Thanks for your reply Yaroslav! The way I do it with Avro seems similar to what you pointed out: ResolvedSchema resultSchema = resultTable.getResolvedSchema(); DataType type = resultSchema.toSinkRowDataType(); org.apache.avro.Schema converted = AvroSchemaConverter.convertToSchema(type.getLogicalType()); I mentioned the ResolvedSchema because it is my starting point after the SQL operation. It seemed to me that I can not retrieve something that contains more schema information from the table so I got myself this. About your other answers: It seems the classes you mentioned can be used to serialize actual Data? However this is not quite what I want to do. Essentially I want to convert the schema of a Flink table to both Protobuf schema and JSON schema (for Avro as you can see I have it already). It seems odd that this is not easily possible, because converting from a JSON schema to a Schema of Flink is possible using the JsonRowSchemaConverter. However the other way is not implemented it seems. This is how I got a Table Schema (that I can use in a table descriptor) from a JSON schema:
TypeInformation<Row> type = JsonRowSchemaConverter.convert(json); DataType row = TableSchema.fromTypeInfo(type).toPhysicalRowDataType(); Schema schema = Schema.newBuilder().fromRowDataType(row).build(); Sidenote: I use deprecated methods here, so if there is a better approach please let me know! But it shows that in Flink its easily possible to create a Schema for a TableDescriptor from a JSON Schema - the other way is just not so trivial it seems. And for Protobuf so far I don’t have any solutions, not even creating a Flink Schema from a Protobuf Schema - not to mention the other way around. -Theo (resent because I accidentally only responded to you, not the Mailing list - sorry)
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