tools/crunchstat-summary/crunchstat_summary/summarizer.py

   1 # Copyright (C) The Arvados Authors. All rights reserved.
   2 #
   3 # SPDX-License-Identifier: AGPL-3.0
   4
   5 import arvados
   6 import collections
   7 import crunchstat_summary.dygraphs
   8 import crunchstat_summary.reader
   9 import datetime
  10 import functools
  11 import itertools
  12 import math
  13 import re
  14 import sys
  15 import threading
  16 import _strptime
  17
  18 from arvados.api import OrderedJsonModel
  19 from crunchstat_summary import logger
  20
  21 # Recommend memory constraints that are this multiple of an integral
  22 # number of GiB. (Actual nodes tend to be sold in sizes like 8 GiB
  23 # that have amounts like 7.5 GiB according to the kernel.)
  24 AVAILABLE_RAM_RATIO = 0.95
  25 MB=2**20
  26
  27 # Workaround datetime.datetime.strptime() thread-safety bug by calling
  28 # it once before starting threads.  https://bugs.python.org/issue7980
  29 datetime.datetime.strptime('1999-12-31_23:59:59', '%Y-%m-%d_%H:%M:%S')
  30
  31
  32 WEBCHART_CLASS = crunchstat_summary.dygraphs.DygraphsChart
  33
  34
  35 class Task(object):
  36     def __init__(self):
  37         self.starttime = None
  38         self.finishtime = None
  39         self.series = collections.defaultdict(list)
  40
  41
  42 class Summarizer(object):
  43     def __init__(self, logdata, label=None, skip_child_jobs=False, uuid=None, **kwargs):
  44         self._logdata = logdata
  45
  46         self.uuid = uuid
  47         self.label = label
  48         self.starttime = None
  49         self.finishtime = None
  50         self._skip_child_jobs = skip_child_jobs
  51
  52         # stats_max: {category: {stat: val}}
  53         self.stats_max = collections.defaultdict(
  54             functools.partial(collections.defaultdict, lambda: 0))
  55         # task_stats: {task_id: {category: {stat: val}}}
  56         self.task_stats = collections.defaultdict(
  57             functools.partial(collections.defaultdict, dict))
  58
  59         self.seq_to_uuid = {}
  60         self.tasks = collections.defaultdict(Task)
  61
  62         # We won't bother recommending new runtime constraints if the
  63         # constraints given when running the job are known to us and
  64         # are already suitable.  If applicable, the subclass
  65         # constructor will overwrite this with something useful.
  66         self.existing_constraints = {}
  67
  68         logger.debug("%s: logdata %s", self.label, logdata)
  69
  70     def run(self):
  71         logger.debug("%s: parsing logdata %s", self.label, self._logdata)
  72         with self._logdata as logdata:
  73             self._run(logdata)
  74
  75     def _run(self, logdata):
  76         self.detected_crunch1 = False
  77         for line in logdata:
  78             if not self.detected_crunch1 and '-8i9sb-' in line:
  79                 self.detected_crunch1 = True
  80
  81             if self.detected_crunch1:
  82                 m = re.search(r'^\S+ \S+ \d+ (?P<seq>\d+) job_task (?P<task_uuid>\S+)$', line)
  83                 if m:
  84                     seq = int(m.group('seq'))
  85                     uuid = m.group('task_uuid')
  86                     self.seq_to_uuid[seq] = uuid
  87                     logger.debug('%s: seq %d is task %s', self.label, seq, uuid)
  88                     continue
  89
  90                 m = re.search(r'^\S+ \S+ \d+ (?P<seq>\d+) (success in|failure \(#., permanent\) after) (?P<elapsed>\d+) seconds', line)
  91                 if m:
  92                     task_id = self.seq_to_uuid[int(m.group('seq'))]
  93                     elapsed = int(m.group('elapsed'))
  94                     self.task_stats[task_id]['time'] = {'elapsed': elapsed}
  95                     if elapsed > self.stats_max['time']['elapsed']:
  96                         self.stats_max['time']['elapsed'] = elapsed
  97                     continue
  98
  99                 m = re.search(r'^\S+ \S+ \d+ (?P<seq>\d+) stderr Queued job (?P<uuid>\S+)$', line)
 100                 if m:
 101                     uuid = m.group('uuid')
 102                     if self._skip_child_jobs:
 103                         logger.warning('%s: omitting stats from child job %s'
 104                                        ' because --skip-child-jobs flag is on',
 105                                        self.label, uuid)
 106                         continue
 107                     logger.debug('%s: follow %s', self.label, uuid)
 108                     child_summarizer = ProcessSummarizer(uuid)
 109                     child_summarizer.stats_max = self.stats_max
 110                     child_summarizer.task_stats = self.task_stats
 111                     child_summarizer.tasks = self.tasks
 112                     child_summarizer.starttime = self.starttime
 113                     child_summarizer.run()
 114                     logger.debug('%s: done %s', self.label, uuid)
 115                     continue
 116
 117                 # 2017-12-02_17:15:08 e51c5-8i9sb-mfp68stkxnqdd6m 63676 0 stderr crunchstat: keepcalls 0 put 2576 get -- interval 10.0000 seconds 0 put 2576 get
 118                 m = re.search(r'^(?P<timestamp>[^\s.]+)(\.\d+)? (?P<job_uuid>\S+) \d+ (?P<seq>\d+) stderr (?P<crunchstat>crunchstat: )(?P<category>\S+) (?P<current>.*?)( -- interval (?P<interval>.*))?\n$', line)
 119                 if not m:
 120                     continue
 121             else:
 122                 # crunch2
 123                 # 2017-12-01T16:56:24.723509200Z crunchstat: keepcalls 0 put 3 get -- interval 10.0000 seconds 0 put 3 get
 124                 m = re.search(r'^(?P<timestamp>\S+) (?P<crunchstat>crunchstat: )?(?P<category>\S+) (?P<current>.*?)( -- interval (?P<interval>.*))?\n$', line)
 125                 if not m:
 126                     continue
 127
 128             if self.label is None:
 129                 try:
 130                     self.label = m.group('job_uuid')
 131                 except IndexError:
 132                     self.label = 'container'
 133             if m.group('category').endswith(':'):
 134                 # "stderr crunchstat: notice: ..."
 135                 continue
 136             elif m.group('category') in ('error', 'caught'):
 137                 continue
 138             elif m.group('category') in ('read', 'open', 'cgroup', 'CID', 'Running'):
 139                 # "stderr crunchstat: read /proc/1234/net/dev: ..."
 140                 # (old logs are less careful with unprefixed error messages)
 141                 continue
 142
 143             if self.detected_crunch1:
 144                 task_id = self.seq_to_uuid[int(m.group('seq'))]
 145             else:
 146                 task_id = 'container'
 147             task = self.tasks[task_id]
 148
 149             # Use the first and last crunchstat timestamps as
 150             # approximations of starttime and finishtime.
 151             timestamp = m.group('timestamp')
 152             if timestamp[10:11] == '_':
 153                 timestamp = datetime.datetime.strptime(
 154                     timestamp, '%Y-%m-%d_%H:%M:%S')
 155             elif timestamp[10:11] == 'T':
 156                 timestamp = datetime.datetime.strptime(
 157                     timestamp[:19], '%Y-%m-%dT%H:%M:%S')
 158             else:
 159                 raise ValueError("Cannot parse timestamp {!r}".format(
 160                     timestamp))
 161
 162             if task.starttime is None:
 163                 logger.debug('%s: task %s starttime %s',
 164                              self.label, task_id, timestamp)
 165             if task.starttime is None or timestamp < task.starttime:
 166                 task.starttime = timestamp
 167             if task.finishtime is None or timestamp > task.finishtime:
 168                 task.finishtime = timestamp
 169
 170             if self.starttime is None or timestamp < task.starttime:
 171                 self.starttime = timestamp
 172             if self.finishtime is None or timestamp < task.finishtime:
 173                 self.finishtime = timestamp
 174
 175             if (not self.detected_crunch1) and task.starttime is not None and task.finishtime is not None:
 176                 elapsed = (task.finishtime - task.starttime).seconds
 177                 self.task_stats[task_id]['time'] = {'elapsed': elapsed}
 178                 if elapsed > self.stats_max['time']['elapsed']:
 179                     self.stats_max['time']['elapsed'] = elapsed
 180
 181             this_interval_s = None
 182             for group in ['current', 'interval']:
 183                 if not m.group(group):
 184                     continue
 185                 category = m.group('category')
 186                 words = m.group(group).split(' ')
 187                 stats = {}
 188                 try:
 189                     for val, stat in zip(words[::2], words[1::2]):
 190                         if '.' in val:
 191                             stats[stat] = float(val)
 192                         else:
 193                             stats[stat] = int(val)
 194                 except ValueError as e:
 195                     # If the line doesn't start with 'crunchstat:' we
 196                     # might have mistaken an error message for a
 197                     # structured crunchstat line.
 198                     if m.group("crunchstat") is None or m.group("category") == "crunchstat":
 199                         logger.warning("%s: log contains message\n  %s", self.label, line)
 200                     else:
 201                         logger.warning(
 202                             '%s: Error parsing value %r (stat %r, category %r): %r',
 203                             self.label, val, stat, category, e)
 204                         logger.warning('%s', line)
 205                     continue
 206                 if 'user' in stats or 'sys' in stats:
 207                     stats['user+sys'] = stats.get('user', 0) + stats.get('sys', 0)
 208                 if 'tx' in stats or 'rx' in stats:
 209                     stats['tx+rx'] = stats.get('tx', 0) + stats.get('rx', 0)
 210                 for stat, val in stats.items():
 211                     if group == 'interval':
 212                         if stat == 'seconds':
 213                             this_interval_s = val
 214                             continue
 215                         elif not (this_interval_s > 0):
 216                             logger.error(
 217                                 "BUG? interval stat given with duration {!r}".
 218                                 format(this_interval_s))
 219                             continue
 220                         else:
 221                             stat = stat + '__rate'
 222                             val = val / this_interval_s
 223                             if stat in ['user+sys__rate', 'tx+rx__rate']:
 224                                 task.series[category, stat].append(
 225                                     (timestamp - self.starttime, val))
 226                     else:
 227                         if stat in ['rss']:
 228                             task.series[category, stat].append(
 229                                 (timestamp - self.starttime, val))
 230                         self.task_stats[task_id][category][stat] = val
 231                     if val > self.stats_max[category][stat]:
 232                         self.stats_max[category][stat] = val
 233         logger.debug('%s: done parsing', self.label)
 234
 235         self.job_tot = collections.defaultdict(
 236             functools.partial(collections.defaultdict, int))
 237         for task_id, task_stat in self.task_stats.items():
 238             for category, stat_last in task_stat.items():
 239                 for stat, val in stat_last.items():
 240                     if stat in ['cpus', 'cache', 'swap', 'rss']:
 241                         # meaningless stats like 16 cpu cores x 5 tasks = 80
 242                         continue
 243                     self.job_tot[category][stat] += val
 244         logger.debug('%s: done totals', self.label)
 245
 246     def long_label(self):
 247         label = self.label
 248         if hasattr(self, 'process') and self.process['uuid'] not in label:
 249             label = '{} ({})'.format(label, self.process['uuid'])
 250         if self.finishtime:
 251             label += ' -- elapsed time '
 252             s = (self.finishtime - self.starttime).total_seconds()
 253             if s > 86400:
 254                 label += '{}d'.format(int(s/86400))
 255             if s > 3600:
 256                 label += '{}h'.format(int(s/3600) % 24)
 257             if s > 60:
 258                 label += '{}m'.format(int(s/60) % 60)
 259             label += '{}s'.format(int(s) % 60)
 260         return label
 261
 262     def text_report(self):
 263         if not self.tasks:
 264             return "(no report generated)\n"
 265         return "\n".join(itertools.chain(
 266             self._text_report_gen(),
 267             self._recommend_gen())) + "\n"
 268
 269     def html_report(self):
 270         return WEBCHART_CLASS(self.label, [self]).html()
 271
 272     def _text_report_gen(self):
 273         yield "\t".join(['category', 'metric', 'task_max', 'task_max_rate', 'job_total'])
 274         for category, stat_max in sorted(self.stats_max.items()):
 275             for stat, val in sorted(stat_max.items()):
 276                 if stat.endswith('__rate'):
 277                     continue
 278                 max_rate = self._format(stat_max.get(stat+'__rate', '-'))
 279                 val = self._format(val)
 280                 tot = self._format(self.job_tot[category].get(stat, '-'))
 281                 yield "\t".join([category, stat, str(val), max_rate, tot])
 282         for args in (
 283                 ('Number of tasks: {}',
 284                  len(self.tasks),
 285                  None),
 286                 ('Max CPU time spent by a single task: {}s',
 287                  self.stats_max['cpu']['user+sys'],
 288                  None),
 289                 ('Max CPU usage in a single interval: {}%',
 290                  self.stats_max['cpu']['user+sys__rate'],
 291                  lambda x: x * 100),
 292                 ('Overall CPU usage: {}%',
 293                  float(self.job_tot['cpu']['user+sys']) /
 294                  self.job_tot['time']['elapsed']
 295                  if self.job_tot['time']['elapsed'] > 0 else 0,
 296                  lambda x: x * 100),
 297                 ('Max memory used by a single task: {}GB',
 298                  self.stats_max['mem']['rss'],
 299                  lambda x: x / 1e9),
 300                 ('Max network traffic in a single task: {}GB',
 301                  self.stats_max['net:eth0']['tx+rx'] +
 302                  self.stats_max['net:keep0']['tx+rx'],
 303                  lambda x: x / 1e9),
 304                 ('Max network speed in a single interval: {}MB/s',
 305                  self.stats_max['net:eth0']['tx+rx__rate'] +
 306                  self.stats_max['net:keep0']['tx+rx__rate'],
 307                  lambda x: x / 1e6),
 308                 ('Keep cache miss rate {}%',
 309                  (float(self.job_tot['keepcache']['miss']) /
 310                  float(self.job_tot['keepcalls']['get']))
 311                  if self.job_tot['keepcalls']['get'] > 0 else 0,
 312                  lambda x: x * 100.0),
 313                 ('Keep cache utilization {}%',
 314                  (float(self.job_tot['blkio:0:0']['read']) /
 315                  float(self.job_tot['net:keep0']['rx']))
 316                  if self.job_tot['net:keep0']['rx'] > 0 else 0,
 317                  lambda x: x * 100.0)):
 318             format_string, val, transform = args
 319             if val == float('-Inf'):
 320                 continue
 321             if transform:
 322                 val = transform(val)
 323             yield "# "+format_string.format(self._format(val))
 324
 325     def _recommend_gen(self):
 326         return itertools.chain(
 327             self._recommend_cpu(),
 328             self._recommend_ram(),
 329             self._recommend_keep_cache())
 330
 331     def _recommend_cpu(self):
 332         """Recommend asking for 4 cores if max CPU usage was 333%"""
 333
 334         constraint_key = self._map_runtime_constraint('vcpus')
 335         cpu_max_rate = self.stats_max['cpu']['user+sys__rate']
 336         if cpu_max_rate == float('-Inf'):
 337             logger.warning('%s: no CPU usage data', self.label)
 338             return
 339         used_cores = max(1, int(math.ceil(cpu_max_rate)))
 340         asked_cores = self.existing_constraints.get(constraint_key)
 341         if asked_cores is None or used_cores < asked_cores:
 342             yield (
 343                 '#!! {} max CPU usage was {}% -- '
 344                 'try runtime_constraints "{}":{}'
 345             ).format(
 346                 self.label,
 347                 math.ceil(cpu_max_rate*100),
 348                 constraint_key,
 349                 int(used_cores))
 350
 351     def _recommend_ram(self):
 352         """Recommend an economical RAM constraint for this job.
 353
 354         Nodes that are advertised as "8 gibibytes" actually have what
 355         we might call "8 nearlygibs" of memory available for jobs.
 356         Here, we calculate a whole number of nearlygibs that would
 357         have sufficed to run the job, then recommend requesting a node
 358         with that number of nearlygibs (expressed as mebibytes).
 359
 360         Requesting a node with "nearly 8 gibibytes" is our best hope
 361         of getting a node that actually has nearly 8 gibibytes
 362         available.  If the node manager is smart enough to account for
 363         the discrepancy itself when choosing/creating a node, we'll
 364         get an 8 GiB node with nearly 8 GiB available.  Otherwise, the
 365         advertised size of the next-size-smaller node (say, 6 GiB)
 366         will be too low to satisfy our request, so we will effectively
 367         get rounded up to 8 GiB.
 368
 369         For example, if we need 7500 MiB, we can ask for 7500 MiB, and
 370         we will generally get a node that is advertised as "8 GiB" and
 371         has at least 7500 MiB available.  However, asking for 8192 MiB
 372         would either result in an unnecessarily expensive 12 GiB node
 373         (if node manager knows about the discrepancy), or an 8 GiB
 374         node which has less than 8192 MiB available and is therefore
 375         considered by crunch-dispatch to be too small to meet our
 376         constraint.
 377
 378         When node manager learns how to predict the available memory
 379         for each node type such that crunch-dispatch always agrees
 380         that a node is big enough to run the job it was brought up
 381         for, all this will be unnecessary.  We'll just ask for exactly
 382         the memory we want -- even if that happens to be 8192 MiB.
 383         """
 384
 385         constraint_key = self._map_runtime_constraint('ram')
 386         used_bytes = self.stats_max['mem']['rss']
 387         if used_bytes == float('-Inf'):
 388             logger.warning('%s: no memory usage data', self.label)
 389             return
 390         used_mib = math.ceil(float(used_bytes) / MB)
 391         asked_mib = self.existing_constraints.get(constraint_key)
 392
 393         nearlygibs = lambda mebibytes: mebibytes/AVAILABLE_RAM_RATIO/1024
 394         if asked_mib is None or (
 395                 math.ceil(nearlygibs(used_mib)) < nearlygibs(asked_mib)):
 396             yield (
 397                 '#!! {} max RSS was {} MiB -- '
 398                 'try runtime_constraints "{}":{}'
 399             ).format(
 400                 self.label,
 401                 int(used_mib),
 402                 constraint_key,
 403                 int(math.ceil(nearlygibs(used_mib))*AVAILABLE_RAM_RATIO*1024*(MB)/self._runtime_constraint_mem_unit()))
 404
 405     def _recommend_keep_cache(self):
 406         """Recommend increasing keep cache if utilization < 80%"""
 407         constraint_key = self._map_runtime_constraint('keep_cache_ram')
 408         if self.job_tot['net:keep0']['rx'] == 0:
 409             return
 410         utilization = (float(self.job_tot['blkio:0:0']['read']) /
 411                        float(self.job_tot['net:keep0']['rx']))
 412         # FIXME: the default on this get won't work correctly
 413         asked_cache = self.existing_constraints.get(constraint_key, 256) * self._runtime_constraint_mem_unit()
 414
 415         if utilization < 0.8:
 416             yield (
 417                 '#!! {} Keep cache utilization was {:.2f}% -- '
 418                 'try runtime_constraints "{}":{} (or more)'
 419             ).format(
 420                 self.label,
 421                 utilization * 100.0,
 422                 constraint_key,
 423                 math.ceil(asked_cache * 2 / self._runtime_constraint_mem_unit()))
 424
 425
 426     def _format(self, val):
 427         """Return a string representation of a stat.
 428
 429         {:.2f} for floats, default format for everything else."""
 430         if isinstance(val, float):
 431             return '{:.2f}'.format(val)
 432         else:
 433             return '{}'.format(val)
 434
 435     def _runtime_constraint_mem_unit(self):
 436         if hasattr(self, 'runtime_constraint_mem_unit'):
 437             return self.runtime_constraint_mem_unit
 438         elif self.detected_crunch1:
 439             return JobSummarizer.runtime_constraint_mem_unit
 440         else:
 441             return ContainerSummarizer.runtime_constraint_mem_unit
 442
 443     def _map_runtime_constraint(self, key):
 444         if hasattr(self, 'map_runtime_constraint'):
 445             return self.map_runtime_constraint[key]
 446         elif self.detected_crunch1:
 447             return JobSummarizer.map_runtime_constraint[key]
 448         else:
 449             return key
 450
 451
 452 class CollectionSummarizer(Summarizer):
 453     def __init__(self, collection_id, **kwargs):
 454         super(CollectionSummarizer, self).__init__(
 455             crunchstat_summary.reader.CollectionReader(collection_id), **kwargs)
 456         self.label = collection_id
 457
 458
 459 def NewSummarizer(process_or_uuid, **kwargs):
 460     """Construct with the appropriate subclass for this uuid/object."""
 461
 462     if isinstance(process_or_uuid, dict):
 463         process = process_or_uuid
 464         uuid = process['uuid']
 465     else:
 466         uuid = process_or_uuid
 467         process = None
 468         arv = arvados.api('v1', model=OrderedJsonModel())
 469
 470     if '-dz642-' in uuid:
 471         if process is None:
 472             process = arv.containers().get(uuid=uuid).execute()
 473         klass = ContainerTreeSummarizer
 474     elif '-xvhdp-' in uuid:
 475         if process is None:
 476             process = arv.container_requests().get(uuid=uuid).execute()
 477         klass = ContainerTreeSummarizer
 478     elif '-8i9sb-' in uuid:
 479         if process is None:
 480             process = arv.jobs().get(uuid=uuid).execute()
 481         klass = JobTreeSummarizer
 482     elif '-d1hrv-' in uuid:
 483         if process is None:
 484             process = arv.pipeline_instances().get(uuid=uuid).execute()
 485         klass = PipelineSummarizer
 486     elif '-4zz18-' in uuid:
 487         return CollectionSummarizer(collection_id=uuid)
 488     else:
 489         raise ArgumentError("Unrecognized uuid %s", uuid)
 490     return klass(process, uuid=uuid, **kwargs)
 491
 492
 493 class ProcessSummarizer(Summarizer):
 494     """Process is a job, pipeline, container, or container request."""
 495
 496     def __init__(self, process, label=None, **kwargs):
 497         rdr = None
 498         self.process = process
 499         if label is None:
 500             label = self.process.get('name', self.process['uuid'])
 501         if self.process.get('log'):
 502             try:
 503                 rdr = crunchstat_summary.reader.CollectionReader(self.process['log'])
 504             except arvados.errors.NotFoundError as e:
 505                 logger.warning("Trying event logs after failing to read "
 506                                "log collection %s: %s", self.process['log'], e)
 507         if rdr is None:
 508             rdr = crunchstat_summary.reader.LiveLogReader(self.process['uuid'])
 509             label = label + ' (partial)'
 510         super(ProcessSummarizer, self).__init__(rdr, label=label, **kwargs)
 511         self.existing_constraints = self.process.get('runtime_constraints', {})
 512
 513
 514 class JobSummarizer(ProcessSummarizer):
 515     runtime_constraint_mem_unit = MB
 516     map_runtime_constraint = {
 517         'keep_cache_ram': 'keep_cache_mb_per_task',
 518         'ram': 'min_ram_mb_per_node',
 519         'vcpus': 'min_cores_per_node',
 520     }
 521
 522
 523 class ContainerSummarizer(ProcessSummarizer):
 524     runtime_constraint_mem_unit = 1
 525
 526
 527 class MultiSummarizer(object):
 528     def __init__(self, children={}, label=None, threads=1, **kwargs):
 529         self.throttle = threading.Semaphore(threads)
 530         self.children = children
 531         self.label = label
 532
 533     def run_and_release(self, target, *args, **kwargs):
 534         try:
 535             return target(*args, **kwargs)
 536         finally:
 537             self.throttle.release()
 538
 539     def run(self):
 540         threads = []
 541         for child in self.children.values():
 542             self.throttle.acquire()
 543             t = threading.Thread(target=self.run_and_release, args=(child.run, ))
 544             t.daemon = True
 545             t.start()
 546             threads.append(t)
 547         for t in threads:
 548             t.join()
 549
 550     def text_report(self):
 551         txt = ''
 552         d = self._descendants()
 553         for child in d.values():
 554             if len(d) > 1:
 555                 txt += '### Summary for {} ({})\n'.format(
 556                     child.label, child.process['uuid'])
 557             txt += child.text_report()
 558             txt += '\n'
 559         return txt
 560
 561     def _descendants(self):
 562         """Dict of self and all descendants.
 563
 564         Nodes with nothing of their own to report (like
 565         MultiSummarizers) are omitted.
 566         """
 567         d = collections.OrderedDict()
 568         for key, child in self.children.items():
 569             if isinstance(child, Summarizer):
 570                 d[key] = child
 571             if isinstance(child, MultiSummarizer):
 572                 d.update(child._descendants())
 573         return d
 574
 575     def html_report(self):
 576         return WEBCHART_CLASS(self.label, iter(self._descendants().values())).html()
 577
 578
 579 class JobTreeSummarizer(MultiSummarizer):
 580     """Summarizes a job and all children listed in its components field."""
 581     def __init__(self, job, label=None, **kwargs):
 582         arv = arvados.api('v1', model=OrderedJsonModel())
 583         label = label or job.get('name', job['uuid'])
 584         children = collections.OrderedDict()
 585         children[job['uuid']] = JobSummarizer(job, label=label, **kwargs)
 586         if job.get('components', None):
 587             preloaded = {}
 588             for j in arv.jobs().index(
 589                     limit=len(job['components']),
 590                     filters=[['uuid','in',list(job['components'].values())]]).execute()['items']:
 591                 preloaded[j['uuid']] = j
 592             for cname in sorted(job['components'].keys()):
 593                 child_uuid = job['components'][cname]
 594                 j = (preloaded.get(child_uuid) or
 595                      arv.jobs().get(uuid=child_uuid).execute())
 596                 children[child_uuid] = JobTreeSummarizer(job=j, label=cname, **kwargs)
 597
 598         super(JobTreeSummarizer, self).__init__(
 599             children=children,
 600             label=label,
 601             **kwargs)
 602
 603
 604 class PipelineSummarizer(MultiSummarizer):
 605     def __init__(self, instance, **kwargs):
 606         children = collections.OrderedDict()
 607         for cname, component in instance['components'].items():
 608             if 'job' not in component:
 609                 logger.warning(
 610                     "%s: skipping component with no job assigned", cname)
 611             else:
 612                 logger.info(
 613                     "%s: job %s", cname, component['job']['uuid'])
 614                 summarizer = JobTreeSummarizer(component['job'], label=cname, **kwargs)
 615                 summarizer.label = '{} {}'.format(
 616                     cname, component['job']['uuid'])
 617                 children[cname] = summarizer
 618         super(PipelineSummarizer, self).__init__(
 619             children=children,
 620             label=instance['uuid'],
 621             **kwargs)
 622
 623
 624 class ContainerTreeSummarizer(MultiSummarizer):
 625     def __init__(self, root, skip_child_jobs=False, **kwargs):
 626         arv = arvados.api('v1', model=OrderedJsonModel())
 627
 628         label = kwargs.pop('label', None) or root.get('name') or root['uuid']
 629         root['name'] = label
 630
 631         children = collections.OrderedDict()
 632         todo = collections.deque((root, ))
 633         while len(todo) > 0:
 634             current = todo.popleft()
 635             label = current['name']
 636             sort_key = current['created_at']
 637             if current['uuid'].find('-xvhdp-') > 0:
 638                 current = arv.containers().get(uuid=current['container_uuid']).execute()
 639
 640             summer = ContainerSummarizer(current, label=label, **kwargs)
 641             summer.sort_key = sort_key
 642             children[current['uuid']] = summer
 643
 644             page_filters = []
 645             while True:
 646                 child_crs = arv.container_requests().index(
 647                     order=['uuid asc'],
 648                     filters=page_filters+[
 649                         ['requesting_container_uuid', '=', current['uuid']]],
 650                 ).execute()
 651                 if not child_crs['items']:
 652                     break
 653                 elif skip_child_jobs:
 654                     logger.warning('%s: omitting stats from %d child containers'
 655                                    ' because --skip-child-jobs flag is on',
 656                                    label, child_crs['items_available'])
 657                     break
 658                 page_filters = [['uuid', '>', child_crs['items'][-1]['uuid']]]
 659                 for cr in child_crs['items']:
 660                     if cr['container_uuid']:
 661                         logger.debug('%s: container req %s', current['uuid'], cr['uuid'])
 662                         cr['name'] = cr.get('name') or cr['uuid']
 663                         todo.append(cr)
 664         sorted_children = collections.OrderedDict()
 665         for uuid in sorted(list(children.keys()), key=lambda uuid: children[uuid].sort_key):
 666             sorted_children[uuid] = children[uuid]
 667         super(ContainerTreeSummarizer, self).__init__(
 668             children=sorted_children,
 669             label=root['name'],
 670             **kwargs)