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https://issues.apache.org/jira/browse/FLINK-17313?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17089472#comment-17089472
]
Wenlong Lyu commented on FLINK-17313:
-------------------------------------
[~dwysakowicz] Regarding LEGACY DECIMAL, I think it is a special case good to
support: the physical presentation of LAGECY DECIMAL is BigDecimal, can
support any precision and scale, so allow such conversion will not break
anything actually and the final precision and scale of the output BigDecimal
still limited by logical data type so no data with error precision will be
generated.
What's more, with such support we can easily fill up the support of decimal in
all kinds of sink with old interface.
> Validation error when insert decimal/timestamp/varchar with precision into
> sink using TypeInformation of row
> ------------------------------------------------------------------------------------------------------------
>
> Key: FLINK-17313
> URL: https://issues.apache.org/jira/browse/FLINK-17313
> Project: Flink
> Issue Type: Bug
> Components: Table SQL / Planner
> Reporter: Terry Wang
> Priority: Major
> Labels: pull-request-available
>
> Test code like follwing(in blink planner):
> {code:java}
> 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)," +
> " c
> timestamp(3)," +
> " ) with (" +
> " 'type' = 'print'" +
> " )");
> tEnv.sqlUpdate("insert into printSink select *,
> current_timestamp from randomSource");
> tEnv.execute("");
> {code}
> Print TableSink implements UpsertStreamTableSink and it's getReocrdType is as
> following:
> {code:java}
> public TypeInformation<Row> getRecordType() {
> return getTableSchema().toRowType();
> }
> {code}
> 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.
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