code: def read_table(
      name: str, index_col: Optional[Union[str, List[str]]] = None
  ) -> DataFrame:
      """
      Read a Spark table and return a DataFrame.
  
      Parameters
      ----------
      name : string
          Table name in Spark.
  
      index_col : str or list of str, optional, default: None
          Index column of table in Spark.
  
      Returns
      -------
      DataFrame
  
      See Also
      --------
      DataFrame.to_table
      read_delta
      read_parquet
      read_spark_io
  
      Examples
      --------
      >>> ps.range(1).to_table('%s.my_table' % db)
      >>> ps.read_table('%s.my_table' % db)
         id
      0   0
  
      >>> ps.range(1).to_table('%s.my_table' % db, index_col="index")
      >>> ps.read_table('%s.my_table' % db, index_col="index")  # doctest: +NORMALIZE_WHITESPACE
             id
      index
      0       0
      """
      if index_col is None:
          log_advice(
              "If `index_col` is not specified for `read_table`, "
              "the default index is attached which can cause additional overhead."
          )
      sdf = default_session().read.table(name)
      index_spark_columns, index_names = _get_index_map(sdf, index_col)
  
      return DataFrame(
          InternalFrame(
              spark_frame=sdf,
              index_spark_columns=index_spark_columns,
              index_names=index_names,
          )
      )
  
imports: from typing import Any, Callable, Dict, List, Optional, Set, Sized, Tuple, Type, Union, cast, no_type_check
  from collections.abc import Iterable
  from datetime import tzinfo
  from functools import reduce
  from io import BytesIO
  import json
  import warnings
  import numpy
  import pandas
  from pandas.api.types import is_datetime64_dtype, is_list_like
  from pandas.tseries.offsets import DateOffset
  import pyarrow
  import pyarrow.parquet
  from pyspark.sql import functions, Column
  from pyspark.sql.functions import pandas_udf
  from pyspark.sql.types import ByteType, ShortType, IntegerType, LongType, FloatType, DoubleType, BooleanType, TimestampType, TimestampNTZType, DecimalType, StringType, DateType, StructType, DataType
  from pyspark.sql.dataframe import DataFrame
  from pyspark import pandas
  from pyspark.pandas._typing import Axis, Dtype, Label, Name
  from pyspark.pandas.base import IndexOpsMixin
  from pyspark.pandas.utils import align_diff_frames, default_session, is_name_like_tuple, is_name_like_value, name_like_string, same_anchor, scol_for, validate_axis, log_advice
  from pyspark.pandas.frame import DataFrame, _reduce_spark_multi
  from pyspark.pandas.internal import InternalFrame, DEFAULT_SERIES_NAME, HIDDEN_COLUMNS, SPARK_INDEX_NAME_FORMAT
  from pyspark.pandas.series import Series, first_series
  from pyspark.pandas.spark.utils import as_nullable_spark_type, force_decimal_precision_scale
  from pyspark.pandas.indexes import Index, DatetimeIndex, TimedeltaIndex
  from pyspark.pandas.indexes.multi import MultiIndex
  from pyspark.sql.utils import get_column_class
label_desc: Use image node_id 6 for calling a global function with example usage: read_table(name, index_col) and returns: DataFrame