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)