GildedRose-Refactoring-Kata/.venv/lib/python3.12/site-packages/mrjob/tools/diagnose.py
2025-06-22 13:36:01 +05:30

168 lines
5.4 KiB
Python

# Copyright 2017-2018 Yelp
# Copyright 2019 Yelp
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Print probable cause of error for a failed step.
Currently this only works on EMR.
Usage::
mrjob diagnose [opts] j-CLUSTERID
Options::
-c CONF_PATHS, --conf-path CONF_PATHS
Path to alternate mrjob.conf file to read from
--no-conf Don't load mrjob.conf even if it's available
--ec2-endpoint EC2_ENDPOINT
Force mrjob to connect to EC2 on this endpoint (e.g.
ec2.us-west-1.amazonaws.com). Default is to infer this
from region.
--emr-endpoint EMR_ENDPOINT
Force mrjob to connect to EMR on this endpoint (e.g.
us-west-1.elasticmapreduce.amazonaws.com). Default is
to infer this from region.
-h, --help show this help message and exit
-q, --quiet Don't print anything to stderr
--region REGION GCE/AWS region to run Dataproc/EMR jobs in.
--s3-endpoint S3_ENDPOINT
Force mrjob to connect to S3 on this endpoint (e.g. s3
-us-west-1.amazonaws.com). You usually shouldn't set
this; by default mrjob will choose the correct
endpoint for each S3 bucket based on its location.
--step-id STEP_ID ID of a particular failed step to diagnose
-v, --verbose print more messages to stderr
.. versionadded:: 0.6.1
"""
from argparse import ArgumentParser
from logging import getLogger
from mrjob.aws import _boto3_paginate
from mrjob.emr import EMRJobRunner
from mrjob.job import MRJob
from mrjob.logs.errors import _format_error
from mrjob.options import _add_basic_args
from mrjob.options import _add_runner_args
from mrjob.options import _alphabetize_actions
from mrjob.options import _filter_by_role
log = getLogger(__name__)
def main(cl_args=None):
arg_parser = _make_arg_parser()
options = arg_parser.parse_args(cl_args)
MRJob.set_up_logging(quiet=options.quiet, verbose=options.verbose)
runner_kwargs = {k: v for k, v in options.__dict__.items()
if k not in ('quiet', 'verbose', 'step_id')}
runner = EMRJobRunner(**runner_kwargs)
emr_client = runner.make_emr_client()
# pick step
step = _get_step(emr_client, options.cluster_id, options.step_id)
if not step:
raise SystemExit(1)
if step['Status']['State'] != 'FAILED':
log.warning('step %s has state %s, not FAILED' %
(step['Id'], step['Status']['State']))
# interpret logs
log.info('Diagnosing step %s (%s)' % (step['Id'], step['Name']))
log_interpretation = dict(step_id=step['Id'])
step_type = _infer_step_type(step)
error = runner._pick_error(log_interpretation, step_type)
# print error
if error:
log.error('Probable cause of failure:\n\n%s\n\n' %
_format_error(error))
else:
log.warning('No error detected')
def _get_step(emr_client, cluster_id, step_id=None):
# just iterate backwards through steps, rather than filtering
# by step ID or status. usually it'll be the last step anyhow
for step in _boto3_paginate('Steps', emr_client, 'list_steps',
ClusterId=cluster_id):
if _step_matches(step, step_id=step_id):
return step
else:
if step_id:
log.error('step %s not found on cluster %s' %
(step_id, cluster_id))
else:
log.error('cluster %s has no failed steps' % cluster_id)
def _step_matches(step, step_id=None):
if not step_id:
return step['Status']['State'] == 'FAILED'
else:
return step['Id'] == step_id
def _infer_step_type(step):
args = step['Config']['Args']
# all that matters for log parsing is picking out Spark steps
# (doesn't matter if it's spark or spark_jar or spark_script)
#
# and of course we don't know the logging habits of jar steps,
# so we might as well use streaming's logic
if '--master' in args and '--deploy-mode' in args:
return 'spark'
else:
return 'streaming'
def _make_arg_parser():
usage = '%(prog)s diagnose [opts] [--step-id STEP_ID] CLUSTER_ID'
description = (
'Get probable cause of failure for step on CLUSTER_ID.'
' By default we look at the last failed step')
arg_parser = ArgumentParser(usage=usage, description=description)
_add_basic_args(arg_parser)
_add_runner_args(
arg_parser,
_filter_by_role(EMRJobRunner.OPT_NAMES, 'connect'))
arg_parser.add_argument(
dest='cluster_id',
help='ID of cluster with failed step')
arg_parser.add_argument(
'--step-id', dest='step_id',
help='ID of a particular failed step to diagnose')
_alphabetize_actions(arg_parser)
return arg_parser
if __name__ == '__main__':
main()