11 # Useful configuration variables:
13 # Number of log lines to use as context in diagnosing failure.
14 LOG_CONTEXT_LINES = 10
16 # Regex that signifies a failed task.
17 FAILED_TASK_REGEX = re.compile(' \d+ failure (.*permanent)')
19 # Regular expressions used to classify failure types.
21 'sys/docker': 'Cannot destroy container',
22 'crunch/node': 'User not found on host',
23 'slurm/comm': 'Communication connection failure'
26 def parse_arguments(arguments):
27 arg_parser = argparse.ArgumentParser(
28 description='Produce a report of Crunch failures within a specified time range')
30 arg_parser.add_argument(
32 help='Start date and time')
33 arg_parser.add_argument(
35 help='End date and time')
37 args = arg_parser.parse_args(arguments)
39 if args.start and not is_valid_timestamp(args.start):
40 raise ValueError(args.start)
41 if args.end and not is_valid_timestamp(args.end):
42 raise ValueError(args.end)
47 def api_timestamp(when=None):
48 """Returns a string representing the timestamp 'when' in a format
49 suitable for delivering to the API server. Defaults to the
53 when = datetime.datetime.utcnow()
54 return when.strftime("%Y-%m-%dT%H:%M:%SZ")
57 def is_valid_timestamp(ts):
58 return re.match(r'\d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2}Z', ts)
61 def jobs_created_between_dates(api, start, end):
62 return arvados.util.list_all(
64 filters=json.dumps([ ['created_at', '>=', start],
65 ['created_at', '<=', end] ]))
68 def job_logs(api, job):
69 # Returns the contents of the log for this job (as an array of lines).
71 log_collection = arvados.CollectionReader(job['log'], api)
72 log_filename = "{}.log.txt".format(job['uuid'])
73 return log_collection.open(log_filename).readlines()
78 def job_user_name(api, user_uuid):
79 def _lookup_user_name(api, user_uuid):
81 return api.users().get(uuid=user_uuid).execute()['full_name']
82 except arvados.errors.ApiError:
85 if user_uuid not in user_names:
86 user_names[user_uuid] = _lookup_user_name(api, user_uuid)
87 return user_names[user_uuid]
90 job_pipeline_names = {}
91 def job_pipeline_name(api, job_uuid):
92 def _lookup_pipeline_name(api, job_uuid):
93 pipelines = api.pipeline_instances().list(
94 filters='[["components", "like", "%{}%"]]'.format(job_uuid)).execute()
95 if pipelines['items']:
96 pi = pipelines['items'][0]
100 # Use the pipeline template name
101 pt = api.pipeline_templates().get(uuid=pi['pipeline_template_uuid']).execute()
106 if job_uuid not in job_pipeline_names:
107 job_pipeline_names[job_uuid] = _lookup_pipeline_name(api, job_uuid)
108 return job_pipeline_names[job_uuid]
111 def is_failed_task(logline):
112 return FAILED_TASK_REGEX.search(logline) != None
115 def main(arguments=None, stdout=sys.stdout, stderr=sys.stderr):
116 args = parse_arguments(arguments)
118 api = arvados.api('v1')
120 now = datetime.datetime.utcnow()
121 start_time = args.start or api_timestamp(now - datetime.timedelta(days=1))
122 end_time = args.end or api_timestamp(now)
124 # Find all jobs created within the specified window,
125 # and their corresponding job logs.
126 jobs_created = jobs_created_between_dates(api, start_time, end_time)
128 for job in jobs_created:
129 jobs_by_state.setdefault(job['state'], [])
130 jobs_by_state[job['state']].append(job)
132 # Find failed jobs and record the job failure text.
134 # failure_stats maps failure types (e.g. "sys/docker") to
135 # a set of job UUIDs that failed for that reason.
137 for job in jobs_by_state['Failed']:
138 job_uuid = job['uuid']
139 logs = job_logs(api, job)
140 # Find the first permanent task failure, and collect the
141 # preceding log lines.
143 for i, lg in enumerate(logs):
144 if is_failed_task(lg):
145 # Get preceding log record to provide context.
146 log_start = i - LOG_CONTEXT_LINES if i >= LOG_CONTEXT_LINES else 0
148 lastlogs = ''.join(logs[log_start:log_end])
149 # try to identify the type of failure.
150 for key, rgx in JOB_FAILURE_TYPES.iteritems():
151 if re.search(rgx, lastlogs):
154 if failure_type is not None:
156 if failure_type is None:
157 failure_type = 'unknown'
158 failure_stats.setdefault(failure_type, set())
159 failure_stats[failure_type].add(job_uuid)
161 # Report percentages of successful, failed and unfinished jobs.
162 print "Start: {:20s}".format(start_time)
163 print "End: {:20s}".format(end_time)
169 job_start_count = len(jobs_created)
170 print " {: <25s} {:4d}".format('Started', job_start_count)
171 for state in ['Complete', 'Failed', 'Queued', 'Cancelled', 'Running']:
172 if state in jobs_by_state:
173 job_count = len(jobs_by_state[state])
174 job_percentage = job_count / float(job_start_count)
175 print " {: <25s} {:4d} ({: >4.0%})".format(state,
180 # Report failure types.
184 # Generate a mapping from failed job uuids to job records, to assist
185 # in generating detailed statistics for job failures.
186 jobs_failed_map = { job['uuid']: job for job in jobs_by_state.get('Failed', []) }
188 # sort the failure stats in descending order by occurrence.
189 sorted_failures = sorted(failure_stats,
191 key=lambda failure_type: len(failure_stats[failure_type]))
192 for failtype in sorted_failures:
193 job_uuids = failure_stats[failtype]
194 failstat = " {: <25s} {:4d} ({: >4.0%})\n".format(
197 len(job_uuids) / float(len(jobs_by_state['Failed'])))
198 failure_summary = failure_summary + failstat
199 failure_detail = failure_detail + failstat
201 job_info = jobs_failed_map[j]
202 job_owner = job_user_name(api, job_info['modified_by_user_uuid'])
203 job_name = job_pipeline_name(api, job_info['uuid'])
204 failure_detail = failure_detail + " {} {: <15.15s} {:29.29s}\n".format(j, job_owner, job_name)
205 failure_detail = failure_detail + "\n"
207 print "Failures by class"
209 print failure_summary
211 print "Failures by class (detail)"
218 if __name__ == "__main__":