def get_data(self, node):
"""
Return telemetry data for the specified node
:param node: InfoGraph node
:return: pandas.DataFrame
"""
queries = InfoGraphNode.get_queries(node)
ret_val = pandas.DataFrame()
try:
ret_val = self._get_data(queries)
except Exception as ex:
LOG.debug("Exception in user code: \n{} {} {}".format('-' * 60),
traceback.print_exc(file=sys.stdout), '-' * 60)
#ret_val.set_index(keys='timestamp')
if InfoGraphNode.node_is_vm(node):
if not ret_val.empty:
ret_val.columns = tm_utils.clean_vm_telemetry_colnames(
ret_val.columns)
return ret_val
def run(self, workload, optimal_node_type='machine'):
"""
Ranks machines by CPU utilization.
:param workload: Contains workload related info and results.
:return: heuristic results
"""
workload_config = workload.get_configuration()
graph = workload.get_latest_graph()
if not graph:
raise KeyError('No graph to be processed.')
scores = LandscapeScore.utilization_scores(graph)
scores_sat = LandscapeScore.saturation_scores(graph)
heuristic_results = pd.DataFrame(columns=[
'node_name',
'type',
'ipaddress',
'compute utilization',
'compute saturation',
'memory utilization',
'memory saturation',
'network utilization',
'network saturation',
'disk utilization',
'disk saturation',
])
heuristic_results_nt = heuristic_results.copy()
device_id_col_name = None
project = None
if workload_config.get('project'):
project = workload_config['project']
device_id_col_name = workload_config['project'] + '_device_id'
heuristic_results[device_id_col_name] = None
telemetry_filter = workload_config.get('telemetry_filter')
for node in graph.nodes(data=True):
node_name = InfoGraphNode.get_name(node)
node_type = InfoGraphNode.get_type(node)
list_node_name = node_name
if node_type == optimal_node_type:
if InfoGraphNode.node_is_vm(node):
vm_name = InfoGraphNode.get_properties(node).get('vm_name')
if vm_name:
list_node_name = vm_name
data = {
'node_name':
list_node_name,
'type':
node_type,
'ipaddress':
InfoGraphNode.get_attributes(node).get('ipaddress'),
'compute utilization':
scores[node_name]['compute'],
'compute saturation':
scores_sat[node_name]['compute'],
'memory utilization':
scores[node_name]['memory'],
'memory saturation':
scores_sat[node_name]['memory'],
'network utilization':
scores[node_name]['network'],
'network saturation':
scores_sat[node_name]['network'],
'disk utilization':
scores[node_name]['disk'],
'disk saturation':
scores_sat[node_name]['disk']
}
if device_id_col_name:
dev_id = InfoGraphNode.get_properties(node).get(
device_id_col_name)
if project == 'mf2c':
dev_id = dev_id.replace('_', '-')
data[device_id_col_name] = dev_id
if InfoGraphNode.get_properties(node).get(
"telemetry_data") is not None:
heuristic_results = heuristic_results.append(
data, ignore_index=True)
elif not telemetry_filter:
heuristic_results_nt = heuristic_results.append(
data, ignore_index=True)
if not workload.get_workload_name().startswith('optimal_'):
if InfoGraphNode.get_type(
node
) == "docker_container" and optimal_node_type == 'machine':
node_name = InfoGraphNode.get_docker_id(node)
heuristic_results = heuristic_results.append(
{
'node_name': node_name,
'type': node_type,
'ipaddress': None,
'compute utilization':
scores[node_name]['compute'],
'compute saturation': None,
'memory utilization': scores[node_name]['memory'],
'memory saturation': None,
'network utilization':
scores[node_name]['network'],
'network saturation': None,
'disk utilization': scores[node_name]['disk'],
'disk saturation': None
},
ignore_index=True)
sort_fields = ['compute utilization']
sort_order = workload_config.get('sort_order')
if sort_order:
sort_fields = []
for val in sort_order:
if val == 'cpu':
sort_fields.append('compute utilization')
if val == 'memory':
sort_fields.append('memory utilization')
if val == 'network':
sort_fields.append('network utilization')
if val == 'disk':
sort_fields.append('disk utilization')
heuristic_results_nt = heuristic_results_nt.replace([0], [None])
heuristic_results = heuristic_results.sort_values(by=sort_fields,
ascending=True)
heuristic_results = heuristic_results.append(heuristic_results_nt,
ignore_index=True)
workload.append_metadata(self.__filter_name__, heuristic_results)
LOG.info('AVG: {}'.format(heuristic_results))
return heuristic_results
def run(self, workload):
tmp_path = "/media/iolie/WORK/data/"
# Extract data from Info Core
service_subgraphs = workload.get_latest_graph()
telemetry = {}
cols = []
if not service_subgraphs or len(service_subgraphs) == 0:
return
# first add telemetry data of all nodes to a dictionary
print "Data merger started " + str(time.time())
for subgraph in service_subgraphs:
for node in subgraph.nodes(data=True):
node_id = node[0]
node_tm = InfoGraphNode.get_telemetry_data(node)
if InfoGraphNode.node_is_vm(node):
if not node_tm.empty:
node_tm.columns = tm_utils.clean_vm_telemetry_colnames(node_tm.columns)
vm_name = InfoGraphNode.get_attributes(node).get("vm_name")
if vm_name:
node_id = vm_name
if not node_tm.empty:
tm = telemetry.get(node_id)
if not isinstance(tm, pd.DataFrame):
#if not tm:
telemetry[node_id] = node_tm
#telemetry[node_id] = [node_tm]
#node_tm.to_csv(tmp_path+node_id, index=False)
else:
telemetry[node_id] = pd.concat([tm, node_tm])
#telemetry[node_id].append(node_tm)
#node_tm.to_csv(tmp_path + node_id, mode='a', header=False, index=False)
InfoGraphNode.set_telemetry_data(node, pd.DataFrame())
print "Data merger finished " + str(time.time())
print telemetry.keys()
print len(telemetry)
# merge subgraphs
graph = None
counter = 0
for subgraph in service_subgraphs:
counter = counter + 1
if not graph and len(subgraph.nodes()) > 0:
graph = subgraph
elif len(subgraph.nodes()) > 0:
graphs.merge_graph(graph, subgraph)
#print "Merged {} subgraphs out of {} subgraphs in all".format(counter, len(service_subgraphs))
# merge telemetry data
#for key in telemetry.keys():
# val = telemetry[key]
# print key + ' {}'.format(len(val))
# if len(val) > 1:
# telemetry[key] = pd.concat(val)
# elif len(val) == 1:
# telemetry[key] = val[0]
# print node_id + ', ' + str(time.time())
# print "Merged telemetry data of {} nodes out of {} nodes in all".format(counter, len(telemetry.keys()))
# set telemetry data on merged graph
for node in graph.nodes(data=True):
node_id = node[0]
if InfoGraphNode.node_is_vm(node):
vm_name = InfoGraphNode.get_attributes(node).get("vm_name")
if vm_name:
node_id = vm_name
tm = telemetry.get(node_id)
#try:
# tm = pd.read_csv(tmp_path + node_id)
#except:
# tm = pd.DataFrame()
if isinstance(tm, pd.DataFrame):
if not tm.empty:
InfoGraphNode.set_telemetry_data(node, tm)
del telemetry[node_id] # delete telemetry data so that only one copy exists in the graph
else:
InfoGraphNode.set_telemetry_data(node, None)
# print "Set telemetry data of node {}".format(node_id)
print "Set telemetry data of merged graph"
workload.save_results(self.__filter_name__, graph)
return graph
