def parse_hadoop_counters_from_line(line, hadoop_version=None):
"""Parse Hadoop counter values from a log line.
The counter log line format changed significantly between Hadoop 0.18 and
0.20, so this function switches between parsers for them.
:param line: log line containing counter data
:type line: str
:return: (counter_dict, step_num) or (None, None)
"""
# start with 2.x parsing, which parses the entire line as JSON
if (hadoop_version is None or
version_gte(hadoop_version, '2') or
(version_gte(hadoop_version, '0.21') and
not version_gte(hadoop_version, '1'))):
counters, step_num = _parse_counters_from_line_2_0(line)
# if we found something, or if hadoop_version isn't None, return it
if counters or hadoop_version:
return counters, step_num
m = _COUNTER_LINE_RE.match(line)
if not m:
return None, None
if hadoop_version is None:
# try both if hadoop_version not specified
counters_1, step_num_1 = parse_hadoop_counters_from_line(line, '0.20')
if counters_1:
return (counters_1, step_num_1)
else:
return parse_hadoop_counters_from_line(line, '0.18')
if uses_020_counters(hadoop_version):
parse_func = _parse_counters_0_20
else:
parse_func = _parse_counters_0_18
counter_substring = m.group('counters')
counters = {}
for group, counter, value in parse_func(counter_substring):
counters.setdefault(group, {})
counters[group].setdefault(counter, 0)
counters[group][counter] += int(value)
return counters, int(m.group('step_num'))
def parse_hadoop_counters_from_line(line, hadoop_version=None):
"""Parse Hadoop counter values from a log line.
The counter log line format changed significantly between Hadoop 0.18 and
0.20, so this function switches between parsers for them.
:param line: log line containing counter data
:type line: str
:return: (counter_dict, step_num) or (None, None)
"""
# start with 2.x parsing, which parses the entire line as JSON
if (hadoop_version is None or version_gte(hadoop_version, '2')
or (version_gte(hadoop_version, '0.21')
and not version_gte(hadoop_version, '1'))):
counters, step_num = _parse_counters_from_line_2_0(line)
# if we found something, or if hadoop_version isn't None, return it
if counters or hadoop_version:
return counters, step_num
m = _COUNTER_LINE_RE.match(line)
if not m:
return None, None
if hadoop_version is None:
# try both if hadoop_version not specified
counters_1, step_num_1 = parse_hadoop_counters_from_line(line, '0.20')
if counters_1:
return (counters_1, step_num_1)
else:
return parse_hadoop_counters_from_line(line, '0.18')
if uses_020_counters(hadoop_version):
parse_func = _parse_counters_0_20
else:
parse_func = _parse_counters_0_18
counter_substring = m.group('counters')
counters = {}
for group, counter, value in parse_func(counter_substring):
counters.setdefault(group, {})
counters[group].setdefault(counter, 0)
counters[group][counter] += int(value)
return counters, int(m.group('step_num'))
def _get_bucket(s3_conn, bucket_name):
"""Wrapper for s3_conn.get_bucket().
This only validate buckets in boto >= 2.25.0, which features quick
validation using HEAD requests (see Issue #865).
"""
return s3_conn.get_bucket(bucket_name,
validate=version_gte(boto.Version, '2.25.0'))
def _get_bucket(s3_conn, bucket_name):
"""Wrapper for s3_conn.get_bucket().
This only validate buckets in boto >= 2.25.0, which features quick
validation using HEAD requests (see Issue #865).
"""
return s3_conn.get_bucket(bucket_name,
validate=version_gte(boto.Version, '2.25.0'))
def mkdir(self, path):
args = ['fs', '-mkdir']
if version_gte(self.get_hadoop_version(), "2.0.0"):
args.append("-p")
args.append(path)
try:
self.invoke_hadoop(args, ok_stderr=[HADOOP_FILE_EXISTS_RE])
except CalledProcessError:
raise IOError("Could not mkdir %s" % path)
def run_job_flow(self, **kwargs):
# going to pop params from kwargs as we process then, and raise
# NotImplementedError at the end if any params are left
now = kwargs.pop('_Now', _boto3_now())
# our newly created cluster, as described by describe_cluster(), plus:
#
# _BootstrapActions: as described by list_bootstrap_actions()
# _InstanceGroups: as described by list_instance_groups()
# _Steps: as decribed by list_steps(), but not reversed
#
# TODO: at some point when we implement instance fleets,
# _InstanceGroups will become optional
cluster = dict(
_BootstrapActions=[],
_InstanceGroups=[],
_Steps=[],
Applications=[],
AutoTerminate=True,
Configurations=[],
Ec2InstanceAttributes=dict(
EmrManagedMasterSecurityGroup='sg-mockmaster',
EmrManagedSlaveSecurityGroup='sg-mockslave',
IamInstanceProfile='',
),
Id='j-MOCKCLUSTER%d' % len(self.mock_emr_clusters),
Name='',
NormalizedInstanceHours=0,
ScaleDownBehavior='TERMINATE_AT_TASK_COMPLETION',
ServiceRole='',
Status=dict(
State='STARTING',
StateChangeReason={},
Timeline=dict(CreationDateTime=now),
),
Tags=[],
TerminationProtected=False,
VisibleToAllUsers=False,
)
def _error(message):
return _ValidationException('RunJobFlow', message)
# Name (required)
_validate_param(kwargs, 'Name', string_types)
cluster['Name'] = kwargs.pop('Name')
# LogUri
if 'LogUri' in kwargs:
_validate_param(kwargs, 'LogUri', string_types)
cluster['LogUri'] = kwargs.pop('LogUri')
# JobFlowRole and ServiceRole (required)
_validate_param(kwargs, 'JobFlowRole', string_types)
cluster['Ec2InstanceAttributes']['IamInstanceProfile'] = kwargs.pop(
'JobFlowRole')
if 'ServiceRole' not in kwargs: # required by API, not boto3
raise _error('ServiceRole is required for creating cluster.')
_validate_param(kwargs, 'ServiceRole', string_types)
cluster['ServiceRole'] = kwargs.pop('ServiceRole')
# AmiVersion and ReleaseLabel
for version_param in ('AmiVersion', 'ReleaseLabel'):
if version_param in kwargs:
_validate_param(kwargs, version_param, string_types)
if 'AmiVersion' in kwargs:
if 'ReleaseLabel' in kwargs:
raise _error(
'Only one AMI version and release label may be specified.'
' Provided AMI: %s, release label: %s.' %
(kwargs['AmiVersion'], kwargs['ReleaseLabel']))
AmiVersion = kwargs.pop('AmiVersion')
running_ami_version = AMI_VERSION_ALIASES.get(
AmiVersion, AmiVersion)
if version_gte(running_ami_version, '4'):
raise _error('The supplied ami version is invalid.')
elif not version_gte(running_ami_version, '2'):
raise _error(
'Job flow role is not compatible with the supplied'
' AMI version')
cluster['RequestedAmiVersion'] = AmiVersion
cluster['RunningAmiVersion'] = running_ami_version
elif 'ReleaseLabel' in kwargs:
ReleaseLabel = kwargs.pop('ReleaseLabel')
running_ami_version = ReleaseLabel.lstrip('emr-')
if not version_gte(running_ami_version, '4'):
raise _error('The supplied release label is invalid: %s.' %
ReleaseLabel)
cluster['ReleaseLabel'] = ReleaseLabel
else:
# note: you can't actually set Hadoop version through boto3
raise _error('Must specify exactly one of the following:'
' release label, AMI version, or Hadoop version.')
# Applications
hadoop_version = map_version(running_ami_version,
AMI_HADOOP_VERSION_UPDATES)
if version_gte(running_ami_version, '4'):
application_names = set(a['Name']
for a in kwargs.pop('Applications', []))
# if Applications is set but doesn't include Hadoop, the
# cluster description won't either! (Even though Hadoop is
# in fact installed.)
if not application_names:
application_names = set(['Hadoop'])
for app_name in sorted(application_names):
if app_name == 'Hadoop':
version = hadoop_version
else:
version = DUMMY_APPLICATION_VERSION
cluster['Applications'].append(
dict(Name=app_name, Version=version))
else:
if kwargs.get('Applications'):
raise _error(
'Cannot specify applications when AMI version is used.'
' Specify supported products or new supported products'
' instead.')
# 'hadoop' is lowercase if AmiVersion specified
cluster['Applications'].append(
dict(Name='hadoop', Version=hadoop_version))
# Configurations
if 'Configurations' in kwargs:
_validate_param(kwargs, 'Configurations', (list, tuple))
if kwargs['Configurations'] and not version_gte(
running_ami_version, '4'):
raise _ValidationException(
'RunJobFlow',
'Cannot specify configurations when AMI version is used.')
cluster['Configurations'] = _normalized_configurations(
kwargs.pop('Configurations'))
# VisibleToAllUsers
if 'VisibleToAllUsers' in kwargs:
_validate_param(kwargs, 'VisibleToAllUsers', bool)
cluster['VisibleToAllUsers'] = kwargs.pop('VisibleToAllUsers')
# pass BootstrapActions off to helper
if 'BootstrapActions' in kwargs:
self._add_bootstrap_actions('RunJobFlow',
kwargs.pop('BootstrapActions'),
cluster)
# pass Instances (required) off to helper
_validate_param(kwargs, 'Instances')
self._add_instances('RunJobFlow',
kwargs.pop('Instances'),
cluster,
now=now)
# pass Steps off to helper
if 'Steps' in kwargs:
self._add_steps('RunJobFlow', kwargs.pop('Steps'), cluster)
# pass Tags off to helper
if 'Tags' in kwargs:
self._add_tags('RunJobFlow', kwargs.pop('Tags'), cluster)
# save AdditionalInfo
if 'AdditionalInfo' in kwargs:
cluster['_AdditionalInfo'] = kwargs.pop('AdditionalInfo')
# catch extra params
if kwargs:
raise NotImplementedError(
'mock RunJobFlow does not support these parameters: %s' %
', '.join(sorted(kwargs)))
self.mock_emr_clusters[cluster['Id']] = cluster
return dict(JobFlowId=cluster['Id'])