def stop_all_hbase():
header_key = request.headers.get('API-KEY')
api_status = check_apiKey(header_key)
if api_status == 'success':
conn = get_postgres_connection()
cur = conn.cursor()
sql = "select status from hbase_hbase where type=1"
cur.execute(sql)
rows = cur.fetchall()
status_list = [' '.join(item) for item in rows]
if "RUNNING" in status_list:
result = run_services.run_bigdata_services(
hbase_stop_cmd, 'HBase Service Stopped',
'Error Stopping HBase Services')
update_hbase_master()
if json.loads(result)["success"]:
cur.execute(sql)
rows = cur.fetchall()
status_list = [' '.join(item) for item in rows]
if "RUNNING" in status_list:
cur.close()
conn.close()
return '{"success": 2, "msg": ["HBase Service not Stopped!!!"]}'
else:
cur.close()
conn.close()
return result
else:
cur.close()
conn.close()
return result
else:
return '{"success": 1}'
else:
return api_status
def dfs_stop():
'''
Stops dfs services (namenode, datanode, zkfc, journalnode)
:return: success if dfs_stop_cmd runs successfully else error message is shown
'''
log.info("\nStopping DFS Services\n")
header_key = request.headers.get('API-KEY')
api_status = check_apiKey(header_key)
if api_status == 'success':
conn = get_postgres_connection()
cur = conn.cursor()
sql = "select status from hdfs_hdfs where type=1"
cur.execute(sql)
rows = cur.fetchall()
cur.close()
conn.close()
status_list = [' '.join(item) for item in rows]
if "RUNNING" in status_list:
result = run_services.run_bigdata_services(dfs_stop_cmd, 'Stopped DFS Services', 'Error Stopping DFS Services')
if json.loads(result)["success"]:
update_namenode_info()
return result
else:
update_namenode_info()
return '{"success": 1}'
else:
return api_status
def stop_spark():
'''
Stops spark
:return: Returns success if spark_stop command executes successfully or error message is shown
'''
log.info("\nStopping spark\n")
header_key = request.headers.get('API-KEY')
api_status = check_apiKey(header_key)
if api_status == 'success':
conn = get_postgres_connection()
cur = conn.cursor()
sql = "select status from spark_spark where type=1"
cur.execute(sql)
rows = cur.fetchall()
status_list = [' '.join(item) for item in rows]
if "RUNNING" in status_list:
result = run_services.run_bigdata_services(spark_stop_cmd,
'spark Stopped',
'Error Stopping spark')
if json.loads(result)["success"]:
sql = """UPDATE spark_spark set status='SHUTDOWN' where type=1 and state=1;"""
cur.execute(sql)
conn.commit()
cur.close()
conn.close()
return result
else:
cur.close()
conn.close()
return '{"success": 1}'
else:
return api_status
def dn_stop(cluster_id):
ip = get_system_ip()
sql = "select id, status, web_port, rpyc_port from hdfs_hdfs where ip='%s' and type=0 and cluster_id=%d" % (ip, cluster_id)
rs = run_services.get_service_status(sql)
id = rs[0]
status = rs[1]
web_port = rs[2]
rpyc_port = rs[3]
if status == "RUNNING":
result = run_services.run_bigdata_services(datanode_stop_cmd, 'Datanode Stopped', 'Error Stopping Datanode')
return run_services.confirm_stop(result, "hdfs_hdfs", id, web_port, rpyc_port)
else:
return '{"success": 1, "msg": ["Datanode Already Stopped!!!"]}'
def dfs_start():
'''
Starts dfs services (namenode, datanode, zkfc, journalnode)
:return: success if dfs_start_cmd runs successfully else error message is shown
'''
log.info("\nStarting DFS Services\n")
header_key = request.headers.get('API-KEY')
api_status = check_apiKey(header_key)
if api_status == 'success':
result = run_services.run_bigdata_services(dfs_start_cmd, 'Started DFS Service', 'Error Starting DFS Services')
update_namenode_info()
return result
else:
return api_status
def nn_start(cluster_id):
ip = get_system_ip()
sql = "select id, status, web_port, rpyc_port from hdfs_hdfs where ip='%s' and type=1 and cluster_id=%d" % (ip, cluster_id)
rs = run_services.get_service_status(sql)
id = rs[0]
status = rs[1]
web_port = rs[2]
rpyc_port = rs[3]
if status != "RUNNING":
result = run_services.run_bigdata_services(namenode_start_cmd, 'Namenode Started', 'Error Starting Namenode')
update_namenode_info()
return run_services.confirm_start(result, "hdfs_hdfs", id, web_port, rpyc_port)
else:
return '{"success": 1, "msg": ["Namenode Already Running!!!"]}'
def es_start(cluster_id):
ip = get_system_ip()
sql = "select id, status, web_port, rpyc_port from elastic_search_elastic_search where ip='%s' and cluster_id=%d" % (ip, cluster_id)
rs = run_services.get_service_status(sql)
id = rs[0]
status = rs[1]
web_port = rs[2]
rpyc_port = rs[3]
if status != "RUNNING":
es_process_name = get_es_process_name()
es_start_cmd = es_start_systemd_cmd if es_process_name == "systemd" else es_start_sysvinit_cmd if es_process_name == "sysv_init" else es_start_bin_cmd
result = run_services.run_bigdata_services(es_start_cmd, 'ES Started',
'Error Starting ES')
return run_services.confirm_start(result, "elastic_search_elastic_search", id, web_port, rpyc_port)
else:
return '{"success": 1, "msg": ["ES Already Running!!!"]}'
def yarn_start():
'''
Starts yarn services (nodemanager, resourcemanager)
:return: Returns success if yarn_start_cmd command executes successfully or error message is shown
'''
log.info("\nStarting Yarn\n")
header_key = request.headers.get('API-KEY')
api_status = check_apiKey(header_key)
if api_status == 'success':
result = run_services.run_bigdata_services(
yarn_start_cmd, 'Started Yarn Services',
'Error Starting Yarn Services')
update_rm_info()
return result
else:
return api_status
def nm_stop(cluster_id):
ip = get_system_ip()
sql = "select id, status, web_port, rpyc_port from yarn_yarn where ip='%s' and type=0 and cluster_id=%d" % (
ip, cluster_id)
rs = run_services.get_service_status(sql)
id = rs[0]
status = rs[1]
web_port = rs[2]
rpyc_port = rs[3]
if status == "RUNNING":
result = run_services.run_bigdata_services(
nm_stop_cmd, 'Node manager Stopped', 'Error Stopping Node manager')
update_rm_info()
return run_services.confirm_stop(result, "yarn_yarn", id, web_port,
rpyc_port)
else:
return '{"success": 1, "msg": ["Node Manager Already Stopped!!!"]}'
def sps_stop(cluster_id):
ip = get_system_ip()
sql = "select id, status, web_port, rpyc_port from spark_spark where ip='%s' and type=0 and cluster_id=%d" % (
ip, cluster_id)
rs = run_services.get_service_status(sql)
id = rs[0]
status = rs[1]
web_port = rs[2]
rpyc_port = rs[3]
if status == "RUNNING":
result = run_services.run_bigdata_services(
stop_spark_slave_cmd, 'spark slave stopped',
'Error Stopping Spark Slave')
return run_services.confirm_stop(result, "spark_spark", id, web_port,
rpyc_port)
else:
return '{"success": 1, "msg": ["Spark Slave Already Stopped!!!"]}'
def spm_start(cluster_id):
ip = get_system_ip()
sql = "select id, status, web_port, rpyc_port from spark_spark where ip='%s' and type=1 and cluster_id=%d" % (
ip, cluster_id)
rs = run_services.get_service_status(sql)
id = rs[0]
status = rs[1]
web_port = rs[2]
rpyc_port = rs[3]
if status != "RUNNING":
result = run_services.run_bigdata_services(
start_spark_master_cmd, 'spark master started',
'Error Starting Spark Master')
return run_services.confirm_start(result, "spark_spark", id, web_port,
rpyc_port)
else:
return '{"success": 1, "msg": ["Spark Master Already Running!!!"]}'
def master_stop(cluster_id):
ip = get_system_ip()
sql = "select id, status, web_port, rpyc_port from hbase_hbase where ip='%s' and type=1 and cluster_id=%d" % (
ip, cluster_id)
rs = run_services.get_service_status(sql)
id = rs[0]
status = rs[1]
web_port = rs[2]
rpyc_port = rs[3]
if status == "RUNNING":
result = run_services.run_bigdata_services(
hmaster_stop_cmd, 'HMaster Stopped', 'Error Stopping HBase Master')
update_hbase_master()
return run_services.confirm_stop(result, "hbase_hbase", id, web_port,
rpyc_port)
else:
return '{"success": 1, "msg": ["HMaster Already Stopped!!!"]}'
def rm_start(cluster_id):
ip = get_system_ip()
sql = "select id, status, web_port, rpyc_port from yarn_yarn where ip='%s' and type=1 and cluster_id=%d" % (
ip, cluster_id)
rs = run_services.get_service_status(sql)
id = rs[0]
status = rs[1]
web_port = rs[2]
rpyc_port = rs[3]
if status != "RUNNING":
result = run_services.run_bigdata_services(
rm_start_cmd, 'Resource manager Started',
'Error Starting Resource manager')
update_rm_info()
return run_services.confirm_start(result, "yarn_yarn", id, web_port,
rpyc_port)
else:
return '{"success": 1, "msg": ["Resource Manager Already Running!!!"]}'
def regionserver_start(cluster_id):
ip = get_system_ip()
sql = "select id, status, web_port, rpyc_port from hbase_hbase where ip='%s' and type=0 and cluster_id=%d" % (
ip, cluster_id)
rs = run_services.get_service_status(sql)
id = rs[0]
status = rs[1]
web_port = rs[2]
rpyc_port = rs[3]
if status != "RUNNING":
result = run_services.run_bigdata_services(
hregionserver_start_cmd, 'Regionserver Started',
'Error Starting Regionserver')
update_hbase_master()
return run_services.confirm_start(result, "hbase_hbase", id, web_port,
rpyc_port)
else:
return '{"success": 1, "msg": ["Regionserver Already Running!!!"]}'
def hbase_start():
'''
Starts hbase services (hbase master, hbase regionserver)
:return: success if hbase_start_cmd runs successfully else error message is shown
'''
log.info("\nStarting HBase\n")
header_key = request.headers.get('API-KEY')
api_status = check_apiKey(header_key)
if api_status == 'success':
result = run_services.run_bigdata_services(
hbase_start_cmd, 'HBase Services Started',
'Error Starting HBase Services')
up_status = update_hbase_master()
if up_status is not None:
if up_status["success"] == 0:
return json.dumps(up_status)
return result
else:
return api_status
def yarn_stop():
log.info("\nStopping Yarn\n")
header_key = request.headers.get('API-KEY')
api_status = check_apiKey(header_key)
if api_status == 'success':
conn = get_postgres_connection()
cur = conn.cursor()
sql = "select status from yarn_yarn where type=1"
cur.execute(sql)
rows = cur.fetchall()
cur.close()
conn.close()
status_list = [' '.join(item) for item in rows]
if "RUNNING" in status_list:
result = run_services.run_bigdata_services(
yarn_stop_cmd, 'Stopped Yarn Services',
'Error Stopping Yarn Services')
if json.loads(result)["success"]:
update_rm_info()
return result
else:
return '{"success": 1}'
else:
return api_status