code: def get_column(
      record_batch: pa.RecordBatch,
      feature_name: types.FeatureName,
      missing_ok: bool = False,
  ) -> Optional[pa.Array]:
      """Get a column by feature name.
  
      Args:
        record_batch: A pa.RecordBatch.
        feature_name: The name of a feature (column) within record_batch.
        missing_ok: If True, returns None for missing feature names.
  
      Returns:
        The column with the specified name, or None if missing_ok is true and
        a column with the specified name is missing, or more than one exist.
  
      Raises:
        KeyError: If a column with the specified name is missing, or more than
        one exist, and missing_ok is False.
      """
      idx = record_batch.schema.get_field_index(feature_name)
      if idx < 0:
          if missing_ok:
              return None
          raise KeyError("missing column %s" % feature_name)
      return record_batch.column(idx)
  
file_path: data-validation/tensorflow_data_validation/arrow/arrow_util.py
imports: from typing import Callable, Dict, Iterable, Optional, Text, Tuple
  import numpy
  import pyarrow
  from tensorflow_data_validation import types
  from tensorflow_data_validation.utils.example_weight_map import ExampleWeightMap
  from tfx_bsl.arrow import array_util
label_desc: Use image node_id 5 for calling a global function with example usage: get_column(record_batch, feature_name, missing_ok) and returns: record_batch, None