[jira] [Created] (FLINK-14042) Different RelDataTypes generated for same TemporalTableFunction

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[jira] [Created] (FLINK-14042) Different RelDataTypes generated for same TemporalTableFunction

Shang Yuanchun (Jira)
Yuval Itzchakov created FLINK-14042:
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             Summary: Different RelDataTypes generated for same TemporalTableFunction
                 Key: FLINK-14042
                 URL: https://issues.apache.org/jira/browse/FLINK-14042
             Project: Flink
          Issue Type: Bug
          Components: Table SQL / Planner
    Affects Versions: 1.8.1
            Reporter: Yuval Itzchakov


Given the following table called "foo":
{code:java}
SELECT event_time, b, c
FROM X
WHERE event_time >= <START_TIME> AND event_time <END_TIME>{code}
And the following temporal table definition defined on "foo":
{code:java}
SELECT a, b, COLLECT(c) c
FROM foo
GROUP BY a, b{code}
I get the following exception:
{code:java}
Exception in thread "main" java.lang.AssertionError: Cannot add expression of different type to set:Exception in thread "main" java.lang.AssertionError: Cannot add expression of different type to set:set type is RecordType(TIMESTAMP(3) NOT NULL event_time, VARCHAR(65536) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary" b, VARCHAR(65536) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary" c0, TIMESTAMP(3) NOT NULL event_time0, VARCHAR(65536) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary" b0, VARCHAR(65536) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary" MULTISET c) NOT NULLexpression type is RecordType(TIMESTAMP(3) NOT NULL event_time, VARCHAR(65536) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary" b, VARCHAR(65536) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary" c0, TIMESTAMP(3) NOT NULL event_time0, VARCHAR(65536) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary" b0, VARCHAR(65536) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary" MULTISET NOT NULL c) NOT NULL
set is rel#17:LogicalCorrelate.NONE(left=HepRelVertex#15,right=HepRelVertex#16,correlation=$cor0,joinType=inner,requiredColumns={0})expression is LogicalTemporalTableJoin#23 at org.apache.calcite.plan.RelOptUtil.verifyTypeEquivalence(RelOptUtil.java:380) at org.apache.calcite.plan.hep.HepRuleCall.transformTo(HepRuleCall.java:57) at org.apache.calcite.plan.RelOptRuleCall.transformTo(RelOptRuleCall.java:234) at org.apache.flink.table.plan.rules.logical.LogicalCorrelateToTemporalTableJoinRule.onMatch(LogicalCorrelateToTemporalTableJoinRule.scala:111) at org.apache.calcite.plan.AbstractRelOptPlanner.fireRule(AbstractRelOptPlanner.java:315) at org.apache.calcite.plan.hep.HepPlanner.applyRule(HepPlanner.java:556) at org.apache.calcite.plan.hep.HepPlanner.applyRules(HepPlanner.java:415) at org.apache.calcite.plan.hep.HepPlanner.executeInstruction(HepPlanner.java:280) at org.apache.calcite.plan.hep.HepInstruction$RuleCollection.execute(HepInstruction.java:74) at org.apache.calcite.plan.hep.HepPlanner.executeProgram(HepPlanner.java:211) at org.apache.calcite.plan.hep.HepPlanner.findBestExp(HepPlanner.java:198) at org.apache.flink.table.api.TableEnvironment.runHepPlanner(TableEnvironment.scala:360) at org.apache.flink.table.api.TableEnvironment.runHepPlannerSimultaneously(TableEnvironment.scala:344) at org.apache.flink.table.api.TableEnvironment.optimizeExpandPlan(TableEnvironment.scala:270) at org.apache.flink.table.api.StreamTableEnvironment.optimize(StreamTableEnvironment.scala:809) at org.apache.flink.table.api.StreamTableEnvironment.writeToSink(StreamTableEnvironment.scala:351) at org.apache.flink.table.api.TableEnvironment.insertInto(TableEnvironment.scala:879) at org.apache.flink.table.api.Table.insertInto(table.scala:1148)
{code}
Digging into the table planner, it appears that when the temporal table is being registered, it goes through `FlinkTypeFactory.buildLogicalRowType`, which uses the following code:
{code:java}
def buildLogicalRowType(
    fieldNames: Seq[String],
    fieldTypes: Seq[TypeInformation[_]])
  : RelDataType = {
  val logicalRowTypeBuilder = builder

  val fields = fieldNames.zip(fieldTypes)
  fields.foreach(f => {
    // time indicators are not nullable
    val nullable = !FlinkTypeFactory.isTimeIndicatorType(f._2)
    logicalRowTypeBuilder.add(f._1, createTypeFromTypeInfo(f._2, nullable))
  })

  logicalRowTypeBuilder.build
}
{code}
 We can see here that `nullable` is derived from `isTimeIndicatorType` method.

On the other hand, when registering the table that uses the TemporalTableFunction in the query, this resolves through `FlinkTableFunctionImpl.getRowType`, which doesn't look up the time indicator flags at all and sets all fields to be nullable:
{code:java}
override def getRowType(typeFactory: RelDataTypeFactory,
                        arguments: util.List[AnyRef]): RelDataType = {
  val flinkTypeFactory = typeFactory.asInstanceOf[FlinkTypeFactory]
  val builder = flinkTypeFactory.builder
  fieldNames
    .zip(fieldTypes)
    .foreach { f =>
      builder.add(f._1, flinkTypeFactory.createTypeFromTypeInfo(f._2, isNullable = true))
    }
  builder.build
}
{code}
This creates a diff between the original schema registered and the inferred schema for usage, which results in the above exception.

I haven't tried this for other complex types, but it seems like this should happen for any advanced type which wasn't nullable to begin with.

 



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