hi,jark:
Thanks for your explanation. I am doing the integration of flink and
iceberg. The iceberg partition needs to be of accurate type, and I cannot
modify it.
I will follow what you suggestion, get the column type by schema, and then
do the cast.
Jark Wu 于2021年1月5日周二 下午3:05写道：
> Hi Jun,
>
Hi Jun,
AFAIK, the main reason to use Map is because it's easy for
serialization and deserialization.
For example, if we use Java `LocalDateTime` instead of String to represent
TIMESTAMP partition value,
then users may deserialize into Java `Timestamp` to Flink framework, which
may cause problems.
hi ,Jack:
If the partition type is int and we pass in a string type, the system will
throw an exception that the type does not match. We can indeed cast by get
the schema, but I think if CatalogPartitionSpec#partitionSpec is of type
Map, there is no need to do cast operation, and the
universal and
Hi Jun,
I'm curious why it doesn't work when represented in string?
You can get the field type from the CatalogTable#getSchema(),
then parse/cast the partition value to the type you want.
Best,
Jark
On Tue, 5 Jan 2021 at 13:43, Jun Zhang wrote:
> Hello dev:
> Now I encounter a problem w
Hello dev:
Now I encounter a problem when using the method
"Catalog#listPartitions(ObjectPath, CatalogPartitionSpec)".
I found that the partitionSpec type in CatalogPartitionSpec is
Map,
This is no problem for hivecatalog, but my subclass of Catalog needs
precise types. For example,
