def get_service(self, node_process):
ui_name = self.get_service_name_by_node_process(node_process)
if ui_name is None:
raise e.PluginInvalidDataException(
_('Service not found in services list'))
version = self.get_chosen_service_version(ui_name)
service = self._find_service_instance(ui_name, version)
if service is None:
raise e.PluginInvalidDataException(_('Can not map service'))
return service
def _create_config_obj(self, item, target='general', scope='cluster',
high_priority=False):
def _prepare_value(value):
if isinstance(value, str):
return value.strip().lower()
return value
conf_name = _prepare_value(item.get('name', None))
conf_value = _prepare_value(item.get('value', None))
if not conf_name:
raise ex.HadoopProvisionError(_("Config missing 'name'"))
if conf_value is None:
raise ex.PluginInvalidDataException(
_("Config '%s' missing 'value'") % conf_name)
if high_priority or item.get('priority', 2) == 1:
priority = 1
else:
priority = 2
return p.Config(
name=conf_name,
applicable_target=target,
scope=scope,
config_type=item.get('config_type', "string"),
config_values=item.get('config_values', None),
default_value=conf_value,
is_optional=item.get('is_optional', True),
description=item.get('description', None),
priority=priority)
def validate_job_execution(self, cluster, job, data):
if not self.edp_supported(cluster.hadoop_version):
raise ex.PluginInvalidDataException(
_('Storm {base} required to run {type} jobs').format(
base=EdpPyleusEngine.edp_base_version, type=job.type))
super(EdpPyleusEngine, self).validate_job_execution(cluster, job, data)
def validate_job_execution(self, cluster, job, data):
if (not self.edp_supported(cluster.hadoop_version)
or not v_utils.get_spark_history_server(cluster)):
raise ex.PluginInvalidDataException(
_('Spark {base} or higher required to run {type} jobs').format(
base=EdpSparkEngine.edp_base_version, type=job.type))
super(EdpSparkEngine, self).validate_job_execution(cluster, job, data)
def validate_job_execution(self, cluster, job, data):
if not self.edp_supported(cluster.hadoop_version):
raise pl_ex.PluginInvalidDataException(
_('Cloudera {base} or higher required to run {type}'
'jobs').format(base=self.edp_base_version, type=job.type))
shs_count = u.get_instances_count(cluster, 'SPARK_YARN_HISTORY_SERVER')
if shs_count != 1:
raise pl_ex.InvalidComponentCountException(
'SPARK_YARN_HISTORY_SERVER', '1', shs_count)
super(EdpSparkEngine, self).validate_job_execution(cluster, job, data)
def validate_job_execution(self, cluster, job, data):
if not self.edp_supported(cluster.hadoop_version):
raise pex.PluginInvalidDataException(
_('Ambari plugin of {base} or higher required to run {type} '
'jobs').format(base=EDPSparkEngine.edp_base_version,
type=job.type))
spark_nodes_count = plugin_utils.get_instances_count(
cluster, p_common.SPARK_JOBHISTORYSERVER)
if spark_nodes_count != 1:
raise pex.InvalidComponentCountException(
p_common.SPARK_JOBHISTORYSERVER, '1', spark_nodes_count)
super(EDPSparkEngine, self).validate_job_execution(cluster, job, data)
