beyond1920 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_r268513943
 
 

 ##########
 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
+
+  /**
+    * Returns an array of this node's inputs. If there are no inputs,
+    * returns an empty list, not null.
+    *
+    * @return Array of this node's inputs
+    */
+  override def getInputNodes: util.List[ExecNode[BatchTableEnvironment, _]] = {
+    List(getInput.asInstanceOf[ExecNode[BatchTableEnvironment, _]])
+  }
+
+  /**
+    * Internal method, translates this node into a Flink operator.
+    *
+    * @param tableEnv The [[BatchTableEnvironment]] of the translated Table.
+    */
+  override protected def translateToPlanInternal(
+    tableEnv: BatchTableEnvironment): StreamTransformation[Any] = {
+    val convertTransformation = sink match {
+      case _: BatchTableSink[T] =>
+        translate(withChangeFlag = false, tableEnv)
+      case streamTableSink: DataStreamTableSink[T] =>
+        translate(withChangeFlag = streamTableSink.withChangeFlag, tableEnv)
+      case _ =>
+        throw new TableException("Only Support BatchTableSink or 
BatchCompatibleStreamTableSink")
+    }
+    // In case of table to bounded stream through 
BatchTableEnvironment#toBoundedStream, we insert a
+    // DataStreamTableSink then wrap it as a LogicalSink, there is no real 
batch table sink, so
+    // we do not need to invoke TableSink#emitBoundedStream and set resource, 
just a translation to
+    // StreamTransformation is ok.
+    val resultTransformation = if (sink.isInstanceOf[DataStreamTableSink[T]]) {
 
 Review comment:
   done

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