code: def read(
      self, table: TableCatalogEntry, batch_mem_size: int = 30000000
  ) -> Iterator[Batch]:
      try:
          db_catalog_entry = self._get_database_catalog_entry(
              table.database_name
          )
          with get_database_handler(
              db_catalog_entry.engine, **db_catalog_entry.params
          ) as handler:
              handler_response = handler.select(table.name)
              # we prefer the generator/iterator when available
              result = []
              if handler_response.data_generator:
                  result = handler_response.data_generator
              elif handler_response.data:
                  result = handler_response.data
  
              if handler.is_sqlalchmey_compatible():
                  # For sql data source, we can deserialize sql rows into numpy array
                  cols = result[0]._fields
                  index_dict = {
                      element.lower(): index
                      for index, element in enumerate(cols)
                  }
                  try:
                      ordered_columns = sorted(
                          table.columns,
                          key=lambda x: index_dict[x.name.lower()],
                      )
                  except KeyError as e:
                      raise Exception(f"Column mismatch with error {e}")
                  result = (
                      _deserialize_sql_row(row, ordered_columns)
                      for row in result
                  )
  
              for df in rebatch(result, batch_mem_size):
                  yield Batch(pd.DataFrame(df))
  
      except Exception as e:
          err_msg = f"Failed to read the table {table.name} in data source {table.database_name} with exception {str(e)}"
          logger.exception(err_msg)
          raise Exception(err_msg)
  
imports: from typing import Iterator, List
  import numpy
  import pandas
  from sqlalchemy import Column, MetaData, Table, create_engine
  from sqlalchemy.ext.declarative import declarative_base
  from sqlalchemy.orm import sessionmaker
  from evadb.catalog.catalog_type import ColumnType
  from evadb.catalog.models.table_catalog import TableCatalogEntry
  from evadb.catalog.models.utils import ColumnCatalogEntry
  from evadb.catalog.schema_utils import SchemaUtils
  from evadb.database import EvaDBDatabase
  from evadb.models.storage.batch import Batch
  from evadb.storage.abstract_storage_engine import AbstractStorageEngine
  from evadb.third_party.databases.interface import get_database_handler
  from evadb.utils.generic_utils import PickleSerializer, rebatch
  from evadb.utils.logging_manager import logger
label_desc: Use image node_id 5 for calling the NativeStorageEngine obj's underlying member method code with example usage: obj.read(table, batch_mem_size) without return types