[FLINK-17313] Validation error when insert decimal/varchar with precision into sink using TypeInformation of row

• Type: Bug
• Status: Closed
• Priority: Major
• Resolution: Fixed
• Fix Version/s: 1.10.1, 1.11.0
• Component/s: Table SQL / Planner
• Labels: pull-request-available
• Assignee: Terry Wang
• Reporter: Terry Wang
• Created: 22/Apr/20 03:10
• Updated: 05/May/20 18:06
• Resolved: 27/Apr/20 09:26

Description

Test code like follwing(in blink planner):

		tEnv.sqlUpdate("create table randomSource (" +
						"		a varchar(10)," +
						"		b decimal(20,2)" +
						"	) with (" +
						"		'type' = 'random'," +
						"		'count' = '10'" +
						"	)");
		tEnv.sqlUpdate("create table printSink (" +
						"		a varchar(10)," +
						"		b decimal(22,2)," +
						"	) with (" +
						"	'type' = 'print'" +
						"	)");
		tEnv.sqlUpdate("insert into printSink select * from randomSource");
		tEnv.execute("");

Print TableSink implements UpsertStreamTableSink and it's getReocrdType is as following:

public TypeInformation<Row> getRecordType() {
		return getTableSchema().toRowType();
	}

Varchar column validation exception is:

org.apache.flink.table.api.ValidationException: Type VARCHAR(10) of table field 'a' does not match with the physical type STRING of the 'a' field of the TableSink consumed type.

at org.apache.flink.table.utils.TypeMappingUtils.lambda$checkPhysicalLogicalTypeCompatible$4(TypeMappingUtils.java:165)
at org.apache.flink.table.utils.TypeMappingUtils$1.defaultMethod(TypeMappingUtils.java:278)
at org.apache.flink.table.utils.TypeMappingUtils$1.defaultMethod(TypeMappingUtils.java:255)
at org.apache.flink.table.types.logical.utils.LogicalTypeDefaultVisitor.visit(LogicalTypeDefaultVisitor.java:67)
at org.apache.flink.table.types.logical.VarCharType.accept(VarCharType.java:157)
at org.apache.flink.table.utils.TypeMappingUtils.checkIfCompatible(TypeMappingUtils.java:255)
at org.apache.flink.table.utils.TypeMappingUtils.checkPhysicalLogicalTypeCompatible(TypeMappingUtils.java:161)
at org.apache.flink.table.planner.sinks.TableSinkUtils$$anonfun$validateLogicalPhysicalTypesCompatible$1.apply$mcVI$sp(TableSinkUtils.scala:315)
at scala.collection.immutable.Range.foreach$mVc$sp(Range.scala:160)
at org.apache.flink.table.planner.sinks.TableSinkUtils$.validateLogicalPhysicalTypesCompatible(TableSinkUtils.scala:308)
at org.apache.flink.table.planner.delegation.PlannerBase$$anonfun$2.apply(PlannerBase.scala:195)
at org.apache.flink.table.planner.delegation.PlannerBase$$anonfun$2.apply(PlannerBase.scala:191)
at scala.Option.map(Option.scala:146)
at org.apache.flink.table.planner.delegation.PlannerBase.translateToRel(PlannerBase.scala:191)
at org.apache.flink.table.planner.delegation.PlannerBase$$anonfun$1.apply(PlannerBase.scala:150)
at org.apache.flink.table.planner.delegation.PlannerBase$$anonfun$1.apply(PlannerBase.scala:150)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.Iterator$class.foreach(Iterator.scala:891)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1334)
at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
at scala.collection.AbstractTraversable.map(Traversable.scala:104)
at org.apache.flink.table.planner.delegation.PlannerBase.translate(PlannerBase.scala:150)
at org.apache.flink.table.api.internal.TableEnvironmentImpl.translate(TableEnvironmentImpl.java:863)
at org.apache.flink.table.api.internal.TableEnvironmentImpl.translateAndClearBuffer(TableEnvironmentImpl.java:855)
at org.apache.flink.table.api.internal.TableEnvironmentImpl.execute(TableEnvironmentImpl.java:822)

Other type validation exception is similar, I dig into and think it's caused by TypeMappingUtils#checkPhysicalLogicalTypeCompatible. It seems that the method doesn't consider the different physical and logical type validation logic of source and sink: logical type should be able to cover the physical type in source, but physical type should be able to cover the logic type in sink vice verse. Besides, the decimal type should be taken more carefully, when target type is Legacy(Decimal), it should be able to accept any precision decimal type.

Issue Links

• links to: GitHub Pull Request #11848
• links to: GitHub Pull Request #11993