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:py:mod:`airflow.providers.google.cloud.operators.looker`
=========================================================
.. py:module:: airflow.providers.google.cloud.operators.looker
.. autoapi-nested-parse::
This module contains Google Cloud Looker operators.
Module Contents
---------------
Classes
~~~~~~~
.. autoapisummary::
airflow.providers.google.cloud.operators.looker.LookerStartPdtBuildOperator
.. py:class:: LookerStartPdtBuildOperator(looker_conn_id, model, view, query_params = None, asynchronous = False, cancel_on_kill = True, wait_time = 10, wait_timeout = None, **kwargs)
Bases: :py:obj:`airflow.models.BaseOperator`
Submits a PDT materialization job to Looker.
:param looker_conn_id: Required. The connection ID to use connecting to Looker.
:param model: Required. The model of the PDT to start building.
:param view: Required. The view of the PDT to start building.
:param query_params: Optional. Additional materialization parameters.
:param asynchronous: Optional. Flag indicating whether to wait for the job
to finish or return immediately.
This is useful for submitting long running jobs and
waiting on them asynchronously using the LookerCheckPdtBuildSensor
:param cancel_on_kill: Optional. Flag which indicates whether cancel the
hook's job or not, when on_kill is called.
:param wait_time: Optional. Number of seconds between checks for job to be
ready. Used only if ``asynchronous`` is False.
:param wait_timeout: Optional. How many seconds wait for job to be ready.
Used only if ``asynchronous`` is False.
.. py:method:: execute(context)
This is the main method to derive when creating an operator.
Context is the same dictionary used as when rendering jinja templates.
Refer to get_template_context for more context.
.. py:method:: on_kill()
Override this method to cleanup subprocesses when a task instance
gets killed. Any use of the threading, subprocess or multiprocessing
module within an operator needs to be cleaned up or it will leave
ghost processes behind.