KurtYoung commented on a change in pull request #8035:
[FLINK-11975][table-planner-blink] Support to run a sql query : 'SELECT * FROM
(VALUES (1, 2, 3)) T(a, b, c)'
URL: https://github.com/apache/flink/pull/8035#discussion_r268917191
##########
File path:
flink-table/flink-table-planner-blink/src/main/scala/org/apache/flink/table/plan/nodes/physical/batch/BatchExecSink.scala
##########
@@ -36,10 +46,99 @@ class BatchExecSink[T](
sink: TableSink[T],
sinkName: String)
extends Sink(cluster, traitSet, inputRel, sink, sinkName)
- with BatchPhysicalRel {
+ with BatchPhysicalRel
+ with BatchExecNode[Any] {
override def copy(traitSet: RelTraitSet, inputs: util.List[RelNode]):
RelNode = {
new BatchExecSink(cluster, traitSet, inputs.get(0), sink, sinkName)
}
+ /**
+ * Returns [[DamBehavior]] of this node.
+ */
+ override def getDamBehavior: DamBehavior = DamBehavior.PIPELINED
Review comment:
The definition of PIPELINED in dam behavior is that the operator will not
cache any data and all records will *pass through* in a pipelined fashion. For
sink operator, the records will not pass through it, right? To me, the behavior
is more like to be `FULL_DAM`, except the sink operator will not return or
output any record after it consumes all the input data.
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