def __init__(self, app_id, info_plugin, collect_period=2, retries=10):
Plugin.__init__(self,
app_id,
info_plugin,
collect_period,
retries=retries)
kubernetes.config.load_kube_config()
self.enable_monasca = info_plugin['graphic_metrics']
if self.enable_monasca:
self.monasca = MonascaConnector()
self.submission_url = info_plugin['count_jobs_url']
self.expected_time = int(info_plugin['expected_time'])
self.number_of_jobs = int(info_plugin['number_of_jobs'])
self.submission_time = datetime.strptime(
info_plugin['submission_time'], '%Y-%m-%dT%H:%M:%S.%fGMT')
self.dimensions = {
'application_id': self.app_id,
'service': 'kubejobs'
}
self.rds = redis.StrictRedis(host=info_plugin['redis_ip'],
port=info_plugin['redis_port'])
self.metric_queue = "%s:metrics" % self.app_id
self.current_job_id = 0
self.b_v1 = kubernetes.client.BatchV1Api()
def __init__(self, app_id, info_plugin, retries=60):
Plugin.__init__(self,
app_id,
info_plugin,
collect_period=5,
retries=retries)
self.monasca = MonascaConnector()
self.submission_url = info_plugin['spark_submisson_url']
self.expected_time = info_plugin['expected_time']
self.remaining_time = int(self.expected_time)
self.job_expected_time = int(self.expected_time)
self.number_of_jobs = int(info_plugin['number_of_jobs'])
self.current_job_id = 0
self.dimensions = {
'application_id': self.app_id,
'service': 'spark-sahara'
}
self.conn = paramiko.SSHClient()
self.conn.set_missing_host_key_policy(paramiko.AutoAddPolicy())
self.conn.connect(hostname=api.mesos_cluster_addr,
username=api.mesos_username,
password=api.mesos_password)
self.spark_id = self._discover_id_from_spark()
def __init__(self,
app_id,
info_plugin,
collect_period=2,
retries=10,
last_replicas=None):
Plugin.__init__(self,
app_id,
info_plugin,
collect_period,
retries=retries)
self.validate(info_plugin)
self.LOG = Log(LOG_NAME, LOG_FILE)
self.enable_detailed_report = info_plugin['enable_detailed_report']
self.expected_time = int(info_plugin['expected_time'])
self.number_of_jobs = int(info_plugin['number_of_jobs'])
self.submission_time = self.get_submission_time(info_plugin)
self.dimensions = self.get_dimensions()
self.rds = self.setup_redis(info_plugin)
self.metric_queue = "%s:metrics" % self.app_id
self.current_job_id = 0
self.job_report = JobReport(info_plugin)
self.report_flag = True
self.enable_generate_job_report = False
self.last_replicas = last_replicas
self.last_error = 0.0
self.last_progress = 0.0
kubernetes.config.load_kube_config(api.k8s_manifest)
self.b_v1 = kubernetes.client.BatchV1Api()
self.datasource = self.setup_datasource(info_plugin)
def __init__(self, app_id, info_plugin, collect_period=2, retries=60, monasca_conn="monasca"):
Plugin.__init__(self, app_id, info_plugin,
collect_period, retries=retries)
if monasca_conn == "monasca":
self.monasca = MonascaConnector()
else:
self.monasca = monasca_conn
self.submission_url = info_plugin['spark_submisson_url']
self.expected_time = info_plugin['expected_time']
self.number_of_jobs = int(info_plugin['number_of_jobs'])
self.job_expected_time = (float(self.expected_time)
/ float(self.number_of_jobs))
self.remaining_time = float(self.expected_time)
self.current_job_id = 0
self.app_id = app_id
self.dimensions = {'application_id': self.app_id,
'service': 'spark-sahara'}
self.job_ratio = 1.0 / self.number_of_jobs
self.first_submission_time = None
def __init__(self, app_id, info_plugin, collect_period=2, retries=10):
Plugin.__init__(self, app_id, info_plugin,
collect_period, retries=retries)
self.enable_visualizer = info_plugin['enable_visualizer']
self.submission_url = info_plugin['count_jobs_url']
self.expected_time = int(info_plugin['expected_time'])
self.number_of_jobs = int(info_plugin['number_of_jobs'])
self.submission_time = datetime.strptime(info_plugin['submission_time'],
'%Y-%m-%dT%H:%M:%S.%fGMT')
self.dimensions = {'application_id': self.app_id,
'service': 'kubejobs'}
self.rds = redis.StrictRedis(host=info_plugin['redis_ip'],
port=info_plugin['redis_port'])
self.metric_queue = "%s:metrics" % self.app_id
self.current_job_id = 0
kubernetes.config.load_kube_config()
self.b_v1 = kubernetes.client.BatchV1Api()
if self.enable_visualizer:
datasource_type = info_plugin['datasource_type']
if datasource_type == "monasca":
self.datasource = MonascaConnector()
elif datasource_type == "influxdb":
influx_url = info_plugin['database_data']['url']
influx_port = info_plugin['database_data']['port']
database_name = info_plugin['database_data']['name']
self.datasource = InfluxConnector(influx_url, influx_port, database_name)
else:
print("Unknown datasource type...!")
def __init__(self, app_id, info_plugin, keypair, retries=60):
Plugin.__init__(self, app_id, info_plugin,
collect_period=5, retries=retries)
self.app_id = app_id
self.host_ip = info_plugin['host_ip']
self.keypair_path = keypair
self.host_username = info_plugin['host_username']
self.log_path = info_plugin['log_path']
self.dimensions = {'app_id': self.app_id, 'host': self.host_ip}
self.last_checked = ''
self.monasca = MonascaConnector()
def __init__(self, app_id, info_plugin, keypair, retries=60):
Plugin.__init__(self, app_id, info_plugin, collect_period=5,
retries=retries)
self.app_id = app_id
self.host_ip = info_plugin['host_ip']
self.expected_time = info_plugin['expected_time']
self.log_path = info_plugin['log_path']
self.keypair_path = keypair
self.host_username = '******'
self.dimensions = {"application_id": self.app_id,
"host": self.host_ip}
self.last_checked = ''
self.start_time = time.time()
self.monasca = MonascaConnector()