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)