#
# SPDX-License-Identifier: AGPL-3.0
-from __future__ import print_function
-
import arvados
import collections
import crunchstat_summary.dygraphs
import threading
import _strptime
-from arvados.api import OrderedJsonModel
from crunchstat_summary import logger
# Recommend memory constraints that are this multiple of an integral
# number of GiB. (Actual nodes tend to be sold in sizes like 8 GiB
# that have amounts like 7.5 GiB according to the kernel.)
-AVAILABLE_RAM_RATIO = 0.95
-
+AVAILABLE_RAM_RATIO = 0.90
+MB=2**20
# Workaround datetime.datetime.strptime() thread-safety bug by calling
# it once before starting threads. https://bugs.python.org/issue7980
class Task(object):
def __init__(self):
self.starttime = None
+ self.finishtime = None
self.series = collections.defaultdict(list)
self.label, uuid)
continue
logger.debug('%s: follow %s', self.label, uuid)
- child_summarizer = ProcessSummarizer(uuid)
+ child_summarizer = NewSummarizer(uuid)
child_summarizer.stats_max = self.stats_max
child_summarizer.task_stats = self.task_stats
child_summarizer.tasks = self.tasks
logger.debug('%s: done %s', self.label, uuid)
continue
- m = re.search(r'^(?P<timestamp>[^\s.]+)(\.\d+)? (?P<job_uuid>\S+) \d+ (?P<seq>\d+) stderr crunchstat: (?P<category>\S+) (?P<current>.*?)( -- interval (?P<interval>.*))?\n$', line)
+ # 2017-12-02_17:15:08 e51c5-8i9sb-mfp68stkxnqdd6m 63676 0 stderr crunchstat: keepcalls 0 put 2576 get -- interval 10.0000 seconds 0 put 2576 get
+ m = re.search(r'^(?P<timestamp>[^\s.]+)(\.\d+)? (?P<job_uuid>\S+) \d+ (?P<seq>\d+) stderr (?P<crunchstat>crunchstat: )(?P<category>\S+) (?P<current>.*?)( -- interval (?P<interval>.*))?\n$', line)
if not m:
continue
else:
# crunch2
- m = re.search(r'^(?P<timestamp>\S+) (?P<category>\S+) (?P<current>.*?)( -- interval (?P<interval>.*))?\n$', line)
+ # 2017-12-01T16:56:24.723509200Z crunchstat: keepcalls 0 put 3 get -- interval 10.0000 seconds 0 put 3 get
+ m = re.search(r'^(?P<timestamp>\S+) (?P<crunchstat>crunchstat: )?(?P<category>\S+) (?P<current>.*?)( -- interval (?P<interval>.*))?\n$', line)
if not m:
continue
try:
self.label = m.group('job_uuid')
except IndexError:
- self.label = 'container'
- if m.group('category').endswith(':'):
+ self.label = 'label #1'
+ category = m.group('category')
+ if category.endswith(':'):
# "stderr crunchstat: notice: ..."
continue
- elif m.group('category') in ('error', 'caught'):
+ elif category in ('error', 'caught'):
continue
- elif m.group('category') in ('read', 'open', 'cgroup', 'CID', 'Running'):
+ elif category in ('read', 'open', 'cgroup', 'CID', 'Running'):
# "stderr crunchstat: read /proc/1234/net/dev: ..."
# (old logs are less careful with unprefixed error messages)
continue
raise ValueError("Cannot parse timestamp {!r}".format(
timestamp))
- if not task.starttime:
- task.starttime = timestamp
+ if task.starttime is None:
logger.debug('%s: task %s starttime %s',
self.label, task_id, timestamp)
- task.finishtime = timestamp
+ if task.starttime is None or timestamp < task.starttime:
+ task.starttime = timestamp
+ if task.finishtime is None or timestamp > task.finishtime:
+ task.finishtime = timestamp
- if not self.starttime:
+ if self.starttime is None or timestamp < self.starttime:
self.starttime = timestamp
- self.finishtime = timestamp
+ if self.finishtime is None or timestamp > self.finishtime:
+ self.finishtime = timestamp
+
+ if (not self.detected_crunch1) and task.starttime is not None and task.finishtime is not None:
+ elapsed = (task.finishtime - task.starttime).seconds
+ self.task_stats[task_id]['time'] = {'elapsed': elapsed}
+ if elapsed > self.stats_max['time']['elapsed']:
+ self.stats_max['time']['elapsed'] = elapsed
this_interval_s = None
for group in ['current', 'interval']:
else:
stats[stat] = int(val)
except ValueError as e:
- logger.warning(
- 'Error parsing value %r (stat %r, category %r): %r',
- val, stat, category, e)
- logger.warning('%s', line)
+ # If the line doesn't start with 'crunchstat:' we
+ # might have mistaken an error message for a
+ # structured crunchstat line.
+ if m.group("crunchstat") is None or m.group("category") == "crunchstat":
+ logger.warning("%s: log contains message\n %s", self.label, line)
+ else:
+ logger.warning(
+ '%s: Error parsing value %r (stat %r, category %r): %r',
+ self.label, val, stat, category, e)
+ logger.warning('%s', line)
continue
if 'user' in stats or 'sys' in stats:
stats['user+sys'] = stats.get('user', 0) + stats.get('sys', 0)
if 'tx' in stats or 'rx' in stats:
stats['tx+rx'] = stats.get('tx', 0) + stats.get('rx', 0)
- for stat, val in stats.iteritems():
- if group == 'interval':
- if stat == 'seconds':
- this_interval_s = val
- continue
- elif not (this_interval_s > 0):
+ if group == 'interval':
+ if 'seconds' in stats:
+ this_interval_s = stats.get('seconds',0)
+ del stats['seconds']
+ if this_interval_s <= 0:
logger.error(
"BUG? interval stat given with duration {!r}".
format(this_interval_s))
- continue
- else:
+ else:
+ logger.error('BUG? interval stat missing duration')
+ for stat, val in stats.items():
+ if group == 'interval' and this_interval_s:
stat = stat + '__rate'
val = val / this_interval_s
- if stat in ['user+sys__rate', 'tx+rx__rate']:
+ if stat in ['user+sys__rate', 'user__rate', 'sys__rate', 'tx+rx__rate', 'rx__rate', 'tx__rate']:
task.series[category, stat].append(
(timestamp - self.starttime, val))
else:
- if stat in ['rss']:
+ if stat in ['rss','used','total']:
task.series[category, stat].append(
(timestamp - self.starttime, val))
self.task_stats[task_id][category][stat] = val
self.job_tot = collections.defaultdict(
functools.partial(collections.defaultdict, int))
- for task_id, task_stat in self.task_stats.iteritems():
- for category, stat_last in task_stat.iteritems():
- for stat, val in stat_last.iteritems():
+ for task_id, task_stat in self.task_stats.items():
+ for category, stat_last in task_stat.items():
+ for stat, val in stat_last.items():
if stat in ['cpus', 'cache', 'swap', 'rss']:
# meaningless stats like 16 cpu cores x 5 tasks = 80
continue
self.job_tot[category][stat] += val
logger.debug('%s: done totals', self.label)
+ missing_category = {
+ 'cpu': 'CPU',
+ 'mem': 'memory',
+ 'net:': 'network I/O',
+ 'statfs': 'storage space',
+ }
+ for task_stat in self.task_stats.values():
+ for category in task_stat.keys():
+ for checkcat in missing_category:
+ if checkcat.endswith(':'):
+ if category.startswith(checkcat):
+ missing_category.pop(checkcat)
+ break
+ else:
+ if category == checkcat:
+ missing_category.pop(checkcat)
+ break
+ for catlabel in missing_category.values():
+ logger.warning('%s: %s stats are missing -- possible cluster configuration issue',
+ self.label, catlabel)
+
def long_label(self):
label = self.label
if hasattr(self, 'process') and self.process['uuid'] not in label:
label = '{} ({})'.format(label, self.process['uuid'])
- if self.finishtime:
- label += ' -- elapsed time '
- s = (self.finishtime - self.starttime).total_seconds()
- if s > 86400:
- label += '{}d'.format(int(s/86400))
- if s > 3600:
- label += '{}h'.format(int(s/3600) % 24)
- if s > 60:
- label += '{}m'.format(int(s/60) % 60)
- label += '{}s'.format(int(s) % 60)
+ return label
+
+ def elapsed_time(self):
+ if not self.finishtime:
+ return ""
+ label = ""
+ s = (self.finishtime - self.starttime).total_seconds()
+ if s > 86400:
+ label += '{}d'.format(int(s/86400))
+ if s > 3600:
+ label += '{}h'.format(int(s/3600) % 24)
+ if s > 60:
+ label += '{}m'.format(int(s/60) % 60)
+ label += '{}s'.format(int(s) % 60)
return label
def text_report(self):
if not self.tasks:
return "(no report generated)\n"
return "\n".join(itertools.chain(
- self._text_report_gen(),
- self._recommend_gen())) + "\n"
+ self._text_report_table_gen(lambda x: "\t".join(x),
+ lambda x: "\t".join(x)),
+ self._text_report_agg_gen(lambda x: "# {}: {}{}".format(x[0], x[1], x[2])),
+ self._recommend_gen(lambda x: "#!! "+x))) + "\n"
def html_report(self):
return WEBCHART_CLASS(self.label, [self]).html()
- def _text_report_gen(self):
- yield "\t".join(['category', 'metric', 'task_max', 'task_max_rate', 'job_total'])
- for category, stat_max in sorted(self.stats_max.iteritems()):
- for stat, val in sorted(stat_max.iteritems()):
+ def _text_report_table_gen(self, headerformat, rowformat):
+ yield headerformat(['category', 'metric', 'task_max', 'task_max_rate', 'job_total'])
+ for category, stat_max in sorted(self.stats_max.items()):
+ for stat, val in sorted(stat_max.items()):
if stat.endswith('__rate'):
continue
max_rate = self._format(stat_max.get(stat+'__rate', '-'))
val = self._format(val)
tot = self._format(self.job_tot[category].get(stat, '-'))
- yield "\t".join([category, stat, str(val), max_rate, tot])
- for args in (
- ('Number of tasks: {}',
- len(self.tasks),
- None),
- ('Max CPU time spent by a single task: {}s',
+ yield rowformat([category, stat, str(val), max_rate, tot])
+
+ def _text_report_agg_gen(self, aggformat):
+ by_single_task = ""
+ if len(self.tasks) > 1:
+ by_single_task = " by a single task"
+ metrics = [
+ ('Elapsed time',
+ self.elapsed_time(),
+ None,
+ ''),
+ ('Max CPU time spent{}'.format(by_single_task),
self.stats_max['cpu']['user+sys'],
- None),
- ('Max CPU usage in a single interval: {}%',
+ None,
+ 's'),
+ ('Max CPU usage in a single interval',
self.stats_max['cpu']['user+sys__rate'],
- lambda x: x * 100),
- ('Overall CPU usage: {}%',
- self.job_tot['cpu']['user+sys'] /
+ lambda x: x * 100,
+ '%'),
+ ('Overall CPU usage',
+ float(self.job_tot['cpu']['user+sys']) /
self.job_tot['time']['elapsed']
if self.job_tot['time']['elapsed'] > 0 else 0,
- lambda x: x * 100),
- ('Max memory used by a single task: {}GB',
+ lambda x: x * 100,
+ '%'),
+ ('Max memory used{}'.format(by_single_task),
self.stats_max['mem']['rss'],
- lambda x: x / 1e9),
- ('Max network traffic in a single task: {}GB',
+ lambda x: x / 1e9,
+ 'GB'),
+ ('Max network traffic{}'.format(by_single_task),
self.stats_max['net:eth0']['tx+rx'] +
self.stats_max['net:keep0']['tx+rx'],
- lambda x: x / 1e9),
- ('Max network speed in a single interval: {}MB/s',
+ lambda x: x / 1e9,
+ 'GB'),
+ ('Max network speed in a single interval',
self.stats_max['net:eth0']['tx+rx__rate'] +
self.stats_max['net:keep0']['tx+rx__rate'],
- lambda x: x / 1e6),
- ('Keep cache miss rate {}%',
+ lambda x: x / 1e6,
+ 'MB/s'),
+ ('Keep cache miss rate',
(float(self.job_tot['keepcache']['miss']) /
float(self.job_tot['keepcalls']['get']))
if self.job_tot['keepcalls']['get'] > 0 else 0,
- lambda x: x * 100.0),
- ('Keep cache utilization {}%',
+ lambda x: x * 100.0,
+ '%'),
+ ('Keep cache utilization',
(float(self.job_tot['blkio:0:0']['read']) /
float(self.job_tot['net:keep0']['rx']))
if self.job_tot['net:keep0']['rx'] > 0 else 0,
- lambda x: x * 100.0)):
- format_string, val, transform = args
+ lambda x: x * 100.0,
+ '%'),
+ ('Temp disk utilization',
+ (float(self.job_tot['statfs']['used']) /
+ float(self.job_tot['statfs']['total']))
+ if self.job_tot['statfs']['total'] > 0 else 0,
+ lambda x: x * 100.0,
+ '%'),
+ ]
+
+ if len(self.tasks) > 1:
+ metrics.insert(0, ('Number of tasks',
+ len(self.tasks),
+ None,
+ ''))
+ for args in metrics:
+ format_string, val, transform, suffix = args
if val == float('-Inf'):
continue
if transform:
val = transform(val)
- yield "# "+format_string.format(self._format(val))
+ yield aggformat((format_string, self._format(val), suffix))
- def _recommend_gen(self):
+ def _recommend_gen(self, recommendformat):
+ # TODO recommend fixing job granularity if elapsed time is too short
return itertools.chain(
- self._recommend_cpu(),
- self._recommend_ram(),
- self._recommend_keep_cache())
+ self._recommend_cpu(recommendformat),
+ self._recommend_ram(recommendformat),
+ self._recommend_keep_cache(recommendformat),
+ self._recommend_temp_disk(recommendformat),
+ )
- def _recommend_cpu(self):
+ def _recommend_cpu(self, recommendformat):
"""Recommend asking for 4 cores if max CPU usage was 333%"""
constraint_key = self._map_runtime_constraint('vcpus')
cpu_max_rate = self.stats_max['cpu']['user+sys__rate']
- if cpu_max_rate == float('-Inf'):
+ if cpu_max_rate == float('-Inf') or cpu_max_rate == 0.0:
logger.warning('%s: no CPU usage data', self.label)
return
+ # TODO Don't necessarily want to recommend on isolated max peak
+ # take average CPU usage into account as well or % time at max
used_cores = max(1, int(math.ceil(cpu_max_rate)))
asked_cores = self.existing_constraints.get(constraint_key)
- if asked_cores is None or used_cores < asked_cores:
- yield (
- '#!! {} max CPU usage was {}% -- '
- 'try runtime_constraints "{}":{}'
+ if asked_cores is None:
+ asked_cores = 1
+ # TODO: This should be more nuanced in cases where max >> avg
+ if used_cores < asked_cores:
+ yield recommendformat(
+ '{} max CPU usage was {}% -- '
+ 'try reducing runtime_constraints to "{}":{}'
).format(
self.label,
- int(math.ceil(cpu_max_rate*100)),
+ math.ceil(cpu_max_rate*100),
constraint_key,
int(used_cores))
- def _recommend_ram(self):
+ # FIXME: This needs to be updated to account for current a-d-c algorithms
+ def _recommend_ram(self, recommendformat):
"""Recommend an economical RAM constraint for this job.
Nodes that are advertised as "8 gibibytes" actually have what
if used_bytes == float('-Inf'):
logger.warning('%s: no memory usage data', self.label)
return
- used_mib = math.ceil(float(used_bytes) / 1048576)
- asked_mib = self.existing_constraints.get(constraint_key)
+ used_mib = math.ceil(float(used_bytes) / MB)
+ asked_mib = self.existing_constraints.get(constraint_key) / MB
nearlygibs = lambda mebibytes: mebibytes/AVAILABLE_RAM_RATIO/1024
- if asked_mib is None or (
- math.ceil(nearlygibs(used_mib)) < nearlygibs(asked_mib)):
- yield (
- '#!! {} max RSS was {} MiB -- '
- 'try runtime_constraints "{}":{}'
+ ratio = 0.5
+ recommend_mib = int(math.ceil(nearlygibs(used_mib/ratio))*AVAILABLE_RAM_RATIO*1024)
+ if used_mib > 0 and (used_mib / asked_mib) < ratio and asked_mib > recommend_mib:
+ yield recommendformat(
+ '{} requested {} MiB of RAM but actual RAM usage was below {}% at {} MiB -- '
+ 'suggest reducing RAM request to {} MiB'
).format(
self.label,
+ int(asked_mib),
+ int(100*ratio),
int(used_mib),
- constraint_key,
- int(math.ceil(nearlygibs(used_mib))*AVAILABLE_RAM_RATIO*1024*(2**20)/self._runtime_constraint_mem_unit()))
+ recommend_mib)
- def _recommend_keep_cache(self):
+ def _recommend_keep_cache(self, recommendformat):
"""Recommend increasing keep cache if utilization < 80%"""
constraint_key = self._map_runtime_constraint('keep_cache_ram')
if self.job_tot['net:keep0']['rx'] == 0:
return
utilization = (float(self.job_tot['blkio:0:0']['read']) /
float(self.job_tot['net:keep0']['rx']))
- asked_mib = self.existing_constraints.get(constraint_key, 256)
+ # FIXME: the default on this get won't work correctly
+ asked_cache = self.existing_constraints.get(constraint_key, 256) * self._runtime_constraint_mem_unit()
if utilization < 0.8:
- yield (
- '#!! {} Keep cache utilization was {:.2f}% -- '
- 'try runtime_constraints "{}":{} (or more)'
+ yield recommendformat(
+ '{} Keep cache utilization was {:.2f}% -- '
+ 'try doubling runtime_constraints to "{}":{} (or more)'
).format(
self.label,
utilization * 100.0,
constraint_key,
- asked_mib*2*(2**20)/self._runtime_constraint_mem_unit())
+ math.ceil(asked_cache * 2 / self._runtime_constraint_mem_unit()))
+
+
+ def _recommend_temp_disk(self, recommendformat):
+ """Recommend decreasing temp disk if utilization < 50%"""
+ total = float(self.job_tot['statfs']['total'])
+ utilization = (float(self.job_tot['statfs']['used']) / total) if total > 0 else 0.0
+
+ if utilization < 50.8 and total > 0:
+ yield recommendformat(
+ '{} max temp disk utilization was {:.0f}% of {:.0f} MiB -- '
+ 'consider reducing "tmpdirMin" and/or "outdirMin"'
+ ).format(
+ self.label,
+ utilization * 100.0,
+ total / MB)
def _format(self, val):
elif self.detected_crunch1:
return JobSummarizer.runtime_constraint_mem_unit
else:
- return ContainerSummarizer.runtime_constraint_mem_unit
+ return ContainerRequestSummarizer.runtime_constraint_mem_unit
def _map_runtime_constraint(self, key):
if hasattr(self, 'map_runtime_constraint'):
else:
uuid = process_or_uuid
process = None
- arv = arvados.api('v1', model=OrderedJsonModel())
+ arv = arvados.api('v1')
if '-dz642-' in uuid:
if process is None:
- process = arv.containers().get(uuid=uuid).execute()
- klass = ContainerTreeSummarizer
+ # Get the associated CR. Doesn't matter which since they all have the same logs
+ crs = arv.container_requests().list(filters=[['container_uuid','=',uuid]],limit=1).execute()['items']
+ if len(crs) > 0:
+ process = crs[0]
+ klass = ContainerRequestTreeSummarizer
elif '-xvhdp-' in uuid:
if process is None:
process = arv.container_requests().get(uuid=uuid).execute()
- klass = ContainerTreeSummarizer
+ klass = ContainerRequestTreeSummarizer
elif '-8i9sb-' in uuid:
if process is None:
process = arv.jobs().get(uuid=uuid).execute()
class ProcessSummarizer(Summarizer):
- """Process is a job, pipeline, container, or container request."""
+ """Process is a job, pipeline, or container request."""
def __init__(self, process, label=None, **kwargs):
rdr = None
self.process = process
if label is None:
label = self.process.get('name', self.process['uuid'])
- if self.process.get('log'):
+ # Pre-Arvados v1.4 everything is in 'log'
+ # For 1.4+ containers have no logs and container_requests have them in 'log_uuid', not 'log'
+ log_collection = self.process.get('log', self.process.get('log_uuid'))
+ if log_collection and self.process.get('state') != 'Uncommitted': # arvados.util.CR_UNCOMMITTED:
try:
- rdr = crunchstat_summary.reader.CollectionReader(self.process['log'])
+ rdr = crunchstat_summary.reader.CollectionReader(log_collection)
except arvados.errors.NotFoundError as e:
logger.warning("Trying event logs after failing to read "
"log collection %s: %s", self.process['log'], e)
if rdr is None:
- rdr = crunchstat_summary.reader.LiveLogReader(self.process['uuid'])
+ uuid = self.process.get('container_uuid', self.process.get('uuid'))
+ rdr = crunchstat_summary.reader.LiveLogReader(uuid)
label = label + ' (partial)'
super(ProcessSummarizer, self).__init__(rdr, label=label, **kwargs)
self.existing_constraints = self.process.get('runtime_constraints', {})
class JobSummarizer(ProcessSummarizer):
- runtime_constraint_mem_unit = 1048576
+ runtime_constraint_mem_unit = MB
map_runtime_constraint = {
'keep_cache_ram': 'keep_cache_mb_per_task',
'ram': 'min_ram_mb_per_node',
}
-class ContainerSummarizer(ProcessSummarizer):
+class ContainerRequestSummarizer(ProcessSummarizer):
runtime_constraint_mem_unit = 1
def run(self):
threads = []
- for child in self.children.itervalues():
+ for child in self.children.values():
self.throttle.acquire()
t = threading.Thread(target=self.run_and_release, args=(child.run, ))
t.daemon = True
def text_report(self):
txt = ''
d = self._descendants()
- for child in d.itervalues():
+ for child in d.values():
if len(d) > 1:
txt += '### Summary for {} ({})\n'.format(
child.label, child.process['uuid'])
MultiSummarizers) are omitted.
"""
d = collections.OrderedDict()
- for key, child in self.children.iteritems():
+ for key, child in self.children.items():
if isinstance(child, Summarizer):
d[key] = child
if isinstance(child, MultiSummarizer):
return d
def html_report(self):
- return WEBCHART_CLASS(self.label, self._descendants().itervalues()).html()
+ tophtml = ""
+ bottomhtml = ""
+ label = self.label
+ if len(self._descendants()) == 1:
+ summarizer = next(iter(self._descendants().values()))
+ tophtml = """{}\n<table class='aggtable'><tbody>{}</tbody></table>\n""".format(
+ "\n".join(summarizer._recommend_gen(lambda x: "<p>{}</p>".format(x))),
+ "\n".join(summarizer._text_report_agg_gen(lambda x: "<tr><th>{}</th><td>{}{}</td></tr>".format(*x))))
+
+ bottomhtml = """<table class='metricstable'><tbody>{}</tbody></table>\n""".format(
+ "\n".join(summarizer._text_report_table_gen(lambda x: "<tr><th>{}</th><th>{}</th><th>{}</th><th>{}</th><th>{}</th></tr>".format(*x),
+ lambda x: "<tr><td>{}</td><td>{}</td><td>{}</td><td>{}</td><td>{}</td></tr>".format(*x))))
+ label = summarizer.long_label()
+
+ return WEBCHART_CLASS(label, iter(self._descendants().values())).html(tophtml, bottomhtml)
class JobTreeSummarizer(MultiSummarizer):
"""Summarizes a job and all children listed in its components field."""
def __init__(self, job, label=None, **kwargs):
- arv = arvados.api('v1', model=OrderedJsonModel())
+ arv = arvados.api('v1')
label = label or job.get('name', job['uuid'])
children = collections.OrderedDict()
children[job['uuid']] = JobSummarizer(job, label=label, **kwargs)
preloaded = {}
for j in arv.jobs().index(
limit=len(job['components']),
- filters=[['uuid','in',job['components'].values()]]).execute()['items']:
+ filters=[['uuid','in',list(job['components'].values())]]).execute()['items']:
preloaded[j['uuid']] = j
for cname in sorted(job['components'].keys()):
child_uuid = job['components'][cname]
class PipelineSummarizer(MultiSummarizer):
def __init__(self, instance, **kwargs):
children = collections.OrderedDict()
- for cname, component in instance['components'].iteritems():
+ for cname, component in instance['components'].items():
if 'job' not in component:
logger.warning(
"%s: skipping component with no job assigned", cname)
**kwargs)
-class ContainerTreeSummarizer(MultiSummarizer):
- def __init__(self, root, **kwargs):
- arv = arvados.api('v1', model=OrderedJsonModel())
+class ContainerRequestTreeSummarizer(MultiSummarizer):
+ def __init__(self, root, skip_child_jobs=False, **kwargs):
+ arv = arvados.api('v1')
label = kwargs.pop('label', None) or root.get('name') or root['uuid']
root['name'] = label
current = todo.popleft()
label = current['name']
sort_key = current['created_at']
- if current['uuid'].find('-xvhdp-') > 0:
- current = arv.containers().get(uuid=current['container_uuid']).execute()
- summer = ContainerSummarizer(current, label=label, **kwargs)
+ summer = ContainerRequestSummarizer(current, label=label, **kwargs)
summer.sort_key = sort_key
children[current['uuid']] = summer
page_filters = []
while True:
- items = arv.container_requests().index(
+ child_crs = arv.container_requests().index(
order=['uuid asc'],
filters=page_filters+[
- ['requesting_container_uuid', '=', current['uuid']]],
- ).execute()['items']
- if not items:
+ ['requesting_container_uuid', '=', current['container_uuid']]],
+ ).execute()
+ if not child_crs['items']:
+ break
+ elif skip_child_jobs:
+ logger.warning('%s: omitting stats from %d child containers'
+ ' because --skip-child-jobs flag is on',
+ label, child_crs['items_available'])
break
- page_filters = [['uuid', '>', items[-1]['uuid']]]
- for cr in items:
+ page_filters = [['uuid', '>', child_crs['items'][-1]['uuid']]]
+ for cr in child_crs['items']:
if cr['container_uuid']:
logger.debug('%s: container req %s', current['uuid'], cr['uuid'])
cr['name'] = cr.get('name') or cr['uuid']
todo.append(cr)
sorted_children = collections.OrderedDict()
- for uuid in sorted(children.keys(), key=lambda uuid: children[uuid].sort_key):
+ for uuid in sorted(list(children.keys()), key=lambda uuid: children[uuid].sort_key):
sorted_children[uuid] = children[uuid]
- super(ContainerTreeSummarizer, self).__init__(
+ super(ContainerRequestTreeSummarizer, self).__init__(
children=sorted_children,
label=root['name'],
**kwargs)
projects / arvados.git / blobdiff