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  # to you under the Apache License, Version 2.0 (the
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  """This module contains an operator to move data from MSSQL to Hive."""
  
  from collections import OrderedDict
  from tempfile import NamedTemporaryFile
  from typing import TYPE_CHECKING, Dict, Optional, Sequence
  
  import pymssql
  import unicodecsv as csv
  
  from airflow.models import BaseOperator
  from airflow.providers.apache.hive.hooks.hive import HiveCliHook
  from airflow.providers.microsoft.mssql.hooks.mssql import MsSqlHook
  
  if TYPE_CHECKING:
      from airflow.utils.context import Context
  
  
  class MsSqlToHiveOperator(BaseOperator):
      """
      Moves data from Microsoft SQL Server to Hive. The operator runs
      your query against Microsoft SQL Server, stores the file locally
      before loading it into a Hive table. If the ``create`` or
      ``recreate`` arguments are set to ``True``,
      a ``CREATE TABLE`` and ``DROP TABLE`` statements are generated.
      Hive data types are inferred from the cursor's metadata.
      Note that the table generated in Hive uses ``STORED AS textfile``
      which isn't the most efficient serialization format. If a
      large amount of data is loaded and/or if the table gets
      queried considerably, you may want to use this operator only to
      stage the data into a temporary table before loading it into its
      final destination using a ``HiveOperator``.
  
      :param sql: SQL query to execute against the Microsoft SQL Server
          database. (templated)
      :param hive_table: target Hive table, use dot notation to target a specific
          database. (templated)
      :param create: whether to create the table if it doesn't exist
      :param recreate: whether to drop and recreate the table at every execution
      :param partition: target partition as a dict of partition columns and
          values. (templated)
      :param delimiter: field delimiter in the file
      :param mssql_conn_id: source Microsoft SQL Server connection
      :param hive_cli_conn_id: Reference to the
          :ref:`Hive CLI connection id <howto/connection:hive_cli>`.
      :param tblproperties: TBLPROPERTIES of the hive table being created
      """
  
      template_fields: Sequence[str] = ('sql', 'partition', 'hive_table')
      template_ext: Sequence[str] = ('.sql',)
      template_fields_renderers = {'sql': 'tsql'}
      ui_color = '#a0e08c'
  
      def __init__(
          self,
          *,
          sql: str,
          hive_table: str,
          create: bool = True,
          recreate: bool = False,
          partition: Optional[Dict] = None,
          delimiter: str = chr(1),
          mssql_conn_id: str = 'mssql_default',
          hive_cli_conn_id: str = 'hive_cli_default',
          tblproperties: Optional[Dict] = None,
          **kwargs,
      ) -> None:
          super().__init__(**kwargs)
          self.sql = sql
          self.hive_table = hive_table
          self.partition = partition
          self.create = create
          self.recreate = recreate
          self.delimiter = delimiter
          self.mssql_conn_id = mssql_conn_id
          self.hive_cli_conn_id = hive_cli_conn_id
          self.partition = partition or {}
          self.tblproperties = tblproperties
  
      @classmethod
      def type_map(cls, mssql_type: int) -> str:
          """Maps MsSQL type to Hive type."""
          map_dict = {
              pymssql.BINARY.value: 'INT',
              pymssql.DECIMAL.value: 'FLOAT',
              pymssql.NUMBER.value: 'INT',
          }
          return map_dict.get(mssql_type, 'STRING')
  
      def execute(self, context: "Context"):
          mssql = MsSqlHook(mssql_conn_id=self.mssql_conn_id)
          self.log.info("Dumping Microsoft SQL Server query results to local file")
          with mssql.get_conn() as conn:
              with conn.cursor() as cursor:
                  cursor.execute(self.sql)
                  with NamedTemporaryFile("w") as tmp_file:
                      csv_writer = csv.writer(tmp_file, delimiter=self.delimiter, encoding='utf-8')
                      field_dict = OrderedDict()
                      col_count = 0
                      for field in cursor.description:
                          col_count += 1
                          col_position = f"Column{col_count}"
                          field_dict[col_position if field[0] == '' else field[0]] = self.type_map(field[1])
                      csv_writer.writerows(cursor)
                      tmp_file.flush()
  
              hive = HiveCliHook(hive_cli_conn_id=self.hive_cli_conn_id)
              self.log.info("Loading file into Hive")
              hive.load_file(
                  tmp_file.name,
                  self.hive_table,
                  field_dict=field_dict,
                  create=self.create,
                  partition=self.partition,
                  delimiter=self.delimiter,
                  recreate=self.recreate,
                  tblproperties=self.tblproperties,
              )
  