X-Git-Url: https://git.arvados.org/arvados.git/blobdiff_plain/4b78fb11974d8bcb0b9e4ecd0162d6a938026c73..3854e6bfcd5344bce5ee0388248cb115e3c5e902:/tools/crunchstat-summary/crunchstat_summary/summarizer.py diff --git a/tools/crunchstat-summary/crunchstat_summary/summarizer.py b/tools/crunchstat-summary/crunchstat_summary/summarizer.py index ba1919fed8..f692469436 100644 --- a/tools/crunchstat-summary/crunchstat_summary/summarizer.py +++ b/tools/crunchstat-summary/crunchstat_summary/summarizer.py @@ -1,14 +1,21 @@ +# Copyright (C) The Arvados Authors. All rights reserved. +# +# SPDX-License-Identifier: AGPL-3.0 + from __future__ import print_function import arvados import collections -import crunchstat_summary.chartjs +import crunchstat_summary.dygraphs +import crunchstat_summary.reader import datetime import functools import itertools import math import re import sys +import threading +import _strptime from arvados.api import OrderedJsonModel from crunchstat_summary import logger @@ -19,6 +26,14 @@ from crunchstat_summary import logger AVAILABLE_RAM_RATIO = 0.95 +# Workaround datetime.datetime.strptime() thread-safety bug by calling +# it once before starting threads. https://bugs.python.org/issue7980 +datetime.datetime.strptime('1999-12-31_23:59:59', '%Y-%m-%d_%H:%M:%S') + + +WEBCHART_CLASS = crunchstat_summary.dygraphs.DygraphsChart + + class Task(object): def __init__(self): self.starttime = None @@ -26,52 +41,123 @@ class Task(object): class Summarizer(object): - existing_constraints = {} - - def __init__(self, logdata, label=None): + def __init__(self, logdata, label=None, skip_child_jobs=False, uuid=None, **kwargs): self._logdata = logdata + + self.uuid = uuid self.label = label self.starttime = None self.finishtime = None - logger.debug("%s: logdata %s", self.label, repr(logdata)) + self._skip_child_jobs = skip_child_jobs - def run(self): - logger.debug("%s: parsing log data", self.label) # stats_max: {category: {stat: val}} self.stats_max = collections.defaultdict( - functools.partial(collections.defaultdict, - lambda: float('-Inf'))) + functools.partial(collections.defaultdict, lambda: 0)) # task_stats: {task_id: {category: {stat: val}}} self.task_stats = collections.defaultdict( functools.partial(collections.defaultdict, dict)) + + self.seq_to_uuid = {} self.tasks = collections.defaultdict(Task) - for line in self._logdata: - m = re.search(r'^\S+ \S+ \d+ (?P\d+) success in (?P\d+) seconds', line) - if m: - task_id = m.group('seq') - elapsed = int(m.group('elapsed')) - self.task_stats[task_id]['time'] = {'elapsed': elapsed} - if elapsed > self.stats_max['time']['elapsed']: - self.stats_max['time']['elapsed'] = elapsed - continue - m = re.search(r'^(?P\S+) (?P\S+) \d+ (?P\d+) stderr crunchstat: (?P\S+) (?P.*?)( -- interval (?P.*))?\n', line) - if not m: - continue + + # We won't bother recommending new runtime constraints if the + # constraints given when running the job are known to us and + # are already suitable. If applicable, the subclass + # constructor will overwrite this with something useful. + self.existing_constraints = {} + + logger.debug("%s: logdata %s", self.label, logdata) + + def run(self): + logger.debug("%s: parsing logdata %s", self.label, self._logdata) + with self._logdata as logdata: + self._run(logdata) + + def _run(self, logdata): + self.detected_crunch1 = False + for line in logdata: + if not self.detected_crunch1 and '-8i9sb-' in line: + self.detected_crunch1 = True + + if self.detected_crunch1: + m = re.search(r'^\S+ \S+ \d+ (?P\d+) job_task (?P\S+)$', line) + if m: + seq = int(m.group('seq')) + uuid = m.group('task_uuid') + self.seq_to_uuid[seq] = uuid + logger.debug('%s: seq %d is task %s', self.label, seq, uuid) + continue + + m = re.search(r'^\S+ \S+ \d+ (?P\d+) (success in|failure \(#., permanent\) after) (?P\d+) seconds', line) + if m: + task_id = self.seq_to_uuid[int(m.group('seq'))] + elapsed = int(m.group('elapsed')) + self.task_stats[task_id]['time'] = {'elapsed': elapsed} + if elapsed > self.stats_max['time']['elapsed']: + self.stats_max['time']['elapsed'] = elapsed + continue + + m = re.search(r'^\S+ \S+ \d+ (?P\d+) stderr Queued job (?P\S+)$', line) + if m: + uuid = m.group('uuid') + if self._skip_child_jobs: + logger.warning('%s: omitting stats from child job %s' + ' because --skip-child-jobs flag is on', + self.label, uuid) + continue + logger.debug('%s: follow %s', self.label, uuid) + child_summarizer = ProcessSummarizer(uuid) + child_summarizer.stats_max = self.stats_max + child_summarizer.task_stats = self.task_stats + child_summarizer.tasks = self.tasks + child_summarizer.starttime = self.starttime + child_summarizer.run() + logger.debug('%s: done %s', self.label, uuid) + continue + + m = re.search(r'^(?P[^\s.]+)(\.\d+)? (?P\S+) \d+ (?P\d+) stderr crunchstat: (?P\S+) (?P.*?)( -- interval (?P.*))?\n$', line) + if not m: + continue + else: + # crunch2 + m = re.search(r'^(?P\S+) (?P\S+) (?P.*?)( -- interval (?P.*))?\n$', line) + if not m: + continue + if self.label is None: - self.label = m.group('job_uuid') - logger.debug('%s: using job uuid as label', self.label) + try: + self.label = m.group('job_uuid') + except IndexError: + self.label = 'container' if m.group('category').endswith(':'): - # "notice:" etc. + # "stderr crunchstat: notice: ..." + continue + elif m.group('category') in ('error', 'caught'): continue - elif m.group('category') == 'error': + elif m.group('category') in ('read', 'open', 'cgroup', 'CID', 'Running'): + # "stderr crunchstat: read /proc/1234/net/dev: ..." + # (old logs are less careful with unprefixed error messages) continue - task_id = m.group('seq') + + if self.detected_crunch1: + task_id = self.seq_to_uuid[int(m.group('seq'))] + else: + task_id = 'container' task = self.tasks[task_id] # Use the first and last crunchstat timestamps as # approximations of starttime and finishtime. - timestamp = datetime.datetime.strptime( - m.group('timestamp'), '%Y-%m-%d_%H:%M:%S') + timestamp = m.group('timestamp') + if timestamp[10:11] == '_': + timestamp = datetime.datetime.strptime( + timestamp, '%Y-%m-%d_%H:%M:%S') + elif timestamp[10:11] == 'T': + timestamp = datetime.datetime.strptime( + timestamp[:19], '%Y-%m-%dT%H:%M:%S') + else: + raise ValueError("Cannot parse timestamp {!r}".format( + timestamp)) + if not task.starttime: task.starttime = timestamp logger.debug('%s: task %s starttime %s', @@ -89,16 +175,18 @@ class Summarizer(object): category = m.group('category') words = m.group(group).split(' ') stats = {} - for val, stat in zip(words[::2], words[1::2]): - try: + try: + for val, stat in zip(words[::2], words[1::2]): if '.' in val: stats[stat] = float(val) else: stats[stat] = int(val) - except ValueError as e: - raise ValueError( - 'Error parsing {} stat in "{}": {!r}'.format( - stat, line, e)) + except ValueError as e: + logger.warning( + 'Error parsing value %r (stat %r, category %r): %r', + 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: @@ -118,14 +206,16 @@ class Summarizer(object): val = val / this_interval_s if stat in ['user+sys__rate', 'tx+rx__rate']: task.series[category, stat].append( - (timestamp - task.starttime, val)) + (timestamp - self.starttime, val)) else: if stat in ['rss']: task.series[category, stat].append( - (timestamp - task.starttime, val)) + (timestamp - self.starttime, val)) self.task_stats[task_id][category][stat] = val if val > self.stats_max[category][stat]: self.stats_max[category][stat] = val + logger.debug('%s: done parsing', self.label) + self.job_tot = collections.defaultdict( functools.partial(collections.defaultdict, int)) for task_id, task_stat in self.task_stats.iteritems(): @@ -135,9 +225,12 @@ class Summarizer(object): # meaningless stats like 16 cpu cores x 5 tasks = 80 continue self.job_tot[category][stat] += val + logger.debug('%s: done totals', self.label) 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() @@ -151,12 +244,14 @@ class Summarizer(object): 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" def html_report(self): - return crunchstat_summary.chartjs.ChartJS(self.label, [self]).html() + return WEBCHART_CLASS(self.label, [self]).html() def _text_report_gen(self): yield "\t".join(['category', 'metric', 'task_max', 'task_max_rate', 'job_total']) @@ -169,6 +264,9 @@ class Summarizer(object): 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', self.stats_max['cpu']['user+sys'], None), @@ -177,17 +275,30 @@ class Summarizer(object): lambda x: x * 100), ('Overall CPU usage: {}%', self.job_tot['cpu']['user+sys'] / - self.job_tot['time']['elapsed'], + 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', self.stats_max['mem']['rss'], lambda x: x / 1e9), ('Max network traffic in a single task: {}GB', - self.stats_max['net:eth0']['tx+rx'], + 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', - self.stats_max['net:eth0']['tx+rx__rate'], - lambda x: x / 1e6)): + self.stats_max['net:eth0']['tx+rx__rate'] + + self.stats_max['net:keep0']['tx+rx__rate'], + lambda x: x / 1e6), + ('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 {}%', + (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 if val == float('-Inf'): continue @@ -198,45 +309,102 @@ class Summarizer(object): def _recommend_gen(self): return itertools.chain( self._recommend_cpu(), - self._recommend_ram()) + self._recommend_ram(), + self._recommend_keep_cache()) def _recommend_cpu(self): """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'): logger.warning('%s: no CPU usage data', self.label) return - used_cores = int(math.ceil(cpu_max_rate)) - asked_cores = self.existing_constraints.get('min_cores_per_node') + 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 "min_cores_per_node":{}' + 'try runtime_constraints "{}":{}' ).format( self.label, int(math.ceil(cpu_max_rate*100)), + constraint_key, int(used_cores)) def _recommend_ram(self): - """Recommend asking for (2048*0.95) MiB RAM if max rss was 1248 MiB""" - - used_ram = self.stats_max['mem']['rss'] - if used_ram == float('-Inf'): + """Recommend an economical RAM constraint for this job. + + Nodes that are advertised as "8 gibibytes" actually have what + we might call "8 nearlygibs" of memory available for jobs. + Here, we calculate a whole number of nearlygibs that would + have sufficed to run the job, then recommend requesting a node + with that number of nearlygibs (expressed as mebibytes). + + Requesting a node with "nearly 8 gibibytes" is our best hope + of getting a node that actually has nearly 8 gibibytes + available. If the node manager is smart enough to account for + the discrepancy itself when choosing/creating a node, we'll + get an 8 GiB node with nearly 8 GiB available. Otherwise, the + advertised size of the next-size-smaller node (say, 6 GiB) + will be too low to satisfy our request, so we will effectively + get rounded up to 8 GiB. + + For example, if we need 7500 MiB, we can ask for 7500 MiB, and + we will generally get a node that is advertised as "8 GiB" and + has at least 7500 MiB available. However, asking for 8192 MiB + would either result in an unnecessarily expensive 12 GiB node + (if node manager knows about the discrepancy), or an 8 GiB + node which has less than 8192 MiB available and is therefore + considered by crunch-dispatch to be too small to meet our + constraint. + + When node manager learns how to predict the available memory + for each node type such that crunch-dispatch always agrees + that a node is big enough to run the job it was brought up + for, all this will be unnecessary. We'll just ask for exactly + the memory we want -- even if that happens to be 8192 MiB. + """ + + constraint_key = self._map_runtime_constraint('ram') + used_bytes = self.stats_max['mem']['rss'] + if used_bytes == float('-Inf'): logger.warning('%s: no memory usage data', self.label) return - used_ram = math.ceil(float(used_ram) / (1<<20)) - asked_ram = self.existing_constraints.get('min_ram_mb_per_node') - if asked_ram is None or ( - math.ceil((used_ram/AVAILABLE_RAM_RATIO)/(1<<10)) < - (asked_ram/AVAILABLE_RAM_RATIO)/(1<<10)): + used_mib = math.ceil(float(used_bytes) / 1048576) + asked_mib = self.existing_constraints.get(constraint_key) + + 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 "min_ram_mb_per_node":{}' + 'try runtime_constraints "{}":{}' ).format( self.label, - int(used_ram), - int(math.ceil((used_ram/AVAILABLE_RAM_RATIO)/(1<<10))*(1<<10)*AVAILABLE_RAM_RATIO)) + int(used_mib), + constraint_key, + int(math.ceil(nearlygibs(used_mib))*AVAILABLE_RAM_RATIO*1024*(2**20)/self._runtime_constraint_mem_unit())) + + def _recommend_keep_cache(self): + """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) + + if utilization < 0.8: + yield ( + '#!! {} Keep cache utilization was {:.2f}% -- ' + 'try runtime_constraints "{}":{} (or more)' + ).format( + self.label, + utilization * 100.0, + constraint_key, + asked_mib*2*(2**20)/self._runtime_constraint_mem_unit()) + def _format(self, val): """Return a string representation of a stat. @@ -247,72 +415,234 @@ class Summarizer(object): else: return '{}'.format(val) + def _runtime_constraint_mem_unit(self): + if hasattr(self, 'runtime_constraint_mem_unit'): + return self.runtime_constraint_mem_unit + elif self.detected_crunch1: + return JobSummarizer.runtime_constraint_mem_unit + else: + return ContainerSummarizer.runtime_constraint_mem_unit + + def _map_runtime_constraint(self, key): + if hasattr(self, 'map_runtime_constraint'): + return self.map_runtime_constraint[key] + elif self.detected_crunch1: + return JobSummarizer.map_runtime_constraint[key] + else: + return key + class CollectionSummarizer(Summarizer): - def __init__(self, collection_id): - collection = arvados.collection.CollectionReader(collection_id) - filenames = [filename for filename in collection] - if len(filenames) != 1: - raise ValueError( - "collection {} has {} files; need exactly one".format( - collection_id, len(filenames))) + def __init__(self, collection_id, **kwargs): super(CollectionSummarizer, self).__init__( - collection.open(filenames[0])) + crunchstat_summary.reader.CollectionReader(collection_id), **kwargs) self.label = collection_id -class JobSummarizer(CollectionSummarizer): - def __init__(self, job): - arv = arvados.api('v1') - if isinstance(job, str): - self.job = arv.jobs().get(uuid=job).execute() - else: - self.job = job - self.label = self.job['uuid'] - self.existing_constraints = self.job.get('runtime_constraints', {}) - if not self.job['log']: - raise ValueError( - "job {} has no log; live summary not implemented".format( - self.job['uuid'])) - super(JobSummarizer, self).__init__(self.job['log']) - self.label = self.job['uuid'] - - -class PipelineSummarizer(): - def __init__(self, pipeline_instance_uuid): +def NewSummarizer(process_or_uuid, **kwargs): + """Construct with the appropriate subclass for this uuid/object.""" + + if isinstance(process_or_uuid, dict): + process = process_or_uuid + uuid = process['uuid'] + else: + uuid = process_or_uuid + process = None arv = arvados.api('v1', model=OrderedJsonModel()) - instance = arv.pipeline_instances().get( - uuid=pipeline_instance_uuid).execute() - self.summarizers = collections.OrderedDict() - for cname, component in instance['components'].iteritems(): - if 'job' not in component: - logger.warning( - "%s: skipping component with no job assigned", cname) - elif component['job'].get('log') is None: - logger.warning( - "%s: skipping job %s with no log available", - cname, component['job'].get('uuid')) - else: - logger.info( - "%s: logdata %s", cname, component['job']['log']) - summarizer = JobSummarizer(component['job']) - summarizer.label = cname - self.summarizers[cname] = summarizer - self.label = pipeline_instance_uuid + + if '-dz642-' in uuid: + if process is None: + process = arv.containers().get(uuid=uuid).execute() + klass = ContainerTreeSummarizer + elif '-xvhdp-' in uuid: + if process is None: + process = arv.container_requests().get(uuid=uuid).execute() + klass = ContainerTreeSummarizer + elif '-8i9sb-' in uuid: + if process is None: + process = arv.jobs().get(uuid=uuid).execute() + klass = JobTreeSummarizer + elif '-d1hrv-' in uuid: + if process is None: + process = arv.pipeline_instances().get(uuid=uuid).execute() + klass = PipelineSummarizer + elif '-4zz18-' in uuid: + return CollectionSummarizer(collection_id=uuid) + else: + raise ArgumentError("Unrecognized uuid %s", uuid) + return klass(process, uuid=uuid, **kwargs) + + +class ProcessSummarizer(Summarizer): + """Process is a job, pipeline, container, 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'): + try: + rdr = crunchstat_summary.reader.CollectionReader(self.process['log']) + 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']) + 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 + map_runtime_constraint = { + 'keep_cache_ram': 'keep_cache_mb_per_task', + 'ram': 'min_ram_mb_per_node', + 'vcpus': 'min_cores_per_node', + } + + +class ContainerSummarizer(ProcessSummarizer): + runtime_constraint_mem_unit = 1 + + +class MultiSummarizer(object): + def __init__(self, children={}, label=None, threads=1, **kwargs): + self.throttle = threading.Semaphore(threads) + self.children = children + self.label = label + + def run_and_release(self, target, *args, **kwargs): + try: + return target(*args, **kwargs) + finally: + self.throttle.release() def run(self): - for summarizer in self.summarizers.itervalues(): - summarizer.run() + threads = [] + for child in self.children.itervalues(): + self.throttle.acquire() + t = threading.Thread(target=self.run_and_release, args=(child.run, )) + t.daemon = True + t.start() + threads.append(t) + for t in threads: + t.join() def text_report(self): txt = '' - for cname, summarizer in self.summarizers.iteritems(): - txt += '### Summary for {} ({})\n'.format( - cname, summarizer.job['uuid']) - txt += summarizer.text_report() + d = self._descendants() + for child in d.itervalues(): + if len(d) > 1: + txt += '### Summary for {} ({})\n'.format( + child.label, child.process['uuid']) + txt += child.text_report() txt += '\n' return txt + def _descendants(self): + """Dict of self and all descendants. + + Nodes with nothing of their own to report (like + MultiSummarizers) are omitted. + """ + d = collections.OrderedDict() + for key, child in self.children.iteritems(): + if isinstance(child, Summarizer): + d[key] = child + if isinstance(child, MultiSummarizer): + d.update(child._descendants()) + return d + def html_report(self): - return crunchstat_summary.chartjs.ChartJS( - self.label, self.summarizers.itervalues()).html() + return WEBCHART_CLASS(self.label, self._descendants().itervalues()).html() + + +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()) + label = label or job.get('name', job['uuid']) + children = collections.OrderedDict() + children[job['uuid']] = JobSummarizer(job, label=label, **kwargs) + if job.get('components', None): + preloaded = {} + for j in arv.jobs().index( + limit=len(job['components']), + filters=[['uuid','in',job['components'].values()]]).execute()['items']: + preloaded[j['uuid']] = j + for cname in sorted(job['components'].keys()): + child_uuid = job['components'][cname] + j = (preloaded.get(child_uuid) or + arv.jobs().get(uuid=child_uuid).execute()) + children[child_uuid] = JobTreeSummarizer(job=j, label=cname, **kwargs) + + super(JobTreeSummarizer, self).__init__( + children=children, + label=label, + **kwargs) + + +class PipelineSummarizer(MultiSummarizer): + def __init__(self, instance, **kwargs): + children = collections.OrderedDict() + for cname, component in instance['components'].iteritems(): + if 'job' not in component: + logger.warning( + "%s: skipping component with no job assigned", cname) + else: + logger.info( + "%s: job %s", cname, component['job']['uuid']) + summarizer = JobTreeSummarizer(component['job'], label=cname, **kwargs) + summarizer.label = '{} {}'.format( + cname, component['job']['uuid']) + children[cname] = summarizer + super(PipelineSummarizer, self).__init__( + children=children, + label=instance['uuid'], + **kwargs) + + +class ContainerTreeSummarizer(MultiSummarizer): + def __init__(self, root, **kwargs): + arv = arvados.api('v1', model=OrderedJsonModel()) + + label = kwargs.pop('label', None) or root.get('name') or root['uuid'] + root['name'] = label + + children = collections.OrderedDict() + todo = collections.deque((root, )) + while len(todo) > 0: + 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.sort_key = sort_key + children[current['uuid']] = summer + + page_filters = [] + while True: + items = arv.container_requests().index( + order=['uuid asc'], + filters=page_filters+[ + ['requesting_container_uuid', '=', current['uuid']]], + ).execute()['items'] + if not items: + break + page_filters = [['uuid', '>', items[-1]['uuid']]] + for cr in 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): + sorted_children[uuid] = children[uuid] + super(ContainerTreeSummarizer, self).__init__( + children=sorted_children, + label=root['name'], + **kwargs)