class_docstr: Base class for handling outputs of the UDF.
class_docstr_tok: ["Base","class","for","handling","outputs","of","the","UDF","."]
docstr: Ingests data to the output feature group.
  
  Args:
      output (T): The output of the feature_processor wrapped function.
      fp_config (FeatureProcessorConfig): The configuration for the feature_processor.
docstr_tok: ["Ingests","data","to","the","output","feature","group",".","Args",":","output","(","T",")",":","The","output","of","the","feature_processor","wrapped","function",".","fp_config","(","FeatureProcessorConfig",")",":","The","configuration","for","the","feature_processor","."]
code: def ingest_udf_output(
      self, output: T, fp_config: FeatureProcessorConfig
  ) -> None:
      """Ingests data to the output feature group.
  
      Args:
          output (T): The output of the feature_processor wrapped function.
          fp_config (FeatureProcessorConfig): The configuration for the feature_processor.
      """
  
file_path: sagemaker-python-sdk/src/sagemaker/feature_store/feature_processor/_udf_output_receiver.py
imports: from __future__ import absolute_import
  import logging
  from abc import ABC, abstractmethod
  from typing import Generic, TypeVar
  import attr
  from py4j.protocol import Py4JJavaError
  from pyspark.sql import DataFrame
  from sagemaker.feature_store.feature_processor import IngestionError
  from sagemaker.feature_store.feature_processor._feature_processor_config import FeatureProcessorConfig
  from sagemaker.feature_store.feature_processor._spark_factory import FeatureStoreManagerFactory
label_desc: Use image node_id 1 for calling the UDFOutputReceiver obj's underlying member method code with example usage: obj.ingest_udf_output(output, fp_config) without return types