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[SPARK-52651][SQL] Handle User Defined Type in Nested ColumnVector #51349

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[SPARK-52651][SQL] Handle User Defined Type in Nested ColumnVector #51349

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23 changes: 18 additions & 5 deletions sql/catalyst/src/main/java/org/apache/spark/sql/vectorized/ColumnVector.java
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Original file line number Diff line number Diff line change
Expand Up @@ -16,6 +16,8 @@
*/
package org.apache.spark.sql.vectorized;

import scala.PartialFunction;

import org.apache.spark.annotation.Evolving;
import org.apache.spark.sql.types.DataType;
import org.apache.spark.sql.types.Decimal;
Expand Down Expand Up @@ -336,10 +338,21 @@ public final VariantVal getVariant(int rowId) {
* Sets up the data type of this column vector.
*/
protected ColumnVector(DataType type) {
if (type instanceof UserDefinedType) {
this.type = ((UserDefinedType) type).sqlType();
} else {
this.type = type;
}
this.type = type.transformRecursively(
new PartialFunction<DataType, DataType>() {
@Override
public boolean isDefinedAt(DataType x) {
return x instanceof UserDefinedType<?>;
}

@Override
public DataType apply(DataType t) {
if (t instanceof UserDefinedType<?> udt) {
return udt.sqlType();
} else {
return t;
}
}
});
}
}
3 changes: 1 addition & 2 deletions ...ain/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetSchemaConverter.scala
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Expand Up @@ -196,8 +196,7 @@ class ParquetToSparkSchemaConverter(
field: ColumnIO,
sparkReadType: Option[DataType] = None): ParquetColumn = {
val targetType = sparkReadType.map {
case udt: UserDefinedType[_] => udt.sqlType
case otherType => otherType
_.transformRecursively { case t: UserDefinedType[_] => t.sqlType }
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@dongjoon-hyun dongjoon-hyun Jul 2, 2025

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Just a question. What about ORC file format?

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@yaooqinn yaooqinn Jul 2, 2025

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Hi @dongjoon-hyun, good question. I have an umbrella ticket for udt improvements. Let me check other formats or readers with followups if necessary

}
field match {
case primitiveColumn: PrimitiveColumnIO => convertPrimitiveField(primitiveColumn, targetType)
Expand Down
25 changes: 24 additions & 1 deletion sql/core/src/test/scala/org/apache/spark/sql/execution/vectorized/ColumnVectorSuite.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -18,6 +18,7 @@
package org.apache.spark.sql.execution.vectorized

import org.apache.spark.SparkFunSuite
import org.apache.spark.sql.YearUDT
import org.apache.spark.sql.catalyst.expressions.SpecificInternalRow
import org.apache.spark.sql.catalyst.plans.SQLHelper
import org.apache.spark.sql.execution.columnar.{ColumnAccessor, ColumnDictionary}
Expand Down Expand Up @@ -926,5 +927,27 @@ class ColumnVectorSuite extends SparkFunSuite with SQLHelper {
}
}
}
}

val yearUDT = new YearUDT
testVectors("user defined type", 10, yearUDT) { testVector =>
assert(testVector.dataType() === IntegerType)
(0 until 10).foreach { i =>
testVector.appendInt(i)
}
}

testVectors("user defined type in map type",
10, MapType(IntegerType, yearUDT)) { testVector =>
assert(testVector.dataType() === MapType(IntegerType, IntegerType))
}

testVectors("user defined type in array type",
10, ArrayType(yearUDT, containsNull = true)) { testVector =>
assert(testVector.dataType() === ArrayType(IntegerType, containsNull = true))
}

testVectors("user defined type in struct type",
10, StructType(Seq(StructField("year", yearUDT)))) { testVector =>
assert(testVector.dataType() === StructType(Seq(StructField("year", IntegerType))))
}
}