def __init__(self, _proj: str, _exp: str, appConf: Dict[str, str] = None):
super(DistributedTestManager, self).__init__(_proj, _exp)
EdasEnv.update(appConf)
log_metrics = appConf.get("log_metrics", False)
self.processManager = ProcessManager.initManager(EdasEnv.parms)
time.sleep(10)
self.processing = False
self.scheduler_info = self.processManager.client.scheduler_info()
self.workers: Dict = self.scheduler_info.pop("workers")
self.logger.info(" @@@@@@@ SCHEDULER INFO: " +
str(self.scheduler_info))
self.logger.info(f" N Workers: {len(self.workers)} ")
for addr, specs in self.workers.items():
self.logger.info(f" -----> Worker {addr}: {specs}")
if log_metrics:
self.metricsThread = Thread(target=self.trackCwtMetrics)
self.metricsThread.start()
variable = "t"
domains = [{"name": "d0"}]
variables = [{
"uri": f"collection://{collection}:",
"name": f"{variable}:v0",
"domain": "d0"
}]
operations = [{"name": "xarray.ave", "input": "v0", "axes": "t"}]
local = True
scheduler = "127.0.0.1:8786"
if __name__ == '__main__':
print(f"Running test")
appConf = {"sources.allowed": "collection,https", "log.metrics": "true"}
EdasEnv.update(appConf)
if local:
print(f"Initializing Local Dask cluster")
client = Client()
else:
if scheduler is None:
cluster = EDASCluster()
print(
"Initializing Dask-distributed cluster with scheduler address: "
+ cluster.scheduler_address)
client = Client(cluster.scheduler_address, timeout=64)
time.sleep(20)
else:
print("Initializing client with existing scheduler at: " +
scheduler)
def __init__(self, _proj: str, _exp: str, appConf: Dict[str, str] = None):
super(LocalTestManager, self).__init__(_proj, _exp)
EdasEnv.update(appConf)
self.processManager = ProcessManager.initManager(EdasEnv.parms)
def __init__(self, _proj: str, _exp: str, appConf: Dict[str, str] = None):
super(LocalTestManager, self).__init__(_proj, _exp)
EdasEnv.update(appConf)
