRow] {
override def flatMap(value: CRow, out: Collector[CRow]): Unit = { }
override def getProducedType: TypeInformation[CRow] = returnType
}
val leftPadder = new MapFunction[CRow, CRow] with
ResultTypeQueryable[CRow] {
val paddingUtil = new OuterJoinPaddingUtil(leftArity, rightArity)
override def map(value: CRow): CRow = new
CRow(paddingUtil.padLeft(value.row), true)
override def getProducedType: TypeInformation[CRow] = returnType
}
val rightPadder = new MapFunction[CRow, CRow] with
ResultTypeQueryable[CRow] {
val paddingUtil = new OuterJoinPaddingUtil(leftArity, rightArity)
override def map(value: CRow): CRow = new
CRow(paddingUtil.padRight(value.row), true)
override def getProducedType: TypeInformation[CRow] = returnType
}
val leftP = leftInput.getParallelism
val rightP = rightInput.getParallelism
joinType match {
case JoinType.INNER =>
leftInput.flatMap(allFilter).name("Empty Inner
Join").setParallelism(leftP)
.union(rightInput.flatMap(allFilter).name("Empty Inner
Join").setParallelism(rightP))
case JoinType.LEFT_OUTER =>
leftInput.map(leftPadder).name("Left Outer
Join").setParallelism(leftP)
.union(rightInput.flatMap(allFilter).name("Left Outer
Join").setParallelism(rightP))
case JoinType.RIGHT_OUTER =>
leftInput.flatMap(allFilter).name("Right Outer
Join").setParallelism(leftP)
.union(rightInput.map(rightPadder).name("Right Outer
Join").setParallelism(rightP))
case JoinType.FULL_OUTER =>
leftInput.map(leftPadder).name("Full Outer
Join").setParallelism(leftP)
.union(rightInput.map(rightPadder).name("Full Outer
Join").setParallelism(rightP))
}
}
```
We also need to make `OuterJoinPaddingUtil` extend `java.io.Serializable`
for this.
> Add support for windowed outer joins for streaming tables
> ---------------------------------------------------------
>
> Key: FLINK-7797
> URL: https://issues.apache.org/jira/browse/FLINK-7797
> Project: Flink
> Issue Type: Sub-task
> Components: Table API & SQL
> Affects Versions: 1.4.0
> Reporter: Fabian Hueske
> Assignee: Xingcan Cui
>
> Currently, only windowed inner joins for streaming tables are supported.
> This issue is about adding support for windowed LEFT, RIGHT, and FULL OUTER
> joins.
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