:mod:`airflow.contrib.executors.mesos_executor` =============================================== .. py:module:: airflow.contrib.executors.mesos_executor Module Contents --------------- .. data:: DEFAULT_FRAMEWORK_NAME :annotation: = Airflow .. data:: FRAMEWORK_CONNID_PREFIX :annotation: = mesos_framework_ .. function:: get_framework_name() .. py:class:: AirflowMesosScheduler(task_queue, result_queue, task_cpu=1, task_mem=256) Bases: :class:`mesos.interface.Scheduler` Airflow Mesos scheduler implements mesos scheduler interface to schedule airflow tasks on mesos. Basically, it schedules a command like 'airflow run --local -p=' to run on a mesos slave. .. method:: registered(self, driver, frameworkId, masterInfo) .. method:: reregistered(self, driver, masterInfo) .. method:: disconnected(self, driver) .. method:: offerRescinded(self, driver, offerId) .. method:: frameworkMessage(self, driver, executorId, slaveId, message) .. method:: executorLost(self, driver, executorId, slaveId, status) .. method:: slaveLost(self, driver, slaveId) .. method:: error(self, driver, message) .. method:: resourceOffers(self, driver, offers) .. method:: statusUpdate(self, driver, update) .. py:class:: MesosExecutor Bases: :class:`airflow.executors.base_executor.BaseExecutor` MesosExecutor allows distributing the execution of task instances to multiple mesos workers. Apache Mesos is a distributed systems kernel which abstracts CPU, memory, storage, and other compute resources away from machines (physical or virtual), enabling fault-tolerant and elastic distributed systems to easily be built and run effectively. See http://mesos.apache.org/ .. method:: start(self) .. method:: execute_async(self, key, command, queue=None, executor_config=None) .. method:: sync(self) .. method:: end(self)