| koder aka kdanilov | a732a60 | 2017-02-01 20:29:56 +0200 | [diff] [blame] | 1 | # --------------------------- LEGACY -------------------------------------------------------------------------------- |
| 2 | |
| 3 | |
| 4 | # # disk_info = None |
| 5 | # # base = None |
| 6 | # # linearity = None |
| 7 | # |
| 8 | # |
| 9 | # def group_by_name(test_data): |
| 10 | # name_map = collections.defaultdict(lambda: []) |
| 11 | # |
| 12 | # for data in test_data: |
| 13 | # name_map[(data.name, data.summary())].append(data) |
| 14 | # |
| 15 | # return name_map |
| 16 | # |
| 17 | # |
| 18 | # def report(name, required_fields): |
| 19 | # def closure(func): |
| 20 | # report_funcs.append((required_fields.split(","), name, func)) |
| 21 | # return func |
| 22 | # return closure |
| 23 | # |
| 24 | # |
| 25 | # def get_test_lcheck_params(pinfo): |
| 26 | # res = [{ |
| 27 | # 's': 'sync', |
| 28 | # 'd': 'direct', |
| 29 | # 'a': 'async', |
| 30 | # 'x': 'sync direct' |
| 31 | # }[pinfo.sync_mode]] |
| 32 | # |
| 33 | # res.append(pinfo.p.rw) |
| 34 | # |
| 35 | # return " ".join(res) |
| 36 | # |
| 37 | # |
| 38 | # def get_emb_data_svg(plt): |
| 39 | # sio = StringIO() |
| 40 | # plt.savefig(sio, format='svg') |
| 41 | # img_start = "<!-- Created with matplotlib (http://matplotlib.org/) -->" |
| 42 | # return sio.getvalue().split(img_start, 1)[1] |
| 43 | # |
| 44 | # |
| 45 | # def get_template(templ_name): |
| 46 | # very_root_dir = os.path.dirname(os.path.dirname(wally.__file__)) |
| 47 | # templ_dir = os.path.join(very_root_dir, 'report_templates') |
| 48 | # templ_file = os.path.join(templ_dir, templ_name) |
| 49 | # return open(templ_file, 'r').read() |
| 50 | # |
| 51 | # |
| 52 | # def group_by(data, func): |
| 53 | # if len(data) < 2: |
| 54 | # yield data |
| 55 | # return |
| 56 | # |
| 57 | # ndata = [(func(dt), dt) for dt in data] |
| 58 | # ndata.sort(key=func) |
| 59 | # pkey, dt = ndata[0] |
| 60 | # curr_list = [dt] |
| 61 | # |
| 62 | # for key, val in ndata[1:]: |
| 63 | # if pkey != key: |
| 64 | # yield curr_list |
| 65 | # curr_list = [val] |
| 66 | # else: |
| 67 | # curr_list.append(val) |
| 68 | # pkey = key |
| 69 | # |
| 70 | # yield curr_list |
| 71 | # |
| 72 | # |
| 73 | # @report('linearity', 'linearity_test') |
| 74 | # def linearity_report(processed_results, lab_info, comment): |
| 75 | # labels_and_data_mp = collections.defaultdict(lambda: []) |
| 76 | # vls = {} |
| 77 | # |
| 78 | # # plot io_time = func(bsize) |
| 79 | # for res in processed_results.values(): |
| 80 | # if res.name.startswith('linearity_test'): |
| 81 | # iotimes = [1000. / val for val in res.iops.raw] |
| 82 | # |
| 83 | # op_summ = get_test_summary(res.params)[:3] |
| 84 | # |
| 85 | # labels_and_data_mp[op_summ].append( |
| 86 | # [res.p.blocksize, res.iops.raw, iotimes]) |
| 87 | # |
| 88 | # cvls = res.params.vals.copy() |
| 89 | # del cvls['blocksize'] |
| 90 | # del cvls['rw'] |
| 91 | # |
| 92 | # cvls.pop('sync', None) |
| 93 | # cvls.pop('direct', None) |
| 94 | # cvls.pop('buffered', None) |
| 95 | # |
| 96 | # if op_summ not in vls: |
| 97 | # vls[op_summ] = cvls |
| 98 | # else: |
| 99 | # assert cvls == vls[op_summ] |
| 100 | # |
| 101 | # all_labels = None |
| 102 | # _, ax1 = plt.subplots() |
| 103 | # for name, labels_and_data in labels_and_data_mp.items(): |
| 104 | # labels_and_data.sort(key=lambda x: ssize2b(x[0])) |
| 105 | # |
| 106 | # labels, _, iotimes = zip(*labels_and_data) |
| 107 | # |
| 108 | # if all_labels is None: |
| 109 | # all_labels = labels |
| 110 | # else: |
| 111 | # assert all_labels == labels |
| 112 | # |
| 113 | # plt.boxplot(iotimes) |
| 114 | # if len(labels_and_data) > 2 and \ |
| 115 | # ssize2b(labels_and_data[-2][0]) >= 4096: |
| 116 | # |
| 117 | # xt = range(1, len(labels) + 1) |
| 118 | # |
| 119 | # def io_time(sz, bw, initial_lat): |
| 120 | # return sz / bw + initial_lat |
| 121 | # |
| 122 | # x = numpy.array(map(ssize2b, labels)) |
| 123 | # y = numpy.array([sum(dt) / len(dt) for dt in iotimes]) |
| 124 | # popt, _ = scipy.optimize.curve_fit(io_time, x, y, p0=(100., 1.)) |
| 125 | # |
| 126 | # y1 = io_time(x, *popt) |
| 127 | # plt.plot(xt, y1, linestyle='--', |
| 128 | # label=name + ' LS linear approx') |
| 129 | # |
| 130 | # for idx, (sz, _, _) in enumerate(labels_and_data): |
| 131 | # if ssize2b(sz) >= 4096: |
| 132 | # break |
| 133 | # |
| 134 | # bw = (x[-1] - x[idx]) / (y[-1] - y[idx]) |
| 135 | # lat = y[-1] - x[-1] / bw |
| 136 | # y2 = io_time(x, bw, lat) |
| 137 | # plt.plot(xt, y2, linestyle='--', |
| 138 | # label=abbv_name_to_full(name) + |
| 139 | # ' (4k & max) linear approx') |
| 140 | # |
| 141 | # plt.setp(ax1, xticklabels=labels) |
| 142 | # |
| 143 | # plt.xlabel("Block size") |
| 144 | # plt.ylabel("IO time, ms") |
| 145 | # |
| 146 | # plt.subplots_adjust(top=0.85) |
| 147 | # plt.legend(bbox_to_anchor=(0.5, 1.15), |
| 148 | # loc='upper center', |
| 149 | # prop={'size': 10}, ncol=2) |
| 150 | # plt.grid() |
| 151 | # iotime_plot = get_emb_data_svg(plt) |
| 152 | # plt.clf() |
| 153 | # |
| 154 | # # plot IOPS = func(bsize) |
| 155 | # _, ax1 = plt.subplots() |
| 156 | # |
| 157 | # for name, labels_and_data in labels_and_data_mp.items(): |
| 158 | # labels_and_data.sort(key=lambda x: ssize2b(x[0])) |
| 159 | # _, data, _ = zip(*labels_and_data) |
| 160 | # plt.boxplot(data) |
| 161 | # avg = [float(sum(arr)) / len(arr) for arr in data] |
| 162 | # xt = range(1, len(data) + 1) |
| 163 | # plt.plot(xt, avg, linestyle='--', |
| 164 | # label=abbv_name_to_full(name) + " avg") |
| 165 | # |
| 166 | # plt.setp(ax1, xticklabels=labels) |
| 167 | # plt.xlabel("Block size") |
| 168 | # plt.ylabel("IOPS") |
| 169 | # plt.legend(bbox_to_anchor=(0.5, 1.15), |
| 170 | # loc='upper center', |
| 171 | # prop={'size': 10}, ncol=2) |
| 172 | # plt.grid() |
| 173 | # plt.subplots_adjust(top=0.85) |
| 174 | # |
| 175 | # iops_plot = get_emb_data_svg(plt) |
| 176 | # |
| 177 | # res = set(get_test_lcheck_params(res) for res in processed_results.values()) |
| 178 | # ncount = list(set(res.testnodes_count for res in processed_results.values())) |
| 179 | # conc = list(set(res.concurence for res in processed_results.values())) |
| 180 | # |
| 181 | # assert len(conc) == 1 |
| 182 | # assert len(ncount) == 1 |
| 183 | # |
| 184 | # descr = { |
| 185 | # 'vm_count': ncount[0], |
| 186 | # 'concurence': conc[0], |
| 187 | # 'oper_descr': ", ".join(res).capitalize() |
| 188 | # } |
| 189 | # |
| 190 | # params_map = {'iotime_vs_size': iotime_plot, |
| 191 | # 'iops_vs_size': iops_plot, |
| 192 | # 'descr': descr} |
| 193 | # |
| 194 | # return get_template('report_linearity.html').format(**params_map) |
| 195 | # |
| 196 | # |
| 197 | # @report('lat_vs_iops', 'lat_vs_iops') |
| 198 | # def lat_vs_iops(processed_results, lab_info, comment): |
| 199 | # lat_iops = collections.defaultdict(lambda: []) |
| 200 | # requsted_vs_real = collections.defaultdict(lambda: {}) |
| 201 | # |
| 202 | # for res in processed_results.values(): |
| 203 | # if res.name.startswith('lat_vs_iops'): |
| 204 | # lat_iops[res.concurence].append((res.lat, |
| 205 | # 0, |
| 206 | # res.iops.average, |
| 207 | # res.iops.deviation)) |
| 208 | # # lat_iops[res.concurence].append((res.lat.average / 1000.0, |
| 209 | # # res.lat.deviation / 1000.0, |
| 210 | # # res.iops.average, |
| 211 | # # res.iops.deviation)) |
| 212 | # requested_iops = res.p.rate_iops * res.concurence |
| 213 | # requsted_vs_real[res.concurence][requested_iops] = \ |
| 214 | # (res.iops.average, res.iops.deviation) |
| 215 | # |
| 216 | # colors = ['red', 'green', 'blue', 'orange', 'magenta', "teal"] |
| 217 | # colors_it = iter(colors) |
| 218 | # for conc, lat_iops in sorted(lat_iops.items()): |
| 219 | # lat, dev, iops, iops_dev = zip(*lat_iops) |
| 220 | # plt.errorbar(iops, lat, xerr=iops_dev, yerr=dev, fmt='ro', |
| 221 | # label=str(conc) + " threads", |
| 222 | # color=next(colors_it)) |
| 223 | # |
| 224 | # plt.xlabel("IOPS") |
| 225 | # plt.ylabel("Latency, ms") |
| 226 | # plt.grid() |
| 227 | # plt.legend(loc=0) |
| 228 | # plt_iops_vs_lat = get_emb_data_svg(plt) |
| 229 | # plt.clf() |
| 230 | # |
| 231 | # colors_it = iter(colors) |
| 232 | # for conc, req_vs_real in sorted(requsted_vs_real.items()): |
| 233 | # req, real = zip(*sorted(req_vs_real.items())) |
| 234 | # iops, dev = zip(*real) |
| 235 | # plt.errorbar(req, iops, yerr=dev, fmt='ro', |
| 236 | # label=str(conc) + " threads", |
| 237 | # color=next(colors_it)) |
| 238 | # plt.xlabel("Requested IOPS") |
| 239 | # plt.ylabel("Get IOPS") |
| 240 | # plt.grid() |
| 241 | # plt.legend(loc=0) |
| 242 | # plt_iops_vs_requested = get_emb_data_svg(plt) |
| 243 | # |
| 244 | # res1 = processed_results.values()[0] |
| 245 | # params_map = {'iops_vs_lat': plt_iops_vs_lat, |
| 246 | # 'iops_vs_requested': plt_iops_vs_requested, |
| 247 | # 'oper_descr': get_test_lcheck_params(res1).capitalize()} |
| 248 | # |
| 249 | # return get_template('report_iops_vs_lat.html').format(**params_map) |
| 250 | # |
| 251 | # |
| 252 | # def render_all_html(comment, info, lab_description, images, templ_name): |
| 253 | # data = info.__dict__.copy() |
| 254 | # for name, val in data.items(): |
| 255 | # if not name.startswith('__'): |
| 256 | # if val is None: |
| 257 | # if name in ('direct_iops_w64_max', 'direct_iops_w_max'): |
| 258 | # data[name] = ('-', '-', '-') |
| 259 | # else: |
| 260 | # data[name] = '-' |
| 261 | # elif isinstance(val, (int, float, long)): |
| 262 | # data[name] = round_3_digit(val) |
| 263 | # |
| 264 | # data['bw_read_max'] = (data['bw_read_max'][0] // 1024, |
| 265 | # data['bw_read_max'][1], |
| 266 | # data['bw_read_max'][2]) |
| 267 | # |
| 268 | # data['bw_write_max'] = (data['bw_write_max'][0] // 1024, |
| 269 | # data['bw_write_max'][1], |
| 270 | # data['bw_write_max'][2]) |
| 271 | # |
| 272 | # images.update(data) |
| 273 | # templ = get_template(templ_name) |
| 274 | # return templ.format(lab_info=lab_description, |
| 275 | # comment=comment, |
| 276 | # **images) |
| 277 | # |
| 278 | # |
| 279 | # def io_chart(title, concurence, |
| 280 | # latv, latv_min, latv_max, |
| 281 | # iops_or_bw, iops_or_bw_err, |
| 282 | # legend, |
| 283 | # log_iops=False, |
| 284 | # log_lat=False, |
| 285 | # boxplots=False, |
| 286 | # latv_50=None, |
| 287 | # latv_95=None, |
| 288 | # error2=None): |
| 289 | # |
| 290 | # matplotlib.rcParams.update({'font.size': 10}) |
| 291 | # points = " MiBps" if legend == 'BW' else "" |
| 292 | # lc = len(concurence) |
| 293 | # width = 0.35 |
| 294 | # xt = range(1, lc + 1) |
| 295 | # |
| 296 | # op_per_vm = [v / (vm * th) for v, (vm, th) in zip(iops_or_bw, concurence)] |
| 297 | # fig, p1 = plt.subplots() |
| 298 | # xpos = [i - width / 2 for i in xt] |
| 299 | # |
| 300 | # p1.bar(xpos, iops_or_bw, |
| 301 | # width=width, |
| 302 | # color='y', |
| 303 | # label=legend) |
| 304 | # |
| 305 | # err1_leg = None |
| 306 | # for pos, y, err in zip(xpos, iops_or_bw, iops_or_bw_err): |
| 307 | # err1_leg = p1.errorbar(pos + width / 2, |
| 308 | # y, |
| 309 | # err, |
| 310 | # color='magenta') |
| 311 | # |
| 312 | # err2_leg = None |
| 313 | # if error2 is not None: |
| 314 | # for pos, y, err in zip(xpos, iops_or_bw, error2): |
| 315 | # err2_leg = p1.errorbar(pos + width / 2 + 0.08, |
| 316 | # y, |
| 317 | # err, |
| 318 | # lw=2, |
| 319 | # alpha=0.5, |
| 320 | # color='teal') |
| 321 | # |
| 322 | # p1.grid(True) |
| 323 | # p1.plot(xt, op_per_vm, '--', label=legend + "/thread", color='black') |
| 324 | # handles1, labels1 = p1.get_legend_handles_labels() |
| 325 | # |
| 326 | # handles1 += [err1_leg] |
| 327 | # labels1 += ["95% conf"] |
| 328 | # |
| 329 | # if err2_leg is not None: |
| 330 | # handles1 += [err2_leg] |
| 331 | # labels1 += ["95% dev"] |
| 332 | # |
| 333 | # p2 = p1.twinx() |
| 334 | # |
| 335 | # if latv_50 is None: |
| 336 | # p2.plot(xt, latv_max, label="lat max") |
| 337 | # p2.plot(xt, latv, label="lat avg") |
| 338 | # p2.plot(xt, latv_min, label="lat min") |
| 339 | # else: |
| 340 | # p2.plot(xt, latv_50, label="lat med") |
| 341 | # p2.plot(xt, latv_95, label="lat 95%") |
| 342 | # |
| 343 | # plt.xlim(0.5, lc + 0.5) |
| 344 | # plt.xticks(xt, ["{0} * {1}".format(vm, th) for (vm, th) in concurence]) |
| 345 | # p1.set_xlabel("VM Count * Thread per VM") |
| 346 | # p1.set_ylabel(legend + points) |
| 347 | # p2.set_ylabel("Latency ms") |
| 348 | # plt.title(title) |
| 349 | # handles2, labels2 = p2.get_legend_handles_labels() |
| 350 | # |
| 351 | # plt.legend(handles1 + handles2, labels1 + labels2, |
| 352 | # loc='center left', bbox_to_anchor=(1.1, 0.81)) |
| 353 | # |
| 354 | # if log_iops: |
| 355 | # p1.set_yscale('log') |
| 356 | # |
| 357 | # if log_lat: |
| 358 | # p2.set_yscale('log') |
| 359 | # |
| 360 | # plt.subplots_adjust(right=0.68) |
| 361 | # |
| 362 | # return get_emb_data_svg(plt) |
| 363 | # |
| 364 | # |
| 365 | # def make_plots(processed_results, plots): |
| 366 | # """ |
| 367 | # processed_results: [PerfInfo] |
| 368 | # plots = [(test_name_prefix:str, fname:str, description:str)] |
| 369 | # """ |
| 370 | # files = {} |
| 371 | # for name_pref, fname, desc in plots: |
| 372 | # chart_data = [] |
| 373 | # |
| 374 | # for res in processed_results: |
| 375 | # summ = res.name + "_" + res.summary |
| 376 | # if summ.startswith(name_pref): |
| 377 | # chart_data.append(res) |
| 378 | # |
| 379 | # if len(chart_data) == 0: |
| 380 | # raise ValueError("Can't found any date for " + name_pref) |
| 381 | # |
| 382 | # use_bw = ssize2b(chart_data[0].p.blocksize) > 16 * 1024 |
| 383 | # |
| 384 | # chart_data.sort(key=lambda x: x.params['vals']['numjobs']) |
| 385 | # |
| 386 | # lat = None |
| 387 | # lat_min = None |
| 388 | # lat_max = None |
| 389 | # |
| 390 | # lat_50 = [x.lat_50 for x in chart_data] |
| 391 | # lat_95 = [x.lat_95 for x in chart_data] |
| 392 | # |
| 393 | # lat_diff_max = max(x.lat_95 / x.lat_50 for x in chart_data) |
| 394 | # lat_log_scale = (lat_diff_max > 10) |
| 395 | # |
| 396 | # testnodes_count = x.testnodes_count |
| 397 | # concurence = [(testnodes_count, x.concurence) |
| 398 | # for x in chart_data] |
| 399 | # |
| 400 | # if use_bw: |
| 401 | # data = [x.bw.average / 1000 for x in chart_data] |
| 402 | # data_conf = [x.bw.confidence / 1000 for x in chart_data] |
| 403 | # data_dev = [x.bw.deviation * 2.5 / 1000 for x in chart_data] |
| 404 | # name = "BW" |
| 405 | # else: |
| 406 | # data = [x.iops.average for x in chart_data] |
| 407 | # data_conf = [x.iops.confidence for x in chart_data] |
| 408 | # data_dev = [x.iops.deviation * 2 for x in chart_data] |
| 409 | # name = "IOPS" |
| 410 | # |
| 411 | # fc = io_chart(title=desc, |
| 412 | # concurence=concurence, |
| 413 | # |
| 414 | # latv=lat, |
| 415 | # latv_min=lat_min, |
| 416 | # latv_max=lat_max, |
| 417 | # |
| 418 | # iops_or_bw=data, |
| 419 | # iops_or_bw_err=data_conf, |
| 420 | # |
| 421 | # legend=name, |
| 422 | # log_lat=lat_log_scale, |
| 423 | # |
| 424 | # latv_50=lat_50, |
| 425 | # latv_95=lat_95, |
| 426 | # |
| 427 | # error2=data_dev) |
| 428 | # files[fname] = fc |
| 429 | # |
| 430 | # return files |
| 431 | # |
| 432 | # |
| 433 | # def find_max_where(processed_results, sync_mode, blocksize, rw, iops=True): |
| 434 | # result = None |
| 435 | # attr = 'iops' if iops else 'bw' |
| 436 | # for measurement in processed_results: |
| 437 | # ok = measurement.sync_mode == sync_mode |
| 438 | # ok = ok and (measurement.p.blocksize == blocksize) |
| 439 | # ok = ok and (measurement.p.rw == rw) |
| 440 | # |
| 441 | # if ok: |
| 442 | # field = getattr(measurement, attr) |
| 443 | # |
| 444 | # if result is None: |
| 445 | # result = field |
| 446 | # elif field.average > result.average: |
| 447 | # result = field |
| 448 | # |
| 449 | # return result |
| 450 | # |
| 451 | # |
| 452 | # def get_disk_info(processed_results): |
| 453 | # di = DiskInfo() |
| 454 | # di.direct_iops_w_max = find_max_where(processed_results, |
| 455 | # 'd', '4k', 'randwrite') |
| 456 | # di.direct_iops_r_max = find_max_where(processed_results, |
| 457 | # 'd', '4k', 'randread') |
| 458 | # |
| 459 | # di.direct_iops_w64_max = find_max_where(processed_results, |
| 460 | # 'd', '64k', 'randwrite') |
| 461 | # |
| 462 | # for sz in ('16m', '64m'): |
| 463 | # di.bw_write_max = find_max_where(processed_results, |
| 464 | # 'd', sz, 'randwrite', False) |
| 465 | # if di.bw_write_max is not None: |
| 466 | # break |
| 467 | # |
| 468 | # if di.bw_write_max is None: |
| 469 | # for sz in ('1m', '2m', '4m', '8m'): |
| 470 | # di.bw_write_max = find_max_where(processed_results, |
| 471 | # 'd', sz, 'write', False) |
| 472 | # if di.bw_write_max is not None: |
| 473 | # break |
| 474 | # |
| 475 | # for sz in ('16m', '64m'): |
| 476 | # di.bw_read_max = find_max_where(processed_results, |
| 477 | # 'd', sz, 'randread', False) |
| 478 | # if di.bw_read_max is not None: |
| 479 | # break |
| 480 | # |
| 481 | # if di.bw_read_max is None: |
| 482 | # di.bw_read_max = find_max_where(processed_results, |
| 483 | # 'd', '1m', 'read', False) |
| 484 | # |
| 485 | # rws4k_iops_lat_th = [] |
| 486 | # for res in processed_results: |
| 487 | # if res.sync_mode in 'xs' and res.p.blocksize == '4k': |
| 488 | # if res.p.rw != 'randwrite': |
| 489 | # continue |
| 490 | # rws4k_iops_lat_th.append((res.iops.average, |
| 491 | # res.lat, |
| 492 | # # res.lat.average, |
| 493 | # res.concurence)) |
| 494 | # |
| 495 | # rws4k_iops_lat_th.sort(key=lambda x: x[2]) |
| 496 | # |
| 497 | # latv = [lat for _, lat, _ in rws4k_iops_lat_th] |
| 498 | # |
| 499 | # for tlat in [10, 30, 100]: |
| 500 | # pos = bisect.bisect_left(latv, tlat) |
| 501 | # if 0 == pos: |
| 502 | # setattr(di, 'rws4k_{}ms'.format(tlat), 0) |
| 503 | # elif pos == len(latv): |
| 504 | # iops3, _, _ = rws4k_iops_lat_th[-1] |
| 505 | # iops3 = int(round_3_digit(iops3)) |
| 506 | # setattr(di, 'rws4k_{}ms'.format(tlat), ">=" + str(iops3)) |
| 507 | # else: |
| 508 | # lat1 = latv[pos - 1] |
| 509 | # lat2 = latv[pos] |
| 510 | # |
| 511 | # iops1, _, th1 = rws4k_iops_lat_th[pos - 1] |
| 512 | # iops2, _, th2 = rws4k_iops_lat_th[pos] |
| 513 | # |
| 514 | # th_lat_coef = (th2 - th1) / (lat2 - lat1) |
| 515 | # th3 = th_lat_coef * (tlat - lat1) + th1 |
| 516 | # |
| 517 | # th_iops_coef = (iops2 - iops1) / (th2 - th1) |
| 518 | # iops3 = th_iops_coef * (th3 - th1) + iops1 |
| 519 | # iops3 = int(round_3_digit(iops3)) |
| 520 | # setattr(di, 'rws4k_{}ms'.format(tlat), iops3) |
| 521 | # |
| 522 | # hdi = DiskInfo() |
| 523 | # |
| 524 | # def pp(x): |
| 525 | # med, conf = x.rounded_average_conf() |
| 526 | # conf_perc = int(float(conf) / med * 100) |
| 527 | # dev_perc = int(float(x.deviation) / med * 100) |
| 528 | # return (round_3_digit(med), conf_perc, dev_perc) |
| 529 | # |
| 530 | # hdi.direct_iops_r_max = pp(di.direct_iops_r_max) |
| 531 | # |
| 532 | # if di.direct_iops_w_max is not None: |
| 533 | # hdi.direct_iops_w_max = pp(di.direct_iops_w_max) |
| 534 | # else: |
| 535 | # hdi.direct_iops_w_max = None |
| 536 | # |
| 537 | # if di.direct_iops_w64_max is not None: |
| 538 | # hdi.direct_iops_w64_max = pp(di.direct_iops_w64_max) |
| 539 | # else: |
| 540 | # hdi.direct_iops_w64_max = None |
| 541 | # |
| 542 | # hdi.bw_write_max = pp(di.bw_write_max) |
| 543 | # hdi.bw_read_max = pp(di.bw_read_max) |
| 544 | # |
| 545 | # hdi.rws4k_10ms = di.rws4k_10ms if 0 != di.rws4k_10ms else None |
| 546 | # hdi.rws4k_30ms = di.rws4k_30ms if 0 != di.rws4k_30ms else None |
| 547 | # hdi.rws4k_100ms = di.rws4k_100ms if 0 != di.rws4k_100ms else None |
| 548 | # return hdi |
| 549 | # |
| 550 | # |
| 551 | # @report('hdd', 'hdd') |
| 552 | # def make_hdd_report(processed_results, lab_info, comment): |
| 553 | # plots = [ |
| 554 | # ('hdd_rrd4k', 'rand_read_4k', 'Random read 4k direct IOPS'), |
| 555 | # ('hdd_rwx4k', 'rand_write_4k', 'Random write 4k sync IOPS') |
| 556 | # ] |
| 557 | # perf_infos = [res.disk_perf_info() for res in processed_results] |
| 558 | # images = make_plots(perf_infos, plots) |
| 559 | # di = get_disk_info(perf_infos) |
| 560 | # return render_all_html(comment, di, lab_info, images, "report_hdd.html") |
| 561 | # |
| 562 | # |
| 563 | # @report('cinder_iscsi', 'cinder_iscsi') |
| 564 | # def make_cinder_iscsi_report(processed_results, lab_info, comment): |
| 565 | # plots = [ |
| 566 | # ('cinder_iscsi_rrd4k', 'rand_read_4k', 'Random read 4k direct IOPS'), |
| 567 | # ('cinder_iscsi_rwx4k', 'rand_write_4k', 'Random write 4k sync IOPS') |
| 568 | # ] |
| 569 | # perf_infos = [res.disk_perf_info() for res in processed_results] |
| 570 | # try: |
| 571 | # images = make_plots(perf_infos, plots) |
| 572 | # except ValueError: |
| 573 | # plots = [ |
| 574 | # ('cinder_iscsi_rrd4k', 'rand_read_4k', 'Random read 4k direct IOPS'), |
| 575 | # ('cinder_iscsi_rws4k', 'rand_write_4k', 'Random write 4k sync IOPS') |
| 576 | # ] |
| 577 | # images = make_plots(perf_infos, plots) |
| 578 | # di = get_disk_info(perf_infos) |
| 579 | # |
| 580 | # return render_all_html(comment, di, lab_info, images, "report_cinder_iscsi.html") |
| 581 | # |
| 582 | # |
| 583 | # @report('ceph', 'ceph') |
| 584 | # def make_ceph_report(processed_results, lab_info, comment): |
| 585 | # plots = [ |
| 586 | # ('ceph_rrd4k', 'rand_read_4k', 'Random read 4k direct IOPS'), |
| 587 | # ('ceph_rws4k', 'rand_write_4k', 'Random write 4k sync IOPS'), |
| 588 | # ('ceph_rrd16m', 'rand_read_16m', 'Random read 16m direct MiBps'), |
| 589 | # ('ceph_rwd16m', 'rand_write_16m', |
| 590 | # 'Random write 16m direct MiBps'), |
| 591 | # ] |
| 592 | # |
| 593 | # perf_infos = [res.disk_perf_info() for res in processed_results] |
| 594 | # images = make_plots(perf_infos, plots) |
| 595 | # di = get_disk_info(perf_infos) |
| 596 | # return render_all_html(comment, di, lab_info, images, "report_ceph.html") |
| 597 | # |
| 598 | # |
| 599 | # @report('mixed', 'mixed') |
| 600 | # def make_mixed_report(processed_results, lab_info, comment): |
| 601 | # # |
| 602 | # # IOPS(X% read) = 100 / ( X / IOPS_W + (100 - X) / IOPS_R ) |
| 603 | # # |
| 604 | # |
| 605 | # perf_infos = [res.disk_perf_info() for res in processed_results] |
| 606 | # mixed = collections.defaultdict(lambda: []) |
| 607 | # |
| 608 | # is_ssd = False |
| 609 | # for res in perf_infos: |
| 610 | # if res.name.startswith('mixed'): |
| 611 | # if res.name.startswith('mixed-ssd'): |
| 612 | # is_ssd = True |
| 613 | # mixed[res.concurence].append((res.p.rwmixread, |
| 614 | # res.lat, |
| 615 | # 0, |
| 616 | # # res.lat.average / 1000.0, |
| 617 | # # res.lat.deviation / 1000.0, |
| 618 | # res.iops.average, |
| 619 | # res.iops.deviation)) |
| 620 | # |
| 621 | # if len(mixed) == 0: |
| 622 | # raise ValueError("No mixed load found") |
| 623 | # |
| 624 | # fig, p1 = plt.subplots() |
| 625 | # p2 = p1.twinx() |
| 626 | # |
| 627 | # colors = ['red', 'green', 'blue', 'orange', 'magenta', "teal"] |
| 628 | # colors_it = iter(colors) |
| 629 | # for conc, mix_lat_iops in sorted(mixed.items()): |
| 630 | # mix_lat_iops = sorted(mix_lat_iops) |
| 631 | # read_perc, lat, dev, iops, iops_dev = zip(*mix_lat_iops) |
| 632 | # p1.errorbar(read_perc, iops, color=next(colors_it), |
| 633 | # yerr=iops_dev, label=str(conc) + " th") |
| 634 | # |
| 635 | # p2.errorbar(read_perc, lat, color=next(colors_it), |
| 636 | # ls='--', yerr=dev, label=str(conc) + " th lat") |
| 637 | # |
| 638 | # if is_ssd: |
| 639 | # p1.set_yscale('log') |
| 640 | # p2.set_yscale('log') |
| 641 | # |
| 642 | # p1.set_xlim(-5, 105) |
| 643 | # |
| 644 | # read_perc = set(read_perc) |
| 645 | # read_perc.add(0) |
| 646 | # read_perc.add(100) |
| 647 | # read_perc = sorted(read_perc) |
| 648 | # |
| 649 | # plt.xticks(read_perc, map(str, read_perc)) |
| 650 | # |
| 651 | # p1.grid(True) |
| 652 | # p1.set_xlabel("% of reads") |
| 653 | # p1.set_ylabel("Mixed IOPS") |
| 654 | # p2.set_ylabel("Latency, ms") |
| 655 | # |
| 656 | # handles1, labels1 = p1.get_legend_handles_labels() |
| 657 | # handles2, labels2 = p2.get_legend_handles_labels() |
| 658 | # plt.subplots_adjust(top=0.85) |
| 659 | # plt.legend(handles1 + handles2, labels1 + labels2, |
| 660 | # bbox_to_anchor=(0.5, 1.15), |
| 661 | # loc='upper center', |
| 662 | # prop={'size': 12}, ncol=3) |
| 663 | # plt.show() |
| 664 | # |
| 665 | # |
| 666 | # def make_load_report(idx, results_dir, fname): |
| 667 | # dpath = os.path.join(results_dir, "io_" + str(idx)) |
| 668 | # files = sorted(os.listdir(dpath)) |
| 669 | # gf = lambda x: "_".join(x.rsplit(".", 1)[0].split('_')[:3]) |
| 670 | # |
| 671 | # for key, group in itertools.groupby(files, gf): |
| 672 | # fname = os.path.join(dpath, key + ".fio") |
| 673 | # |
| 674 | # cfgs = list(parse_all_in_1(open(fname).read(), fname)) |
| 675 | # |
| 676 | # fname = os.path.join(dpath, key + "_lat.log") |
| 677 | # |
| 678 | # curr = [] |
| 679 | # arrays = [] |
| 680 | # |
| 681 | # with open(fname) as fd: |
| 682 | # for offset, lat, _, _ in csv.reader(fd): |
| 683 | # offset = int(offset) |
| 684 | # lat = int(lat) |
| 685 | # if len(curr) > 0 and curr[-1][0] > offset: |
| 686 | # arrays.append(curr) |
| 687 | # curr = [] |
| 688 | # curr.append((offset, lat)) |
| 689 | # arrays.append(curr) |
| 690 | # conc = int(cfgs[0].vals.get('numjobs', 1)) |
| 691 | # |
| 692 | # if conc != 5: |
| 693 | # continue |
| 694 | # |
| 695 | # assert len(arrays) == len(cfgs) * conc |
| 696 | # |
| 697 | # garrays = [[(0, 0)] for _ in range(conc)] |
| 698 | # |
| 699 | # for offset in range(len(cfgs)): |
| 700 | # for acc, new_arr in zip(garrays, arrays[offset * conc:(offset + 1) * conc]): |
| 701 | # last = acc[-1][0] |
| 702 | # for off, lat in new_arr: |
| 703 | # acc.append((off / 1000. + last, lat / 1000.)) |
| 704 | # |
| 705 | # for cfg, arr in zip(cfgs, garrays): |
| 706 | # plt.plot(*zip(*arr[1:])) |
| 707 | # plt.show() |
| 708 | # exit(1) |
| 709 | # |
| 710 | # |
| 711 | # def make_io_report(dinfo, comment, path, lab_info=None): |
| 712 | # lab_info = { |
| 713 | # "total_disk": "None", |
| 714 | # "total_memory": "None", |
| 715 | # "nodes_count": "None", |
| 716 | # "processor_count": "None" |
| 717 | # } |
| 718 | # |
| 719 | # try: |
| 720 | # res_fields = sorted(v.name for v in dinfo) |
| 721 | # |
| 722 | # found = False |
| 723 | # for fields, name, func in report_funcs: |
| 724 | # for field in fields: |
| 725 | # pos = bisect.bisect_left(res_fields, field) |
| 726 | # |
| 727 | # if pos == len(res_fields): |
| 728 | # break |
| 729 | # |
| 730 | # if not res_fields[pos].startswith(field): |
| 731 | # break |
| 732 | # else: |
| 733 | # found = True |
| 734 | # hpath = path.format(name) |
| 735 | # |
| 736 | # try: |
| 737 | # report = func(dinfo, lab_info, comment) |
| 738 | # except: |
| 739 | # logger.exception("Diring {0} report generation".format(name)) |
| 740 | # continue |
| 741 | # |
| 742 | # if report is not None: |
| 743 | # try: |
| 744 | # with open(hpath, "w") as fd: |
| 745 | # fd.write(report) |
| 746 | # except: |
| 747 | # logger.exception("Diring saving {0} report".format(name)) |
| 748 | # continue |
| 749 | # logger.info("Report {0} saved into {1}".format(name, hpath)) |
| 750 | # else: |
| 751 | # logger.warning("No report produced by {0!r}".format(name)) |
| 752 | # |
| 753 | # if not found: |
| 754 | # logger.warning("No report generator found for this load") |
| 755 | # |
| 756 | # except Exception as exc: |
| 757 | # import traceback |
| 758 | # traceback.print_exc() |
| 759 | # logger.error("Failed to generate html report:" + str(exc)) |
| 760 | # |
| 761 | # |
| 762 | # # @classmethod |
| 763 | # # def prepare_data(cls, results) -> List[Dict[str, Any]]: |
| 764 | # # """create a table with io performance report for console""" |
| 765 | # # |
| 766 | # # def key_func(data: FioRunResult) -> Tuple[str, str, str, str, int]: |
| 767 | # # tpl = data.summary_tpl() |
| 768 | # # return (data.name, |
| 769 | # # tpl.oper, |
| 770 | # # tpl.mode, |
| 771 | # # ssize2b(tpl.bsize), |
| 772 | # # int(tpl.th_count) * int(tpl.vm_count)) |
| 773 | # # res = [] |
| 774 | # # |
| 775 | # # for item in sorted(results, key=key_func): |
| 776 | # # test_dinfo = item.disk_perf_info() |
| 777 | # # testnodes_count = len(item.config.nodes) |
| 778 | # # |
| 779 | # # iops, _ = test_dinfo.iops.rounded_average_conf() |
| 780 | # # |
| 781 | # # if test_dinfo.iops_sys is not None: |
| 782 | # # iops_sys, iops_sys_conf = test_dinfo.iops_sys.rounded_average_conf() |
| 783 | # # _, iops_sys_dev = test_dinfo.iops_sys.rounded_average_dev() |
| 784 | # # iops_sys_per_vm = round_3_digit(iops_sys / testnodes_count) |
| 785 | # # iops_sys = round_3_digit(iops_sys) |
| 786 | # # else: |
| 787 | # # iops_sys = None |
| 788 | # # iops_sys_per_vm = None |
| 789 | # # iops_sys_dev = None |
| 790 | # # iops_sys_conf = None |
| 791 | # # |
| 792 | # # bw, bw_conf = test_dinfo.bw.rounded_average_conf() |
| 793 | # # _, bw_dev = test_dinfo.bw.rounded_average_dev() |
| 794 | # # conf_perc = int(round(bw_conf * 100 / bw)) |
| 795 | # # dev_perc = int(round(bw_dev * 100 / bw)) |
| 796 | # # |
| 797 | # # lat_50 = round_3_digit(int(test_dinfo.lat_50)) |
| 798 | # # lat_95 = round_3_digit(int(test_dinfo.lat_95)) |
| 799 | # # lat_avg = round_3_digit(int(test_dinfo.lat_avg)) |
| 800 | # # |
| 801 | # # iops_per_vm = round_3_digit(iops / testnodes_count) |
| 802 | # # bw_per_vm = round_3_digit(bw / testnodes_count) |
| 803 | # # |
| 804 | # # iops = round_3_digit(iops) |
| 805 | # # bw = round_3_digit(bw) |
| 806 | # # |
| 807 | # # summ = "{0.oper}{0.mode} {0.bsize:>4} {0.th_count:>3}th {0.vm_count:>2}vm".format(item.summary_tpl()) |
| 808 | # # |
| 809 | # # res.append({"name": key_func(item)[0], |
| 810 | # # "key": key_func(item)[:4], |
| 811 | # # "summ": summ, |
| 812 | # # "iops": int(iops), |
| 813 | # # "bw": int(bw), |
| 814 | # # "conf": str(conf_perc), |
| 815 | # # "dev": str(dev_perc), |
| 816 | # # "iops_per_vm": int(iops_per_vm), |
| 817 | # # "bw_per_vm": int(bw_per_vm), |
| 818 | # # "lat_50": lat_50, |
| 819 | # # "lat_95": lat_95, |
| 820 | # # "lat_avg": lat_avg, |
| 821 | # # |
| 822 | # # "iops_sys": iops_sys, |
| 823 | # # "iops_sys_per_vm": iops_sys_per_vm, |
| 824 | # # "sys_conf": iops_sys_conf, |
| 825 | # # "sys_dev": iops_sys_dev}) |
| 826 | # # |
| 827 | # # return res |
| 828 | # # |
| 829 | # # Field = collections.namedtuple("Field", ("header", "attr", "allign", "size")) |
| 830 | # # fiels_and_header = [ |
| 831 | # # Field("Name", "name", "l", 7), |
| 832 | # # Field("Description", "summ", "l", 19), |
| 833 | # # Field("IOPS\ncum", "iops", "r", 3), |
| 834 | # # # Field("IOPS_sys\ncum", "iops_sys", "r", 3), |
| 835 | # # Field("KiBps\ncum", "bw", "r", 6), |
| 836 | # # Field("Cnf %\n95%", "conf", "r", 3), |
| 837 | # # Field("Dev%", "dev", "r", 3), |
| 838 | # # Field("iops\n/vm", "iops_per_vm", "r", 3), |
| 839 | # # Field("KiBps\n/vm", "bw_per_vm", "r", 6), |
| 840 | # # Field("lat ms\nmedian", "lat_50", "r", 3), |
| 841 | # # Field("lat ms\n95%", "lat_95", "r", 3), |
| 842 | # # Field("lat\navg", "lat_avg", "r", 3), |
| 843 | # # ] |
| 844 | # # |
| 845 | # # fiels_and_header_dct = dict((item.attr, item) for item in fiels_and_header) |
| 846 | # # |
| 847 | # # @classmethod |
| 848 | # # def format_for_console(cls, results) -> str: |
| 849 | # # """create a table with io performance report for console""" |
| 850 | # # |
| 851 | # # tab = texttable.Texttable(max_width=120) |
| 852 | # # tab.set_deco(tab.HEADER | tab.VLINES | tab.BORDER) |
| 853 | # # tab.set_cols_align([f.allign for f in cls.fiels_and_header]) |
| 854 | # # sep = ["-" * f.size for f in cls.fiels_and_header] |
| 855 | # # tab.header([f.header for f in cls.fiels_and_header]) |
| 856 | # # prev_k = None |
| 857 | # # for item in cls.prepare_data(results): |
| 858 | # # if prev_k is not None: |
| 859 | # # if prev_k != item["key"]: |
| 860 | # # tab.add_row(sep) |
| 861 | # # |
| 862 | # # prev_k = item["key"] |
| 863 | # # tab.add_row([item[f.attr] for f in cls.fiels_and_header]) |
| 864 | # # |
| 865 | # # return tab.draw() |
| 866 | # # |
| 867 | # # @classmethod |
| 868 | # # def format_diff_for_console(cls, list_of_results: List[Any]) -> str: |
| 869 | # # """create a table with io performance report for console""" |
| 870 | # # |
| 871 | # # tab = texttable.Texttable(max_width=200) |
| 872 | # # tab.set_deco(tab.HEADER | tab.VLINES | tab.BORDER) |
| 873 | # # |
| 874 | # # header = [ |
| 875 | # # cls.fiels_and_header_dct["name"].header, |
| 876 | # # cls.fiels_and_header_dct["summ"].header, |
| 877 | # # ] |
| 878 | # # allign = ["l", "l"] |
| 879 | # # |
| 880 | # # header.append("IOPS ~ Cnf% ~ Dev%") |
| 881 | # # allign.extend(["r"] * len(list_of_results)) |
| 882 | # # header.extend( |
| 883 | # # "IOPS_{0} %".format(i + 2) for i in range(len(list_of_results[1:])) |
| 884 | # # ) |
| 885 | # # |
| 886 | # # header.append("BW") |
| 887 | # # allign.extend(["r"] * len(list_of_results)) |
| 888 | # # header.extend( |
| 889 | # # "BW_{0} %".format(i + 2) for i in range(len(list_of_results[1:])) |
| 890 | # # ) |
| 891 | # # |
| 892 | # # header.append("LAT") |
| 893 | # # allign.extend(["r"] * len(list_of_results)) |
| 894 | # # header.extend( |
| 895 | # # "LAT_{0}".format(i + 2) for i in range(len(list_of_results[1:])) |
| 896 | # # ) |
| 897 | # # |
| 898 | # # tab.header(header) |
| 899 | # # sep = ["-" * 3] * len(header) |
| 900 | # # processed_results = map(cls.prepare_data, list_of_results) |
| 901 | # # |
| 902 | # # key2results = [] |
| 903 | # # for res in processed_results: |
| 904 | # # key2results.append(dict( |
| 905 | # # ((item["name"], item["summ"]), item) for item in res |
| 906 | # # )) |
| 907 | # # |
| 908 | # # prev_k = None |
| 909 | # # iops_frmt = "{0[iops]} ~ {0[conf]:>2} ~ {0[dev]:>2}" |
| 910 | # # for item in processed_results[0]: |
| 911 | # # if prev_k is not None: |
| 912 | # # if prev_k != item["key"]: |
| 913 | # # tab.add_row(sep) |
| 914 | # # |
| 915 | # # prev_k = item["key"] |
| 916 | # # |
| 917 | # # key = (item['name'], item['summ']) |
| 918 | # # line = list(key) |
| 919 | # # base = key2results[0][key] |
| 920 | # # |
| 921 | # # line.append(iops_frmt.format(base)) |
| 922 | # # |
| 923 | # # for test_results in key2results[1:]: |
| 924 | # # val = test_results.get(key) |
| 925 | # # if val is None: |
| 926 | # # line.append("-") |
| 927 | # # elif base['iops'] == 0: |
| 928 | # # line.append("Nan") |
| 929 | # # else: |
| 930 | # # prc_val = {'dev': val['dev'], 'conf': val['conf']} |
| 931 | # # prc_val['iops'] = int(100 * val['iops'] / base['iops']) |
| 932 | # # line.append(iops_frmt.format(prc_val)) |
| 933 | # # |
| 934 | # # line.append(base['bw']) |
| 935 | # # |
| 936 | # # for test_results in key2results[1:]: |
| 937 | # # val = test_results.get(key) |
| 938 | # # if val is None: |
| 939 | # # line.append("-") |
| 940 | # # elif base['bw'] == 0: |
| 941 | # # line.append("Nan") |
| 942 | # # else: |
| 943 | # # line.append(int(100 * val['bw'] / base['bw'])) |
| 944 | # # |
| 945 | # # for test_results in key2results: |
| 946 | # # val = test_results.get(key) |
| 947 | # # if val is None: |
| 948 | # # line.append("-") |
| 949 | # # else: |
| 950 | # # line.append("{0[lat_50]} - {0[lat_95]}".format(val)) |
| 951 | # # |
| 952 | # # tab.add_row(line) |
| 953 | # # |
| 954 | # # tab.set_cols_align(allign) |
| 955 | # # return tab.draw() |
| 956 | # |
| 957 | # |
| 958 | # # READ_IOPS_DISCSTAT_POS = 3 |
| 959 | # # WRITE_IOPS_DISCSTAT_POS = 7 |
| 960 | # # |
| 961 | # # |
| 962 | # # def load_sys_log_file(ftype: str, fname: str) -> TimeSeriesValue: |
| 963 | # # assert ftype == 'iops' |
| 964 | # # pval = None |
| 965 | # # with open(fname) as fd: |
| 966 | # # iops = [] |
| 967 | # # for ln in fd: |
| 968 | # # params = ln.split() |
| 969 | # # cval = int(params[WRITE_IOPS_DISCSTAT_POS]) + \ |
| 970 | # # int(params[READ_IOPS_DISCSTAT_POS]) |
| 971 | # # if pval is not None: |
| 972 | # # iops.append(cval - pval) |
| 973 | # # pval = cval |
| 974 | # # |
| 975 | # # vals = [(idx * 1000, val) for idx, val in enumerate(iops)] |
| 976 | # # return TimeSeriesValue(vals) |
| 977 | # # |
| 978 | # # |
| 979 | # # def load_test_results(folder: str, run_num: int) -> 'FioRunResult': |
| 980 | # # res = {} |
| 981 | # # params = None |
| 982 | # # |
| 983 | # # fn = os.path.join(folder, str(run_num) + '_params.yaml') |
| 984 | # # params = yaml.load(open(fn).read()) |
| 985 | # # |
| 986 | # # conn_ids_set = set() |
| 987 | # # rr = r"{}_(?P<conn_id>.*?)_(?P<type>[^_.]*)\.\d+\.log$".format(run_num) |
| 988 | # # for fname in os.listdir(folder): |
| 989 | # # rm = re.match(rr, fname) |
| 990 | # # if rm is None: |
| 991 | # # continue |
| 992 | # # |
| 993 | # # conn_id_s = rm.group('conn_id') |
| 994 | # # conn_id = conn_id_s.replace('_', ':') |
| 995 | # # ftype = rm.group('type') |
| 996 | # # |
| 997 | # # if ftype not in ('iops', 'bw', 'lat'): |
| 998 | # # continue |
| 999 | # # |
| 1000 | # # ts = load_fio_log_file(os.path.join(folder, fname)) |
| 1001 | # # res.setdefault(ftype, {}).setdefault(conn_id, []).append(ts) |
| 1002 | # # |
| 1003 | # # conn_ids_set.add(conn_id) |
| 1004 | # # |
| 1005 | # # rr = r"{}_(?P<conn_id>.*?)_(?P<type>[^_.]*)\.sys\.log$".format(run_num) |
| 1006 | # # for fname in os.listdir(folder): |
| 1007 | # # rm = re.match(rr, fname) |
| 1008 | # # if rm is None: |
| 1009 | # # continue |
| 1010 | # # |
| 1011 | # # conn_id_s = rm.group('conn_id') |
| 1012 | # # conn_id = conn_id_s.replace('_', ':') |
| 1013 | # # ftype = rm.group('type') |
| 1014 | # # |
| 1015 | # # if ftype not in ('iops', 'bw', 'lat'): |
| 1016 | # # continue |
| 1017 | # # |
| 1018 | # # ts = load_sys_log_file(ftype, os.path.join(folder, fname)) |
| 1019 | # # res.setdefault(ftype + ":sys", {}).setdefault(conn_id, []).append(ts) |
| 1020 | # # |
| 1021 | # # conn_ids_set.add(conn_id) |
| 1022 | # # |
| 1023 | # # mm_res = {} |
| 1024 | # # |
| 1025 | # # if len(res) == 0: |
| 1026 | # # raise ValueError("No data was found") |
| 1027 | # # |
| 1028 | # # for key, data in res.items(): |
| 1029 | # # conn_ids = sorted(conn_ids_set) |
| 1030 | # # awail_ids = [conn_id for conn_id in conn_ids if conn_id in data] |
| 1031 | # # matr = [data[conn_id] for conn_id in awail_ids] |
| 1032 | # # mm_res[key] = MeasurementMatrix(matr, awail_ids) |
| 1033 | # # |
| 1034 | # # raw_res = {} |
| 1035 | # # for conn_id in conn_ids: |
| 1036 | # # fn = os.path.join(folder, "{0}_{1}_rawres.json".format(run_num, conn_id_s)) |
| 1037 | # # |
| 1038 | # # # remove message hack |
| 1039 | # # fc = "{" + open(fn).read().split('{', 1)[1] |
| 1040 | # # raw_res[conn_id] = json.loads(fc) |
| 1041 | # # |
| 1042 | # # fio_task = FioJobSection(params['name']) |
| 1043 | # # fio_task.vals.update(params['vals']) |
| 1044 | # # |
| 1045 | # # config = TestConfig('io', params, None, params['nodes'], folder, None) |
| 1046 | # # return FioRunResult(config, fio_task, mm_res, raw_res, params['intervals'], run_num) |
| 1047 | # # |
| 1048 | # |
| 1049 | # # class DiskPerfInfo: |
| 1050 | # # def __init__(self, name: str, summary: str, params: Dict[str, Any], testnodes_count: int) -> None: |
| 1051 | # # self.name = name |
| 1052 | # # self.bw = None |
| 1053 | # # self.iops = None |
| 1054 | # # self.lat = None |
| 1055 | # # self.lat_50 = None |
| 1056 | # # self.lat_95 = None |
| 1057 | # # self.lat_avg = None |
| 1058 | # # |
| 1059 | # # self.raw_bw = [] |
| 1060 | # # self.raw_iops = [] |
| 1061 | # # self.raw_lat = [] |
| 1062 | # # |
| 1063 | # # self.params = params |
| 1064 | # # self.testnodes_count = testnodes_count |
| 1065 | # # self.summary = summary |
| 1066 | # # |
| 1067 | # # self.sync_mode = get_test_sync_mode(self.params['vals']) |
| 1068 | # # self.concurence = self.params['vals'].get('numjobs', 1) |
| 1069 | # # |
| 1070 | # # |
| 1071 | # # class IOTestResults: |
| 1072 | # # def __init__(self, suite_name: str, fio_results: 'FioRunResult', log_directory: str): |
| 1073 | # # self.suite_name = suite_name |
| 1074 | # # self.fio_results = fio_results |
| 1075 | # # self.log_directory = log_directory |
| 1076 | # # |
| 1077 | # # def __iter__(self): |
| 1078 | # # return iter(self.fio_results) |
| 1079 | # # |
| 1080 | # # def __len__(self): |
| 1081 | # # return len(self.fio_results) |
| 1082 | # # |
| 1083 | # # def get_yamable(self) -> Dict[str, List[str]]: |
| 1084 | # # items = [(fio_res.summary(), fio_res.idx) for fio_res in self] |
| 1085 | # # return {self.suite_name: [self.log_directory] + items} |
| 1086 | # |
| 1087 | # |
| 1088 | # # class FioRunResult(TestResults): |
| 1089 | # # """ |
| 1090 | # # Fio run results |
| 1091 | # # config: TestConfig |
| 1092 | # # fio_task: FioJobSection |
| 1093 | # # ts_results: {str: MeasurementMatrix[TimeSeriesValue]} |
| 1094 | # # raw_result: ???? |
| 1095 | # # run_interval:(float, float) - test tun time, used for sensors |
| 1096 | # # """ |
| 1097 | # # def __init__(self, config, fio_task, ts_results, raw_result, run_interval, idx): |
| 1098 | # # |
| 1099 | # # self.name = fio_task.name.rsplit("_", 1)[0] |
| 1100 | # # self.fio_task = fio_task |
| 1101 | # # self.idx = idx |
| 1102 | # # |
| 1103 | # # self.bw = ts_results['bw'] |
| 1104 | # # self.lat = ts_results['lat'] |
| 1105 | # # self.iops = ts_results['iops'] |
| 1106 | # # |
| 1107 | # # if 'iops:sys' in ts_results: |
| 1108 | # # self.iops_sys = ts_results['iops:sys'] |
| 1109 | # # else: |
| 1110 | # # self.iops_sys = None |
| 1111 | # # |
| 1112 | # # res = {"bw": self.bw, |
| 1113 | # # "lat": self.lat, |
| 1114 | # # "iops": self.iops, |
| 1115 | # # "iops:sys": self.iops_sys} |
| 1116 | # # |
| 1117 | # # self.sensors_data = None |
| 1118 | # # self._pinfo = None |
| 1119 | # # TestResults.__init__(self, config, res, raw_result, run_interval) |
| 1120 | # # |
| 1121 | # # def get_params_from_fio_report(self): |
| 1122 | # # nodes = self.bw.connections_ids |
| 1123 | # # |
| 1124 | # # iops = [self.raw_result[node]['jobs'][0]['mixed']['iops'] for node in nodes] |
| 1125 | # # total_ios = [self.raw_result[node]['jobs'][0]['mixed']['total_ios'] for node in nodes] |
| 1126 | # # runtime = [self.raw_result[node]['jobs'][0]['mixed']['runtime'] / 1000 for node in nodes] |
| 1127 | # # flt_iops = [float(ios) / rtime for ios, rtime in zip(total_ios, runtime)] |
| 1128 | # # |
| 1129 | # # bw = [self.raw_result[node]['jobs'][0]['mixed']['bw'] for node in nodes] |
| 1130 | # # total_bytes = [self.raw_result[node]['jobs'][0]['mixed']['io_bytes'] for node in nodes] |
| 1131 | # # flt_bw = [float(tbytes) / rtime for tbytes, rtime in zip(total_bytes, runtime)] |
| 1132 | # # |
| 1133 | # # return {'iops': iops, |
| 1134 | # # 'flt_iops': flt_iops, |
| 1135 | # # 'bw': bw, |
| 1136 | # # 'flt_bw': flt_bw} |
| 1137 | # # |
| 1138 | # # def summary(self): |
| 1139 | # # return get_test_summary(self.fio_task, len(self.config.nodes)) |
| 1140 | # # |
| 1141 | # # def summary_tpl(self): |
| 1142 | # # return get_test_summary_tuple(self.fio_task, len(self.config.nodes)) |
| 1143 | # # |
| 1144 | # # def get_lat_perc_50_95_multy(self): |
| 1145 | # # lat_mks = collections.defaultdict(lambda: 0) |
| 1146 | # # num_res = 0 |
| 1147 | # # |
| 1148 | # # for result in self.raw_result.values(): |
| 1149 | # # num_res += len(result['jobs']) |
| 1150 | # # for job_info in result['jobs']: |
| 1151 | # # for k, v in job_info['latency_ms'].items(): |
| 1152 | # # if isinstance(k, basestring) and k.startswith('>='): |
| 1153 | # # lat_mks[int(k[2:]) * 1000] += v |
| 1154 | # # else: |
| 1155 | # # lat_mks[int(k) * 1000] += v |
| 1156 | # # |
| 1157 | # # for k, v in job_info['latency_us'].items(): |
| 1158 | # # lat_mks[int(k)] += v |
| 1159 | # # |
| 1160 | # # for k, v in lat_mks.items(): |
| 1161 | # # lat_mks[k] = float(v) / num_res |
| 1162 | # # return get_lat_perc_50_95(lat_mks) |
| 1163 | # # |
| 1164 | # # def disk_perf_info(self, avg_interval=2.0): |
| 1165 | # # |
| 1166 | # # if self._pinfo is not None: |
| 1167 | # # return self._pinfo |
| 1168 | # # |
| 1169 | # # testnodes_count = len(self.config.nodes) |
| 1170 | # # |
| 1171 | # # pinfo = DiskPerfInfo(self.name, |
| 1172 | # # self.summary(), |
| 1173 | # # self.params, |
| 1174 | # # testnodes_count) |
| 1175 | # # |
| 1176 | # # def prepare(data, drop=1): |
| 1177 | # # if data is None: |
| 1178 | # # return data |
| 1179 | # # |
| 1180 | # # res = [] |
| 1181 | # # for ts_data in data: |
| 1182 | # # if ts_data.average_interval() < avg_interval: |
| 1183 | # # ts_data = ts_data.derived(avg_interval) |
| 1184 | # # |
| 1185 | # # # drop last value on bounds |
| 1186 | # # # as they may contains ranges without activities |
| 1187 | # # assert len(ts_data.values) >= drop + 1, str(drop) + " " + str(ts_data.values) |
| 1188 | # # |
| 1189 | # # if drop > 0: |
| 1190 | # # res.append(ts_data.values[:-drop]) |
| 1191 | # # else: |
| 1192 | # # res.append(ts_data.values) |
| 1193 | # # |
| 1194 | # # return res |
| 1195 | # # |
| 1196 | # # def agg_data(matr): |
| 1197 | # # arr = sum(matr, []) |
| 1198 | # # min_len = min(map(len, arr)) |
| 1199 | # # res = [] |
| 1200 | # # for idx in range(min_len): |
| 1201 | # # res.append(sum(dt[idx] for dt in arr)) |
| 1202 | # # return res |
| 1203 | # # |
| 1204 | # # pinfo.raw_lat = map(prepare, self.lat.per_vm()) |
| 1205 | # # num_th = sum(map(len, pinfo.raw_lat)) |
| 1206 | # # lat_avg = [val / num_th for val in agg_data(pinfo.raw_lat)] |
| 1207 | # # pinfo.lat_avg = data_property(lat_avg).average / 1000 # us to ms |
| 1208 | # # |
| 1209 | # # pinfo.lat_50, pinfo.lat_95 = self.get_lat_perc_50_95_multy() |
| 1210 | # # pinfo.lat = pinfo.lat_50 |
| 1211 | # # |
| 1212 | # # pinfo.raw_bw = map(prepare, self.bw.per_vm()) |
| 1213 | # # pinfo.raw_iops = map(prepare, self.iops.per_vm()) |
| 1214 | # # |
| 1215 | # # if self.iops_sys is not None: |
| 1216 | # # pinfo.raw_iops_sys = map(prepare, self.iops_sys.per_vm()) |
| 1217 | # # pinfo.iops_sys = data_property(agg_data(pinfo.raw_iops_sys)) |
| 1218 | # # else: |
| 1219 | # # pinfo.raw_iops_sys = None |
| 1220 | # # pinfo.iops_sys = None |
| 1221 | # # |
| 1222 | # # fparams = self.get_params_from_fio_report() |
| 1223 | # # fio_report_bw = sum(fparams['flt_bw']) |
| 1224 | # # fio_report_iops = sum(fparams['flt_iops']) |
| 1225 | # # |
| 1226 | # # agg_bw = agg_data(pinfo.raw_bw) |
| 1227 | # # agg_iops = agg_data(pinfo.raw_iops) |
| 1228 | # # |
| 1229 | # # log_bw_avg = average(agg_bw) |
| 1230 | # # log_iops_avg = average(agg_iops) |
| 1231 | # # |
| 1232 | # # # update values to match average from fio report |
| 1233 | # # coef_iops = fio_report_iops / float(log_iops_avg) |
| 1234 | # # coef_bw = fio_report_bw / float(log_bw_avg) |
| 1235 | # # |
| 1236 | # # bw_log = data_property([val * coef_bw for val in agg_bw]) |
| 1237 | # # iops_log = data_property([val * coef_iops for val in agg_iops]) |
| 1238 | # # |
| 1239 | # # bw_report = data_property([fio_report_bw]) |
| 1240 | # # iops_report = data_property([fio_report_iops]) |
| 1241 | # # |
| 1242 | # # # When IOPS/BW per thread is too low |
| 1243 | # # # data from logs is rounded to match |
| 1244 | # # iops_per_th = sum(sum(pinfo.raw_iops, []), []) |
| 1245 | # # if average(iops_per_th) > 10: |
| 1246 | # # pinfo.iops = iops_log |
| 1247 | # # pinfo.iops2 = iops_report |
| 1248 | # # else: |
| 1249 | # # pinfo.iops = iops_report |
| 1250 | # # pinfo.iops2 = iops_log |
| 1251 | # # |
| 1252 | # # bw_per_th = sum(sum(pinfo.raw_bw, []), []) |
| 1253 | # # if average(bw_per_th) > 10: |
| 1254 | # # pinfo.bw = bw_log |
| 1255 | # # pinfo.bw2 = bw_report |
| 1256 | # # else: |
| 1257 | # # pinfo.bw = bw_report |
| 1258 | # # pinfo.bw2 = bw_log |
| 1259 | # # |
| 1260 | # # self._pinfo = pinfo |
| 1261 | # # |
| 1262 | # # return pinfo |
| 1263 | # |
| 1264 | # # class TestResult: |
| 1265 | # # """Hold all information for a given test - test info, |
| 1266 | # # sensors data and performance results for test period from all nodes""" |
| 1267 | # # run_id = None # type: int |
| 1268 | # # test_info = None # type: Any |
| 1269 | # # begin_time = None # type: int |
| 1270 | # # end_time = None # type: int |
| 1271 | # # sensors = None # Dict[Tuple[str, str, str], TimeSeries] |
| 1272 | # # performance = None # Dict[Tuple[str, str], TimeSeries] |
| 1273 | # # |
| 1274 | # # class TestResults: |
| 1275 | # # """ |
| 1276 | # # this class describe test results |
| 1277 | # # |
| 1278 | # # config:TestConfig - test config object |
| 1279 | # # params:dict - parameters from yaml file for this test |
| 1280 | # # results:{str:MeasurementMesh} - test results object |
| 1281 | # # raw_result:Any - opaque object to store raw results |
| 1282 | # # run_interval:(float, float) - test tun time, used for sensors |
| 1283 | # # """ |
| 1284 | # # |
| 1285 | # # def __init__(self, |
| 1286 | # # config: TestConfig, |
| 1287 | # # results: Dict[str, Any], |
| 1288 | # # raw_result: Any, |
| 1289 | # # run_interval: Tuple[float, float]) -> None: |
| 1290 | # # self.config = config |
| 1291 | # # self.params = config.params |
| 1292 | # # self.results = results |
| 1293 | # # self.raw_result = raw_result |
| 1294 | # # self.run_interval = run_interval |
| 1295 | # # |
| 1296 | # # def __str__(self) -> str: |
| 1297 | # # res = "{0}({1}):\n results:\n".format( |
| 1298 | # # self.__class__.__name__, |
| 1299 | # # self.summary()) |
| 1300 | # # |
| 1301 | # # for name, val in self.results.items(): |
| 1302 | # # res += " {0}={1}\n".format(name, val) |
| 1303 | # # |
| 1304 | # # res += " params:\n" |
| 1305 | # # |
| 1306 | # # for name, val in self.params.items(): |
| 1307 | # # res += " {0}={1}\n".format(name, val) |
| 1308 | # # |
| 1309 | # # return res |
| 1310 | # # |
| 1311 | # # def summary(self) -> str: |
| 1312 | # # raise NotImplementedError() |
| 1313 | # # return "" |
| 1314 | # # |
| 1315 | # # def get_yamable(self) -> Any: |
| 1316 | # # raise NotImplementedError() |
| 1317 | # # return None |
| 1318 | # |
| 1319 | # |
| 1320 | # |
| 1321 | # # class MeasurementMatrix: |
| 1322 | # # """ |
| 1323 | # # data:[[MeasurementResult]] - VM_COUNT x TH_COUNT matrix of MeasurementResult |
| 1324 | # # """ |
| 1325 | # # def __init__(self, data, connections_ids): |
| 1326 | # # self.data = data |
| 1327 | # # self.connections_ids = connections_ids |
| 1328 | # # |
| 1329 | # # def per_vm(self): |
| 1330 | # # return self.data |
| 1331 | # # |
| 1332 | # # def per_th(self): |
| 1333 | # # return sum(self.data, []) |
| 1334 | # |
| 1335 | # |
| 1336 | # # class MeasurementResults: |
| 1337 | # # data = None # type: List[Any] |
| 1338 | # # |
| 1339 | # # def stat(self) -> StatProps: |
| 1340 | # # return data_property(self.data) |
| 1341 | # # |
| 1342 | # # def __str__(self) -> str: |
| 1343 | # # return 'TS([' + ", ".join(map(str, self.data)) + '])' |
| 1344 | # # |
| 1345 | # # |
| 1346 | # # class SimpleVals(MeasurementResults): |
| 1347 | # # """ |
| 1348 | # # data:[float] - list of values |
| 1349 | # # """ |
| 1350 | # # def __init__(self, data: List[float]) -> None: |
| 1351 | # # self.data = data |
| 1352 | # # |
| 1353 | # # |
| 1354 | # # class TimeSeriesValue(MeasurementResults): |
| 1355 | # # """ |
| 1356 | # # data:[(float, float, float)] - list of (start_time, lenght, average_value_for_interval) |
| 1357 | # # odata: original values |
| 1358 | # # """ |
| 1359 | # # def __init__(self, data: List[Tuple[float, float]]) -> None: |
| 1360 | # # assert len(data) > 0 |
| 1361 | # # self.odata = data[:] |
| 1362 | # # self.data = [] # type: List[Tuple[float, float, float]] |
| 1363 | # # |
| 1364 | # # cstart = 0.0 |
| 1365 | # # for nstart, nval in data: |
| 1366 | # # self.data.append((cstart, nstart - cstart, nval)) |
| 1367 | # # cstart = nstart |
| 1368 | # # |
| 1369 | # # @property |
| 1370 | # # def values(self) -> List[float]: |
| 1371 | # # return [val[2] for val in self.data] |
| 1372 | # # |
| 1373 | # # def average_interval(self) -> float: |
| 1374 | # # return float(sum([val[1] for val in self.data])) / len(self.data) |
| 1375 | # # |
| 1376 | # # def skip(self, seconds) -> 'TimeSeriesValue': |
| 1377 | # # nres = [] |
| 1378 | # # for start, ln, val in self.data: |
| 1379 | # # nstart = start + ln - seconds |
| 1380 | # # if nstart > 0: |
| 1381 | # # nres.append([nstart, val]) |
| 1382 | # # return self.__class__(nres) |
| 1383 | # # |
| 1384 | # # def derived(self, tdelta) -> 'TimeSeriesValue': |
| 1385 | # # end = self.data[-1][0] + self.data[-1][1] |
| 1386 | # # tdelta = float(tdelta) |
| 1387 | # # |
| 1388 | # # ln = end / tdelta |
| 1389 | # # |
| 1390 | # # if ln - int(ln) > 0: |
| 1391 | # # ln += 1 |
| 1392 | # # |
| 1393 | # # res = [[tdelta * i, 0.0] for i in range(int(ln))] |
| 1394 | # # |
| 1395 | # # for start, lenght, val in self.data: |
| 1396 | # # start_idx = int(start / tdelta) |
| 1397 | # # end_idx = int((start + lenght) / tdelta) |
| 1398 | # # |
| 1399 | # # for idx in range(start_idx, end_idx + 1): |
| 1400 | # # rstart = tdelta * idx |
| 1401 | # # rend = tdelta * (idx + 1) |
| 1402 | # # |
| 1403 | # # intersection_ln = min(rend, start + lenght) - max(start, rstart) |
| 1404 | # # if intersection_ln > 0: |
| 1405 | # # try: |
| 1406 | # # res[idx][1] += val * intersection_ln / tdelta |
| 1407 | # # except IndexError: |
| 1408 | # # raise |
| 1409 | # # |
| 1410 | # # return self.__class__(res) |
| 1411 | # |
| 1412 | # |
| 1413 | # def console_report_stage(ctx: TestRun) -> None: |
| 1414 | # # TODO(koder): load data from storage |
| 1415 | # raise NotImplementedError("...") |
| 1416 | # # first_report = True |
| 1417 | # # text_rep_fname = ctx.config.text_report_file |
| 1418 | # # |
| 1419 | # # with open(text_rep_fname, "w") as fd: |
| 1420 | # # for tp, data in ctx.results.items(): |
| 1421 | # # if 'io' == tp and data is not None: |
| 1422 | # # rep_lst = [] |
| 1423 | # # for result in data: |
| 1424 | # # rep_lst.append( |
| 1425 | # # IOPerfTest.format_for_console(list(result))) |
| 1426 | # # rep = "\n\n".join(rep_lst) |
| 1427 | # # elif tp in ['mysql', 'pgbench'] and data is not None: |
| 1428 | # # rep = MysqlTest.format_for_console(data) |
| 1429 | # # elif tp == 'omg': |
| 1430 | # # rep = OmgTest.format_for_console(data) |
| 1431 | # # else: |
| 1432 | # # logger.warning("Can't generate text report for " + tp) |
| 1433 | # # continue |
| 1434 | # # |
| 1435 | # # fd.write(rep) |
| 1436 | # # fd.write("\n") |
| 1437 | # # |
| 1438 | # # if first_report: |
| 1439 | # # logger.info("Text report were stored in " + text_rep_fname) |
| 1440 | # # first_report = False |
| 1441 | # # |
| 1442 | # # print("\n" + rep + "\n") |
| 1443 | # |
| 1444 | # |
| 1445 | # # def test_load_report_stage(cfg: Config, ctx: TestRun) -> None: |
| 1446 | # # load_rep_fname = cfg.load_report_file |
| 1447 | # # found = False |
| 1448 | # # for idx, (tp, data) in enumerate(ctx.results.items()): |
| 1449 | # # if 'io' == tp and data is not None: |
| 1450 | # # if found: |
| 1451 | # # logger.error("Making reports for more than one " + |
| 1452 | # # "io block isn't supported! All " + |
| 1453 | # # "report, except first are skipped") |
| 1454 | # # continue |
| 1455 | # # found = True |
| 1456 | # # report.make_load_report(idx, cfg['results'], load_rep_fname) |
| 1457 | # # |
| 1458 | # # |
| 1459 | # |
| 1460 | # # def html_report_stage(ctx: TestRun) -> None: |
| 1461 | # # TODO(koder): load data from storage |
| 1462 | # # raise NotImplementedError("...") |
| 1463 | # # html_rep_fname = cfg.html_report_file |
| 1464 | # # found = False |
| 1465 | # # for tp, data in ctx.results.items(): |
| 1466 | # # if 'io' == tp and data is not None: |
| 1467 | # # if found or len(data) > 1: |
| 1468 | # # logger.error("Making reports for more than one " + |
| 1469 | # # "io block isn't supported! All " + |
| 1470 | # # "report, except first are skipped") |
| 1471 | # # continue |
| 1472 | # # found = True |
| 1473 | # # report.make_io_report(list(data[0]), |
| 1474 | # # cfg.get('comment', ''), |
| 1475 | # # html_rep_fname, |
| 1476 | # # lab_info=ctx.nodes) |
| 1477 | # |
| 1478 | # # |
| 1479 | # # def load_data_from_path(test_res_dir: str) -> Mapping[str, List[Any]]: |
| 1480 | # # files = get_test_files(test_res_dir) |
| 1481 | # # raw_res = yaml_load(open(files['raw_results']).read()) |
| 1482 | # # res = collections.defaultdict(list) |
| 1483 | # # |
| 1484 | # # for tp, test_lists in raw_res: |
| 1485 | # # for tests in test_lists: |
| 1486 | # # for suite_name, suite_data in tests.items(): |
| 1487 | # # result_folder = suite_data[0] |
| 1488 | # # res[tp].append(TOOL_TYPE_MAPPER[tp].load(suite_name, result_folder)) |
| 1489 | # # |
| 1490 | # # return res |
| 1491 | # # |
| 1492 | # # |
| 1493 | # # def load_data_from_path_stage(var_dir: str, _, ctx: TestRun) -> None: |
| 1494 | # # for tp, vals in load_data_from_path(var_dir).items(): |
| 1495 | # # ctx.results.setdefault(tp, []).extend(vals) |
| 1496 | # # |
| 1497 | # # |
| 1498 | # # def load_data_from(var_dir: str) -> Callable[[TestRun], None]: |
| 1499 | # # return functools.partial(load_data_from_path_stage, var_dir) |