Source code for hive_operator

# -*- 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
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
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# limitations under the License.
import re

from airflow.hooks.hive_hooks import HiveCliHook
from airflow.models import BaseOperator
from airflow.utils.decorators import apply_defaults
from airflow.utils.operator_helpers import context_to_airflow_vars

[docs]class HiveOperator(BaseOperator): """ Executes hql code in a specific Hive database. :param hql: the hql to be executed :type hql: string :param hive_cli_conn_id: reference to the Hive database :type hive_cli_conn_id: string :param hiveconf_jinja_translate: when True, hiveconf-type templating ${var} gets translated into jinja-type templating {{ var }}. Note that you may want to use this along with the ``DAG(user_defined_macros=myargs)`` parameter. View the DAG object documentation for more details. :type hiveconf_jinja_translate: boolean :param script_begin_tag: If defined, the operator will get rid of the part of the script before the first occurrence of `script_begin_tag` :type script_begin_tag: str :param mapred_queue: queue used by the Hadoop CapacityScheduler :type mapred_queue: string :param mapred_queue_priority: priority within CapacityScheduler queue. Possible settings include: VERY_HIGH, HIGH, NORMAL, LOW, VERY_LOW :type mapred_queue_priority: string :param mapred_job_name: This name will appear in the jobtracker. This can make monitoring easier. :type mapred_job_name: string """ template_fields = ('hql', 'schema') template_ext = ('.hql', '.sql',) ui_color = '#f0e4ec' @apply_defaults def __init__( self, hql, hive_cli_conn_id='hive_cli_default', schema='default', hiveconf_jinja_translate=False, script_begin_tag=None, run_as_owner=False, mapred_queue=None, mapred_queue_priority=None, mapred_job_name=None, *args, **kwargs): super(HiveOperator, self).__init__(*args, **kwargs) self.hiveconf_jinja_translate = hiveconf_jinja_translate self.hql = hql self.schema = schema self.hive_cli_conn_id = hive_cli_conn_id self.script_begin_tag = script_begin_tag self.run_as = None if run_as_owner: self.run_as = self.dag.owner self.mapred_queue = mapred_queue self.mapred_queue_priority = mapred_queue_priority self.mapred_job_name = mapred_job_name def get_hook(self): return HiveCliHook( hive_cli_conn_id=self.hive_cli_conn_id, run_as=self.run_as, mapred_queue=self.mapred_queue, mapred_queue_priority=self.mapred_queue_priority, mapred_job_name=self.mapred_job_name) def prepare_template(self): if self.hiveconf_jinja_translate: self.hql = re.sub( "(\$\{([ a-zA-Z0-9_]*)\})", "{{ \g<2> }}", self.hql) if self.script_begin_tag and self.script_begin_tag in self.hql: self.hql = "\n".join(self.hql.split(self.script_begin_tag)[1:]) def execute(self, context):'Executing: %s', self.hql) self.hook = self.get_hook() self.hook.run_cli(hql=self.hql, schema=self.schema, hive_conf=context_to_airflow_vars(context)) def dry_run(self): self.hook = self.get_hook() self.hook.test_hql(hql=self.hql) def on_kill(self): self.hook.kill()