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# to you under the Apache License, Version 2.0 (the
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from __future__ import annotations
import os
import re
from functools import cached_property
from typing import TYPE_CHECKING, Any, Sequence
from airflow.configuration import conf
from airflow.models import BaseOperator
from airflow.providers.apache.hive.hooks.hive import HiveCliHook
from airflow.utils import operator_helpers
from airflow.utils.operator_helpers import context_to_airflow_vars
if TYPE_CHECKING:
from airflow.utils.context import Context
[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)
:param hive_cli_conn_id: Reference to the
:ref:`Hive CLI connection id <howto/connection:hive_cli>`. (templated)
:param hiveconfs: if defined, these key value pairs will be passed
to hive as ``-hiveconf "key"="value"``
: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.
: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`
:param mapred_queue: queue used by the Hadoop CapacityScheduler. (templated)
:param mapred_queue_priority: priority within CapacityScheduler queue.
Possible settings include: VERY_HIGH, HIGH, NORMAL, LOW, VERY_LOW
:param mapred_job_name: This name will appear in the jobtracker.
This can make monitoring easier.
:param hive_cli_params: parameters passed to hive CLO
:param auth: optional authentication option passed for the Hive connection
:param proxy_user: Run HQL code as this user.
"""
[docs] template_fields: Sequence[str] = (
"hql",
"schema",
"hive_cli_conn_id",
"mapred_queue",
"hiveconfs",
"mapred_job_name",
"mapred_queue_priority",
"proxy_user",
)
[docs] template_ext: Sequence[str] = (
".hql",
".sql",
)
[docs] template_fields_renderers = {"hql": "hql"}
def __init__(
self,
*,
hql: str,
hive_cli_conn_id: str = "hive_cli_default",
schema: str = "default",
hiveconfs: dict[Any, Any] | None = None,
hiveconf_jinja_translate: bool = False,
script_begin_tag: str | None = None,
mapred_queue: str | None = None,
mapred_queue_priority: str | None = None,
mapred_job_name: str | None = None,
hive_cli_params: str = "",
auth: str | None = None,
proxy_user: str | None = None,
**kwargs: Any,
) -> None:
super().__init__(**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.mapred_queue = mapred_queue
self.mapred_queue_priority = mapred_queue_priority
self.mapred_job_name = mapred_job_name
self.hive_cli_params = hive_cli_params
self.auth = auth
self.proxy_user = proxy_user
job_name_template = conf.get_mandatory_value(
"hive",
"mapred_job_name_template",
fallback="Airflow HiveOperator task for {hostname}.{dag_id}.{task_id}.{execution_date}",
)
self.mapred_job_name_template: str = job_name_template
@cached_property
[docs] def hook(self) -> HiveCliHook:
"""Get Hive cli hook."""
return HiveCliHook(
hive_cli_conn_id=self.hive_cli_conn_id,
mapred_queue=self.mapred_queue,
mapred_queue_priority=self.mapred_queue_priority,
mapred_job_name=self.mapred_job_name,
hive_cli_params=self.hive_cli_params,
auth=self.auth,
proxy_user=self.proxy_user,
)
[docs] def prepare_template(self) -> None:
if self.hiveconf_jinja_translate:
self.hql = re.sub(r"(\$\{(hiveconf:)?([ a-zA-Z0-9_]*)\})", r"{{ \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:])
[docs] def execute(self, context: Context) -> None:
self.log.info("Executing: %s", self.hql)
# 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"]
if ti.execution_date is None:
raise RuntimeError("execution_date is None")
self.hook.mapred_job_name = self.mapred_job_name_template.format(
dag_id=ti.dag_id,
task_id=ti.task_id,
execution_date=ti.execution_date.isoformat(),
hostname=ti.hostname.split(".")[0],
)
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)
[docs] def dry_run(self) -> None:
# Reset airflow environment variables to prevent
# existing env vars from impacting behavior.
self.clear_airflow_vars()
self.hook.test_hql(hql=self.hql)
[docs] def on_kill(self) -> None:
if self.hook:
self.hook.kill()
[docs] def clear_airflow_vars(self) -> None:
"""Reset airflow environment variables to prevent existing ones from impacting behavior."""
blank_env_vars = {
value["env_var_format"]: "" for value in operator_helpers.AIRFLOW_VAR_NAME_FORMAT_MAPPING.values()
}
os.environ.update(blank_env_vars)
