hehuiyuan created FLINK-20301:
---------------------------------
Summary: Flink sql 1.10 : Legacy Decimal and decimal for Array
that is not Compatible
Key: FLINK-20301
URL: https://issues.apache.org/jira/browse/FLINK-20301
Project: Flink
Issue Type: Bug
Components: Table SQL / Planner
Reporter: hehuiyuan
Attachments: image-2020-11-23-23-48-02-102.png
The error log:
{code:java}
Exception in thread "main" org.apache.flink.table.api.ValidationException: Type
ARRAY<DECIMAL(38, 18)> of table field 'numbers' does not match with the
physical type ARRAY<LEGACY('DECIMAL', 'DECIMAL')> of the 'numbers' field of the
TableSource return type.Exception in thread "main"
org.apache.flink.table.api.ValidationException: Type ARRAY<DECIMAL(38, 18)> of
table field 'numbers' does not match with the physical type
ARRAY<LEGACY('DECIMAL', 'DECIMAL')> of the 'numbers' field of the TableSource
return type. at
org.apache.flink.table.utils.TypeMappingUtils.lambda$checkPhysicalLogicalTypeCompatible$4(TypeMappingUtils.java:160)
at
org.apache.flink.table.utils.TypeMappingUtils.checkPhysicalLogicalTypeCompatible(TypeMappingUtils.java:185)
at
org.apache.flink.table.utils.TypeMappingUtils.lambda$computeInCompositeType$8(TypeMappingUtils.java:246)
at java.util.stream.Collectors.lambda$toMap$58(Collectors.java:1321) at
java.util.stream.ReduceOps$3ReducingSink.accept(ReduceOps.java:169) at
java.util.ArrayList$ArrayListSpliterator.forEachRemaining(ArrayList.java:1382)
at java.util.stream.AbstractPipeline.copyInto(AbstractPipeline.java:481) at
java.util.stream.AbstractPipeline.wrapAndCopyInto(AbstractPipeline.java:471) at
java.util.stream.ReduceOps$ReduceOp.evaluateSequential(ReduceOps.java:708) at
java.util.stream.AbstractPipeline.evaluate(AbstractPipeline.java:234) at
java.util.stream.ReferencePipeline.collect(ReferencePipeline.java:499) at
org.apache.flink.table.utils.TypeMappingUtils.computeInCompositeType(TypeMappingUtils.java:228)
at
org.apache.flink.table.utils.TypeMappingUtils.computePhysicalIndices(TypeMappingUtils.java:206)
at
org.apache.flink.table.utils.TypeMappingUtils.computePhysicalIndicesOrTimeAttributeMarkers(TypeMappingUtils.java:110)
at
org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecTableSourceScan.computeIndexMapping(StreamExecTableSourceScan.scala:212)
at
org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecTableSourceScan.translateToPlanInternal(StreamExecTableSourceScan.scala:107)
at
org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecTableSourceScan.translateToPlanInternal(StreamExecTableSourceScan.scala:62)
at
org.apache.flink.table.planner.plan.nodes.exec.ExecNode$class.translateToPlan(ExecNode.scala:58)
at
org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecTableSourceScan.translateToPlan(StreamExecTableSourceScan.scala:62)
at
org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecSink.translateToTransformation(StreamExecSink.scala:184)
at
org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecSink.translateToPlanInternal(StreamExecSink.scala:118)
at
org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecSink.translateToPlanInternal(StreamExecSink.scala:48)
at
org.apache.flink.table.planner.plan.nodes.exec.ExecNode$class.translateToPlan(ExecNode.scala:58)
at
org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecSink.translateToPlan(StreamExecSink.scala:48)
at
org.apache.flink.table.planner.delegation.StreamPlanner$$anonfun$translateToPlan$1.apply(StreamPlanner.scala:60)
at
org.apache.flink.table.planner.delegation.StreamPlanner$$anonfun$translateToPlan$1.apply(StreamPlanner.scala:59)
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:893) at
scala.collection.AbstractIterator.foreach(Iterator.scala:1336) 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.StreamPlanner.translateToPlan(StreamPlanner.scala:59)
at
org.apache.flink.table.planner.delegation.PlannerBase.translate(PlannerBase.scala:153)
at
org.apache.flink.table.api.internal.TableEnvironmentImpl.translate(TableEnvironmentImpl.java:685)
at
org.apache.flink.table.api.internal.TableEnvironmentImpl.sqlUpdate(TableEnvironmentImpl.java:495)
{code}
Background :
Flink SQL --- blink ---1.10
The shema for TableSource is JSON:
{code:java}
"{type:'object',properties:{age:{type:'number'},numbers: { type: 'array',
items: { type: 'number' } },name:{type:'string'},dt:{type: 'string', format:
'date-time'},timehour:{type: 'string', format: 'time'} }}"
{code}
The validate throw exception :
Type ARRAY<DECIMAL(38, 18)> of table field 'numbers' does not match with the
physical type ARRAY<LEGACY('DECIMAL', 'DECIMAL')> of the 'numbers' field of the
TableSource return type.
The type `Array[Decimal]` should be considered.
!image-2020-11-23-23-48-02-102.png|width=594,height=364!
I think the `visit ( ArrayType source)` should be considered.
{code:java}
@Override
public Boolean visit(ArrayType sourceType1){
if (sourceType1 instanceof ArrayType
&& sourceType1.getElementType().getTypeRoot() == LogicalTypeRoot.DECIMAL) {
DecimalType logicalDecimalType = (DecimalType)sourceType1.getElementType();
if (logicalDecimalType.getPrecision() != DecimalType.MAX_PRECISION ||
logicalDecimalType.getScale() != 18) {
throw new ValidationException(
"Legacy decimal type can only be mapped to DECIMAL(38, 18).");
}
return true;
}
return false;
}
{code}
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