pyflink.datastream.stream_execution_environment.StreamExecutionEnvironment.register_type#
- StreamExecutionEnvironment.register_type(type_class_name: str)[source]#
Registers the given type with the serialization stack. If the type is eventually serialized as a POJO, then the type is registered with the POJO serializer. If the type ends up being serialized with Kryo, then it will be registered at Kryo to make sure that only tags are written.
Example:
>>> env.register_type("com.aaa.bbb.TypeClass")
- Parameters
type_class_name – The full-qualified java class name of the type to register.
Note
Deprecated since version 1.19: Register data types and serializers through hard codes is deprecated, because you need to modify the codes when upgrading job version. You should configure this by option pipeline.serialization-config.