# -*- coding: utf-8 -*-
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# to you under the Apache License, Version 2.0 (the
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#
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from __future__ import unicode_literals
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 or hive script in a specific Hive database.
:param hql: the hql to be executed. Note that you may also use
a relative path from the dag file of a (template) hive
script. (templated)
:type hql: string
:param hive_cli_conn_id: reference to the Hive database. (templated)
:type hive_cli_conn_id: string
:param hiveconfs: if defined, these key value pairs will be passed
to hive as ``-hiveconf "key"="value"``
:type hiveconfs: dict
:param hiveconf_jinja_translate: when True, hiveconf-type templating
${var} gets translated into jinja-type templating {{ var }} and
${hiveconf: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. (templated)
: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', 'hive_cli_conn_id', 'mapred_queue',
'hiveconfs', 'mapred_job_name', 'mapred_queue_priority')
template_ext = ('.hql', '.sql',)
ui_color = '#f0e4ec'
@apply_defaults
def __init__(
self, hql,
hive_cli_conn_id='hive_cli_default',
schema='default',
hiveconfs=None,
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.hql = hql
self.hive_cli_conn_id = hive_cli_conn_id
self.schema = schema
self.hiveconfs = hiveconfs or {}
self.hiveconf_jinja_translate = hiveconf_jinja_translate
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
# assigned lazily - just for consistency we can create the attribute with a
# `None` initial value, later it will be populated by the execute method.
# This also makes `on_kill` implementation consistent since it assumes `self.hook`
# is defined.
self.hook = None
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(
"(\$\{(hiveconf:)?([ a-zA-Z0-9_]*)\})", "{{ \g<3> }}", 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):
self.log.info('Executing: %s', self.hql)
self.hook = self.get_hook()
# set the mapred_job_name if it's not set with dag, task, execution time info
if not self.mapred_job_name:
ti = context['ti']
self.hook.mapred_job_name = 'Airflow HiveOperator task for {}.{}.{}.{}'\
.format(ti.hostname.split('.')[0], ti.dag_id, ti.task_id,
ti.execution_date.isoformat())
if self.hiveconf_jinja_translate:
self.hiveconfs = context_to_airflow_vars(context)
else:
self.hiveconfs.update(context_to_airflow_vars(context))
self.log.info('Passing HiveConf: %s', self.hiveconfs)
self.hook.run_cli(hql=self.hql, schema=self.schema, hive_conf=self.hiveconfs)
def dry_run(self):
self.hook = self.get_hook()
self.hook.test_hql(hql=self.hql)
def on_kill(self):
if self.hook:
self.hook.kill()