docstr: Intakes a raw SQL query and returns the answer given by the ML engine. 
docstr_tok: ["Intakes","a","raw","SQL","query","and","returns","the","answer","given","by","the","ML","engine","."]
code: def native_query(self, query: str) -> Response:
      """Intakes a raw SQL query and returns the answer given by the ML engine."""
      query_ast = self.parser(query, dialect=self.dialect)
      return self.query(query_ast)
  
imports: import socket
  import datetime
  from typing import Optional
  import pandas
  from sqlalchemy import func, null
  from sqlalchemy.sql.functions import coalesce
  from mindsdb_sql import parse_sql
  from mindsdb.utilities.config import Config
  import mindsdb.interfaces.storage.db
  from mindsdb.integrations.libs.response import HandlerResponse, RESPONSE_TYPE
  from mindsdb.__about__ import __version__
  from mindsdb.utilities.hooks import after_predict
  from mindsdb.interfaces.model.model_controller import ModelController
  from mindsdb.interfaces.model.functions import get_model_record
  from mindsdb.integrations.libs.const import PREDICTOR_STATUS
  from mindsdb.interfaces.database.database import DatabaseController
  from mindsdb.interfaces.storage.model_fs import ModelStorage, HandlerStorage
  from mindsdb.utilities.context import context
  from mindsdb.interfaces.model.functions import get_model_records
  from mindsdb.utilities.functions import mark_process
  import mindsdb.utilities.profiler
  from mindsdb.utilities.ml_task_queue.producer import MLTaskProducer
  from mindsdb.utilities.ml_task_queue.const import ML_TASK_TYPE
  from mindsdb.integrations.libs.process_cache import process_cache, empty_callback
label_desc: Use image node_id 5 for calling the BaseMLEngineExec obj's underlying member method code with example usage: obj.native_query(query) and returns: self