def scale_data(datadict): iops_series_raw = datadict["iops_series_raw"] iops_stddev_series_raw = datadict["iops_stddev_series_raw"] lat_series_raw = datadict["lat_series_raw"] lat_stddev_series_raw = datadict["lat_stddev_series_raw"] cpu_usr = datadict["cpu"]["cpu_usr"] cpu_sys = datadict["cpu"]["cpu_sys"] if "ss_settings" in datadict.keys(): ss_data_bw_mean = datadict["ss_data_bw_mean"] ss_data_iops_mean = datadict["ss_data_iops_mean"] # # Latency data must be scaled, IOPs will not be scaled. # latency_scale_factor = supporting.get_scale_factor_lat(lat_series_raw) scaled_latency_data = supporting.scale_yaxis(lat_series_raw, latency_scale_factor) # # Latency data must be rounded. # scaled_latency_data_rounded = supporting.round_metric_series( scaled_latency_data["data"]) scaled_latency_data["data"] = scaled_latency_data_rounded # # Latency stddev must be scaled with same scale factor as the data # lat_stdev_scaled = supporting.scale_yaxis(lat_stddev_series_raw, latency_scale_factor) lat_stdev_scaled_rounded = supporting.round_metric_series( lat_stdev_scaled["data"]) # # Latency data is converted to percent. # lat_stddev_percent = supporting.raw_stddev_to_percent( scaled_latency_data["data"], lat_stdev_scaled_rounded) lat_stddev_percent = [int(x) for x in lat_stddev_percent] scaled_latency_data["stddev"] = supporting.round_metric_series( lat_stddev_percent) # # IOPS data is rounded iops_series_rounded = supporting.round_metric_series(iops_series_raw) # # IOPS stddev is converted to percent iops_stdev_rounded = supporting.round_metric_series(iops_stddev_series_raw) iops_stdev_rounded_percent = supporting.raw_stddev_to_percent( iops_series_rounded, iops_stdev_rounded) iops_stdev_rounded_percent = [int(x) for x in iops_stdev_rounded_percent] # # # Steady state bandwidth data must be scaled. if "ss_settings" in datadict.keys(): if datadict["ss_settings"]: ss_bw_scalefactor = supporting.get_scale_factor_bw_ss( ss_data_bw_mean) ss_data_bw_mean = supporting.scale_yaxis(ss_data_bw_mean, ss_bw_scalefactor) ss_data_bw_mean["data"] = supporting.round_metric_series( ss_data_bw_mean["data"]) ss_iops_scalefactor = supporting.get_scale_factor_iops( ss_data_iops_mean) ss_data_iops_mean = supporting.scale_yaxis(ss_data_iops_mean, ss_iops_scalefactor) ss_data_iops_mean["data"] = supporting.round_metric_series( ss_data_iops_mean["data"]) datadict["y1_axis"] = { "data": iops_series_rounded, "format": "IOPS", "stddev": iops_stdev_rounded_percent, } datadict["y2_axis"] = scaled_latency_data if cpu_sys and cpu_usr: datadict["cpu"] = {"cpu_sys": cpu_sys, "cpu_usr": cpu_usr} if "ss_settings" in datadict.keys(): if datadict["ss_settings"]: datadict["ss_data_bw_mean"] = ss_data_bw_mean datadict["ss_data_iops_mean"] = ss_data_iops_mean return datadict
def scale_data(datadict): iops_series_raw = datadict['iops_series_raw'] iops_stddev_series_raw = datadict['iops_stddev_series_raw'] lat_series_raw = datadict['lat_series_raw'] lat_stddev_series_raw = datadict['lat_stddev_series_raw'] cpu_usr = datadict['cpu']['cpu_usr'] cpu_sys = datadict['cpu']['cpu_sys'] # # Latency data must be scaled, IOPs will not be scaled. # latency_scale_factor = supporting.get_scale_factor(lat_series_raw) scaled_latency_data = supporting.scale_yaxis_latency( lat_series_raw, latency_scale_factor) # # Latency data must be rounded. # scaled_latency_data_rounded = supporting.round_metric_series( scaled_latency_data['data']) scaled_latency_data['data'] = scaled_latency_data_rounded # # Latency stddev must be scaled with same scale factor as the data # lat_stdev_scaled = supporting.scale_yaxis_latency(lat_stddev_series_raw, latency_scale_factor) lat_stdev_scaled_rounded = supporting.round_metric_series( lat_stdev_scaled['data']) # # Latency data is converted to percent. # lat_stddev_percent = supporting.raw_stddev_to_percent( scaled_latency_data['data'], lat_stdev_scaled_rounded) lat_stddev_percent = [int(x) for x in lat_stddev_percent] scaled_latency_data['stddev'] = supporting.round_metric_series( lat_stddev_percent) # # IOPS data is rounded iops_series_rounded = supporting.round_metric_series(iops_series_raw) # # IOPS stddev is converted to percent iops_stdev_rounded = supporting.round_metric_series(iops_stddev_series_raw) iops_stdev_rounded_percent = supporting.raw_stddev_to_percent( iops_series_rounded, iops_stdev_rounded) iops_stdev_rounded_percent = [int(x) for x in iops_stdev_rounded_percent] # # datadict['y1_axis'] = { 'data': iops_series_rounded, 'format': "IOPS", 'stddev': iops_stdev_rounded_percent } datadict['y2_axis'] = scaled_latency_data if cpu_sys and cpu_usr: datadict['cpu'] = {'cpu_sys': cpu_sys, 'cpu_usr': cpu_usr} return datadict
def get_record_set(settings, dataset, dataset_types, rw, numjobs): """The supplied dataset, a list of flat dictionaries with data is filtered based on the parameters as set by the command line. The filtered data is also scaled and rounded. """ if settings['rw'] == 'randrw': if len(settings['filter']) > 1 or not settings['filter']: print( "Since we are processing randrw data, you must specify a filter for either read or write data, not both." ) exit(1) record_set = { 'x_axis': dataset_types['iodepth'], 'x_axis_format': 'Queue Depth', 'y1_axis': None, 'y2_axis': None, 'numjobs': numjobs } iops_series_raw = [] iops_stddev_series_raw = [] lat_series_raw = [] lat_stddev_series_raw = [] for depth in dataset_types['iodepth']: for record in dataset: if (int(record['iodepth']) == int(depth)) and int( record['numjobs']) == int(numjobs[0]) and record[ 'rw'] == rw and record['type'] in settings['filter']: iops_series_raw.append(record['iops']) lat_series_raw.append(record['lat']) iops_stddev_series_raw.append(record['iops_stddev']) lat_stddev_series_raw.append(record['lat_stddev']) # # Latency data must be scaled, IOPs will not be scaled. # latency_scale_factor = supporting.get_scale_factor(lat_series_raw) scaled_latency_data = supporting.scale_yaxis_latency( lat_series_raw, latency_scale_factor) # # Latency data must be rounded. # scaled_latency_data_rounded = supporting.round_metric_series( scaled_latency_data['data']) scaled_latency_data['data'] = scaled_latency_data_rounded # # Latency stddev must be scaled with same scale factor as the data # lat_stdev_scaled = supporting.scale_yaxis_latency(lat_stddev_series_raw, latency_scale_factor) lat_stdev_scaled_rounded = supporting.round_metric_series( lat_stdev_scaled['data']) # # Latency data is converted to percent. # lat_stddev_percent = supporting.raw_stddev_to_percent( scaled_latency_data['data'], lat_stdev_scaled_rounded) lat_stddev_percent = [int(x) for x in lat_stddev_percent] scaled_latency_data['stddev'] = supporting.round_metric_series( lat_stddev_percent) # # IOPS data is rounded iops_series_rounded = supporting.round_metric_series(iops_series_raw) # # IOPS stddev is converted to percent iops_stdev_rounded = supporting.round_metric_series(iops_stddev_series_raw) iops_stdev_rounded_percent = supporting.raw_stddev_to_percent( iops_series_rounded, iops_stdev_rounded) iops_stdev_rounded_percent = [int(x) for x in iops_stdev_rounded_percent] # # record_set['y1_axis'] = { 'data': iops_series_rounded, 'format': "IOPS", 'stddev': iops_stdev_rounded_percent } record_set['y2_axis'] = scaled_latency_data return record_set
def scale_data(datadict, settings): if settings["type"] is None or len(settings["type"]) == 0: settings["type"] = ['iops', 'lat'] left_series_raw = datadict[settings['type'][0] + "_series_raw"] if settings['type'][0] + "_stddev_series_raw" in datadict: left_stddev_series_raw = datadict[settings['type'][0] + "_stddev_series_raw"] else: left_stddev_series_raw = None if len(settings['type']) == 2: right_series_raw = datadict[settings['type'][1] + "_series_raw"] if settings['type'][1] + "_stddev_series_raw" in datadict: right_stddev_series_raw = datadict[settings['type'][1] + "_stddev_series_raw"] else: right_stddev_series_raw = None else: right_series_raw = None cpu_usr = datadict["cpu"]["cpu_usr"] cpu_sys = datadict["cpu"]["cpu_sys"] if "ss_settings" in datadict.keys(): ss_data_bw_mean = datadict["ss_data_bw_mean"] ss_data_iops_mean = datadict["ss_data_iops_mean"] # # Latency data must be scaled, IOPs will not be scaled. # if right_series_raw is not None: latency_scale_factor = supporting.get_scale_factor_lat( right_series_raw) scaled_latency_data = supporting.scale_yaxis(right_series_raw, latency_scale_factor) # # Latency data must be rounded. # scaled_latency_data_rounded = supporting.round_metric_series( scaled_latency_data["data"]) scaled_latency_data["data"] = scaled_latency_data_rounded # # Latency stddev must be scaled with same scale factor as the data # lat_stdev_scaled = supporting.scale_yaxis(right_stddev_series_raw, latency_scale_factor) lat_stdev_scaled_rounded = supporting.round_metric_series( lat_stdev_scaled["data"]) # # Latency data is converted to percent. # lat_stddev_percent = supporting.raw_stddev_to_percent( scaled_latency_data["data"], lat_stdev_scaled_rounded) lat_stddev_percent = [int(x) for x in lat_stddev_percent] scaled_latency_data["stddev"] = supporting.round_metric_series( lat_stddev_percent) # # IOPS data is rounded left_series_rounded = supporting.round_metric_series(left_series_raw) # # IOPS stddev is converted to percent if left_stddev_series_raw is not None: left_stdev_rounded = supporting.round_metric_series( left_stddev_series_raw) left_stdev_rounded_percent = supporting.raw_stddev_to_percent( left_series_rounded, left_stdev_rounded) left_stdev_rounded_percent = [ int(x) for x in left_stdev_rounded_percent ] else: left_stdev_rounded_percent = None # # # Steady state bandwidth data must be scaled. if "ss_settings" in datadict.keys(): if datadict["ss_settings"]: ss_bw_scalefactor = supporting.get_scale_factor_bw_ss( ss_data_bw_mean) ss_data_bw_mean = supporting.scale_yaxis(ss_data_bw_mean, ss_bw_scalefactor) ss_data_bw_mean["data"] = supporting.round_metric_series( ss_data_bw_mean["data"]) ss_iops_scalefactor = supporting.get_scale_factor_iops( ss_data_iops_mean) ss_data_iops_mean = supporting.scale_yaxis(ss_data_iops_mean, ss_iops_scalefactor) ss_data_iops_mean["data"] = supporting.round_metric_series( ss_data_iops_mean["data"]) datadict["y1_axis"] = { "data": left_series_rounded, "format": labelByType(settings["type"][0]), "stddev": left_stdev_rounded_percent, } if right_series_raw is not None: datadict["y2_axis"] = scaled_latency_data if cpu_sys and cpu_usr: datadict["cpu"] = {"cpu_sys": cpu_sys, "cpu_usr": cpu_usr} if "ss_settings" in datadict.keys(): if datadict["ss_settings"]: datadict["ss_data_bw_mean"] = ss_data_bw_mean datadict["ss_data_iops_mean"] = ss_data_iops_mean return datadict