本文整理汇总了Python中lib.membase.api.rest_client.RestConnection.get_running_eventing_apps方法的典型用法代码示例。如果您正苦于以下问题：Python RestConnection.get_running_eventing_apps方法的具体用法？Python RestConnection.get_running_eventing_apps怎么用？Python RestConnection.get_running_eventing_apps使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类lib.membase.api.rest_client.RestConnection的用法示例。
在下文中一共展示了RestConnection.get_running_eventing_apps方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: EventingBaseTest
# 需要导入模块: from lib.membase.api.rest_client import RestConnection [as 别名]
# 或者: from lib.membase.api.rest_client.RestConnection import get_running_eventing_apps [as 别名]
#.........这里部分代码省略.........
# body['settings']['rbacuser'] = rbacuser
body['settings']['skip_timer_threshold'] = skip_timer_threshold
body['settings']['sock_batch_size'] = sock_batch_size
body['settings']['tick_duration'] = tick_duration
body['settings']['timer_processing_tick_interval'] = timer_processing_tick_interval
body['settings']['timer_worker_pool_size'] = timer_worker_pool_size
body['settings']['worker_count'] = worker_count
body['settings']['processing_status'] = processing_status
body['settings']['cpp_worker_thread_count'] = cpp_worker_thread_count
body['settings']['execution_timeout'] = execution_timeout
body['settings']['data_chan_size'] = data_chan_size
body['settings']['worker_queue_cap'] = worker_queue_cap
# See MB-27967, the reason for adding this config
body['settings']['use_memory_manager'] = self.use_memory_manager
# since deadline_timeout has to always greater than execution_timeout
if execution_timeout != 3:
deadline_timeout = execution_timeout + 1
body['settings']['deadline_timeout'] = deadline_timeout
body['settings']['timer_storage_chan_size'] = self.timer_storage_chan_size
return body
def wait_for_bootstrap_to_complete(self, name, iterations=20):
result = self.rest.get_deployed_eventing_apps()
count = 0
while name not in result and count < iterations:
self.sleep(30, message="Waiting for eventing node to come out of bootstrap state...")
count += 1
result = self.rest.get_deployed_eventing_apps()
if count == iterations:
raise Exception(
'Eventing took lot of time to come out of bootstrap state or did not successfully bootstrap')
def wait_for_undeployment(self, name, iterations=20):
result = self.rest.get_running_eventing_apps()
count = 0
while name in result and count < iterations:
self.sleep(30, message="Waiting for undeployment of function...")
count += 1
result = self.rest.get_deployed_eventing_apps()
if count == iterations:
raise Exception('Eventing took lot of time to undeploy')
def verify_eventing_results(self, name, expected_dcp_mutations, doc_timer_events=False, on_delete=False,
skip_stats_validation=False, bucket=None, timeout=600):
# This resets the rest server as the previously used rest server might be out of cluster due to rebalance
num_nodes = self.refresh_rest_server()
eventing_nodes = self.get_nodes_from_services_map(service_type="eventing", get_all_nodes=True)
if bucket is None:
bucket=self.dst_bucket_name
if not skip_stats_validation:
# we can't rely on DCP_MUTATION stats when doc timers events are set.
# TODO : add this back when getEventProcessingStats works reliably for doc timer events as well
if not doc_timer_events:
count = 0
if num_nodes <= 1:
stats = self.rest.get_event_processing_stats(name)
else:
stats = self.rest.get_aggregate_event_processing_stats(name)
if on_delete:
mutation_type = "DCP_DELETION"
else:
mutation_type = "DCP_MUTATION"
actual_dcp_mutations = stats[mutation_type]
# This is required when binary data is involved where DCP_MUTATION will have process DCP_MUTATIONS
# but ignore it
# wait for eventing node to process dcp mutations