def test_usgs_integration(self):
'''
test_usgs_integration
Test full DM Services Integration using usgs
'''
cc = self.container
assertions = self.assertTrue
#-----------------------------
# Copy below here
#-----------------------------
pubsub_management_service = PubsubManagementServiceClient(node=cc.node)
ingestion_management_service = IngestionManagementServiceClient(node=cc.node)
dataset_management_service = DatasetManagementServiceClient(node=cc.node)
data_retriever_service = DataRetrieverServiceClient(node=cc.node)
transform_management_service = TransformManagementServiceClient(node=cc.node)
process_dispatcher = ProcessDispatcherServiceClient(node=cc.node)
process_list = []
datasets = []
datastore_name = 'test_usgs_integration'
#---------------------------
# Set up ingestion
#---------------------------
# Configure ingestion using eight workers, ingesting to test_dm_integration datastore with the SCIDATA profile
log.debug('Calling create_ingestion_configuration')
ingestion_configuration_id = ingestion_management_service.create_ingestion_configuration(
exchange_point_id='science_data',
couch_storage=CouchStorage(datastore_name=datastore_name,datastore_profile='SCIDATA'),
number_of_workers=8
)
#
ingestion_management_service.activate_ingestion_configuration(
ingestion_configuration_id=ingestion_configuration_id)
usgs_stream_def = USGS_stream_definition()
stream_def_id = pubsub_management_service.create_stream_definition(container=usgs_stream_def, name='Junk definition')
#---------------------------
# Set up the producers (CTD Simulators)
#---------------------------
# Launch five simulated CTD producers
for iteration in xrange(2):
# Make a stream to output on
stream_id = pubsub_management_service.create_stream(stream_definition_id=stream_def_id)
#---------------------------
# Set up the datasets
#---------------------------
dataset_id = dataset_management_service.create_dataset(
stream_id=stream_id,
datastore_name=datastore_name,
view_name='datasets/stream_join_granule'
)
# Keep track of the datasets
datasets.append(dataset_id)
stream_policy_id = ingestion_management_service.create_dataset_configuration(
dataset_id = dataset_id,
archive_data = True,
archive_metadata = True,
ingestion_configuration_id = ingestion_configuration_id
)
producer_definition = ProcessDefinition()
producer_definition.executable = {
'module':'ion.agents.eoi.handler.usgs_stream_publisher',
'class':'UsgsPublisher'
}
configuration = {
'process':{
'stream_id':stream_id,
}
}
procdef_id = process_dispatcher.create_process_definition(process_definition=producer_definition)
log.debug('LUKE_DEBUG: procdef_id: %s', procdef_id)
pid = process_dispatcher.schedule_process(process_definition_id=procdef_id, configuration=configuration)
# Keep track, we'll kill 'em later.
process_list.append(pid)
# Get about 4 seconds of data
time.sleep(4)
#---------------------------
# Stop producing data
#---------------------------
for process in process_list:
process_dispatcher.cancel_process(process)
#----------------------------------------------
# The replay and the transform, a love story.
#----------------------------------------------
# Happy Valentines to the clever coder who catches the above!
transform_definition = ProcessDefinition()
transform_definition.executable = {
'module':'ion.processes.data.transforms.transform_example',
'class':'TransformCapture'
}
transform_definition_id = process_dispatcher.create_process_definition(process_definition=transform_definition)
dataset_id = datasets.pop() # Just need one for now
replay_id, stream_id = data_retriever_service.define_replay(dataset_id=dataset_id)
#--------------------------------------------
# I'm Selling magazine subscriptions here!
#--------------------------------------------
subscription = pubsub_management_service.create_subscription(query=StreamQuery(stream_ids=[stream_id]),
exchange_name='transform_capture_point')
#--------------------------------------------
# Start the transform (capture)
#--------------------------------------------
transform_id = transform_management_service.create_transform(
name='capture_transform',
in_subscription_id=subscription,
process_definition_id=transform_definition_id
)
transform_management_service.activate_transform(transform_id=transform_id)
#--------------------------------------------
# BEGIN REPLAY!
#--------------------------------------------
data_retriever_service.start_replay(replay_id=replay_id)
#--------------------------------------------
# Lets get some boundaries
#--------------------------------------------
bounds = dataset_management_service.get_dataset_bounds(dataset_id=dataset_id)
def test_dm_integration(self):
'''
test_salinity_transform
Test full DM Services Integration
'''
cc = self.container
assertions = self.assertTrue
#-----------------------------
# Copy below here to run as a script (don't forget the imports of course!)
#-----------------------------
# Create some service clients...
pubsub_management_service = PubsubManagementServiceClient(node=cc.node)
ingestion_management_service = IngestionManagementServiceClient(node=cc.node)
dataset_management_service = DatasetManagementServiceClient(node=cc.node)
data_retriever_service = DataRetrieverServiceClient(node=cc.node)
transform_management_service = TransformManagementServiceClient(node=cc.node)
process_dispatcher = ProcessDispatcherServiceClient(node=cc.node)
# declare some handy variables
datastore_name = 'test_dm_integration'
###
### In the beginning there were two stream definitions...
###
# create a stream definition for the data from the ctd simulator
ctd_stream_def = SBE37_CDM_stream_definition()
ctd_stream_def_id = pubsub_management_service.create_stream_definition(container=ctd_stream_def, name='Simulated CTD data')
# create a stream definition for the data from the salinity Transform
sal_stream_def_id = pubsub_management_service.create_stream_definition(container=SalinityTransform.outgoing_stream_def, name='Scalar Salinity data stream')
###
### And two process definitions...
###
# one for the ctd simulator...
producer_definition = ProcessDefinition()
producer_definition.executable = {
'module':'ion.processes.data.ctd_stream_publisher',
'class':'SimpleCtdPublisher'
}
ctd_sim_procdef_id = process_dispatcher.create_process_definition(process_definition=producer_definition)
# one for the salinity transform
producer_definition = ProcessDefinition()
producer_definition.executable = {
'module':'ion.processes.data.transforms.ctd.ctd_L2_salinity',
'class':'SalinityTransform'
}
salinity_transform_procdef_id = process_dispatcher.create_process_definition(process_definition=producer_definition)
#---------------------------
# Set up ingestion - this is an operator concern - not done by SA in a deployed system
#---------------------------
# Configure ingestion using eight workers, ingesting to test_dm_integration datastore with the SCIDATA profile
log.debug('Calling create_ingestion_configuration')
ingestion_configuration_id = ingestion_management_service.create_ingestion_configuration(
exchange_point_id='science_data',
couch_storage=CouchStorage(datastore_name=datastore_name,datastore_profile='SCIDATA'),
number_of_workers=1
)
#
ingestion_management_service.activate_ingestion_configuration(
ingestion_configuration_id=ingestion_configuration_id)
#---------------------------
# Set up the producer (CTD Simulator)
#---------------------------
# Create the stream
ctd_stream_id = pubsub_management_service.create_stream(stream_definition_id=ctd_stream_def_id)
# Set up the datasets
ctd_dataset_id = dataset_management_service.create_dataset(
stream_id=ctd_stream_id,
datastore_name=datastore_name,
view_name='datasets/stream_join_granule'
)
# Configure ingestion of this dataset
ctd_dataset_config_id = ingestion_management_service.create_dataset_configuration(
dataset_id = ctd_dataset_id,
archive_data = True,
archive_metadata = True,
ingestion_configuration_id = ingestion_configuration_id, # you need to know the ingestion configuration id!
)
# Hold onto ctd_dataset_config_id if you want to stop/start ingestion of that dataset by the ingestion service
#---------------------------
# Set up the salinity transform
#---------------------------
# Create the stream
sal_stream_id = pubsub_management_service.create_stream(stream_definition_id=sal_stream_def_id)
# Set up the datasets
sal_dataset_id = dataset_management_service.create_dataset(
stream_id=sal_stream_id,
datastore_name=datastore_name,
view_name='datasets/stream_join_granule'
)
# Configure ingestion of the salinity as a dataset
sal_dataset_config_id = ingestion_management_service.create_dataset_configuration(
dataset_id = sal_dataset_id,
archive_data = True,
archive_metadata = True,
ingestion_configuration_id = ingestion_configuration_id, # you need to know the ingestion configuration id!
)
# Hold onto sal_dataset_config_id if you want to stop/start ingestion of that dataset by the ingestion service
# Create a subscription as input to the transform
sal_transform_input_subscription_id = pubsub_management_service.create_subscription(
query = StreamQuery(stream_ids=[ctd_stream_id,]),
exchange_name='salinity_transform_input') # how do we make these names??? i.e. Should they be anonymous?
# create the salinity transform
sal_transform_id = transform_management_service.create_transform(
name='example salinity transform',
in_subscription_id=sal_transform_input_subscription_id,
out_streams={'output':sal_stream_id,},
process_definition_id = salinity_transform_procdef_id,
# no configuration needed at this time...
)
# start the transform - for a test case it makes sense to do it before starting the producer but it is not required
transform_management_service.activate_transform(transform_id=sal_transform_id)
# Start the ctd simulator to produce some data
configuration = {
'process':{
'stream_id':ctd_stream_id,
}
}
ctd_sim_pid = process_dispatcher.schedule_process(process_definition_id=ctd_sim_procdef_id, configuration=configuration)
###
### Make a subscriber in the test to listen for salinity data
###
salinity_subscription_id = pubsub_management_service.create_subscription(
query=StreamQuery([sal_stream_id,]),
exchange_name = 'salinity_test',
name = "test salinity subscription",
)
pid = cc.spawn_process(name='dummy_process_for_test',
module='pyon.ion.process',
cls='SimpleProcess',
config={})
dummy_process = cc.proc_manager.procs[pid]
subscriber_registrar = StreamSubscriberRegistrar(process=dummy_process, node=cc.node)
result = gevent.event.AsyncResult()
results = []
def message_received(message, headers):
# Heads
log.warn('Salinity data received!')
results.append(message)
if len(results) >3:
result.set(True)
subscriber = subscriber_registrar.create_subscriber(exchange_name='salinity_test', callback=message_received)
subscriber.start()
# after the queue has been created it is safe to activate the subscription
pubsub_management_service.activate_subscription(subscription_id=salinity_subscription_id)
# Assert that we have received data
assertions(result.get(timeout=10))
# stop the flow parse the messages...
process_dispatcher.cancel_process(ctd_sim_pid) # kill the ctd simulator process - that is enough data
for message in results:
psd = PointSupplementStreamParser(stream_definition=SalinityTransform.outgoing_stream_def, stream_granule=message)
# Test the handy info method for the names of fields in the stream def
assertions('salinity' in psd.list_field_names())
# you have to know the name of the coverage in stream def
salinity = psd.get_values('salinity')
import numpy
assertions(isinstance(salinity, numpy.ndarray))
assertions(numpy.nanmin(salinity) > 0.0) # salinity should always be greater than 0
def test_replay_integration(self):
'''
test_replay_integration
'''
import numpy as np
# Keep the import it's used in the vector comparison below even though pycharm says its unused.
cc = self.container
XP = self.XP
assertions = self.assertTrue
### Every thing below here can be run as a script:
log.debug('Got it')
pubsub_management_service = PubsubManagementServiceClient(node=cc.node)
ingestion_management_service = IngestionManagementServiceClient(node=cc.node)
dataset_management_service = DatasetManagementServiceClient(node=cc.node)
data_retriever_service = DataRetrieverServiceClient(node=cc.node)
datastore_name = 'dm_test_replay_integration'
producer = Publisher(name=(XP,'stream producer'))
ingestion_configuration_id = ingestion_management_service.create_ingestion_configuration(
exchange_point_id=XP,
couch_storage=CouchStorage(datastore_name=datastore_name,datastore_profile='SCIDATA'),
hdf_storage=HdfStorage(),
number_of_workers=1
)
ingestion_management_service.activate_ingestion_configuration(
ingestion_configuration_id=ingestion_configuration_id
)
definition = SBE37_CDM_stream_definition()
data_stream_id = definition.data_stream_id
encoding_id = definition.identifiables[data_stream_id].encoding_id
element_count_id = definition.identifiables[data_stream_id].element_count_id
stream_def_id = pubsub_management_service.create_stream_definition(
container=definition
)
stream_id = pubsub_management_service.create_stream(
stream_definition_id=stream_def_id
)
dataset_id = dataset_management_service.create_dataset(
stream_id=stream_id,
datastore_name=datastore_name,
view_name='datasets/dataset_by_id'
)
ingestion_management_service.create_dataset_configuration(
dataset_id=dataset_id,
archive_data=True,
archive_metadata=True,
ingestion_configuration_id = ingestion_configuration_id
)
definition.stream_resource_id = stream_id
packet = _create_packet(definition)
input_file = FileSystem.mktemp()
input_file.write(packet.identifiables[data_stream_id].values)
input_file_path = input_file.name
input_file.close()
fields=[
'conductivity',
'height',
'latitude',
'longitude',
'pressure',
'temperature',
'time'
]
input_vectors = acquire_data([input_file_path],fields , 2).next()
producer.publish(msg=packet, to_name=(XP,'%s.data' % stream_id))
replay_id, replay_stream_id = data_retriever_service.define_replay(dataset_id)
ar = gevent.event.AsyncResult()
def sub_listen(msg, headers):
assertions(isinstance(msg,StreamGranuleContainer),'replayed message is not a granule.')
hdf_string = msg.identifiables[data_stream_id].values
sha1 = hashlib.sha1(hdf_string).hexdigest().upper()
assertions(sha1 == msg.identifiables[encoding_id].sha1,'Checksum failed.')
assertions(msg.identifiables[element_count_id].value==1, 'record replay count is incorrect %d.' % msg.identifiables[element_count_id].value)
output_file = FileSystem.mktemp()
output_file.write(msg.identifiables[data_stream_id].values)
output_file_path = output_file.name
output_file.close()
output_vectors = acquire_data([output_file_path],fields,2).next()
for field in fields:
comparison = (input_vectors[field]['values']==output_vectors[field]['values'])
assertions(comparison.all(), 'vector mismatch: %s vs %s' %
(input_vectors[field]['values'],output_vectors[field]['values']))
FileSystem.unlink(output_file_path)
ar.set(True)
subscriber = Subscriber(name=(XP,'replay listener'),callback=sub_listen)
g = gevent.Greenlet(subscriber.listen, binding='%s.data' % replay_stream_id)
g.start()
data_retriever_service.start_replay(replay_id)
ar.get(timeout=10)
FileSystem.unlink(input_file_path)
def test_dm_integration(self):
'''
test_salinity_transform
Test full DM Services Integration
'''
cc = self.container
assertions = self.assertTrue
#-----------------------------
# Copy below here to run as a script (don't forget the imports of course!)
#-----------------------------
# Create some service clients...
pubsub_management_service = PubsubManagementServiceClient(node=cc.node)
ingestion_management_service = IngestionManagementServiceClient(
node=cc.node)
dataset_management_service = DatasetManagementServiceClient(
node=cc.node)
data_retriever_service = DataRetrieverServiceClient(node=cc.node)
transform_management_service = TransformManagementServiceClient(
node=cc.node)
process_dispatcher = ProcessDispatcherServiceClient(node=cc.node)
# declare some handy variables
datastore_name = 'test_dm_integration'
###
### In the beginning there were two stream definitions...
###
# create a stream definition for the data from the ctd simulator
ctd_stream_def = SBE37_CDM_stream_definition()
ctd_stream_def_id = pubsub_management_service.create_stream_definition(
container=ctd_stream_def, name='Simulated CTD data')
# create a stream definition for the data from the salinity Transform
sal_stream_def_id = pubsub_management_service.create_stream_definition(
container=SalinityTransform.outgoing_stream_def,
name='Scalar Salinity data stream')
###
### And two process definitions...
###
# one for the ctd simulator...
producer_definition = ProcessDefinition()
producer_definition.executable = {
'module': 'ion.processes.data.ctd_stream_publisher',
'class': 'SimpleCtdPublisher'
}
ctd_sim_procdef_id = process_dispatcher.create_process_definition(
process_definition=producer_definition)
# one for the salinity transform
producer_definition = ProcessDefinition()
producer_definition.executable = {
'module': 'ion.processes.data.transforms.ctd.ctd_L2_salinity',
'class': 'SalinityTransform'
}
salinity_transform_procdef_id = process_dispatcher.create_process_definition(
process_definition=producer_definition)
#---------------------------
# Set up ingestion - this is an operator concern - not done by SA in a deployed system
#---------------------------
# Configure ingestion using eight workers, ingesting to test_dm_integration datastore with the SCIDATA profile
log.debug('Calling create_ingestion_configuration')
ingestion_configuration_id = ingestion_management_service.create_ingestion_configuration(
exchange_point_id='science_data',
couch_storage=CouchStorage(datastore_name=datastore_name,
datastore_profile='SCIDATA'),
number_of_workers=1)
#
ingestion_management_service.activate_ingestion_configuration(
ingestion_configuration_id=ingestion_configuration_id)
#---------------------------
# Set up the producer (CTD Simulator)
#---------------------------
# Create the stream
ctd_stream_id = pubsub_management_service.create_stream(
stream_definition_id=ctd_stream_def_id)
# Set up the datasets
ctd_dataset_id = dataset_management_service.create_dataset(
stream_id=ctd_stream_id,
datastore_name=datastore_name,
view_name='datasets/stream_join_granule')
# Configure ingestion of this dataset
ctd_dataset_config_id = ingestion_management_service.create_dataset_configuration(
dataset_id=ctd_dataset_id,
archive_data=True,
archive_metadata=True,
ingestion_configuration_id=
ingestion_configuration_id, # you need to know the ingestion configuration id!
)
# Hold onto ctd_dataset_config_id if you want to stop/start ingestion of that dataset by the ingestion service
#---------------------------
# Set up the salinity transform
#---------------------------
# Create the stream
sal_stream_id = pubsub_management_service.create_stream(
stream_definition_id=sal_stream_def_id)
# Set up the datasets
sal_dataset_id = dataset_management_service.create_dataset(
stream_id=sal_stream_id,
datastore_name=datastore_name,
view_name='datasets/stream_join_granule')
# Configure ingestion of the salinity as a dataset
sal_dataset_config_id = ingestion_management_service.create_dataset_configuration(
dataset_id=sal_dataset_id,
archive_data=True,
archive_metadata=True,
ingestion_configuration_id=
ingestion_configuration_id, # you need to know the ingestion configuration id!
)
# Hold onto sal_dataset_config_id if you want to stop/start ingestion of that dataset by the ingestion service
# Create a subscription as input to the transform
sal_transform_input_subscription_id = pubsub_management_service.create_subscription(
query=StreamQuery(stream_ids=[
ctd_stream_id,
]),
exchange_name='salinity_transform_input'
) # how do we make these names??? i.e. Should they be anonymous?
# create the salinity transform
sal_transform_id = transform_management_service.create_transform(
name='example salinity transform',
in_subscription_id=sal_transform_input_subscription_id,
out_streams={
'output': sal_stream_id,
},
process_definition_id=salinity_transform_procdef_id,
# no configuration needed at this time...
)
# start the transform - for a test case it makes sense to do it before starting the producer but it is not required
transform_management_service.activate_transform(
transform_id=sal_transform_id)
# Start the ctd simulator to produce some data
configuration = {
'process': {
'stream_id': ctd_stream_id,
}
}
ctd_sim_pid = process_dispatcher.schedule_process(
process_definition_id=ctd_sim_procdef_id,
configuration=configuration)
###
### Make a subscriber in the test to listen for salinity data
###
salinity_subscription_id = pubsub_management_service.create_subscription(
query=StreamQuery([
sal_stream_id,
]),
exchange_name='salinity_test',
name="test salinity subscription",
)
pid = cc.spawn_process(name='dummy_process_for_test',
module='pyon.ion.process',
cls='SimpleProcess',
config={})
dummy_process = cc.proc_manager.procs[pid]
subscriber_registrar = StreamSubscriberRegistrar(process=dummy_process,
node=cc.node)
result = gevent.event.AsyncResult()
results = []
def message_received(message, headers):
# Heads
log.warn('Salinity data received!')
results.append(message)
if len(results) > 3:
result.set(True)
subscriber = subscriber_registrar.create_subscriber(
exchange_name='salinity_test', callback=message_received)
subscriber.start()
# after the queue has been created it is safe to activate the subscription
pubsub_management_service.activate_subscription(
subscription_id=salinity_subscription_id)
# Assert that we have received data
assertions(result.get(timeout=10))
# stop the flow parse the messages...
process_dispatcher.cancel_process(
ctd_sim_pid
) # kill the ctd simulator process - that is enough data
for message in results:
psd = PointSupplementStreamParser(
stream_definition=SalinityTransform.outgoing_stream_def,
stream_granule=message)
# Test the handy info method for the names of fields in the stream def
assertions('salinity' in psd.list_field_names())
# you have to know the name of the coverage in stream def
salinity = psd.get_values('salinity')
import numpy
assertions(isinstance(salinity, numpy.ndarray))
assertions(numpy.nanmin(salinity) >
0.0) # salinity should always be greater than 0
class DMCollaborationIntTest(IonIntegrationTestCase):
def setUp(self):
self._start_container()
config = DotDict()
config.bootstrap.processes.ingestion.module = 'ion.processes.data.ingestion.ingestion_worker_a'
config.bootstrap.processes.replay.module = 'ion.processes.data.replay.replay_process_a'
self.container.start_rel_from_url('res/deploy/r2dm.yml', config)
self.datastore_name = 'test_datasets'
self.pubsub_management = PubsubManagementServiceClient()
self.ingestion_management = IngestionManagementServiceClient()
self.dataset_management = DatasetManagementServiceClient()
self.process_dispatcher = ProcessDispatcherServiceClient()
self.data_retriever = DataRetrieverServiceClient()
def subscriber_action(self, msg, header):
if not hasattr(self,'received'):
self.received = 0
if not hasattr(self, 'async_done'):
self.async_done = AsyncResult()
self.received += 1
if self.received >= 2:
self.async_done.set(True)
def test_ingest_to_replay(self):
self.async_done = AsyncResult()
sysname = get_sys_name()
datastore = self.container.datastore_manager.get_datastore(self.datastore_name,'SCIDATA')
producer_definition = ProcessDefinition(name='Example Data Producer')
producer_definition.executable = {
'module':'ion.processes.data.example_data_producer',
'class' :'ExampleDataProducer'
}
process_definition_id = self.process_dispatcher.create_process_definition(process_definition=producer_definition)
ingestion_configuration_id = self.ingestion_management.create_ingestion_configuration(
exchange_point_id = 'science_data',
couch_storage=CouchStorage(datastore_name=self.datastore_name,datastore_profile='SCIDATA'),
number_of_workers=1
)
self.ingestion_management.activate_ingestion_configuration(
ingestion_configuration_id=ingestion_configuration_id)
stream_id = self.pubsub_management.create_stream(name='data stream')
dataset_id = self.dataset_management.create_dataset(
stream_id = stream_id,
datastore_name = self.datastore_name,
)
self.ingestion_management.create_dataset_configuration(
dataset_id = dataset_id,
archive_data = True,
archive_metadata = True,
ingestion_configuration_id = ingestion_configuration_id
)
configuration = {
'process': {
'stream_id' : stream_id
}
}
self.process_dispatcher.schedule_process(process_definition_id, configuration=configuration)
replay_id, stream_id = self.data_retriever.define_replay(dataset_id = dataset_id)
subscriber = Subscriber(name=('%s.science_data' % sysname, 'test_queue'), callback=self.subscriber_action, binding='%s.data' % stream_id)
gevent.spawn(subscriber.listen)
done = False
while not done:
results = datastore.query_view('manifest/by_dataset')
if len(results) >= 2:
done = True
self.data_retriever.start_replay(replay_id)
self.async_done.get(timeout=10)
def test_raw_stream_integration(self):
cc = self.container
assertions = self.assertTrue
#-----------------------------
# Copy below here to run as a script (don't forget the imports of course!)
#-----------------------------
# Create some service clients...
pubsub_management_service = PubsubManagementServiceClient(node=cc.node)
ingestion_management_service = IngestionManagementServiceClient(
node=cc.node)
dataset_management_service = DatasetManagementServiceClient(
node=cc.node)
process_dispatcher = ProcessDispatcherServiceClient(node=cc.node)
# declare some handy variables
datastore_name = 'test_dm_integration'
###
### In the beginning there was one stream definitions...
###
# create a stream definition for the data from the ctd simulator
raw_ctd_stream_def = SBE37_RAW_stream_definition()
raw_ctd_stream_def_id = pubsub_management_service.create_stream_definition(
container=raw_ctd_stream_def, name='Simulated RAW CTD data')
###
### And two process definitions...
###
# one for the ctd simulator...
producer_definition = ProcessDefinition()
producer_definition.executable = {
'module': 'ion.processes.data.raw_stream_publisher',
'class': 'RawStreamPublisher'
}
raw_ctd_sim_procdef_id = process_dispatcher.create_process_definition(
process_definition=producer_definition)
#---------------------------
# Set up ingestion - this is an operator concern - not done by SA in a deployed system
#---------------------------
# Configure ingestion using eight workers, ingesting to test_dm_integration datastore with the SCIDATA profile
log.debug('Calling create_ingestion_configuration')
ingestion_configuration_id = ingestion_management_service.create_ingestion_configuration(
exchange_point_id='science_data',
couch_storage=CouchStorage(datastore_name=datastore_name,
datastore_profile='SCIDATA'),
number_of_workers=1)
#
ingestion_management_service.activate_ingestion_configuration(
ingestion_configuration_id=ingestion_configuration_id)
#---------------------------
# Set up the producer (CTD Simulator)
#---------------------------
# Create the stream
raw_ctd_stream_id = pubsub_management_service.create_stream(
stream_definition_id=raw_ctd_stream_def_id)
# Set up the datasets
raw_ctd_dataset_id = dataset_management_service.create_dataset(
stream_id=raw_ctd_stream_id,
datastore_name=datastore_name,
view_name='datasets/stream_join_granule')
# Configure ingestion of this dataset
raw_ctd_dataset_config_id = ingestion_management_service.create_dataset_configuration(
dataset_id=raw_ctd_dataset_id,
archive_data=True,
archive_metadata=True,
ingestion_configuration_id=
ingestion_configuration_id, # you need to know the ingestion configuration id!
)
# Hold onto ctd_dataset_config_id if you want to stop/start ingestion of that dataset by the ingestion service
# Start the ctd simulator to produce some data
configuration = {
'process': {
'stream_id': raw_ctd_stream_id,
}
}
raw_sim_pid = process_dispatcher.schedule_process(
process_definition_id=raw_ctd_sim_procdef_id,
configuration=configuration)
###
### Make a subscriber in the test to listen for salinity data
###
raw_subscription_id = pubsub_management_service.create_subscription(
query=StreamQuery([
raw_ctd_stream_id,
]),
exchange_name='raw_test',
name="test raw subscription",
)
# this is okay - even in cei mode!
pid = cc.spawn_process(name='dummy_process_for_test',
module='pyon.ion.process',
cls='SimpleProcess',
config={})
dummy_process = cc.proc_manager.procs[pid]
subscriber_registrar = StreamSubscriberRegistrar(process=dummy_process,
node=cc.node)
result = gevent.event.AsyncResult()
results = []
def message_received(message, headers):
# Heads
log.warn('Raw data received!')
results.append(message)
if len(results) > 3:
result.set(True)
subscriber = subscriber_registrar.create_subscriber(
exchange_name='raw_test', callback=message_received)
subscriber.start()
# after the queue has been created it is safe to activate the subscription
pubsub_management_service.activate_subscription(
subscription_id=raw_subscription_id)
# Assert that we have received data
assertions(result.get(timeout=10))
# stop the flow parse the messages...
process_dispatcher.cancel_process(
raw_sim_pid
) # kill the ctd simulator process - that is enough data
gevent.sleep(1)
for message in results:
sha1 = message.identifiables['stream_encoding'].sha1
data = message.identifiables['data_stream'].values
filename = FileSystem.get_hierarchical_url(FS.CACHE, sha1, ".raw")
with open(filename, 'r') as f:
assertions(data == f.read())
def test_replay_integration(self):
'''
test_replay_integration
'''
import numpy as np
# Keep the import it's used in the vector comparison below even though pycharm says its unused.
cc = self.container
XP = self.XP
assertions = self.assertTrue
### Every thing below here can be run as a script:
log.debug('Got it')
pubsub_management_service = PubsubManagementServiceClient(node=cc.node)
ingestion_management_service = IngestionManagementServiceClient(
node=cc.node)
dataset_management_service = DatasetManagementServiceClient(
node=cc.node)
data_retriever_service = DataRetrieverServiceClient(node=cc.node)
datastore_name = 'dm_test_replay_integration'
producer = Publisher(name=(XP, 'stream producer'))
ingestion_configuration_id = ingestion_management_service.create_ingestion_configuration(
exchange_point_id=XP,
couch_storage=CouchStorage(datastore_name=datastore_name,
datastore_profile='SCIDATA'),
hdf_storage=HdfStorage(),
number_of_workers=1)
ingestion_management_service.activate_ingestion_configuration(
ingestion_configuration_id=ingestion_configuration_id)
definition = SBE37_CDM_stream_definition()
data_stream_id = definition.data_stream_id
encoding_id = definition.identifiables[data_stream_id].encoding_id
element_count_id = definition.identifiables[
data_stream_id].element_count_id
stream_def_id = pubsub_management_service.create_stream_definition(
container=definition)
stream_id = pubsub_management_service.create_stream(
stream_definition_id=stream_def_id)
dataset_id = dataset_management_service.create_dataset(
stream_id=stream_id,
datastore_name=datastore_name,
view_name='datasets/dataset_by_id')
ingestion_management_service.create_dataset_configuration(
dataset_id=dataset_id,
archive_data=True,
archive_metadata=True,
ingestion_configuration_id=ingestion_configuration_id)
definition.stream_resource_id = stream_id
packet = _create_packet(definition)
input_file = FileSystem.mktemp()
input_file.write(packet.identifiables[data_stream_id].values)
input_file_path = input_file.name
input_file.close()
fields = [
'conductivity', 'height', 'latitude', 'longitude', 'pressure',
'temperature', 'time'
]
input_vectors = acquire_data([input_file_path], fields, 2).next()
producer.publish(msg=packet, to_name=(XP, '%s.data' % stream_id))
replay_id, replay_stream_id = data_retriever_service.define_replay(
dataset_id)
ar = gevent.event.AsyncResult()
def sub_listen(msg, headers):
assertions(isinstance(msg, StreamGranuleContainer),
'replayed message is not a granule.')
hdf_string = msg.identifiables[data_stream_id].values
sha1 = hashlib.sha1(hdf_string).hexdigest().upper()
assertions(sha1 == msg.identifiables[encoding_id].sha1,
'Checksum failed.')
assertions(
msg.identifiables[element_count_id].value == 1,
'record replay count is incorrect %d.' %
msg.identifiables[element_count_id].value)
output_file = FileSystem.mktemp()
output_file.write(msg.identifiables[data_stream_id].values)
output_file_path = output_file.name
output_file.close()
output_vectors = acquire_data([output_file_path], fields, 2).next()
for field in fields:
comparison = (input_vectors[field]['values'] ==
output_vectors[field]['values'])
assertions(
comparison.all(), 'vector mismatch: %s vs %s' %
(input_vectors[field]['values'],
output_vectors[field]['values']))
FileSystem.unlink(output_file_path)
ar.set(True)
subscriber = Subscriber(name=(XP, 'replay listener'),
callback=sub_listen)
g = gevent.Greenlet(subscriber.listen,
binding='%s.data' % replay_stream_id)
g.start()
data_retriever_service.start_replay(replay_id)
ar.get(timeout=10)
FileSystem.unlink(input_file_path)
def test_usgs_integration(self):
'''
test_usgs_integration
Test full DM Services Integration using usgs
'''
cc = self.container
assertions = self.assertTrue
#-----------------------------
# Copy below here
#-----------------------------
pubsub_management_service = PubsubManagementServiceClient(node=cc.node)
ingestion_management_service = IngestionManagementServiceClient(node=cc.node)
dataset_management_service = DatasetManagementServiceClient(node=cc.node)
data_retriever_service = DataRetrieverServiceClient(node=cc.node)
transform_management_service = TransformManagementServiceClient(node=cc.node)
process_dispatcher = ProcessDispatcherServiceClient(node=cc.node)
process_list = []
datasets = []
datastore_name = 'test_usgs_integration'
#---------------------------
# Set up ingestion
#---------------------------
# Configure ingestion using eight workers, ingesting to test_dm_integration datastore with the SCIDATA profile
log.debug('Calling create_ingestion_configuration')
ingestion_configuration_id = ingestion_management_service.create_ingestion_configuration(
exchange_point_id='science_data',
couch_storage=CouchStorage(datastore_name=datastore_name,datastore_profile='SCIDATA'),
number_of_workers=8
)
#
ingestion_management_service.activate_ingestion_configuration(
ingestion_configuration_id=ingestion_configuration_id)
usgs_stream_def = USGS_stream_definition()
stream_def_id = pubsub_management_service.create_stream_definition(container=usgs_stream_def, name='Junk definition')
#---------------------------
# Set up the producers (CTD Simulators)
#---------------------------
# Launch five simulated CTD producers
for iteration in xrange(2):
# Make a stream to output on
stream_id = pubsub_management_service.create_stream(stream_definition_id=stream_def_id)
#---------------------------
# Set up the datasets
#---------------------------
dataset_id = dataset_management_service.create_dataset(
stream_id=stream_id,
datastore_name=datastore_name,
view_name='datasets/stream_join_granule'
)
# Keep track of the datasets
datasets.append(dataset_id)
stream_policy_id = ingestion_management_service.create_dataset_configuration(
dataset_id = dataset_id,
archive_data = True,
archive_metadata = True,
ingestion_configuration_id = ingestion_configuration_id
)
producer_definition = ProcessDefinition()
producer_definition.executable = {
'module':'eoi.agent.handler.usgs_stream_publisher',
'class':'UsgsPublisher'
}
configuration = {
'process':{
'stream_id':stream_id,
}
}
procdef_id = process_dispatcher.create_process_definition(process_definition=producer_definition)
log.debug('LUKE_DEBUG: procdef_id: %s', procdef_id)
pid = process_dispatcher.schedule_process(process_definition_id=procdef_id, configuration=configuration)
# Keep track, we'll kill 'em later.
process_list.append(pid)
# Get about 4 seconds of data
time.sleep(4)
#---------------------------
# Stop producing data
#---------------------------
for process in process_list:
process_dispatcher.cancel_process(process)
#----------------------------------------------
# The replay and the transform, a love story.
#----------------------------------------------
# Happy Valentines to the clever coder who catches the above!
transform_definition = ProcessDefinition()
transform_definition.executable = {
'module':'ion.processes.data.transforms.transform_example',
'class':'TransformCapture'
}
transform_definition_id = process_dispatcher.create_process_definition(process_definition=transform_definition)
dataset_id = datasets.pop() # Just need one for now
replay_id, stream_id = data_retriever_service.define_replay(dataset_id=dataset_id)
#--------------------------------------------
# I'm Selling magazine subscriptions here!
#--------------------------------------------
subscription = pubsub_management_service.create_subscription(query=StreamQuery(stream_ids=[stream_id]),
exchange_name='transform_capture_point')
#--------------------------------------------
# Start the transform (capture)
#--------------------------------------------
transform_id = transform_management_service.create_transform(
name='capture_transform',
in_subscription_id=subscription,
process_definition_id=transform_definition_id
)
transform_management_service.activate_transform(transform_id=transform_id)
#--------------------------------------------
# BEGIN REPLAY!
#--------------------------------------------
data_retriever_service.start_replay(replay_id=replay_id)
#--------------------------------------------
# Lets get some boundaries
#--------------------------------------------
bounds = dataset_management_service.get_dataset_bounds(dataset_id=dataset_id)
def test_replay_integration(self):
'''
Test full DM Services Integration
'''
cc = self.container
### Every thing below here can be run as a script:
pubsub_management_service = PubsubManagementServiceClient(node=cc.node)
ingestion_management_service = IngestionManagementServiceClient(node=cc.node)
dataset_management_service = DatasetManagementServiceClient(node=cc.node)
data_retriever_service = DataRetrieverServiceClient(node=cc.node)
resource_registry_service = ResourceRegistryServiceClient(node=cc.node)
#------------------------------------------------------------------------------------------------------
# Datastore name
#------------------------------------------------------------------------------------------------------
datastore_name = 'test_replay_integration'
#------------------------------------------------------------------------------------------------------
# Spawn process
#------------------------------------------------------------------------------------------------------
pid = cc.spawn_process(name='dummy_process_for_test',
module='pyon.ion.process',
cls='SimpleProcess',
config={})
dummy_process = cc.proc_manager.procs[pid]
#------------------------------------------------------------------------------------------------------
# Set up subscriber
#------------------------------------------------------------------------------------------------------
# Normally the user does not see or create the publisher, this is part of the containers business.
# For the test we need to set it up explicitly
publisher_registrar = StreamPublisherRegistrar(process=dummy_process, node=cc.node)
subscriber_registrar = StreamSubscriberRegistrar(process=cc, node=cc.node)
#------------------------------------------------------------------------------------------------------
# Set up ingestion
#------------------------------------------------------------------------------------------------------
# Configure ingestion using eight workers, ingesting to test_dm_integration datastore with the SCIDATA profile
ingestion_configuration_id = ingestion_management_service.create_ingestion_configuration(
exchange_point_id='science_data',
couch_storage=CouchStorage(datastore_name=datastore_name, datastore_profile='SCIDATA'),
hdf_storage=HdfStorage(),
number_of_workers=1,
)
ingestion_management_service.activate_ingestion_configuration(
ingestion_configuration_id=ingestion_configuration_id)
#------------------------------------------------------------------------------------------------------
# Grab the transforms acting as ingestion workers
#------------------------------------------------------------------------------------------------------
transforms = [resource_registry_service.read(assoc.o)
for assoc in resource_registry_service.find_associations(ingestion_configuration_id, PRED.hasTransform)]
proc_1 = cc.proc_manager.procs[transforms[0].process_id]
log.info("PROCESS 1: %s" % str(proc_1))
#------------------------------------------------------------------------------------------------------
# Set up the test hooks for the gevent event AsyncResult object
#------------------------------------------------------------------------------------------------------
def ingestion_worker_received(message, headers):
ar.set(message)
proc_1.ingest_process_test_hook = ingestion_worker_received
#------------------------------------------------------------------------------------------------------
# Set up the producers (CTD Simulators)
#------------------------------------------------------------------------------------------------------
ctd_stream_def = ctd_stream_definition()
stream_def_id = pubsub_management_service.create_stream_definition(container=ctd_stream_def, name='Junk definition')
stream_id = pubsub_management_service.create_stream(stream_definition_id=stream_def_id)
#------------------------------------------------------------------------------------------------------
# Set up the dataset config
#------------------------------------------------------------------------------------------------------
dataset_id = dataset_management_service.create_dataset(
stream_id=stream_id,
datastore_name=datastore_name,
view_name='datasets/stream_join_granule'
)
dataset_config_id = ingestion_management_service.create_dataset_configuration(
dataset_id = dataset_id,
archive_data = True,
archive_metadata = True,
ingestion_configuration_id = ingestion_configuration_id
)
#------------------------------------------------------------------------------------------------------
# Launch a ctd_publisher
#------------------------------------------------------------------------------------------------------
publisher = publisher_registrar.create_publisher(stream_id=stream_id)
#------------------------------------------------------------------------
# Create a packet and publish it
#------------------------------------------------------------------------
ctd_packet = _create_packet(stream_id)
published_hdfstring = ctd_packet.identifiables['ctd_data'].values
publisher.publish(ctd_packet)
#------------------------------------------------------------------------------------------------------
# Catch what the ingestion worker gets! Assert it is the same packet that was published!
#------------------------------------------------------------------------------------------------------
packet = ar.get(timeout=2)
#------------------------------------------------------------------------------------------------------
# Create subscriber to listen to the replays
#------------------------------------------------------------------------------------------------------
replay_id, replay_stream_id = data_retriever_service.define_replay(dataset_id)
query = StreamQuery(stream_ids=[replay_stream_id])
subscription_id = pubsub_management_service.create_subscription(query = query, exchange_name='replay_capture_point' ,name = 'replay_capture_point')
# It is not required or even generally a good idea to use the subscription resource name as the queue name, but it makes things simple here
# Normally the container creates and starts subscribers for you when a transform process is spawned
subscriber = subscriber_registrar.create_subscriber(exchange_name='replay_capture_point', callback=_subscriber_call_back)
subscriber.start()
pubsub_management_service.activate_subscription(subscription_id)
#------------------------------------------------------------------------------------------------------
# Start the replay
#------------------------------------------------------------------------------------------------------
data_retriever_service.start_replay(replay_id)
#------------------------------------------------------------------------------------------------------
# Get the hdf string from the captured stream in the replay
#------------------------------------------------------------------------------------------------------
retrieved_hdf_string = ar2.get(timeout=2)
### Non scriptable portion of the test
#------------------------------------------------------------------------------------------------------
# Assert that it matches the message we sent
#------------------------------------------------------------------------------------------------------
self.assertEquals(packet.identifiables['stream_encoding'].sha1, ctd_packet.identifiables['stream_encoding'].sha1)
self.assertEquals(retrieved_hdf_string, published_hdfstring)
def test_raw_stream_integration(self):
cc = self.container
assertions = self.assertTrue
# -----------------------------
# Copy below here to run as a script (don't forget the imports of course!)
# -----------------------------
# Create some service clients...
pubsub_management_service = PubsubManagementServiceClient(node=cc.node)
ingestion_management_service = IngestionManagementServiceClient(node=cc.node)
dataset_management_service = DatasetManagementServiceClient(node=cc.node)
process_dispatcher = ProcessDispatcherServiceClient(node=cc.node)
# declare some handy variables
datastore_name = "test_dm_integration"
datastore = cc.datastore_manager.get_datastore(datastore_name, profile=DataStore.DS_PROFILE.SCIDATA)
###
### And two process definitions...
###
# one for the ctd simulator...
producer_definition = ProcessDefinition(name="Example Data Producer")
producer_definition.executable = {
"module": "ion.processes.data.example_data_producer",
"class": "ExampleDataProducer",
}
producer_procdef_id = process_dispatcher.create_process_definition(process_definition=producer_definition)
# ---------------------------
# Set up ingestion - this is an operator concern - not done by SA in a deployed system
# ---------------------------
# Configure ingestion using eight workers, ingesting to test_dm_integration datastore with the SCIDATA profile
log.debug("Calling create_ingestion_configuration")
ingestion_configuration_id = ingestion_management_service.create_ingestion_configuration(
exchange_point_id="science_data",
couch_storage=CouchStorage(datastore_name=datastore_name, datastore_profile="SCIDATA"),
number_of_workers=1,
)
#
ingestion_management_service.activate_ingestion_configuration(
ingestion_configuration_id=ingestion_configuration_id
)
# ---------------------------
# Set up the producer (CTD Simulator)
# ---------------------------
# Create the stream
stream_id = pubsub_management_service.create_stream(name="A data stream")
# Set up the datasets
dataset_id = dataset_management_service.create_dataset(
stream_id=stream_id, datastore_name=datastore_name, view_name="Undefined!"
)
# Configure ingestion of this dataset
dataset_ingest_config_id = ingestion_management_service.create_dataset_configuration(
dataset_id=dataset_id,
archive_data=True,
archive_metadata=True,
ingestion_configuration_id=ingestion_configuration_id, # you need to know the ingestion configuration id!
)
# Hold onto dataset_ingest_config_id if you want to stop/start ingestion of that dataset by the ingestion service
# Start the ctd simulator to produce some data
configuration = {"process": {"stream_id": stream_id}}
producer_pid = process_dispatcher.schedule_process(
process_definition_id=producer_procdef_id, configuration=configuration
)
found = False
processes = cc.proc_manager.procs.values()
for proc in processes:
if isinstance(proc, IngestionWorker):
found = True
break
self.assertTrue(found, "%s" % cc.proc_manager.procs)
done = False
while not done:
results = datastore.query_view("manifest/by_dataset")
if len(results) >= 5:
done = True
