code: def _native_vector_index_scan(self):
      search_feat = self._get_search_query_results()
      search_feat = search_feat.reshape(-1).tolist()
  
      tb_catalog_entry = list(self.node.find_all(StoragePlan))[0].table
      db_catalog_entry = self.db.catalog().get_database_catalog_entry(
          tb_catalog_entry.database_name
      )
      with get_database_handler(
          db_catalog_entry.engine, **db_catalog_entry.params
      ) as handler:
          resp = handler.execute_native_query(
              f"""SELECT * FROM {tb_catalog_entry.name}
                                                  ORDER BY {self.feat_column.name} <-> '{search_feat}'
                                                  LIMIT {self.limit_count}"""
          )
          if resp.error is not None:
              raise ExecutorError(
                  f"Native index can encounters {resp.error}"
              )
          res = Batch(frames=resp.data)
          res.modify_column_alias(tb_catalog_entry.name)
          yield res
  
imports: from typing import Iterator
  import pandas
  from evadb.catalog.models.utils import VectorStoreType
  from evadb.catalog.sql_config import ROW_NUM_COLUMN
  from evadb.database import EvaDBDatabase
  from evadb.executor.abstract_executor import AbstractExecutor
  from evadb.executor.executor_utils import ExecutorError, handle_vector_store_params
  from evadb.models.storage.batch import Batch
  from evadb.plan_nodes.storage_plan import StoragePlan
  from evadb.plan_nodes.vector_index_scan_plan import VectorIndexScanPlan
  from evadb.third_party.databases.interface import get_database_handler
  from evadb.third_party.vector_stores.types import VectorIndexQuery
  from evadb.third_party.vector_stores.utils import VectorStoreFactory
  from evadb.utils.logging_manager import logger
label_desc: Use image node_id 4 for calling the VectorIndexScanExecutor obj's underlying member method code with example usage: obj._native_vector_index_scan() without return types