def testGetQueueName(self): self.assertEqual("foo", util.get_queue_name("foo")) os.environ["HTTP_X_APPENGINE_QUEUENAME"] = "foo" self.assertEqual("foo", util.get_queue_name(None)) os.environ["HTTP_X_APPENGINE_QUEUENAME"] = "__cron" self.assertEqual(parameters.config.QUEUE_NAME, util.get_queue_name(None))
def start_map(name, handler_spec, reader_spec, mapper_parameters, shard_count=None, output_writer_spec=None, mapreduce_parameters=None, base_path=None, queue_name=None, eta=None, countdown=None, hooks_class_name=None, _app=None, in_xg_transaction=False): """Start a new, mapper-only mapreduce. Args: name: mapreduce name. Used only for display purposes. handler_spec: fully qualified name of mapper handler function/class to call. reader_spec: fully qualified name of mapper reader to use mapper_parameters: dictionary of parameters to pass to mapper. These are mapper-specific and also used for reader initialization. shard_count: number of shards to create. mapreduce_parameters: dictionary of mapreduce parameters relevant to the whole job. base_path: base path of mapreduce library handler specified in app.yaml. "/mapreduce" by default. queue_name: taskqueue queue name to be used for mapreduce tasks. see util.get_queue_name. eta: absolute time when the MR should execute. May not be specified if 'countdown' is also supplied. This may be timezone-aware or timezone-naive. countdown: time in seconds into the future that this MR should execute. Defaults to zero. hooks_class_name: fully qualified name of a hooks.Hooks subclass. in_xg_transaction: controls what transaction scope to use to start this MR job. If True, there has to be an already opened cross-group transaction scope. MR will use one entity group from it. If False, MR will create an independent transaction to start the job regardless of any existing transaction scopes. Returns: mapreduce id as string. """ if shard_count is None: shard_count = parameters.config.SHARD_COUNT if base_path is None: base_path = parameters.config.BASE_PATH if mapper_parameters: mapper_parameters = dict(mapper_parameters) if mapreduce_parameters: mapreduce_parameters = dict(mapreduce_parameters) if "base_path" not in mapreduce_parameters: mapreduce_parameters["base_path"] = base_path else: mapreduce_parameters = {"base_path": base_path} mapper_spec = model.MapperSpec(handler_spec, reader_spec, mapper_parameters, shard_count, output_writer_spec=output_writer_spec) if in_xg_transaction and not db.is_in_transaction(): logging.warning("Expects an opened xg transaction to start mapreduce " "when transactional is True.") return handlers.StartJobHandler._start_map( name, mapper_spec, mapreduce_parameters, queue_name=util.get_queue_name(queue_name), eta=eta, countdown=countdown, hooks_class_name=hooks_class_name, _app=_app, in_xg_transaction=in_xg_transaction)
def start_map(name, handler_spec, reader_spec, mapper_parameters, shard_count=None, output_writer_spec=None, mapreduce_parameters=None, base_path=None, queue_name=None, eta=None, countdown=None, hooks_class_name=None, _app=None, in_xg_transaction=False): """Start a new, mapper-only mapreduce. Deprecated! Use map_job.start instead. If a value can be specified both from an explicit argument and from a dictionary, the value from the explicit argument wins. Args: name: mapreduce name. Used only for display purposes. handler_spec: fully qualified name of mapper handler function/class to call. reader_spec: fully qualified name of mapper reader to use mapper_parameters: dictionary of parameters to pass to mapper. These are mapper-specific and also used for reader/writer initialization. Should have format {"input_reader": {}, "output_writer":{}}. Old deprecated style does not have sub dictionaries. shard_count: number of shards to create. mapreduce_parameters: dictionary of mapreduce parameters relevant to the whole job. base_path: base path of mapreduce library handler specified in app.yaml. "/mapreduce" by default. queue_name: taskqueue queue name to be used for mapreduce tasks. see util.get_queue_name. eta: absolute time when the MR should execute. May not be specified if 'countdown' is also supplied. This may be timezone-aware or timezone-naive. countdown: time in seconds into the future that this MR should execute. Defaults to zero. hooks_class_name: fully qualified name of a hooks.Hooks subclass. in_xg_transaction: controls what transaction scope to use to start this MR job. If True, there has to be an already opened cross-group transaction scope. MR will use one entity group from it. If False, MR will create an independent transaction to start the job regardless of any existing transaction scopes. Returns: mapreduce id as string. """ if shard_count is None: shard_count = parameters.config.SHARD_COUNT if mapper_parameters: mapper_parameters = dict(mapper_parameters) # Make sure this old API fill all parameters with default values. mr_params = map_job.JobConfig._get_default_mr_params() if mapreduce_parameters: mr_params.update(mapreduce_parameters) # Override default values if user specified them as arguments. if base_path: mr_params["base_path"] = base_path mr_params["queue_name"] = util.get_queue_name(queue_name) mapper_spec = model.MapperSpec(handler_spec, reader_spec, mapper_parameters, shard_count, output_writer_spec=output_writer_spec) if in_xg_transaction and not db.is_in_transaction(): log.warning("Expects an opened xg transaction to start mapreduce " "when transactional is True.") return handlers.StartJobHandler._start_map( name, mapper_spec, mr_params, # TODO(user): Now that "queue_name" is part of mr_params. # Remove all the other ways to get queue_name after one release. queue_name=mr_params["queue_name"], eta=eta, countdown=countdown, hooks_class_name=hooks_class_name, _app=_app, in_xg_transaction=in_xg_transaction)
def start_map(name, handler_spec, reader_spec, mapper_parameters, shard_count=None, output_writer_spec=None, mapreduce_parameters=None, base_path=None, queue_name=None, eta=None, countdown=None, hooks_class_name=None, _app=None, in_xg_transaction=False): """Start a new, mapper-only mapreduce. Args: name: mapreduce name. Used only for display purposes. handler_spec: fully qualified name of mapper handler function/class to call. reader_spec: fully qualified name of mapper reader to use mapper_parameters: dictionary of parameters to pass to mapper. These are mapper-specific and also used for reader initialization. shard_count: number of shards to create. mapreduce_parameters: dictionary of mapreduce parameters relevant to the whole job. base_path: base path of mapreduce library handler specified in app.yaml. "/mapreduce" by default. queue_name: taskqueue queue name to be used for mapreduce tasks. see util.get_queue_name. eta: absolute time when the MR should execute. May not be specified if 'countdown' is also supplied. This may be timezone-aware or timezone-naive. countdown: time in seconds into the future that this MR should execute. Defaults to zero. hooks_class_name: fully qualified name of a hooks.Hooks subclass. in_xg_transaction: controls what transaction scope to use to start this MR job. If True, there has to be an already opened cross-group transaction scope. MR will use one entity group from it. If False, MR will create an independent transaction to start the job regardless of any existing transaction scopes. Returns: mapreduce id as string. """ if shard_count is None: shard_count = parameters.DEFAULT_SHARD_COUNT if base_path is None: # pylint: disable=protected-access base_path = parameters._DEFAULT_BASE_PATH if mapper_parameters: mapper_parameters = dict(mapper_parameters) if mapreduce_parameters: mapreduce_parameters = dict(mapreduce_parameters) mapper_spec = model.MapperSpec(handler_spec, reader_spec, mapper_parameters, shard_count, output_writer_spec=output_writer_spec) if in_xg_transaction and not db.is_in_transaction(): logging.warning("Expects an opened xg transaction to start mapreduce " "when transactional is True.") return handlers.StartJobHandler._start_map( name, mapper_spec, mapreduce_parameters or {}, base_path=base_path, queue_name=util.get_queue_name(queue_name), eta=eta, countdown=countdown, hooks_class_name=hooks_class_name, _app=_app, in_xg_transaction=in_xg_transaction)
def start_map(name, handler_spec, reader_spec, mapper_parameters, shard_count=None, output_writer_spec=None, mapreduce_parameters=None, base_path=None, queue_name=None, eta=None, countdown=None, hooks_class_name=None, _app=None, in_xg_transaction=False): """Start a new, mapper-only mapreduce. Deprecated! Use map_job.start instead. If a value can be specified both from an explicit argument and from a dictionary, the value from the explicit argument wins. Args: name: mapreduce name. Used only for display purposes. handler_spec: fully qualified name of mapper handler function/class to call. reader_spec: fully qualified name of mapper reader to use mapper_parameters: dictionary of parameters to pass to mapper. These are mapper-specific and also used for reader/writer initialization. Should have format {"input_reader": {}, "output_writer":{}}. Old deprecated style does not have sub dictionaries. shard_count: number of shards to create. mapreduce_parameters: dictionary of mapreduce parameters relevant to the whole job. base_path: base path of mapreduce library handler specified in app.yaml. "/mapreduce" by default. queue_name: taskqueue queue name to be used for mapreduce tasks. see util.get_queue_name. eta: absolute time when the MR should execute. May not be specified if 'countdown' is also supplied. This may be timezone-aware or timezone-naive. countdown: time in seconds into the future that this MR should execute. Defaults to zero. hooks_class_name: fully qualified name of a hooks.Hooks subclass. in_xg_transaction: controls what transaction scope to use to start this MR job. If True, there has to be an already opened cross-group transaction scope. MR will use one entity group from it. If False, MR will create an independent transaction to start the job regardless of any existing transaction scopes. Returns: mapreduce id as string. """ if shard_count is None: shard_count = parameters.config.SHARD_COUNT if mapper_parameters: mapper_parameters = dict(mapper_parameters) # Make sure this old API fill all parameters with default values. mr_params = map_job.JobConfig._get_default_mr_params() if mapreduce_parameters: mr_params.update(mapreduce_parameters) # Override default values if user specified them as arguments. if base_path: mr_params["base_path"] = base_path mr_params["queue_name"] = util.get_queue_name(queue_name) mapper_spec = model.MapperSpec(handler_spec, reader_spec, mapper_parameters, shard_count, output_writer_spec=output_writer_spec) if in_xg_transaction and not db.is_in_transaction(): logging.warning("Expects an opened xg transaction to start mapreduce " "when transactional is True.") return handlers.StartJobHandler._start_map( name, mapper_spec, mr_params, # TODO(user): Now that "queue_name" is part of mr_params. # Remove all the other ways to get queue_name after one release. queue_name=mr_params["queue_name"], eta=eta, countdown=countdown, hooks_class_name=hooks_class_name, _app=_app, in_xg_transaction=in_xg_transaction)