wuchong commented on a change in pull request #10667: [FLINK-15313][table] Fix
can't insert decimal data into sink using TypeInformation
URL: https://github.com/apache/flink/pull/10667#discussion_r361116539
##########
File path:
flink-table/flink-table-planner-blink/src/main/scala/org/apache/flink/table/planner/sinks/TableSinkUtils.scala
##########
@@ -18,67 +18,99 @@
package org.apache.flink.table.planner.sinks
-import org.apache.flink.table.api.ValidationException
-import org.apache.flink.table.catalog.ObjectIdentifier
+import org.apache.flink.api.java.tuple.{Tuple2 => JTuple2}
+import org.apache.flink.api.java.typeutils.{GenericTypeInfo, TupleTypeInfo}
+import org.apache.flink.api.scala.typeutils.CaseClassTypeInfo
+import org.apache.flink.table.api.{TableException, TableSchema, Types,
ValidationException}
+import org.apache.flink.table.catalog.{CatalogTable, ObjectIdentifier}
+import org.apache.flink.table.dataformat.BaseRow
import org.apache.flink.table.operations.CatalogSinkModifyOperation
-import
org.apache.flink.table.runtime.types.LogicalTypeDataTypeConverter.fromDataTypeToLogicalType
-import org.apache.flink.table.runtime.types.PlannerTypeUtils
-import org.apache.flink.table.sinks.{PartitionableTableSink, TableSink}
+import org.apache.flink.table.planner.calcite.FlinkTypeFactory
+import org.apache.flink.table.planner.plan.utils.RelOptUtils
+import org.apache.flink.table.sinks._
+import org.apache.flink.table.types.DataType
+import
org.apache.flink.table.types.inference.TypeTransformations.{legacyDecimalToDefaultDecimal,
toNullable}
+import org.apache.flink.table.types.logical.utils.{LogicalTypeCasts,
LogicalTypeChecks}
+import org.apache.flink.table.types.logical.{LegacyTypeInformationType,
RowType}
+import org.apache.flink.table.types.utils.DataTypeUtils
+import
org.apache.flink.table.types.utils.TypeConversions.{fromLegacyInfoToDataType,
fromLogicalToDataType}
+import org.apache.flink.table.utils.{TableSchemaUtils, TypeMappingUtils}
+import org.apache.flink.types.Row
+import org.apache.calcite.rel.RelNode
import scala.collection.JavaConversions._
object TableSinkUtils {
/**
- * Checks if the given [[CatalogSinkModifyOperation]]'s query can be
written to
- * the given [[TableSink]]. It checks if the names & the field types match.
If the table
- * sink is a [[PartitionableTableSink]], also check that the partitions are
valid.
+ * Checks if the given query can be written into the given sink. It checks
the field types
+ * should be compatible (types should equal including precisions). If types
are not compatible,
+ * but can be implicitly casted, a cast projection will be applied.
Otherwise, an exception will
+ * be thrown.
+ *
+ * @param query the query to be checked
+ * @param sinkSchema the schema of sink to be checked
+ * @param typeFactory type factory
+ * @return the query RelNode which may be applied the implicitly cast
projection.
+ */
+ def validateSchemaAndApplyImplicitCast(
+ query: RelNode,
+ sinkSchema: TableSchema,
+ typeFactory: FlinkTypeFactory,
+ sinkIdentifier: Option[String] = None): RelNode = {
+
+ val queryLogicalType = DataTypeUtils
+ // convert type to nullable, because we ignore nullability when writing
query into sink
Review comment:
It is equivalent no matter `toNullable` or not, because if the nullability
is not the same, we will add a implicit cast. The purpose to ignore nullable at
earlier stage is in order to avoid cast project as much as possible, otherwise,
we have to update a lot of XML plan files.
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