dawidwys commented on a change in pull request #13763:
URL: https://github.com/apache/flink/pull/13763#discussion_r512596226
##########
File path:
flink-formats/flink-avro/src/main/java/org/apache/flink/formats/avro/typeutils/AvroSchemaConverter.java
##########
@@ -297,17 +299,22 @@ private static DataType convertToDataType(Schema schema) {
* @return Avro's {@link Schema} matching this logical type.
*/
public static Schema convertToSchema(LogicalType logicalType) {
- return convertToSchema(logicalType, "record");
+ return convertToSchema(logicalType, "record", true);
}
/**
* Converts Flink SQL {@link LogicalType} (can be nested) into an Avro
schema.
*
* @param logicalType logical type
* @param rowName the record name
+ * @param top whether it is parsing the root record,
+ * if it is, the logical type nullability would be
ignored
* @return Avro's {@link Schema} matching this logical type.
*/
- public static Schema convertToSchema(LogicalType logicalType, String
rowName) {
+ public static Schema convertToSchema(
+ LogicalType logicalType,
+ String rowName,
+ boolean top) {
Review comment:
Is it necessary? Shouldn't the `top` be handled in the planner and just
passed with a correct setting in the `logicalType`? I think it is a bit too
deep to fix it here.
##########
File path:
flink-formats/flink-avro/src/test/java/org/apache/flink/formats/avro/AvroRowDataDeSerializationSchemaTest.java
##########
@@ -181,10 +181,11 @@ public void testSpecificType() throws Exception {
encoder.flush();
byte[] input = byteArrayOutputStream.toByteArray();
+ // SE/DE SpecificRecord using the GenericRecord way only
supports non-nullable data type.
Review comment:
That comment is misleading. There is no limitation in the actual
handling of nulls with SpecificRecord/GenericRecord.
It's just that the `LogicalTimeRecord` has those fields declared as
`notNull`. The previous `dataType` was just wrong and did not describe the
`LogicalTimeRecord` correctly.
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