Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/21847#discussion_r206369093
--- Diff:
external/avro/src/main/scala/org/apache/spark/sql/avro/AvroSerializer.scala ---
@@ -165,16 +182,118 @@ class AvroSerializer(rootCatalystType: DataType,
rootAvroType: Schema, nullable:
result
}
- private def resolveNullableType(avroType: Schema, nullable: Boolean):
Schema = {
- if (nullable) {
+ // Resolve an Avro union against a supplied DataType, i.e. a LongType
compared against
+ // a ["null", "long"] should return a schema of type Schema.Type.LONG
+ // This function also handles resolving a DataType against unions of 2
or more types, i.e.
+ // an IntType resolves against a ["int", "long", "null"] will correctly
return a schema of
+ // type Schema.Type.LONG
+ private def resolveUnionType(avroType: Schema, catalystType: DataType,
+ nullable: Boolean): Schema = {
+ if (avroType.getType == Type.UNION) {
// avro uses union to represent nullable type.
- val fields = avroType.getTypes.asScala
- assert(fields.length == 2)
- val actualType = fields.filter(_.getType != NULL)
- assert(actualType.length == 1)
+ val fieldTypes = avroType.getTypes.asScala
+
+ // If we're nullable, we need to have at least two types. Cases
with more than two types
+ // are captured in test("read read-write, read-write w/ schema,
read") w/ test.avro input
+ if (nullable && fieldTypes.length < 2) {
+ throw new IncompatibleSchemaException(
+ s"Cannot resolve nullable ${catalystType} against union type
${avroType}")
+ }
+
+ val actualType = catalystType match {
+ case NullType => fieldTypes.filter(_.getType == Type.NULL)
+ case BooleanType => fieldTypes.filter(_.getType == Type.BOOLEAN)
+ case ByteType => fieldTypes.filter(_.getType == Type.INT)
+ case BinaryType =>
+ val at = fieldTypes.filter(x => x.getType == Type.BYTES ||
x.getType == Type.FIXED)
+ if (at.length > 1) {
--- End diff --
Do we need this check here? Seems L242 check will also handle the case?
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