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https://issues.apache.org/jira/browse/FLINK-8577?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16694629#comment-16694629
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ASF GitHub Bot commented on FLINK-8577:
---------------------------------------
dianfu commented on a change in pull request #6787: [FLINK-8577][table]
Implement proctime DataStream to Table upsert conversion
URL: https://github.com/apache/flink/pull/6787#discussion_r235346023
##########
File path:
flink-libraries/flink-table/src/main/scala/org/apache/flink/table/plan/nodes/datastream/StreamScan.scala
##########
@@ -19,22 +19,138 @@
package org.apache.flink.table.plan.nodes.datastream
import org.apache.calcite.rex.RexNode
-import org.apache.flink.api.common.functions.{MapFunction, RichMapFunction}
+import org.apache.flink.api.common.functions.RichMapFunction
import org.apache.flink.api.common.typeinfo.TypeInformation
+import org.apache.flink.api.java.tuple.{Tuple2 => JTuple2}
import org.apache.flink.configuration.Configuration
import org.apache.flink.streaming.api.datastream.DataStream
import org.apache.flink.streaming.api.functions.ProcessFunction
-import org.apache.flink.table.api.TableConfig
+import org.apache.flink.table.api.{TableConfig, Types}
import org.apache.flink.table.codegen.{FunctionCodeGenerator,
GeneratedFunction}
import org.apache.flink.table.plan.nodes.CommonScan
import org.apache.flink.table.plan.schema.RowSchema
import org.apache.flink.types.Row
-import org.apache.flink.table.runtime.CRowOutputProcessRunner
import org.apache.flink.table.runtime.types.{CRow, CRowTypeInfo}
import org.apache.flink.table.typeutils.TimeIndicatorTypeInfo
+import java.lang.{Boolean => JBool}
+
+import org.apache.flink.api.java.typeutils.TupleTypeInfo
+import org.apache.flink.api.scala.typeutils.CaseClassTypeInfo
+import
org.apache.flink.table.runtime.conversion.{ExternalTypeToCRowProcessRunner,
JavaTupleToCRowProcessRunner, ScalaTupleToCRowProcessRunner}
trait StreamScan extends CommonScan[CRow] with DataStreamRel {
+ protected def convertUpsertToInternalRow(
+ schema: RowSchema,
+ input: DataStream[Any],
+ fieldIdxs: Array[Int],
+ config: TableConfig,
+ rowtimeExpression: Option[RexNode]): DataStream[CRow] = {
+
+ val internalType = schema.typeInfo
+ val cRowType = CRowTypeInfo(internalType)
+
+ val hasTimeIndicator = fieldIdxs.exists(f =>
+ f == TimeIndicatorTypeInfo.ROWTIME_STREAM_MARKER ||
+ f == TimeIndicatorTypeInfo.PROCTIME_STREAM_MARKER)
+
+ val dsType = input.getType
+
+ dsType match {
+ // Scala tuple
+ case t: CaseClassTypeInfo[_]
+ if t.getTypeClass == classOf[(_, _)] && t.getTypeAt(0) ==
Types.BOOLEAN =>
+
+ val inputType = t.getTypeAt[Any](1)
+ if (inputType == internalType && !hasTimeIndicator) {
+ // input is already of correct type. Only need to wrap it as CRow
+ input.asInstanceOf[DataStream[(Boolean, Row)]]
+ .map(new RichMapFunction[(Boolean, Row), CRow] {
+ @transient private var outCRow: CRow = null
Review comment:
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> Implement proctime DataStream to Table upsert conversion.
> ---------------------------------------------------------
>
> Key: FLINK-8577
> URL: https://issues.apache.org/jira/browse/FLINK-8577
> Project: Flink
> Issue Type: Sub-task
> Components: Table API & SQL
> Reporter: Hequn Cheng
> Assignee: Hequn Cheng
> Priority: Major
> Labels: pull-request-available
>
> Api will looks like:
> {code:java}
> DataStream[(String, Long, Int)] input = ???
> // upsert with keyTable
> table = tEnv.upsertFromStream(input, 'a, 'b, 'c.key)
> // upsert without key -> single row tableTable
> table = tEnv.upsertFromStream(input, 'a, 'b, 'c){code}
> A simple design
> [doc|https://docs.google.com/document/d/1yMEi9xkm3pNYNmmZykbLzqtKjFVezaWe0y7Xqd0c1zE/edit?usp=sharing]
> about this subtask.
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