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Posted to issues@flink.apache.org by "Jing Zhang (JIRA)" <ji...@apache.org> on 2019/07/17 06:38:00 UTC
[jira] [Updated] (FLINK-13301) Some PlannerExpression resultType is
not consistent with Calcite Type inference
[ https://issues.apache.org/jira/browse/FLINK-13301?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Jing Zhang updated FLINK-13301:
-------------------------------
Description:
Some PlannerExpression resultType is not consistent with Calcite Type inference. The problem could be happened when run the following example:
{code:java}
// prepare source Data
val testData = new mutable.MutableList[(Int)]
testData.+=((3))
val t = env.fromCollection(testData).toTable(tEnv).as('a)
// register a TableSink
val fieldNames = Array("f0")
val fieldTypes: Array[TypeInformation[_]] = Array(Types.INT())
// val fieldTypes: Array[TypeInformation[_]] = Array(Types.LONG())
val sink = new MemoryTableSourceSinkUtil.UnsafeMemoryAppendTableSink
tEnv.registerTableSink("targetTable", sink.configure(fieldNames, fieldTypes))
t.select('a.floor()).insertInto("targetTable")
env.execute()
{code}
The cause is ResultType of `floor` is LONG_TYPE_INFO, while in Calcite `SqlFloorFunction` infers returnType is the type of the first argument(INT in the above case).
If I change `fieldTypes` to Array(Types.INT()), the following error will be thrown in compile phase.
{code:java}
org.apache.flink.table.api.ValidationException: Field types of query result and registered TableSink [targetTable] do not match.
Query result schema: [_c0: Long]
TableSink schema: [f0: Integer]
at org.apache.flink.table.sinks.TableSinkUtils$.validateSink(TableSinkUtils.scala:59)
at org.apache.flink.table.planner.StreamPlanner$$anonfun$2.apply(StreamPlanner.scala:158)
at org.apache.flink.table.planner.StreamPlanner$$anonfun$2.apply(StreamPlanner.scala:157)
at scala.Option.map(Option.scala:146)
at org.apache.flink.table.planner.StreamPlanner.org$apache$flink$table$planner$StreamPlanner$$translate(StreamPlanner.scala:157)
at org.apache.flink.table.planner.StreamPlanner$$anonfun$translate$1.apply(StreamPlanner.scala:129)
at org.apache.flink.table.planner.StreamPlanner$$anonfun$translate$1.apply(StreamPlanner.scala:129)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.Iterator$class.foreach(Iterator.scala:891)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1334)
at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
{code}
And If I change `fieldTypes` to Array(Types.LONG()), the other error will be thrown in runtime.
{code:java}
org.apache.flink.table.api.TableException: Result field does not match requested type. Requested: Long; Actual: Integer
at org.apache.flink.table.planner.Conversions$$anonfun$generateRowConverterFunction$2.apply(Conversions.scala:103)
at org.apache.flink.table.planner.Conversions$$anonfun$generateRowConverterFunction$2.apply(Conversions.scala:98)
at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:186)
at org.apache.flink.table.planner.Conversions$.generateRowConverterFunction(Conversions.scala:98)
at org.apache.flink.table.planner.DataStreamConversions$.getConversionMapper(DataStreamConversions.scala:135)
at org.apache.flink.table.planner.DataStreamConversions$.convert(DataStreamConversions.scala:91)
{code}
{color:red}Above inconsistent problem also exists in `Floor`, `Ceil`, `Mod` and so on. {color}
was:
Some PlannerExpression resultType is not consistent with Calcite Type inference. The problem could be happened when run the following example:
{code:java}
// prepare source Data
val testData = new mutable.MutableList[(Int)]
testData.+=((3))
val t = env.fromCollection(testData).toTable(tEnv).as('a)
// register a TableSink
val fieldNames = Array("f0")
val fieldTypes: Array[TypeInformation[_]] = Array(Types.INT())
// val fieldTypes: Array[TypeInformation[_]] = Array(Types.LONG())
val sink = new MemoryTableSourceSinkUtil.UnsafeMemoryAppendTableSink
tEnv.registerTableSink("targetTable", sink.configure(fieldNames, fieldTypes))
t.select('a.floor()).insertInto("targetTable")
env.execute()
{code}
The cause is ResultType of `floor` is LONG_TYPE_INFO, while in Calcite `SqlFloorFunction` infers returnType is the type of the first argument(INT in the above case).
If I change `fieldTypes` to Array(Types.INT()), the following error will be thrown in compile phase.
{code:java}
org.apache.flink.table.api.ValidationException: Field types of query result and registered TableSink [targetTable] do not match.
Query result schema: [_c0: Long]
TableSink schema: [f0: Integer]
at org.apache.flink.table.sinks.TableSinkUtils$.validateSink(TableSinkUtils.scala:59)
at org.apache.flink.table.planner.StreamPlanner$$anonfun$2.apply(StreamPlanner.scala:158)
at org.apache.flink.table.planner.StreamPlanner$$anonfun$2.apply(StreamPlanner.scala:157)
at scala.Option.map(Option.scala:146)
at org.apache.flink.table.planner.StreamPlanner.org$apache$flink$table$planner$StreamPlanner$$translate(StreamPlanner.scala:157)
at org.apache.flink.table.planner.StreamPlanner$$anonfun$translate$1.apply(StreamPlanner.scala:129)
at org.apache.flink.table.planner.StreamPlanner$$anonfun$translate$1.apply(StreamPlanner.scala:129)
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)
{code}
And If I change `fieldTypes` to Array(Types.LONG()), the other error will be thrown in runtime.
{code:java}
org.apache.flink.table.api.TableException: Result field does not match requested type. Requested: Long; Actual: Integer
at org.apache.flink.table.planner.Conversions$$anonfun$generateRowConverterFunction$2.apply(Conversions.scala:103)
at org.apache.flink.table.planner.Conversions$$anonfun$generateRowConverterFunction$2.apply(Conversions.scala:98)
at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:186)
at org.apache.flink.table.planner.Conversions$.generateRowConverterFunction(Conversions.scala:98)
at org.apache.flink.table.planner.DataStreamConversions$.getConversionMapper(DataStreamConversions.scala:135)
at org.apache.flink.table.planner.DataStreamConversions$.convert(DataStreamConversions.scala:91)
{code}
Above inconsistent problem also exists in `Floor`, `Ceil`, `Mod` and so on.
> Some PlannerExpression resultType is not consistent with Calcite Type inference
> -------------------------------------------------------------------------------
>
> Key: FLINK-13301
> URL: https://issues.apache.org/jira/browse/FLINK-13301
> Project: Flink
> Issue Type: Task
> Components: Table SQL / API
> Reporter: Jing Zhang
> Priority: Major
>
> Some PlannerExpression resultType is not consistent with Calcite Type inference. The problem could be happened when run the following example:
> {code:java}
> // prepare source Data
> val testData = new mutable.MutableList[(Int)]
> testData.+=((3))
> val t = env.fromCollection(testData).toTable(tEnv).as('a)
> // register a TableSink
> val fieldNames = Array("f0")
> val fieldTypes: Array[TypeInformation[_]] = Array(Types.INT())
> // val fieldTypes: Array[TypeInformation[_]] = Array(Types.LONG())
> val sink = new MemoryTableSourceSinkUtil.UnsafeMemoryAppendTableSink
> tEnv.registerTableSink("targetTable", sink.configure(fieldNames, fieldTypes))
>
> t.select('a.floor()).insertInto("targetTable")
> env.execute()
> {code}
> The cause is ResultType of `floor` is LONG_TYPE_INFO, while in Calcite `SqlFloorFunction` infers returnType is the type of the first argument(INT in the above case).
> If I change `fieldTypes` to Array(Types.INT()), the following error will be thrown in compile phase.
> {code:java}
> org.apache.flink.table.api.ValidationException: Field types of query result and registered TableSink [targetTable] do not match.
> Query result schema: [_c0: Long]
> TableSink schema: [f0: Integer]
> at org.apache.flink.table.sinks.TableSinkUtils$.validateSink(TableSinkUtils.scala:59)
> at org.apache.flink.table.planner.StreamPlanner$$anonfun$2.apply(StreamPlanner.scala:158)
> at org.apache.flink.table.planner.StreamPlanner$$anonfun$2.apply(StreamPlanner.scala:157)
> at scala.Option.map(Option.scala:146)
> at org.apache.flink.table.planner.StreamPlanner.org$apache$flink$table$planner$StreamPlanner$$translate(StreamPlanner.scala:157)
> at org.apache.flink.table.planner.StreamPlanner$$anonfun$translate$1.apply(StreamPlanner.scala:129)
> at org.apache.flink.table.planner.StreamPlanner$$anonfun$translate$1.apply(StreamPlanner.scala:129)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> at scala.collection.Iterator$class.foreach(Iterator.scala:891)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1334)
> at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
> {code}
> And If I change `fieldTypes` to Array(Types.LONG()), the other error will be thrown in runtime.
> {code:java}
> org.apache.flink.table.api.TableException: Result field does not match requested type. Requested: Long; Actual: Integer
> at org.apache.flink.table.planner.Conversions$$anonfun$generateRowConverterFunction$2.apply(Conversions.scala:103)
> at org.apache.flink.table.planner.Conversions$$anonfun$generateRowConverterFunction$2.apply(Conversions.scala:98)
> at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
> at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:186)
> at org.apache.flink.table.planner.Conversions$.generateRowConverterFunction(Conversions.scala:98)
> at org.apache.flink.table.planner.DataStreamConversions$.getConversionMapper(DataStreamConversions.scala:135)
> at org.apache.flink.table.planner.DataStreamConversions$.convert(DataStreamConversions.scala:91)
> {code}
> {color:red}Above inconsistent problem also exists in `Floor`, `Ceil`, `Mod` and so on. {color}
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