danny0405 commented on a change in pull request #13763:
URL: https://github.com/apache/flink/pull/13763#discussion_r513370899
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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:
I had offline discussion with @wuchong and @dawidwys , and after some
research, we found that a non-nullable row type is more reasonable.
But because the change is huge(many codes that convert a type info to data
type assumes nullable true before), me and @wuchong decide to change the method
signature to `convertToSchema(RowType schema)` and add a notion to the method
doc that the passed in `schema` must be the top level record type.
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