X-Git-Url: https://git.arvados.org/arvados.git/blobdiff_plain/0343fe988fdc50bdfb1ac34204c1a4998fc7c446..207136fe4f9787ac7f99cba448ed5a2a05a6f8dd:/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 ccee1e24d2..a88e4d5c41 100644 --- a/tools/crunchstat-summary/crunchstat_summary/summarizer.py +++ b/tools/crunchstat-summary/crunchstat_summary/summarizer.py @@ -3,12 +3,15 @@ from __future__ import print_function import arvados import collections import crunchstat_summary.chartjs +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 +22,11 @@ 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') + + class Task(object): def __init__(self): self.starttime = None @@ -26,20 +34,17 @@ class Task(object): class Summarizer(object): - existing_constraints = {} - - def __init__(self, logdata, label=None, include_child_jobs=True): + def __init__(self, logdata, label=None, skip_child_jobs=False): self._logdata = logdata self.label = label self.starttime = None self.finishtime = None - self._include_child_jobs = include_child_jobs + self._skip_child_jobs = skip_child_jobs # 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)) @@ -47,10 +52,16 @@ class Summarizer(object): self.seq_to_uuid = {} self.tasks = collections.defaultdict(Task) - logger.debug("%s: logdata %s", self.label, repr(logdata)) + # 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 log data", self.label) + logger.debug("%s: parsing logdata %s", self.label, self._logdata) for line in self._logdata: m = re.search(r'^\S+ \S+ \d+ (?P\d+) job_task (?P\S+)$', line) if m: @@ -60,7 +71,7 @@ class Summarizer(object): logger.debug('%s: seq %d is task %s', self.label, seq, uuid) continue - m = re.search(r'^\S+ \S+ \d+ (?P\d+) success in (?P\d+) seconds', line) + 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')) @@ -72,8 +83,9 @@ class Summarizer(object): m = re.search(r'^\S+ \S+ \d+ (?P\d+) stderr Queued job (?P\S+)$', line) if m: uuid = m.group('uuid') - if not self._include_child_jobs: - logger.warning('%s: omitting %s (try --include-child-job)', + 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) @@ -81,11 +93,12 @@ class Summarizer(object): 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+) (?P\S+) \d+ (?P\d+) stderr crunchstat: (?P\S+) (?P.*?)( -- interval (?P.*))?\n', line) + 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 @@ -93,9 +106,13 @@ class Summarizer(object): self.label = m.group('job_uuid') logger.debug('%s: using job uuid as label', self.label) 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') == 'read': + # "stderr crunchstat: read /proc/1234/net/dev: ..." + # (crunchstat formatting fixed, but old logs still say this) continue task_id = self.seq_to_uuid[int(m.group('seq'))] task = self.tasks[task_id] @@ -150,11 +167,11 @@ 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 @@ -186,6 +203,8 @@ 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" @@ -215,17 +234,30 @@ 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 @@ -236,7 +268,8 @@ 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%""" @@ -245,8 +278,8 @@ class Summarizer(object): 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('min_cores_per_node') if asked_cores is None or used_cores < asked_cores: yield ( '#!! {} max CPU usage was {}% -- ' @@ -257,24 +290,74 @@ class Summarizer(object): 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. + """ + + 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('min_ram_mb_per_node') + + 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":{}' ).format( self.label, - int(used_ram), - int(math.ceil((used_ram/AVAILABLE_RAM_RATIO)/(1<<10))*(1<<10)*AVAILABLE_RAM_RATIO)) + int(used_mib), + int(math.ceil(nearlygibs(used_mib))*AVAILABLE_RAM_RATIO*1024)) + + def _recommend_keep_cache(self): + """Recommend increasing keep cache if utilization < 80%""" + 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('keep_cache_mb_per_task', 256) + + if utilization < 0.8: + yield ( + '#!! {} Keep cache utilization was {:.2f}% -- ' + 'try runtime_constraints "keep_cache_mb_per_task":{} (or more)' + ).format( + self.label, + utilization * 100.0, + asked_mib*2) + def _format(self, val): """Return a string representation of a stat. @@ -288,36 +371,36 @@ class Summarizer(object): class CollectionSummarizer(Summarizer): def __init__(self, collection_id, **kwargs): - logger.debug('load collection %s', 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))) super(CollectionSummarizer, self).__init__( - collection.open(filenames[0]), **kwargs) + crunchstat_summary.reader.CollectionReader(collection_id), **kwargs) self.label = collection_id -class JobSummarizer(CollectionSummarizer): +class JobSummarizer(Summarizer): def __init__(self, job, **kwargs): arv = arvados.api('v1') - if isinstance(job, str): + if isinstance(job, basestring): self.job = arv.jobs().get(uuid=job).execute() else: self.job = job - self.label = self.job['uuid'] + rdr = None + if self.job.get('log'): + try: + rdr = crunchstat_summary.reader.CollectionReader(self.job['log']) + except arvados.errors.NotFoundError as e: + logger.warning("Trying event logs after failing to read " + "log collection %s: %s", self.job['log'], e) + else: + label = self.job['uuid'] + if rdr is None: + rdr = crunchstat_summary.reader.LiveLogReader(self.job['uuid']) + label = self.job['uuid'] + ' (partial)' + super(JobSummarizer, self).__init__(rdr, **kwargs) + self.label = label 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'], **kwargs) - self.label = self.job['uuid'] -class PipelineSummarizer(): +class PipelineSummarizer(object): def __init__(self, pipeline_instance_uuid, **kwargs): arv = arvados.api('v1', model=OrderedJsonModel()) instance = arv.pipeline_instances().get( @@ -327,21 +410,24 @@ class PipelineSummarizer(): 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']) + "%s: job %s", cname, component['job']['uuid']) summarizer = JobSummarizer(component['job'], **kwargs) - summarizer.label = cname + summarizer.label = '{} {}'.format( + cname, component['job']['uuid']) self.summarizers[cname] = summarizer self.label = pipeline_instance_uuid def run(self): + threads = [] for summarizer in self.summarizers.itervalues(): - summarizer.run() + t = threading.Thread(target=summarizer.run) + t.daemon = True + t.start() + threads.append(t) + for t in threads: + t.join() def text_report(self): txt = ''