| import abc |
| import logging |
| from typing import Dict, Any, Iterator, Tuple, cast, List |
| |
| import numpy |
| import scipy |
| import matplotlib |
| import matplotlib.pyplot as plt |
| |
| |
| matplotlib.use('svg') |
| |
| |
| from .utils import ssize2b |
| from .stage import Stage, StepOrder |
| from .test_run_class import TestRun |
| from .result_classes import NormStatProps |
| |
| |
| logger = logging.getLogger("wally") |
| |
| |
| class ConsoleReportStage(Stage): |
| |
| priority = StepOrder.REPORT |
| |
| def run(self, ctx: TestRun) -> None: |
| # TODO(koder): load data from storage |
| raise NotImplementedError("...") |
| |
| |
| class HtmlReportStage(Stage): |
| |
| priority = StepOrder.REPORT |
| |
| def run(self, ctx: TestRun) -> None: |
| # TODO(koder): load data from storage |
| raise NotImplementedError("...") |
| |
| |
| # TODO: need to be revised, have to user StatProps fields instead |
| class StoragePerfSummary: |
| def __init__(self, name: str) -> None: |
| self.direct_iops_r_max = 0 # type: int |
| self.direct_iops_w_max = 0 # type: int |
| |
| # 64 used instead of 4k to faster feed caches |
| self.direct_iops_w64_max = 0 # type: int |
| |
| self.rws4k_10ms = 0 # type: int |
| self.rws4k_30ms = 0 # type: int |
| self.rws4k_100ms = 0 # type: int |
| self.bw_write_max = 0 # type: int |
| self.bw_read_max = 0 # type: int |
| |
| self.bw = None # type: float |
| self.iops = None # type: float |
| self.lat = None # type: float |
| self.lat_50 = None # type: float |
| self.lat_95 = None # type: float |
| |
| |
| class HTMLBlock: |
| data = None # type: str |
| js_links = [] # type: List[str] |
| css_links = [] # type: List[str] |
| |
| |
| class Reporter(metaclass=abc.ABCMeta): |
| @abc.abstractmethod |
| def get_divs(self, config, storage) -> Iterator[Tuple[str, str, HTMLBlock]]: |
| pass |
| |
| |
| # Main performance report |
| class PerformanceSummary(Reporter): |
| """Creates graph, which show how IOPS and Latency depend on QD""" |
| |
| |
| # Main performance report |
| class IOPS_QD(Reporter): |
| """Creates graph, which show how IOPS and Latency depend on QD""" |
| |
| |
| # Linearization report |
| class IOPS_Bsize(Reporter): |
| """Creates graphs, which show how IOPS and Latency depend on block size""" |
| |
| |
| # IOPS/latency distribution |
| class IOPSHist(Reporter): |
| """IOPS.latency distribution histogram""" |
| |
| |
| # IOPS/latency over test time |
| class IOPSTime(Reporter): |
| """IOPS/latency during test""" |
| def get_divs(self, config, storage) -> Iterator[Tuple[str, str, HTMLBlock]]: |
| pass |
| |
| |
| # Cluster load over test time |
| class ClusterLoad(Reporter): |
| """IOPS/latency during test""" |
| |
| |
| # Node load over test time |
| class NodeLoad(Reporter): |
| """IOPS/latency during test""" |
| |
| |
| # Ceph cluster summary |
| class CephClusterSummary(Reporter): |
| """IOPS/latency during test""" |
| |
| |
| # TODO: Resource consumption report |
| # TODO: Ceph operation breakout report |
| # TODO: Resource consumption for different type of test |
| |
| |
| # |
| # # disk_info = None |
| # # base = None |
| # # linearity = None |
| # |
| # |
| # def group_by_name(test_data): |
| # name_map = collections.defaultdict(lambda: []) |
| # |
| # for data in test_data: |
| # name_map[(data.name, data.summary())].append(data) |
| # |
| # return name_map |
| # |
| # |
| # def report(name, required_fields): |
| # def closure(func): |
| # report_funcs.append((required_fields.split(","), name, func)) |
| # return func |
| # return closure |
| # |
| # |
| # def get_test_lcheck_params(pinfo): |
| # res = [{ |
| # 's': 'sync', |
| # 'd': 'direct', |
| # 'a': 'async', |
| # 'x': 'sync direct' |
| # }[pinfo.sync_mode]] |
| # |
| # res.append(pinfo.p.rw) |
| # |
| # return " ".join(res) |
| # |
| # |
| # def get_emb_data_svg(plt): |
| # sio = StringIO() |
| # plt.savefig(sio, format='svg') |
| # img_start = "<!-- Created with matplotlib (http://matplotlib.org/) -->" |
| # return sio.getvalue().split(img_start, 1)[1] |
| # |
| # |
| # def get_template(templ_name): |
| # very_root_dir = os.path.dirname(os.path.dirname(wally.__file__)) |
| # templ_dir = os.path.join(very_root_dir, 'report_templates') |
| # templ_file = os.path.join(templ_dir, templ_name) |
| # return open(templ_file, 'r').read() |
| # |
| # |
| # def group_by(data, func): |
| # if len(data) < 2: |
| # yield data |
| # return |
| # |
| # ndata = [(func(dt), dt) for dt in data] |
| # ndata.sort(key=func) |
| # pkey, dt = ndata[0] |
| # curr_list = [dt] |
| # |
| # for key, val in ndata[1:]: |
| # if pkey != key: |
| # yield curr_list |
| # curr_list = [val] |
| # else: |
| # curr_list.append(val) |
| # pkey = key |
| # |
| # yield curr_list |
| # |
| # |
| # @report('linearity', 'linearity_test') |
| # def linearity_report(processed_results, lab_info, comment): |
| # labels_and_data_mp = collections.defaultdict(lambda: []) |
| # vls = {} |
| # |
| # # plot io_time = func(bsize) |
| # for res in processed_results.values(): |
| # if res.name.startswith('linearity_test'): |
| # iotimes = [1000. / val for val in res.iops.raw] |
| # |
| # op_summ = get_test_summary(res.params)[:3] |
| # |
| # labels_and_data_mp[op_summ].append( |
| # [res.p.blocksize, res.iops.raw, iotimes]) |
| # |
| # cvls = res.params.vals.copy() |
| # del cvls['blocksize'] |
| # del cvls['rw'] |
| # |
| # cvls.pop('sync', None) |
| # cvls.pop('direct', None) |
| # cvls.pop('buffered', None) |
| # |
| # if op_summ not in vls: |
| # vls[op_summ] = cvls |
| # else: |
| # assert cvls == vls[op_summ] |
| # |
| # all_labels = None |
| # _, ax1 = plt.subplots() |
| # for name, labels_and_data in labels_and_data_mp.items(): |
| # labels_and_data.sort(key=lambda x: ssize2b(x[0])) |
| # |
| # labels, _, iotimes = zip(*labels_and_data) |
| # |
| # if all_labels is None: |
| # all_labels = labels |
| # else: |
| # assert all_labels == labels |
| # |
| # plt.boxplot(iotimes) |
| # if len(labels_and_data) > 2 and \ |
| # ssize2b(labels_and_data[-2][0]) >= 4096: |
| # |
| # xt = range(1, len(labels) + 1) |
| # |
| # def io_time(sz, bw, initial_lat): |
| # return sz / bw + initial_lat |
| # |
| # x = numpy.array(map(ssize2b, labels)) |
| # y = numpy.array([sum(dt) / len(dt) for dt in iotimes]) |
| # popt, _ = scipy.optimize.curve_fit(io_time, x, y, p0=(100., 1.)) |
| # |
| # y1 = io_time(x, *popt) |
| # plt.plot(xt, y1, linestyle='--', |
| # label=name + ' LS linear approx') |
| # |
| # for idx, (sz, _, _) in enumerate(labels_and_data): |
| # if ssize2b(sz) >= 4096: |
| # break |
| # |
| # bw = (x[-1] - x[idx]) / (y[-1] - y[idx]) |
| # lat = y[-1] - x[-1] / bw |
| # y2 = io_time(x, bw, lat) |
| # plt.plot(xt, y2, linestyle='--', |
| # label=abbv_name_to_full(name) + |
| # ' (4k & max) linear approx') |
| # |
| # plt.setp(ax1, xticklabels=labels) |
| # |
| # plt.xlabel("Block size") |
| # plt.ylabel("IO time, ms") |
| # |
| # plt.subplots_adjust(top=0.85) |
| # plt.legend(bbox_to_anchor=(0.5, 1.15), |
| # loc='upper center', |
| # prop={'size': 10}, ncol=2) |
| # plt.grid() |
| # iotime_plot = get_emb_data_svg(plt) |
| # plt.clf() |
| # |
| # # plot IOPS = func(bsize) |
| # _, ax1 = plt.subplots() |
| # |
| # for name, labels_and_data in labels_and_data_mp.items(): |
| # labels_and_data.sort(key=lambda x: ssize2b(x[0])) |
| # _, data, _ = zip(*labels_and_data) |
| # plt.boxplot(data) |
| # avg = [float(sum(arr)) / len(arr) for arr in data] |
| # xt = range(1, len(data) + 1) |
| # plt.plot(xt, avg, linestyle='--', |
| # label=abbv_name_to_full(name) + " avg") |
| # |
| # plt.setp(ax1, xticklabels=labels) |
| # plt.xlabel("Block size") |
| # plt.ylabel("IOPS") |
| # plt.legend(bbox_to_anchor=(0.5, 1.15), |
| # loc='upper center', |
| # prop={'size': 10}, ncol=2) |
| # plt.grid() |
| # plt.subplots_adjust(top=0.85) |
| # |
| # iops_plot = get_emb_data_svg(plt) |
| # |
| # res = set(get_test_lcheck_params(res) for res in processed_results.values()) |
| # ncount = list(set(res.testnodes_count for res in processed_results.values())) |
| # conc = list(set(res.concurence for res in processed_results.values())) |
| # |
| # assert len(conc) == 1 |
| # assert len(ncount) == 1 |
| # |
| # descr = { |
| # 'vm_count': ncount[0], |
| # 'concurence': conc[0], |
| # 'oper_descr': ", ".join(res).capitalize() |
| # } |
| # |
| # params_map = {'iotime_vs_size': iotime_plot, |
| # 'iops_vs_size': iops_plot, |
| # 'descr': descr} |
| # |
| # return get_template('report_linearity.html').format(**params_map) |
| # |
| # |
| # @report('lat_vs_iops', 'lat_vs_iops') |
| # def lat_vs_iops(processed_results, lab_info, comment): |
| # lat_iops = collections.defaultdict(lambda: []) |
| # requsted_vs_real = collections.defaultdict(lambda: {}) |
| # |
| # for res in processed_results.values(): |
| # if res.name.startswith('lat_vs_iops'): |
| # lat_iops[res.concurence].append((res.lat, |
| # 0, |
| # res.iops.average, |
| # res.iops.deviation)) |
| # # lat_iops[res.concurence].append((res.lat.average / 1000.0, |
| # # res.lat.deviation / 1000.0, |
| # # res.iops.average, |
| # # res.iops.deviation)) |
| # requested_iops = res.p.rate_iops * res.concurence |
| # requsted_vs_real[res.concurence][requested_iops] = \ |
| # (res.iops.average, res.iops.deviation) |
| # |
| # colors = ['red', 'green', 'blue', 'orange', 'magenta', "teal"] |
| # colors_it = iter(colors) |
| # for conc, lat_iops in sorted(lat_iops.items()): |
| # lat, dev, iops, iops_dev = zip(*lat_iops) |
| # plt.errorbar(iops, lat, xerr=iops_dev, yerr=dev, fmt='ro', |
| # label=str(conc) + " threads", |
| # color=next(colors_it)) |
| # |
| # plt.xlabel("IOPS") |
| # plt.ylabel("Latency, ms") |
| # plt.grid() |
| # plt.legend(loc=0) |
| # plt_iops_vs_lat = get_emb_data_svg(plt) |
| # plt.clf() |
| # |
| # colors_it = iter(colors) |
| # for conc, req_vs_real in sorted(requsted_vs_real.items()): |
| # req, real = zip(*sorted(req_vs_real.items())) |
| # iops, dev = zip(*real) |
| # plt.errorbar(req, iops, yerr=dev, fmt='ro', |
| # label=str(conc) + " threads", |
| # color=next(colors_it)) |
| # plt.xlabel("Requested IOPS") |
| # plt.ylabel("Get IOPS") |
| # plt.grid() |
| # plt.legend(loc=0) |
| # plt_iops_vs_requested = get_emb_data_svg(plt) |
| # |
| # res1 = processed_results.values()[0] |
| # params_map = {'iops_vs_lat': plt_iops_vs_lat, |
| # 'iops_vs_requested': plt_iops_vs_requested, |
| # 'oper_descr': get_test_lcheck_params(res1).capitalize()} |
| # |
| # return get_template('report_iops_vs_lat.html').format(**params_map) |
| # |
| # |
| # def render_all_html(comment, info, lab_description, images, templ_name): |
| # data = info.__dict__.copy() |
| # for name, val in data.items(): |
| # if not name.startswith('__'): |
| # if val is None: |
| # if name in ('direct_iops_w64_max', 'direct_iops_w_max'): |
| # data[name] = ('-', '-', '-') |
| # else: |
| # data[name] = '-' |
| # elif isinstance(val, (int, float, long)): |
| # data[name] = round_3_digit(val) |
| # |
| # data['bw_read_max'] = (data['bw_read_max'][0] // 1024, |
| # data['bw_read_max'][1], |
| # data['bw_read_max'][2]) |
| # |
| # data['bw_write_max'] = (data['bw_write_max'][0] // 1024, |
| # data['bw_write_max'][1], |
| # data['bw_write_max'][2]) |
| # |
| # images.update(data) |
| # templ = get_template(templ_name) |
| # return templ.format(lab_info=lab_description, |
| # comment=comment, |
| # **images) |
| # |
| # |
| # def io_chart(title, concurence, |
| # latv, latv_min, latv_max, |
| # iops_or_bw, iops_or_bw_err, |
| # legend, |
| # log_iops=False, |
| # log_lat=False, |
| # boxplots=False, |
| # latv_50=None, |
| # latv_95=None, |
| # error2=None): |
| # |
| # matplotlib.rcParams.update({'font.size': 10}) |
| # points = " MiBps" if legend == 'BW' else "" |
| # lc = len(concurence) |
| # width = 0.35 |
| # xt = range(1, lc + 1) |
| # |
| # op_per_vm = [v / (vm * th) for v, (vm, th) in zip(iops_or_bw, concurence)] |
| # fig, p1 = plt.subplots() |
| # xpos = [i - width / 2 for i in xt] |
| # |
| # p1.bar(xpos, iops_or_bw, |
| # width=width, |
| # color='y', |
| # label=legend) |
| # |
| # err1_leg = None |
| # for pos, y, err in zip(xpos, iops_or_bw, iops_or_bw_err): |
| # err1_leg = p1.errorbar(pos + width / 2, |
| # y, |
| # err, |
| # color='magenta') |
| # |
| # err2_leg = None |
| # if error2 is not None: |
| # for pos, y, err in zip(xpos, iops_or_bw, error2): |
| # err2_leg = p1.errorbar(pos + width / 2 + 0.08, |
| # y, |
| # err, |
| # lw=2, |
| # alpha=0.5, |
| # color='teal') |
| # |
| # p1.grid(True) |
| # p1.plot(xt, op_per_vm, '--', label=legend + "/thread", color='black') |
| # handles1, labels1 = p1.get_legend_handles_labels() |
| # |
| # handles1 += [err1_leg] |
| # labels1 += ["95% conf"] |
| # |
| # if err2_leg is not None: |
| # handles1 += [err2_leg] |
| # labels1 += ["95% dev"] |
| # |
| # p2 = p1.twinx() |
| # |
| # if latv_50 is None: |
| # p2.plot(xt, latv_max, label="lat max") |
| # p2.plot(xt, latv, label="lat avg") |
| # p2.plot(xt, latv_min, label="lat min") |
| # else: |
| # p2.plot(xt, latv_50, label="lat med") |
| # p2.plot(xt, latv_95, label="lat 95%") |
| # |
| # plt.xlim(0.5, lc + 0.5) |
| # plt.xticks(xt, ["{0} * {1}".format(vm, th) for (vm, th) in concurence]) |
| # p1.set_xlabel("VM Count * Thread per VM") |
| # p1.set_ylabel(legend + points) |
| # p2.set_ylabel("Latency ms") |
| # plt.title(title) |
| # handles2, labels2 = p2.get_legend_handles_labels() |
| # |
| # plt.legend(handles1 + handles2, labels1 + labels2, |
| # loc='center left', bbox_to_anchor=(1.1, 0.81)) |
| # |
| # if log_iops: |
| # p1.set_yscale('log') |
| # |
| # if log_lat: |
| # p2.set_yscale('log') |
| # |
| # plt.subplots_adjust(right=0.68) |
| # |
| # return get_emb_data_svg(plt) |
| # |
| # |
| # def make_plots(processed_results, plots): |
| # """ |
| # processed_results: [PerfInfo] |
| # plots = [(test_name_prefix:str, fname:str, description:str)] |
| # """ |
| # files = {} |
| # for name_pref, fname, desc in plots: |
| # chart_data = [] |
| # |
| # for res in processed_results: |
| # summ = res.name + "_" + res.summary |
| # if summ.startswith(name_pref): |
| # chart_data.append(res) |
| # |
| # if len(chart_data) == 0: |
| # raise ValueError("Can't found any date for " + name_pref) |
| # |
| # use_bw = ssize2b(chart_data[0].p.blocksize) > 16 * 1024 |
| # |
| # chart_data.sort(key=lambda x: x.params['vals']['numjobs']) |
| # |
| # lat = None |
| # lat_min = None |
| # lat_max = None |
| # |
| # lat_50 = [x.lat_50 for x in chart_data] |
| # lat_95 = [x.lat_95 for x in chart_data] |
| # |
| # lat_diff_max = max(x.lat_95 / x.lat_50 for x in chart_data) |
| # lat_log_scale = (lat_diff_max > 10) |
| # |
| # testnodes_count = x.testnodes_count |
| # concurence = [(testnodes_count, x.concurence) |
| # for x in chart_data] |
| # |
| # if use_bw: |
| # data = [x.bw.average / 1000 for x in chart_data] |
| # data_conf = [x.bw.confidence / 1000 for x in chart_data] |
| # data_dev = [x.bw.deviation * 2.5 / 1000 for x in chart_data] |
| # name = "BW" |
| # else: |
| # data = [x.iops.average for x in chart_data] |
| # data_conf = [x.iops.confidence for x in chart_data] |
| # data_dev = [x.iops.deviation * 2 for x in chart_data] |
| # name = "IOPS" |
| # |
| # fc = io_chart(title=desc, |
| # concurence=concurence, |
| # |
| # latv=lat, |
| # latv_min=lat_min, |
| # latv_max=lat_max, |
| # |
| # iops_or_bw=data, |
| # iops_or_bw_err=data_conf, |
| # |
| # legend=name, |
| # log_lat=lat_log_scale, |
| # |
| # latv_50=lat_50, |
| # latv_95=lat_95, |
| # |
| # error2=data_dev) |
| # files[fname] = fc |
| # |
| # return files |
| # |
| # |
| # def find_max_where(processed_results, sync_mode, blocksize, rw, iops=True): |
| # result = None |
| # attr = 'iops' if iops else 'bw' |
| # for measurement in processed_results: |
| # ok = measurement.sync_mode == sync_mode |
| # ok = ok and (measurement.p.blocksize == blocksize) |
| # ok = ok and (measurement.p.rw == rw) |
| # |
| # if ok: |
| # field = getattr(measurement, attr) |
| # |
| # if result is None: |
| # result = field |
| # elif field.average > result.average: |
| # result = field |
| # |
| # return result |
| # |
| # |
| # def get_disk_info(processed_results): |
| # di = DiskInfo() |
| # di.direct_iops_w_max = find_max_where(processed_results, |
| # 'd', '4k', 'randwrite') |
| # di.direct_iops_r_max = find_max_where(processed_results, |
| # 'd', '4k', 'randread') |
| # |
| # di.direct_iops_w64_max = find_max_where(processed_results, |
| # 'd', '64k', 'randwrite') |
| # |
| # for sz in ('16m', '64m'): |
| # di.bw_write_max = find_max_where(processed_results, |
| # 'd', sz, 'randwrite', False) |
| # if di.bw_write_max is not None: |
| # break |
| # |
| # if di.bw_write_max is None: |
| # for sz in ('1m', '2m', '4m', '8m'): |
| # di.bw_write_max = find_max_where(processed_results, |
| # 'd', sz, 'write', False) |
| # if di.bw_write_max is not None: |
| # break |
| # |
| # for sz in ('16m', '64m'): |
| # di.bw_read_max = find_max_where(processed_results, |
| # 'd', sz, 'randread', False) |
| # if di.bw_read_max is not None: |
| # break |
| # |
| # if di.bw_read_max is None: |
| # di.bw_read_max = find_max_where(processed_results, |
| # 'd', '1m', 'read', False) |
| # |
| # rws4k_iops_lat_th = [] |
| # for res in processed_results: |
| # if res.sync_mode in 'xs' and res.p.blocksize == '4k': |
| # if res.p.rw != 'randwrite': |
| # continue |
| # rws4k_iops_lat_th.append((res.iops.average, |
| # res.lat, |
| # # res.lat.average, |
| # res.concurence)) |
| # |
| # rws4k_iops_lat_th.sort(key=lambda x: x[2]) |
| # |
| # latv = [lat for _, lat, _ in rws4k_iops_lat_th] |
| # |
| # for tlat in [10, 30, 100]: |
| # pos = bisect.bisect_left(latv, tlat) |
| # if 0 == pos: |
| # setattr(di, 'rws4k_{}ms'.format(tlat), 0) |
| # elif pos == len(latv): |
| # iops3, _, _ = rws4k_iops_lat_th[-1] |
| # iops3 = int(round_3_digit(iops3)) |
| # setattr(di, 'rws4k_{}ms'.format(tlat), ">=" + str(iops3)) |
| # else: |
| # lat1 = latv[pos - 1] |
| # lat2 = latv[pos] |
| # |
| # iops1, _, th1 = rws4k_iops_lat_th[pos - 1] |
| # iops2, _, th2 = rws4k_iops_lat_th[pos] |
| # |
| # th_lat_coef = (th2 - th1) / (lat2 - lat1) |
| # th3 = th_lat_coef * (tlat - lat1) + th1 |
| # |
| # th_iops_coef = (iops2 - iops1) / (th2 - th1) |
| # iops3 = th_iops_coef * (th3 - th1) + iops1 |
| # iops3 = int(round_3_digit(iops3)) |
| # setattr(di, 'rws4k_{}ms'.format(tlat), iops3) |
| # |
| # hdi = DiskInfo() |
| # |
| # def pp(x): |
| # med, conf = x.rounded_average_conf() |
| # conf_perc = int(float(conf) / med * 100) |
| # dev_perc = int(float(x.deviation) / med * 100) |
| # return (round_3_digit(med), conf_perc, dev_perc) |
| # |
| # hdi.direct_iops_r_max = pp(di.direct_iops_r_max) |
| # |
| # if di.direct_iops_w_max is not None: |
| # hdi.direct_iops_w_max = pp(di.direct_iops_w_max) |
| # else: |
| # hdi.direct_iops_w_max = None |
| # |
| # if di.direct_iops_w64_max is not None: |
| # hdi.direct_iops_w64_max = pp(di.direct_iops_w64_max) |
| # else: |
| # hdi.direct_iops_w64_max = None |
| # |
| # hdi.bw_write_max = pp(di.bw_write_max) |
| # hdi.bw_read_max = pp(di.bw_read_max) |
| # |
| # hdi.rws4k_10ms = di.rws4k_10ms if 0 != di.rws4k_10ms else None |
| # hdi.rws4k_30ms = di.rws4k_30ms if 0 != di.rws4k_30ms else None |
| # hdi.rws4k_100ms = di.rws4k_100ms if 0 != di.rws4k_100ms else None |
| # return hdi |
| # |
| # |
| # @report('hdd', 'hdd') |
| # def make_hdd_report(processed_results, lab_info, comment): |
| # plots = [ |
| # ('hdd_rrd4k', 'rand_read_4k', 'Random read 4k direct IOPS'), |
| # ('hdd_rwx4k', 'rand_write_4k', 'Random write 4k sync IOPS') |
| # ] |
| # perf_infos = [res.disk_perf_info() for res in processed_results] |
| # images = make_plots(perf_infos, plots) |
| # di = get_disk_info(perf_infos) |
| # return render_all_html(comment, di, lab_info, images, "report_hdd.html") |
| # |
| # |
| # @report('cinder_iscsi', 'cinder_iscsi') |
| # def make_cinder_iscsi_report(processed_results, lab_info, comment): |
| # plots = [ |
| # ('cinder_iscsi_rrd4k', 'rand_read_4k', 'Random read 4k direct IOPS'), |
| # ('cinder_iscsi_rwx4k', 'rand_write_4k', 'Random write 4k sync IOPS') |
| # ] |
| # perf_infos = [res.disk_perf_info() for res in processed_results] |
| # try: |
| # images = make_plots(perf_infos, plots) |
| # except ValueError: |
| # plots = [ |
| # ('cinder_iscsi_rrd4k', 'rand_read_4k', 'Random read 4k direct IOPS'), |
| # ('cinder_iscsi_rws4k', 'rand_write_4k', 'Random write 4k sync IOPS') |
| # ] |
| # images = make_plots(perf_infos, plots) |
| # di = get_disk_info(perf_infos) |
| # |
| # return render_all_html(comment, di, lab_info, images, "report_cinder_iscsi.html") |
| # |
| # |
| # @report('ceph', 'ceph') |
| # def make_ceph_report(processed_results, lab_info, comment): |
| # plots = [ |
| # ('ceph_rrd4k', 'rand_read_4k', 'Random read 4k direct IOPS'), |
| # ('ceph_rws4k', 'rand_write_4k', 'Random write 4k sync IOPS'), |
| # ('ceph_rrd16m', 'rand_read_16m', 'Random read 16m direct MiBps'), |
| # ('ceph_rwd16m', 'rand_write_16m', |
| # 'Random write 16m direct MiBps'), |
| # ] |
| # |
| # perf_infos = [res.disk_perf_info() for res in processed_results] |
| # images = make_plots(perf_infos, plots) |
| # di = get_disk_info(perf_infos) |
| # return render_all_html(comment, di, lab_info, images, "report_ceph.html") |
| # |
| # |
| # @report('mixed', 'mixed') |
| # def make_mixed_report(processed_results, lab_info, comment): |
| # # |
| # # IOPS(X% read) = 100 / ( X / IOPS_W + (100 - X) / IOPS_R ) |
| # # |
| # |
| # perf_infos = [res.disk_perf_info() for res in processed_results] |
| # mixed = collections.defaultdict(lambda: []) |
| # |
| # is_ssd = False |
| # for res in perf_infos: |
| # if res.name.startswith('mixed'): |
| # if res.name.startswith('mixed-ssd'): |
| # is_ssd = True |
| # mixed[res.concurence].append((res.p.rwmixread, |
| # res.lat, |
| # 0, |
| # # res.lat.average / 1000.0, |
| # # res.lat.deviation / 1000.0, |
| # res.iops.average, |
| # res.iops.deviation)) |
| # |
| # if len(mixed) == 0: |
| # raise ValueError("No mixed load found") |
| # |
| # fig, p1 = plt.subplots() |
| # p2 = p1.twinx() |
| # |
| # colors = ['red', 'green', 'blue', 'orange', 'magenta', "teal"] |
| # colors_it = iter(colors) |
| # for conc, mix_lat_iops in sorted(mixed.items()): |
| # mix_lat_iops = sorted(mix_lat_iops) |
| # read_perc, lat, dev, iops, iops_dev = zip(*mix_lat_iops) |
| # p1.errorbar(read_perc, iops, color=next(colors_it), |
| # yerr=iops_dev, label=str(conc) + " th") |
| # |
| # p2.errorbar(read_perc, lat, color=next(colors_it), |
| # ls='--', yerr=dev, label=str(conc) + " th lat") |
| # |
| # if is_ssd: |
| # p1.set_yscale('log') |
| # p2.set_yscale('log') |
| # |
| # p1.set_xlim(-5, 105) |
| # |
| # read_perc = set(read_perc) |
| # read_perc.add(0) |
| # read_perc.add(100) |
| # read_perc = sorted(read_perc) |
| # |
| # plt.xticks(read_perc, map(str, read_perc)) |
| # |
| # p1.grid(True) |
| # p1.set_xlabel("% of reads") |
| # p1.set_ylabel("Mixed IOPS") |
| # p2.set_ylabel("Latency, ms") |
| # |
| # handles1, labels1 = p1.get_legend_handles_labels() |
| # handles2, labels2 = p2.get_legend_handles_labels() |
| # plt.subplots_adjust(top=0.85) |
| # plt.legend(handles1 + handles2, labels1 + labels2, |
| # bbox_to_anchor=(0.5, 1.15), |
| # loc='upper center', |
| # prop={'size': 12}, ncol=3) |
| # plt.show() |
| # |
| # |
| # def make_load_report(idx, results_dir, fname): |
| # dpath = os.path.join(results_dir, "io_" + str(idx)) |
| # files = sorted(os.listdir(dpath)) |
| # gf = lambda x: "_".join(x.rsplit(".", 1)[0].split('_')[:3]) |
| # |
| # for key, group in itertools.groupby(files, gf): |
| # fname = os.path.join(dpath, key + ".fio") |
| # |
| # cfgs = list(parse_all_in_1(open(fname).read(), fname)) |
| # |
| # fname = os.path.join(dpath, key + "_lat.log") |
| # |
| # curr = [] |
| # arrays = [] |
| # |
| # with open(fname) as fd: |
| # for offset, lat, _, _ in csv.reader(fd): |
| # offset = int(offset) |
| # lat = int(lat) |
| # if len(curr) > 0 and curr[-1][0] > offset: |
| # arrays.append(curr) |
| # curr = [] |
| # curr.append((offset, lat)) |
| # arrays.append(curr) |
| # conc = int(cfgs[0].vals.get('numjobs', 1)) |
| # |
| # if conc != 5: |
| # continue |
| # |
| # assert len(arrays) == len(cfgs) * conc |
| # |
| # garrays = [[(0, 0)] for _ in range(conc)] |
| # |
| # for offset in range(len(cfgs)): |
| # for acc, new_arr in zip(garrays, arrays[offset * conc:(offset + 1) * conc]): |
| # last = acc[-1][0] |
| # for off, lat in new_arr: |
| # acc.append((off / 1000. + last, lat / 1000.)) |
| # |
| # for cfg, arr in zip(cfgs, garrays): |
| # plt.plot(*zip(*arr[1:])) |
| # plt.show() |
| # exit(1) |
| # |
| # |
| # def make_io_report(dinfo, comment, path, lab_info=None): |
| # lab_info = { |
| # "total_disk": "None", |
| # "total_memory": "None", |
| # "nodes_count": "None", |
| # "processor_count": "None" |
| # } |
| # |
| # try: |
| # res_fields = sorted(v.name for v in dinfo) |
| # |
| # found = False |
| # for fields, name, func in report_funcs: |
| # for field in fields: |
| # pos = bisect.bisect_left(res_fields, field) |
| # |
| # if pos == len(res_fields): |
| # break |
| # |
| # if not res_fields[pos].startswith(field): |
| # break |
| # else: |
| # found = True |
| # hpath = path.format(name) |
| # |
| # try: |
| # report = func(dinfo, lab_info, comment) |
| # except: |
| # logger.exception("Diring {0} report generation".format(name)) |
| # continue |
| # |
| # if report is not None: |
| # try: |
| # with open(hpath, "w") as fd: |
| # fd.write(report) |
| # except: |
| # logger.exception("Diring saving {0} report".format(name)) |
| # continue |
| # logger.info("Report {0} saved into {1}".format(name, hpath)) |
| # else: |
| # logger.warning("No report produced by {0!r}".format(name)) |
| # |
| # if not found: |
| # logger.warning("No report generator found for this load") |
| # |
| # except Exception as exc: |
| # import traceback |
| # traceback.print_exc() |
| # logger.error("Failed to generate html report:" + str(exc)) |
| # |
| # |
| # # @classmethod |
| # # def prepare_data(cls, results) -> List[Dict[str, Any]]: |
| # # """create a table with io performance report for console""" |
| # # |
| # # def key_func(data: FioRunResult) -> Tuple[str, str, str, str, int]: |
| # # tpl = data.summary_tpl() |
| # # return (data.name, |
| # # tpl.oper, |
| # # tpl.mode, |
| # # ssize2b(tpl.bsize), |
| # # int(tpl.th_count) * int(tpl.vm_count)) |
| # # res = [] |
| # # |
| # # for item in sorted(results, key=key_func): |
| # # test_dinfo = item.disk_perf_info() |
| # # testnodes_count = len(item.config.nodes) |
| # # |
| # # iops, _ = test_dinfo.iops.rounded_average_conf() |
| # # |
| # # if test_dinfo.iops_sys is not None: |
| # # iops_sys, iops_sys_conf = test_dinfo.iops_sys.rounded_average_conf() |
| # # _, iops_sys_dev = test_dinfo.iops_sys.rounded_average_dev() |
| # # iops_sys_per_vm = round_3_digit(iops_sys / testnodes_count) |
| # # iops_sys = round_3_digit(iops_sys) |
| # # else: |
| # # iops_sys = None |
| # # iops_sys_per_vm = None |
| # # iops_sys_dev = None |
| # # iops_sys_conf = None |
| # # |
| # # bw, bw_conf = test_dinfo.bw.rounded_average_conf() |
| # # _, bw_dev = test_dinfo.bw.rounded_average_dev() |
| # # conf_perc = int(round(bw_conf * 100 / bw)) |
| # # dev_perc = int(round(bw_dev * 100 / bw)) |
| # # |
| # # lat_50 = round_3_digit(int(test_dinfo.lat_50)) |
| # # lat_95 = round_3_digit(int(test_dinfo.lat_95)) |
| # # lat_avg = round_3_digit(int(test_dinfo.lat_avg)) |
| # # |
| # # iops_per_vm = round_3_digit(iops / testnodes_count) |
| # # bw_per_vm = round_3_digit(bw / testnodes_count) |
| # # |
| # # iops = round_3_digit(iops) |
| # # bw = round_3_digit(bw) |
| # # |
| # # summ = "{0.oper}{0.mode} {0.bsize:>4} {0.th_count:>3}th {0.vm_count:>2}vm".format(item.summary_tpl()) |
| # # |
| # # res.append({"name": key_func(item)[0], |
| # # "key": key_func(item)[:4], |
| # # "summ": summ, |
| # # "iops": int(iops), |
| # # "bw": int(bw), |
| # # "conf": str(conf_perc), |
| # # "dev": str(dev_perc), |
| # # "iops_per_vm": int(iops_per_vm), |
| # # "bw_per_vm": int(bw_per_vm), |
| # # "lat_50": lat_50, |
| # # "lat_95": lat_95, |
| # # "lat_avg": lat_avg, |
| # # |
| # # "iops_sys": iops_sys, |
| # # "iops_sys_per_vm": iops_sys_per_vm, |
| # # "sys_conf": iops_sys_conf, |
| # # "sys_dev": iops_sys_dev}) |
| # # |
| # # return res |
| # # |
| # # Field = collections.namedtuple("Field", ("header", "attr", "allign", "size")) |
| # # fiels_and_header = [ |
| # # Field("Name", "name", "l", 7), |
| # # Field("Description", "summ", "l", 19), |
| # # Field("IOPS\ncum", "iops", "r", 3), |
| # # # Field("IOPS_sys\ncum", "iops_sys", "r", 3), |
| # # Field("KiBps\ncum", "bw", "r", 6), |
| # # Field("Cnf %\n95%", "conf", "r", 3), |
| # # Field("Dev%", "dev", "r", 3), |
| # # Field("iops\n/vm", "iops_per_vm", "r", 3), |
| # # Field("KiBps\n/vm", "bw_per_vm", "r", 6), |
| # # Field("lat ms\nmedian", "lat_50", "r", 3), |
| # # Field("lat ms\n95%", "lat_95", "r", 3), |
| # # Field("lat\navg", "lat_avg", "r", 3), |
| # # ] |
| # # |
| # # fiels_and_header_dct = dict((item.attr, item) for item in fiels_and_header) |
| # # |
| # # @classmethod |
| # # def format_for_console(cls, results) -> str: |
| # # """create a table with io performance report for console""" |
| # # |
| # # tab = texttable.Texttable(max_width=120) |
| # # tab.set_deco(tab.HEADER | tab.VLINES | tab.BORDER) |
| # # tab.set_cols_align([f.allign for f in cls.fiels_and_header]) |
| # # sep = ["-" * f.size for f in cls.fiels_and_header] |
| # # tab.header([f.header for f in cls.fiels_and_header]) |
| # # prev_k = None |
| # # for item in cls.prepare_data(results): |
| # # if prev_k is not None: |
| # # if prev_k != item["key"]: |
| # # tab.add_row(sep) |
| # # |
| # # prev_k = item["key"] |
| # # tab.add_row([item[f.attr] for f in cls.fiels_and_header]) |
| # # |
| # # return tab.draw() |
| # # |
| # # @classmethod |
| # # def format_diff_for_console(cls, list_of_results: List[Any]) -> str: |
| # # """create a table with io performance report for console""" |
| # # |
| # # tab = texttable.Texttable(max_width=200) |
| # # tab.set_deco(tab.HEADER | tab.VLINES | tab.BORDER) |
| # # |
| # # header = [ |
| # # cls.fiels_and_header_dct["name"].header, |
| # # cls.fiels_and_header_dct["summ"].header, |
| # # ] |
| # # allign = ["l", "l"] |
| # # |
| # # header.append("IOPS ~ Cnf% ~ Dev%") |
| # # allign.extend(["r"] * len(list_of_results)) |
| # # header.extend( |
| # # "IOPS_{0} %".format(i + 2) for i in range(len(list_of_results[1:])) |
| # # ) |
| # # |
| # # header.append("BW") |
| # # allign.extend(["r"] * len(list_of_results)) |
| # # header.extend( |
| # # "BW_{0} %".format(i + 2) for i in range(len(list_of_results[1:])) |
| # # ) |
| # # |
| # # header.append("LAT") |
| # # allign.extend(["r"] * len(list_of_results)) |
| # # header.extend( |
| # # "LAT_{0}".format(i + 2) for i in range(len(list_of_results[1:])) |
| # # ) |
| # # |
| # # tab.header(header) |
| # # sep = ["-" * 3] * len(header) |
| # # processed_results = map(cls.prepare_data, list_of_results) |
| # # |
| # # key2results = [] |
| # # for res in processed_results: |
| # # key2results.append(dict( |
| # # ((item["name"], item["summ"]), item) for item in res |
| # # )) |
| # # |
| # # prev_k = None |
| # # iops_frmt = "{0[iops]} ~ {0[conf]:>2} ~ {0[dev]:>2}" |
| # # for item in processed_results[0]: |
| # # if prev_k is not None: |
| # # if prev_k != item["key"]: |
| # # tab.add_row(sep) |
| # # |
| # # prev_k = item["key"] |
| # # |
| # # key = (item['name'], item['summ']) |
| # # line = list(key) |
| # # base = key2results[0][key] |
| # # |
| # # line.append(iops_frmt.format(base)) |
| # # |
| # # for test_results in key2results[1:]: |
| # # val = test_results.get(key) |
| # # if val is None: |
| # # line.append("-") |
| # # elif base['iops'] == 0: |
| # # line.append("Nan") |
| # # else: |
| # # prc_val = {'dev': val['dev'], 'conf': val['conf']} |
| # # prc_val['iops'] = int(100 * val['iops'] / base['iops']) |
| # # line.append(iops_frmt.format(prc_val)) |
| # # |
| # # line.append(base['bw']) |
| # # |
| # # for test_results in key2results[1:]: |
| # # val = test_results.get(key) |
| # # if val is None: |
| # # line.append("-") |
| # # elif base['bw'] == 0: |
| # # line.append("Nan") |
| # # else: |
| # # line.append(int(100 * val['bw'] / base['bw'])) |
| # # |
| # # for test_results in key2results: |
| # # val = test_results.get(key) |
| # # if val is None: |
| # # line.append("-") |
| # # else: |
| # # line.append("{0[lat_50]} - {0[lat_95]}".format(val)) |
| # # |
| # # tab.add_row(line) |
| # # |
| # # tab.set_cols_align(allign) |
| # # return tab.draw() |
| # |
| # |
| # # READ_IOPS_DISCSTAT_POS = 3 |
| # # WRITE_IOPS_DISCSTAT_POS = 7 |
| # # |
| # # |
| # # def load_sys_log_file(ftype: str, fname: str) -> TimeSeriesValue: |
| # # assert ftype == 'iops' |
| # # pval = None |
| # # with open(fname) as fd: |
| # # iops = [] |
| # # for ln in fd: |
| # # params = ln.split() |
| # # cval = int(params[WRITE_IOPS_DISCSTAT_POS]) + \ |
| # # int(params[READ_IOPS_DISCSTAT_POS]) |
| # # if pval is not None: |
| # # iops.append(cval - pval) |
| # # pval = cval |
| # # |
| # # vals = [(idx * 1000, val) for idx, val in enumerate(iops)] |
| # # return TimeSeriesValue(vals) |
| # # |
| # # |
| # # def load_test_results(folder: str, run_num: int) -> 'FioRunResult': |
| # # res = {} |
| # # params = None |
| # # |
| # # fn = os.path.join(folder, str(run_num) + '_params.yaml') |
| # # params = yaml.load(open(fn).read()) |
| # # |
| # # conn_ids_set = set() |
| # # rr = r"{}_(?P<conn_id>.*?)_(?P<type>[^_.]*)\.\d+\.log$".format(run_num) |
| # # for fname in os.listdir(folder): |
| # # rm = re.match(rr, fname) |
| # # if rm is None: |
| # # continue |
| # # |
| # # conn_id_s = rm.group('conn_id') |
| # # conn_id = conn_id_s.replace('_', ':') |
| # # ftype = rm.group('type') |
| # # |
| # # if ftype not in ('iops', 'bw', 'lat'): |
| # # continue |
| # # |
| # # ts = load_fio_log_file(os.path.join(folder, fname)) |
| # # res.setdefault(ftype, {}).setdefault(conn_id, []).append(ts) |
| # # |
| # # conn_ids_set.add(conn_id) |
| # # |
| # # rr = r"{}_(?P<conn_id>.*?)_(?P<type>[^_.]*)\.sys\.log$".format(run_num) |
| # # for fname in os.listdir(folder): |
| # # rm = re.match(rr, fname) |
| # # if rm is None: |
| # # continue |
| # # |
| # # conn_id_s = rm.group('conn_id') |
| # # conn_id = conn_id_s.replace('_', ':') |
| # # ftype = rm.group('type') |
| # # |
| # # if ftype not in ('iops', 'bw', 'lat'): |
| # # continue |
| # # |
| # # ts = load_sys_log_file(ftype, os.path.join(folder, fname)) |
| # # res.setdefault(ftype + ":sys", {}).setdefault(conn_id, []).append(ts) |
| # # |
| # # conn_ids_set.add(conn_id) |
| # # |
| # # mm_res = {} |
| # # |
| # # if len(res) == 0: |
| # # raise ValueError("No data was found") |
| # # |
| # # for key, data in res.items(): |
| # # conn_ids = sorted(conn_ids_set) |
| # # awail_ids = [conn_id for conn_id in conn_ids if conn_id in data] |
| # # matr = [data[conn_id] for conn_id in awail_ids] |
| # # mm_res[key] = MeasurementMatrix(matr, awail_ids) |
| # # |
| # # raw_res = {} |
| # # for conn_id in conn_ids: |
| # # fn = os.path.join(folder, "{0}_{1}_rawres.json".format(run_num, conn_id_s)) |
| # # |
| # # # remove message hack |
| # # fc = "{" + open(fn).read().split('{', 1)[1] |
| # # raw_res[conn_id] = json.loads(fc) |
| # # |
| # # fio_task = FioJobSection(params['name']) |
| # # fio_task.vals.update(params['vals']) |
| # # |
| # # config = TestConfig('io', params, None, params['nodes'], folder, None) |
| # # return FioRunResult(config, fio_task, mm_res, raw_res, params['intervals'], run_num) |
| # # |
| # |
| # # class DiskPerfInfo: |
| # # def __init__(self, name: str, summary: str, params: Dict[str, Any], testnodes_count: int) -> None: |
| # # self.name = name |
| # # self.bw = None |
| # # self.iops = None |
| # # self.lat = None |
| # # self.lat_50 = None |
| # # self.lat_95 = None |
| # # self.lat_avg = None |
| # # |
| # # self.raw_bw = [] |
| # # self.raw_iops = [] |
| # # self.raw_lat = [] |
| # # |
| # # self.params = params |
| # # self.testnodes_count = testnodes_count |
| # # self.summary = summary |
| # # |
| # # self.sync_mode = get_test_sync_mode(self.params['vals']) |
| # # self.concurence = self.params['vals'].get('numjobs', 1) |
| # # |
| # # |
| # # class IOTestResults: |
| # # def __init__(self, suite_name: str, fio_results: 'FioRunResult', log_directory: str): |
| # # self.suite_name = suite_name |
| # # self.fio_results = fio_results |
| # # self.log_directory = log_directory |
| # # |
| # # def __iter__(self): |
| # # return iter(self.fio_results) |
| # # |
| # # def __len__(self): |
| # # return len(self.fio_results) |
| # # |
| # # def get_yamable(self) -> Dict[str, List[str]]: |
| # # items = [(fio_res.summary(), fio_res.idx) for fio_res in self] |
| # # return {self.suite_name: [self.log_directory] + items} |
| # |
| # |
| # # class FioRunResult(TestResults): |
| # # """ |
| # # Fio run results |
| # # config: TestConfig |
| # # fio_task: FioJobSection |
| # # ts_results: {str: MeasurementMatrix[TimeSeriesValue]} |
| # # raw_result: ???? |
| # # run_interval:(float, float) - test tun time, used for sensors |
| # # """ |
| # # def __init__(self, config, fio_task, ts_results, raw_result, run_interval, idx): |
| # # |
| # # self.name = fio_task.name.rsplit("_", 1)[0] |
| # # self.fio_task = fio_task |
| # # self.idx = idx |
| # # |
| # # self.bw = ts_results['bw'] |
| # # self.lat = ts_results['lat'] |
| # # self.iops = ts_results['iops'] |
| # # |
| # # if 'iops:sys' in ts_results: |
| # # self.iops_sys = ts_results['iops:sys'] |
| # # else: |
| # # self.iops_sys = None |
| # # |
| # # res = {"bw": self.bw, |
| # # "lat": self.lat, |
| # # "iops": self.iops, |
| # # "iops:sys": self.iops_sys} |
| # # |
| # # self.sensors_data = None |
| # # self._pinfo = None |
| # # TestResults.__init__(self, config, res, raw_result, run_interval) |
| # # |
| # # def get_params_from_fio_report(self): |
| # # nodes = self.bw.connections_ids |
| # # |
| # # iops = [self.raw_result[node]['jobs'][0]['mixed']['iops'] for node in nodes] |
| # # total_ios = [self.raw_result[node]['jobs'][0]['mixed']['total_ios'] for node in nodes] |
| # # runtime = [self.raw_result[node]['jobs'][0]['mixed']['runtime'] / 1000 for node in nodes] |
| # # flt_iops = [float(ios) / rtime for ios, rtime in zip(total_ios, runtime)] |
| # # |
| # # bw = [self.raw_result[node]['jobs'][0]['mixed']['bw'] for node in nodes] |
| # # total_bytes = [self.raw_result[node]['jobs'][0]['mixed']['io_bytes'] for node in nodes] |
| # # flt_bw = [float(tbytes) / rtime for tbytes, rtime in zip(total_bytes, runtime)] |
| # # |
| # # return {'iops': iops, |
| # # 'flt_iops': flt_iops, |
| # # 'bw': bw, |
| # # 'flt_bw': flt_bw} |
| # # |
| # # def summary(self): |
| # # return get_test_summary(self.fio_task, len(self.config.nodes)) |
| # # |
| # # def summary_tpl(self): |
| # # return get_test_summary_tuple(self.fio_task, len(self.config.nodes)) |
| # # |
| # # def get_lat_perc_50_95_multy(self): |
| # # lat_mks = collections.defaultdict(lambda: 0) |
| # # num_res = 0 |
| # # |
| # # for result in self.raw_result.values(): |
| # # num_res += len(result['jobs']) |
| # # for job_info in result['jobs']: |
| # # for k, v in job_info['latency_ms'].items(): |
| # # if isinstance(k, basestring) and k.startswith('>='): |
| # # lat_mks[int(k[2:]) * 1000] += v |
| # # else: |
| # # lat_mks[int(k) * 1000] += v |
| # # |
| # # for k, v in job_info['latency_us'].items(): |
| # # lat_mks[int(k)] += v |
| # # |
| # # for k, v in lat_mks.items(): |
| # # lat_mks[k] = float(v) / num_res |
| # # return get_lat_perc_50_95(lat_mks) |
| # # |
| # # def disk_perf_info(self, avg_interval=2.0): |
| # # |
| # # if self._pinfo is not None: |
| # # return self._pinfo |
| # # |
| # # testnodes_count = len(self.config.nodes) |
| # # |
| # # pinfo = DiskPerfInfo(self.name, |
| # # self.summary(), |
| # # self.params, |
| # # testnodes_count) |
| # # |
| # # def prepare(data, drop=1): |
| # # if data is None: |
| # # return data |
| # # |
| # # res = [] |
| # # for ts_data in data: |
| # # if ts_data.average_interval() < avg_interval: |
| # # ts_data = ts_data.derived(avg_interval) |
| # # |
| # # # drop last value on bounds |
| # # # as they may contains ranges without activities |
| # # assert len(ts_data.values) >= drop + 1, str(drop) + " " + str(ts_data.values) |
| # # |
| # # if drop > 0: |
| # # res.append(ts_data.values[:-drop]) |
| # # else: |
| # # res.append(ts_data.values) |
| # # |
| # # return res |
| # # |
| # # def agg_data(matr): |
| # # arr = sum(matr, []) |
| # # min_len = min(map(len, arr)) |
| # # res = [] |
| # # for idx in range(min_len): |
| # # res.append(sum(dt[idx] for dt in arr)) |
| # # return res |
| # # |
| # # pinfo.raw_lat = map(prepare, self.lat.per_vm()) |
| # # num_th = sum(map(len, pinfo.raw_lat)) |
| # # lat_avg = [val / num_th for val in agg_data(pinfo.raw_lat)] |
| # # pinfo.lat_avg = data_property(lat_avg).average / 1000 # us to ms |
| # # |
| # # pinfo.lat_50, pinfo.lat_95 = self.get_lat_perc_50_95_multy() |
| # # pinfo.lat = pinfo.lat_50 |
| # # |
| # # pinfo.raw_bw = map(prepare, self.bw.per_vm()) |
| # # pinfo.raw_iops = map(prepare, self.iops.per_vm()) |
| # # |
| # # if self.iops_sys is not None: |
| # # pinfo.raw_iops_sys = map(prepare, self.iops_sys.per_vm()) |
| # # pinfo.iops_sys = data_property(agg_data(pinfo.raw_iops_sys)) |
| # # else: |
| # # pinfo.raw_iops_sys = None |
| # # pinfo.iops_sys = None |
| # # |
| # # fparams = self.get_params_from_fio_report() |
| # # fio_report_bw = sum(fparams['flt_bw']) |
| # # fio_report_iops = sum(fparams['flt_iops']) |
| # # |
| # # agg_bw = agg_data(pinfo.raw_bw) |
| # # agg_iops = agg_data(pinfo.raw_iops) |
| # # |
| # # log_bw_avg = average(agg_bw) |
| # # log_iops_avg = average(agg_iops) |
| # # |
| # # # update values to match average from fio report |
| # # coef_iops = fio_report_iops / float(log_iops_avg) |
| # # coef_bw = fio_report_bw / float(log_bw_avg) |
| # # |
| # # bw_log = data_property([val * coef_bw for val in agg_bw]) |
| # # iops_log = data_property([val * coef_iops for val in agg_iops]) |
| # # |
| # # bw_report = data_property([fio_report_bw]) |
| # # iops_report = data_property([fio_report_iops]) |
| # # |
| # # # When IOPS/BW per thread is too low |
| # # # data from logs is rounded to match |
| # # iops_per_th = sum(sum(pinfo.raw_iops, []), []) |
| # # if average(iops_per_th) > 10: |
| # # pinfo.iops = iops_log |
| # # pinfo.iops2 = iops_report |
| # # else: |
| # # pinfo.iops = iops_report |
| # # pinfo.iops2 = iops_log |
| # # |
| # # bw_per_th = sum(sum(pinfo.raw_bw, []), []) |
| # # if average(bw_per_th) > 10: |
| # # pinfo.bw = bw_log |
| # # pinfo.bw2 = bw_report |
| # # else: |
| # # pinfo.bw = bw_report |
| # # pinfo.bw2 = bw_log |
| # # |
| # # self._pinfo = pinfo |
| # # |
| # # return pinfo |
| # |
| # # class TestResult: |
| # # """Hold all information for a given test - test info, |
| # # sensors data and performance results for test period from all nodes""" |
| # # run_id = None # type: int |
| # # test_info = None # type: Any |
| # # begin_time = None # type: int |
| # # end_time = None # type: int |
| # # sensors = None # Dict[Tuple[str, str, str], TimeSeries] |
| # # performance = None # Dict[Tuple[str, str], TimeSeries] |
| # # |
| # # class TestResults: |
| # # """ |
| # # this class describe test results |
| # # |
| # # config:TestConfig - test config object |
| # # params:dict - parameters from yaml file for this test |
| # # results:{str:MeasurementMesh} - test results object |
| # # raw_result:Any - opaque object to store raw results |
| # # run_interval:(float, float) - test tun time, used for sensors |
| # # """ |
| # # |
| # # def __init__(self, |
| # # config: TestConfig, |
| # # results: Dict[str, Any], |
| # # raw_result: Any, |
| # # run_interval: Tuple[float, float]) -> None: |
| # # self.config = config |
| # # self.params = config.params |
| # # self.results = results |
| # # self.raw_result = raw_result |
| # # self.run_interval = run_interval |
| # # |
| # # def __str__(self) -> str: |
| # # res = "{0}({1}):\n results:\n".format( |
| # # self.__class__.__name__, |
| # # self.summary()) |
| # # |
| # # for name, val in self.results.items(): |
| # # res += " {0}={1}\n".format(name, val) |
| # # |
| # # res += " params:\n" |
| # # |
| # # for name, val in self.params.items(): |
| # # res += " {0}={1}\n".format(name, val) |
| # # |
| # # return res |
| # # |
| # # def summary(self) -> str: |
| # # raise NotImplementedError() |
| # # return "" |
| # # |
| # # def get_yamable(self) -> Any: |
| # # raise NotImplementedError() |
| # # return None |
| # |
| # |
| # |
| # # class MeasurementMatrix: |
| # # """ |
| # # data:[[MeasurementResult]] - VM_COUNT x TH_COUNT matrix of MeasurementResult |
| # # """ |
| # # def __init__(self, data, connections_ids): |
| # # self.data = data |
| # # self.connections_ids = connections_ids |
| # # |
| # # def per_vm(self): |
| # # return self.data |
| # # |
| # # def per_th(self): |
| # # return sum(self.data, []) |
| # |
| # |
| # # class MeasurementResults: |
| # # data = None # type: List[Any] |
| # # |
| # # def stat(self) -> StatProps: |
| # # return data_property(self.data) |
| # # |
| # # def __str__(self) -> str: |
| # # return 'TS([' + ", ".join(map(str, self.data)) + '])' |
| # # |
| # # |
| # # class SimpleVals(MeasurementResults): |
| # # """ |
| # # data:[float] - list of values |
| # # """ |
| # # def __init__(self, data: List[float]) -> None: |
| # # self.data = data |
| # # |
| # # |
| # # class TimeSeriesValue(MeasurementResults): |
| # # """ |
| # # data:[(float, float, float)] - list of (start_time, lenght, average_value_for_interval) |
| # # odata: original values |
| # # """ |
| # # def __init__(self, data: List[Tuple[float, float]]) -> None: |
| # # assert len(data) > 0 |
| # # self.odata = data[:] |
| # # self.data = [] # type: List[Tuple[float, float, float]] |
| # # |
| # # cstart = 0.0 |
| # # for nstart, nval in data: |
| # # self.data.append((cstart, nstart - cstart, nval)) |
| # # cstart = nstart |
| # # |
| # # @property |
| # # def values(self) -> List[float]: |
| # # return [val[2] for val in self.data] |
| # # |
| # # def average_interval(self) -> float: |
| # # return float(sum([val[1] for val in self.data])) / len(self.data) |
| # # |
| # # def skip(self, seconds) -> 'TimeSeriesValue': |
| # # nres = [] |
| # # for start, ln, val in self.data: |
| # # nstart = start + ln - seconds |
| # # if nstart > 0: |
| # # nres.append([nstart, val]) |
| # # return self.__class__(nres) |
| # # |
| # # def derived(self, tdelta) -> 'TimeSeriesValue': |
| # # end = self.data[-1][0] + self.data[-1][1] |
| # # tdelta = float(tdelta) |
| # # |
| # # ln = end / tdelta |
| # # |
| # # if ln - int(ln) > 0: |
| # # ln += 1 |
| # # |
| # # res = [[tdelta * i, 0.0] for i in range(int(ln))] |
| # # |
| # # for start, lenght, val in self.data: |
| # # start_idx = int(start / tdelta) |
| # # end_idx = int((start + lenght) / tdelta) |
| # # |
| # # for idx in range(start_idx, end_idx + 1): |
| # # rstart = tdelta * idx |
| # # rend = tdelta * (idx + 1) |
| # # |
| # # intersection_ln = min(rend, start + lenght) - max(start, rstart) |
| # # if intersection_ln > 0: |
| # # try: |
| # # res[idx][1] += val * intersection_ln / tdelta |
| # # except IndexError: |
| # # raise |
| # # |
| # # return self.__class__(res) |
| # |
| # |
| # def console_report_stage(ctx: TestRun) -> None: |
| # # TODO(koder): load data from storage |
| # raise NotImplementedError("...") |
| # # first_report = True |
| # # text_rep_fname = ctx.config.text_report_file |
| # # |
| # # with open(text_rep_fname, "w") as fd: |
| # # for tp, data in ctx.results.items(): |
| # # if 'io' == tp and data is not None: |
| # # rep_lst = [] |
| # # for result in data: |
| # # rep_lst.append( |
| # # IOPerfTest.format_for_console(list(result))) |
| # # rep = "\n\n".join(rep_lst) |
| # # elif tp in ['mysql', 'pgbench'] and data is not None: |
| # # rep = MysqlTest.format_for_console(data) |
| # # elif tp == 'omg': |
| # # rep = OmgTest.format_for_console(data) |
| # # else: |
| # # logger.warning("Can't generate text report for " + tp) |
| # # continue |
| # # |
| # # fd.write(rep) |
| # # fd.write("\n") |
| # # |
| # # if first_report: |
| # # logger.info("Text report were stored in " + text_rep_fname) |
| # # first_report = False |
| # # |
| # # print("\n" + rep + "\n") |
| # |
| # |
| # # def test_load_report_stage(cfg: Config, ctx: TestRun) -> None: |
| # # load_rep_fname = cfg.load_report_file |
| # # found = False |
| # # for idx, (tp, data) in enumerate(ctx.results.items()): |
| # # if 'io' == tp and data is not None: |
| # # if found: |
| # # logger.error("Making reports for more than one " + |
| # # "io block isn't supported! All " + |
| # # "report, except first are skipped") |
| # # continue |
| # # found = True |
| # # report.make_load_report(idx, cfg['results'], load_rep_fname) |
| # # |
| # # |
| # |
| # # def html_report_stage(ctx: TestRun) -> None: |
| # # TODO(koder): load data from storage |
| # # raise NotImplementedError("...") |
| # # html_rep_fname = cfg.html_report_file |
| # # found = False |
| # # for tp, data in ctx.results.items(): |
| # # if 'io' == tp and data is not None: |
| # # if found or len(data) > 1: |
| # # logger.error("Making reports for more than one " + |
| # # "io block isn't supported! All " + |
| # # "report, except first are skipped") |
| # # continue |
| # # found = True |
| # # report.make_io_report(list(data[0]), |
| # # cfg.get('comment', ''), |
| # # html_rep_fname, |
| # # lab_info=ctx.nodes) |
| # |
| # # |
| # # def load_data_from_path(test_res_dir: str) -> Mapping[str, List[Any]]: |
| # # files = get_test_files(test_res_dir) |
| # # raw_res = yaml_load(open(files['raw_results']).read()) |
| # # res = collections.defaultdict(list) |
| # # |
| # # for tp, test_lists in raw_res: |
| # # for tests in test_lists: |
| # # for suite_name, suite_data in tests.items(): |
| # # result_folder = suite_data[0] |
| # # res[tp].append(TOOL_TYPE_MAPPER[tp].load(suite_name, result_folder)) |
| # # |
| # # return res |
| # # |
| # # |
| # # def load_data_from_path_stage(var_dir: str, _, ctx: TestRun) -> None: |
| # # for tp, vals in load_data_from_path(var_dir).items(): |
| # # ctx.results.setdefault(tp, []).extend(vals) |
| # # |
| # # |
| # # def load_data_from(var_dir: str) -> Callable[[TestRun], None]: |
| # # return functools.partial(load_data_from_path_stage, var_dir) |