src/etl/examples/hive-example/dags/acme/operators/hive_operators.py
# -*- coding: utf-8 -*-
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import logging
from tempfile import NamedTemporaryFile
import unicodecsv as csv
from collections import OrderedDict
import time
from airflow.hooks.postgres_hook import PostgresHook
from acme.hooks.hive_hooks import HiveCliHook
from airflow.models import BaseOperator
from airflow.utils.decorators import apply_defaults
from datetime import datetime
class PostgresToHiveOperator(BaseOperator):
"""
Moves data from Postgres to Hive. The operator runs your query against
Postgres, 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
:type sql: str
:param hive_table: target Hive table, use dot notation to target a
specific database
: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
: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
"""
template_fields = ('sql', 'parameters', 'partition', 'hive_table')
template_ext = ('.sql',)
ui_color = '#ededed'
@apply_defaults
def __init__(
self,
sql,
hive_table,
create=True,
recreate=False,
partition=None,
delimiter=chr(1),
postgres_conn_id='postgres_default',
hive_cli_conn_id='hive_cli_default',
parameters=None,
*args, **kwargs):
super(PostgresToHiveOperator, self).__init__(*args, **kwargs)
self.sql = sql
self.parameters = parameters
self.hive_table = hive_table
self.partition = partition
self.create = create
self.recreate = recreate
self.delimiter = str(delimiter)
self.postgres_conn_id = postgres_conn_id
self.hive_cli_conn_id = hive_cli_conn_id
self.partition = partition or {}
@classmethod
def type_map(cls, postgres_type):
d = {
16: 'STRING', # BOOL
20: 'INT',
21: 'INT',
23: 'INT',
700: 'DOUBLE',
701: 'DOUBLE',
1114: 'TIMESTAMP',
1082: 'DATE',
1043: 'STRING',
705: 'STRING'
}
if postgres_type not in d:
raise Exception('Unrecognized data type {0}'.format(postgres_type))
return d[postgres_type]
def execute(self, context):
hive = HiveCliHook(hive_cli_conn_id=self.hive_cli_conn_id)
pg = PostgresHook(postgres_conn_id=self.postgres_conn_id)
logging.info("Dumping postgres query results to local file")
conn = pg.get_conn()
cursor = conn.cursor()
cursor.execute(self.sql, self.parameters)
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()
logging.info("Loading file into Hive")
hive.load_file(
f.name,
self.hive_table,
field_dict=field_dict,
create=self.create,
partition=self.partition,
delimiter=self.delimiter,
recreate=self.recreate)