Source code for airflow.operators.mysql_to_hive

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from builtins import chr
from collections import OrderedDict
import unicodecsv as csv
from tempfile import NamedTemporaryFile
import MySQLdb

from airflow.hooks.hive_hooks import HiveCliHook
from airflow.hooks.mysql_hook import MySqlHook
from airflow.models import BaseOperator
from airflow.utils.decorators import apply_defaults

[docs]class MySqlToHiveTransfer(BaseOperator): """ Moves data from MySql to Hive. The operator runs your query against MySQL, 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 MySQL database. (templated) :type sql: str :param hive_table: target Hive table, use dot notation to target a specific database. (templated) :type hive_table: str :param create: whether to create the table if it doesn't exist :type create: bool :param recreate: whether to drop and recreate the table at every execution :type recreate: bool :param partition: target partition as a dict of partition columns and values. (templated) :type partition: dict :param delimiter: field delimiter in the file :type delimiter: str :param mysql_conn_id: source mysql connection :type mysql_conn_id: str :param hive_conn_id: destination hive connection :type hive_conn_id: str :param tblproperties: TBLPROPERTIES of the hive table being created :type tblproperties: dict """
[docs] template_fields = ('sql', 'partition', 'hive_table')
[docs] template_ext = ('.sql',)
[docs] ui_color = '#a0e08c'
@apply_defaults def __init__( self, sql, hive_table, create=True, recreate=False, partition=None, delimiter=chr(1), mysql_conn_id='mysql_default', hive_cli_conn_id='hive_cli_default', tblproperties=None, *args, **kwargs): super(MySqlToHiveTransfer, self).__init__(*args, **kwargs) self.sql = sql self.hive_table = hive_table self.partition = partition self.create = create self.recreate = recreate self.delimiter = str(delimiter) self.mysql_conn_id = mysql_conn_id self.hive_cli_conn_id = hive_cli_conn_id self.partition = partition or {} self.tblproperties = tblproperties @classmethod
[docs] def type_map(cls, mysql_type): t = MySQLdb.constants.FIELD_TYPE d = { t.BIT: 'INT', t.DECIMAL: 'DOUBLE', t.NEWDECIMAL: 'DOUBLE', t.DOUBLE: 'DOUBLE', t.FLOAT: 'DOUBLE', t.INT24: 'INT', t.LONG: 'BIGINT', t.LONGLONG: 'DECIMAL(38,0)', t.SHORT: 'INT', t.TINY: 'SMALLINT', t.YEAR: 'INT', t.TIMESTAMP: 'TIMESTAMP', } return d[mysql_type] if mysql_type in d else 'STRING'
[docs] def execute(self, context): hive = HiveCliHook(hive_cli_conn_id=self.hive_cli_conn_id) mysql = MySqlHook(mysql_conn_id=self.mysql_conn_id)"Dumping MySQL query results to local file") conn = mysql.get_conn() cursor = conn.cursor() cursor.execute(self.sql) with NamedTemporaryFile("wb") as f: csv_writer = csv.writer(f, delimiter=self.delimiter, encoding="utf-8") field_dict = OrderedDict() for field in cursor.description: field_dict[field[0]] = self.type_map(field[1]) csv_writer.writerows(cursor) f.flush() cursor.close() conn.close()"Loading file into Hive") hive.load_file(, self.hive_table, field_dict=field_dict, create=self.create, partition=self.partition, delimiter=self.delimiter, recreate=self.recreate, tblproperties=self.tblproperties)

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