KurtYoung commented on a change in pull request #8435:
[FLINK-12443][table-planner-blink] Replace InternalType with LogicalType in
blink
URL: https://github.com/apache/flink/pull/8435#discussion_r290568761
##########
File path:
flink-table/flink-table-planner-blink/src/main/scala/org/apache/flink/table/calcite/FlinkTypeFactory.scala
##########
@@ -406,78 +416,76 @@ object FlinkTypeFactory {
case _ => false
}
- def toInternalType(relDataType: RelDataType): InternalType =
relDataType.getSqlTypeName match {
- case BOOLEAN => InternalTypes.BOOLEAN
- case TINYINT => InternalTypes.BYTE
- case SMALLINT => InternalTypes.SHORT
- case INTEGER => InternalTypes.INT
- case BIGINT => InternalTypes.LONG
- case FLOAT => InternalTypes.FLOAT
- case DOUBLE => InternalTypes.DOUBLE
- case VARCHAR | CHAR => InternalTypes.STRING
- case VARBINARY | BINARY => InternalTypes.BINARY
- case DECIMAL => InternalTypes.createDecimalType(relDataType.getPrecision,
relDataType.getScale)
-
- // time indicators
- case TIMESTAMP if relDataType.isInstanceOf[TimeIndicatorRelDataType] =>
- val indicator = relDataType.asInstanceOf[TimeIndicatorRelDataType]
- if (indicator.isEventTime) {
- InternalTypes.ROWTIME_INDICATOR
- } else {
- InternalTypes.PROCTIME_INDICATOR
- }
-
- // temporal types
- case DATE => InternalTypes.DATE
- case TIME => InternalTypes.TIME
- case TIMESTAMP => InternalTypes.TIMESTAMP
- case typeName if YEAR_INTERVAL_TYPES.contains(typeName) =>
InternalTypes.INTERVAL_MONTHS
- case typeName if DAY_INTERVAL_TYPES.contains(typeName) =>
InternalTypes.INTERVAL_MILLIS
-
- case NULL =>
- throw new TableException(
- "Type NULL is not supported. Null values must have a supported type.")
-
- // symbol for special flags e.g. TRIM's BOTH, LEADING, TRAILING
- // are represented as Enum
- case SYMBOL => InternalTypes.createGenericType(classOf[Enum[_]])
-
- // extract encapsulated Type
- case ANY if relDataType.isInstanceOf[GenericRelDataType] =>
- val genericRelDataType = relDataType.asInstanceOf[GenericRelDataType]
- genericRelDataType.genericType
-
- case ROW if relDataType.isInstanceOf[RowRelDataType] =>
- val compositeRelDataType = relDataType.asInstanceOf[RowRelDataType]
- compositeRelDataType.rowType
-
- case ROW if relDataType.isInstanceOf[RelRecordType] =>
- val relRecordType = relDataType.asInstanceOf[RelRecordType]
- new RowSchema(relRecordType).internalType
-
- case MULTISET if relDataType.isInstanceOf[MultisetRelDataType] =>
- val multisetRelDataType = relDataType.asInstanceOf[MultisetRelDataType]
- multisetRelDataType.multisetType
-
- case ARRAY if relDataType.isInstanceOf[ArrayRelDataType] =>
- val arrayRelDataType = relDataType.asInstanceOf[ArrayRelDataType]
- arrayRelDataType.arrayType
-
- case MAP if relDataType.isInstanceOf[MapRelDataType] =>
- val mapRelDataType = relDataType.asInstanceOf[MapRelDataType]
- mapRelDataType.mapType
+ def toLogicalType(relDataType: RelDataType): LogicalType = {
+ val logicalType = relDataType.getSqlTypeName match {
+ case BOOLEAN => new BooleanType()
+ case TINYINT => new TinyIntType()
+ case SMALLINT => new SmallIntType()
+ case INTEGER => new IntType()
+ case BIGINT => new BigIntType()
+ case FLOAT => new FloatType()
+ case DOUBLE => new DoubleType()
+ case VARCHAR | CHAR => new VarCharType(VarCharType.MAX_LENGTH)
Review comment:
for VARCHAR, i think we should respect the precision
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