def test_clustermetric():
# construct 2 SARMetric
metric1 = SARMetric(
"SAR-cpuusage-host1", "sar.cpuusage.out", "host1", ".", "logs", "SAR-cpuusage-host1", None, None, {}, None
)
metric1.csv_column_map["logs/SAR-cpuusage-host1.all.percent-sys.csv"] = "all.%sys"
metric1.column_csv_map["all.%sys"] = "logs/SAR-cpuusage-host1.all.percent-sys.csv"
metric2 = SARMetric(
"SAR-cpuusage-host2", "sar.cpuusage.out", "host2", ".", "logs", "SAR-cpuusage-host2", None, None, {}, None
)
metric2.csv_column_map["logs/SAR-cpuusage-host2.all.percent-sys.csv"] = "all.%sys"
metric2.column_csv_map["all.%sys"] = "logs/SAR-cpuusage-host2.all.percent-sys.csv"
# construct a ClusterMetric
aggregate_metrics = "SAR-cpuusage.all.percent-sys:raw,avg,sum,count"
section = "CLUSTER-cpuusage-1"
label = "CLUSTER-cpuusage-1"
resource_path = "resources"
rule_strings = {}
output_directory = tmp_dir
aggregate_hosts = "host1 host2"
other_options = {}
ts_start = None
ts_end = None
metrics = [metric1, metric2]
cur_metric = ClusterMetric(
section,
aggregate_hosts,
aggregate_metrics,
metrics,
output_directory,
resource_path,
label,
ts_start,
ts_end,
rule_strings,
None,
)
# create sub-directory of resource_path
sub_dir = os.path.join(output_directory, resource_path)
if not os.path.exists(sub_dir):
os.makedirs(sub_dir)
# the only method to test; it will write to the directory the final csv files;
cur_metric.collect()
# check the existance of the output files
functions = aggregate_metrics.split(":")
prefix = functions[0].split(".") #'SAR-cpuusage.all.percent-sys'
prefix[0] = section
prefix = ".".join(prefix) # CLUSTER-cpuusage-1.all.percent-sys
for func in functions[1].split(","): #'raw,avg,sum,count'
file_name = prefix + "." + func + ".csv"
file_path = os.path.join(sub_dir, file_name)
# print 'file to check = ' + file_path #resources/CLUSTER-cpuusage-1.all.percent-sys.raw.csv
assert os.path.exists(file_path)
def test_clustermetric():
# construct 2 SARMetric
metric1 = SARMetric('SAR-cpuusage-host1', 'sar.cpuusage.out', 'host1', '.',
'logs', 'SAR-cpuusage-host1', None, None, {}, None,
None)
metric1.csv_column_map[
'logs/SAR-cpuusage-host1.all.percent-sys.csv'] = 'all.%sys'
metric1.column_csv_map[
'all.%sys'] = 'logs/SAR-cpuusage-host1.all.percent-sys.csv'
metric2 = SARMetric('SAR-cpuusage-host2', 'sar.cpuusage.out', 'host2', '.',
'logs', 'SAR-cpuusage-host2', None, None, {}, None,
None)
metric2.csv_column_map[
'logs/SAR-cpuusage-host2.all.percent-sys.csv'] = 'all.%sys'
metric2.column_csv_map[
'all.%sys'] = 'logs/SAR-cpuusage-host2.all.percent-sys.csv'
# construct a ClusterMetric
aggregate_metrics = 'SAR-cpuusage.all.percent-sys:raw,avg,sum,count'
section = 'CLUSTER-cpuusage-1'
label = 'CLUSTER-cpuusage-1'
resource_path = 'resources'
rule_strings = {}
output_directory = tmp_dir
aggregate_hosts = 'host1 host2'
other_options = {}
ts_start = None
ts_end = None
metrics = [metric1, metric2]
cur_metric = ClusterMetric(section, aggregate_hosts, aggregate_metrics,
metrics, output_directory, resource_path, label,
ts_start, ts_end, rule_strings, None, None)
# create sub-directory of resource_path
sub_dir = os.path.join(output_directory, resource_path)
if not os.path.exists(sub_dir):
os.makedirs(sub_dir)
# the only method to test; it will write to the directory the final csv files;
cur_metric.collect()
# check the existance of the output files
functions = aggregate_metrics.split(':')
prefix = functions[0].split('.') # 'SAR-cpuusage.all.percent-sys'
prefix[0] = section
prefix = '.'.join(prefix) # CLUSTER-cpuusage-1.all.percent-sys
for func in functions[1].split(','): # 'raw,avg,sum,count'
file_name = prefix + '.' + func + '.csv'
file_path = os.path.join(sub_dir, file_name)
# print 'file to check = ' + file_path # resources/CLUSTER-cpuusage-1.all.percent-sys.raw.csv
assert os.path.exists(file_path)
def test_clustermetric():
#construct 2 SARMetric
metric1 = SARMetric('SAR-cpuusage-host1', 'sar.cpuusage.out', 'host1', '.', 'logs', 'SAR-cpuusage-host1', None, None, {}, None, None);
metric1.csv_column_map['logs/SAR-cpuusage-host1.all.percent-sys.csv'] = 'all.%sys'
metric1.column_csv_map['all.%sys'] = 'logs/SAR-cpuusage-host1.all.percent-sys.csv'
metric2 = SARMetric('SAR-cpuusage-host2', 'sar.cpuusage.out', 'host2', '.', 'logs', 'SAR-cpuusage-host2', None, None, {}, None, None);
metric2.csv_column_map['logs/SAR-cpuusage-host2.all.percent-sys.csv'] = 'all.%sys'
metric2.column_csv_map['all.%sys'] = 'logs/SAR-cpuusage-host2.all.percent-sys.csv'
#construct a ClusterMetric
aggregate_metrics = 'SAR-cpuusage.all.percent-sys:raw,avg,sum,count'
section = 'CLUSTER-cpuusage-1'
label = 'CLUSTER-cpuusage-1'
resource_path = 'resources'
rule_strings = {}
output_directory = tmp_dir
aggregate_hosts = 'host1 host2'
other_options = {}
ts_start = None
ts_end = None
metrics = [metric1, metric2]
cur_metric = ClusterMetric(section, aggregate_hosts, aggregate_metrics, metrics, output_directory, resource_path, label, ts_start, ts_end, rule_strings, None, None)
# create sub-directory of resource_path
sub_dir = os.path.join(output_directory, resource_path)
if not os.path.exists(sub_dir):
os.makedirs(sub_dir)
# the only method to test; it will write to the directory the final csv files;
cur_metric.collect()
#check the existance of the output files
functions = aggregate_metrics.split(':')
prefix = functions[0].split('.') #'SAR-cpuusage.all.percent-sys'
prefix[0] = section
prefix = '.'.join(prefix) #CLUSTER-cpuusage-1.all.percent-sys
for func in functions[1].split(','): #'raw,avg,sum,count'
file_name = prefix + '.' + func + '.csv'
file_path = os.path.join(sub_dir, file_name)
# print 'file to check = ' + file_path #resources/CLUSTER-cpuusage-1.all.percent-sys.raw.csv
assert os.path.exists(file_path)
