danny0405 commented on a change in pull request #13763:
URL: https://github.com/apache/flink/pull/13763#discussion_r513264987
##########
File path:
flink-formats/flink-avro/src/main/java/org/apache/flink/formats/avro/typeutils/AvroSchemaConverter.java
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@@ -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:
>Excuse me, but I wholeheartedly disagree with your statement. null =/=
(null, null). (null, null) is still NOT NULL. A whole row in a Table can not be
null. Only particular columns can be null. Therefore the top level row of a
Table is always NOT NULL.
You can test it in PostgreSQL with the following SQL:
```sql
create type my_type as (a int, b varchar(20));
create table t1(
f0 my_type,
f1 varchar(20)
);
insert into t1 values((null, null), 'def');
select f0 is null from t1; -- it returns true
```
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