def start_cluster(self, cluster):
nn_instance = utils.get_instance(cluster, "namenode")
sm_instance = utils.get_instance(cluster, "master")
dn_instances = utils.get_instances(cluster, "datanode")
# Start the name node
with remote.get_remote(nn_instance) as r:
run.format_namenode(r)
run.start_processes(r, "namenode")
# start the data nodes
self._start_slave_datanode_processes(dn_instances)
LOG.info(_LI("Hadoop services in cluster %s have been started"),
cluster.name)
with remote.get_remote(nn_instance) as r:
r.execute_command("sudo -u hdfs hdfs dfs -mkdir -p /user/$USER/")
r.execute_command("sudo -u hdfs hdfs dfs -chown $USER "
"/user/$USER/")
# start spark nodes
if sm_instance:
with remote.get_remote(sm_instance) as r:
run.start_spark_master(r, self._spark_home(cluster))
LOG.info(_LI("Spark service at '%s' has been started"),
sm_instance.hostname())
LOG.info(_LI('Cluster %s has been started successfully'), cluster.name)
self._set_cluster_info(cluster)
def _extract_configs_to_extra(self, cluster):
nn = utils.get_instance(cluster, "namenode")
sp_master = utils.get_instance(cluster, "master")
sp_slaves = utils.get_instances(cluster, "slave")
extra = dict()
config_master = config_slaves = ""
if sp_master is not None:
config_master = c_helper.generate_spark_env_configs(cluster)
if sp_slaves is not None:
slavenames = []
for slave in sp_slaves:
slavenames.append(slave.hostname())
config_slaves = c_helper.generate_spark_slaves_configs(slavenames)
else:
config_slaves = "\n"
for ng in cluster.node_groups:
extra[ng.id] = {
"xml": c_helper.generate_xml_configs(ng.configuration(), ng.storage_paths(), nn.hostname(), None),
"setup_script": c_helper.generate_hadoop_setup_script(
ng.storage_paths(), c_helper.extract_hadoop_environment_confs(ng.configuration())
),
"sp_master": config_master,
"sp_slaves": config_slaves,
}
if c_helper.is_data_locality_enabled(cluster):
topology_data = th.generate_topology_map(cluster, CONF.enable_hypervisor_awareness)
extra["topology_data"] = "\n".join([k + " " + v for k, v in topology_data.items()]) + "\n"
return extra
def start_cluster(self, cluster):
nn_instance = utils.get_instance(cluster, "namenode")
sm_instance = utils.get_instance(cluster, "master")
dn_instances = utils.get_instances(cluster, "datanode")
# Start the name node
with remote.get_remote(nn_instance) as r:
run.format_namenode(r)
run.start_processes(r, "namenode")
# start the data nodes
self._start_slave_datanode_processes(dn_instances)
LOG.info("Hadoop services in cluster %s have been started" %
cluster.name)
with remote.get_remote(nn_instance) as r:
r.execute_command("sudo -u hdfs hdfs dfs -mkdir -p /user/$USER/")
r.execute_command(("sudo -u hdfs hdfs dfs -chown $USER "
"/user/$USER/"))
# start spark nodes
if sm_instance:
with remote.get_remote(sm_instance) as r:
run.start_spark_master(r, self._spark_home(cluster))
LOG.info("Spark service at '%s' has been started",
sm_instance.hostname())
LOG.info('Cluster %s has been started successfully' % cluster.name)
self._set_cluster_info(cluster)
def scale_cluster(self, cluster, instances):
master = utils.get_instance(cluster, "master")
r_master = remote.get_remote(master)
run.stop_spark(r_master, self._spark_home(cluster))
self._setup_instances(cluster, instances)
nn = utils.get_instance(cluster, "namenode")
run.refresh_nodes(remote.get_remote(nn), "dfsadmin")
self._start_slave_datanode_processes(instances)
run.start_spark_master(r_master, self._spark_home(cluster))
LOG.info(_LI("Spark master service at '%s' has been restarted"), master.hostname())
def scale_cluster(self, cluster, instances):
master = utils.get_instance(cluster, "master")
r_master = remote.get_remote(master)
run.stop_spark(r_master, self._spark_home(cluster))
self._setup_instances(cluster, instances)
nn = utils.get_instance(cluster, "namenode")
run.refresh_nodes(remote.get_remote(nn), "dfsadmin")
self._start_slave_datanode_processes(instances)
run.start_spark_master(r_master, self._spark_home(cluster))
LOG.info(_LI("Spark master service at '%s' has been restarted"),
master.hostname())
def scale_cluster(cluster, instances):
scale_ins_hosts = [i.fqdn() for i in instances]
dn_hosts = [dn.fqdn() for dn in u.get_datanodes(cluster)]
tt_hosts = [tt.fqdn() for tt in u.get_tasktrackers(cluster)]
to_scale_dn = []
to_scale_tt = []
for i in scale_ins_hosts:
if i in dn_hosts:
to_scale_dn.append(i)
if i in tt_hosts:
to_scale_tt.append(i)
client = c.IntelClient(u.get_instance(cluster, 'manager'), cluster.name)
rack = '/Default'
client.nodes.add(scale_ins_hosts, rack, 'hadoop',
'/home/hadoop/.ssh/id_rsa')
client.cluster.install_software(scale_ins_hosts)
if to_scale_tt:
client.services.mapred.add_nodes('TaskTracker', to_scale_tt)
if to_scale_dn:
client.services.hdfs.add_nodes('DataNode', to_scale_dn)
client.nodes.config()
if to_scale_dn:
client.services.hdfs.start()
if to_scale_tt:
client.services.mapred.start()
def install_cluster(cluster):
mng_instance = u.get_instance(cluster, 'manager')
all_hosts = list(set([i.fqdn() for i in u.get_instances(cluster)]))
client = c.IntelClient(mng_instance, cluster.name)
LOG.info("Create cluster")
client.cluster.create()
LOG.info("Add nodes to cluster")
rack = '/Default'
client.nodes.add(all_hosts, rack, 'hadoop',
'/home/hadoop/.ssh/id_rsa')
LOG.info("Install software")
client.cluster.install_software(all_hosts)
LOG.info("Configure services")
_configure_services(client, cluster)
LOG.info("Deploy cluster")
client.nodes.config(force=True)
LOG.info("Provisioning configs")
# cinder and ephemeral drive support
_configure_storage(client, cluster)
# swift support
_configure_swift(client, cluster)
# user configs
_add_user_params(client, cluster)
LOG.info("Format HDFS")
client.services.hdfs.format()
def scale_cluster(cluster, instances):
scale_ins_hosts = [i.fqdn() for i in instances]
dn_hosts = [dn.fqdn() for dn in u.get_datanodes(cluster)]
tt_hosts = [tt.fqdn() for tt in u.get_tasktrackers(cluster)]
to_scale_dn = []
to_scale_tt = []
for i in scale_ins_hosts:
if i in dn_hosts:
to_scale_dn.append(i)
if i in tt_hosts:
to_scale_tt.append(i)
client = c.IntelClient(u.get_instance(cluster, 'manager'), cluster.name)
rack = '/Default'
client.nodes.add(scale_ins_hosts, rack, 'hadoop',
'/home/hadoop/.ssh/id_rsa')
client.cluster.install_software(scale_ins_hosts)
if to_scale_tt:
client.services.mapred.add_nodes('TaskTracker', to_scale_tt)
if to_scale_dn:
client.services.hdfs.add_nodes('DataNode', to_scale_dn)
client.nodes.config()
if to_scale_dn:
client.services.hdfs.start()
if to_scale_tt:
client.services.mapred.start()
def install_cluster(cluster):
mng_instance = u.get_instance(cluster, 'manager')
all_hosts = list(set([i.fqdn() for i in u.get_instances(cluster)]))
client = c.IntelClient(mng_instance, cluster.name)
LOG.info("Create cluster")
client.cluster.create()
LOG.info("Add nodes to cluster")
rack = '/Default'
client.nodes.add(all_hosts, rack, 'hadoop', '/home/hadoop/.ssh/id_rsa')
LOG.info("Install software")
client.cluster.install_software(all_hosts)
LOG.info("Configure services")
_configure_services(client, cluster)
LOG.info("Deploy cluster")
client.nodes.config(force=True)
LOG.info("Provisioning configs")
# cinder and ephemeral drive support
_configure_storage(client, cluster)
# swift support
_configure_swift(client, cluster)
# user configs
_add_user_params(client, cluster)
LOG.info("Format HDFS")
client.services.hdfs.format()
def decommission_nodes(cluster, instances):
dec_hosts = [i.fqdn() for i in instances]
dn_hosts = [dn.fqdn() for dn in u.get_datanodes(cluster)]
nm_hosts = [nm.fqdn() for nm in u.get_nodemanagers(cluster)]
client = c.IntelClient(u.get_instance(cluster, 'manager'), cluster.name)
dec_dn_hosts = []
for dec_host in dec_hosts:
if dec_host in dn_hosts:
dec_dn_hosts.append(dec_host)
if dec_dn_hosts:
client.services.hdfs.decommission_nodes(dec_dn_hosts)
#TODO(alazarev) make timeout configurable (bug #1262897)
timeout = 14400 # 4 hours
cur_time = 0
for host in dec_dn_hosts:
while cur_time < timeout:
if client.services.hdfs.get_datanode_status(
host) == 'Decomissioned':
break
context.sleep(5)
cur_time += 5
else:
LOG.warn("Failed to decomission node '%s' of cluster '%s' "
"in %s minutes" % (host, cluster.name, timeout / 60))
client.nodes.stop(dec_hosts)
# wait stop services
#TODO(alazarev) make timeout configurable (bug #1262897)
timeout = 600 # 10 minutes
cur_time = 0
for instance in instances:
while cur_time < timeout:
stopped = True
if instance.fqdn() in dn_hosts:
stopped = stopped and _is_hadoop_service_stopped(
instance, 'hadoop-hdfs-datanode')
if instance.fqdn() in nm_hosts:
stopped = stopped and _is_hadoop_service_stopped(
instance, 'hadoop-yarn-nodemanager')
if stopped:
break
else:
context.sleep(5)
cur_time += 5
else:
LOG.warn("Failed to stop services on node '%s' of cluster '%s' "
"in %s minutes" % (instance, cluster.name, timeout / 60))
for node in dec_hosts:
LOG.info("Deleting node '%s' on cluster '%s'" % (node, cluster.name))
client.nodes.delete(node)
def _set_cluster_info(self, cluster):
nn = utils.get_instance(cluster, "namenode")
sp_master = utils.get_instance(cluster, "master")
info = {}
if nn:
address = c_helper.get_config_value("HDFS", "dfs.http.address", cluster)
port = address[address.rfind(":") + 1 :]
info["HDFS"] = {"Web UI": "http://%s:%s" % (nn.management_ip, port)}
info["HDFS"]["NameNode"] = "hdfs://%s:8020" % nn.hostname()
if sp_master:
port = c_helper.get_config_value("Spark", "Master webui port", cluster)
if port is not None:
info["Spark"] = {"Web UI": "http://%s:%s" % (sp_master.management_ip, port)}
ctx = context.ctx()
conductor.cluster_update(ctx, cluster, {"info": info})
def _extract_configs_to_extra(self, cluster):
nn = utils.get_instance(cluster, "namenode")
sp_master = utils.get_instance(cluster, "master")
sp_slaves = utils.get_instances(cluster, "slave")
extra = dict()
config_master = config_slaves = ''
if sp_master is not None:
config_master = c_helper.generate_spark_env_configs(cluster)
if sp_slaves is not None:
slavenames = []
for slave in sp_slaves:
slavenames.append(slave.hostname())
config_slaves = c_helper.generate_spark_slaves_configs(slavenames)
else:
config_slaves = "\n"
for ng in cluster.node_groups:
extra[ng.id] = {
'xml':
c_helper.generate_xml_configs(
ng.configuration(),
ng.storage_paths(),
nn.hostname(),
None,
),
'setup_script':
c_helper.generate_hadoop_setup_script(
ng.storage_paths(),
c_helper.extract_hadoop_environment_confs(
ng.configuration())),
'sp_master':
config_master,
'sp_slaves':
config_slaves
}
if c_helper.is_data_locality_enabled(cluster):
topology_data = th.generate_topology_map(
cluster, CONF.enable_hypervisor_awareness)
extra['topology_data'] = "\n".join(
[k + " " + v for k, v in topology_data.items()]) + "\n"
return extra
def decommission_nodes(self, cluster, instances):
sls = utils.get_instances(cluster, "slave")
dns = utils.get_instances(cluster, "datanode")
decommission_dns = False
decommission_sls = False
for i in instances:
if 'datanode' in i.node_group.node_processes:
dns.remove(i)
decommission_dns = True
if 'slave' in i.node_group.node_processes:
sls.remove(i)
decommission_sls = True
nn = utils.get_instance(cluster, "namenode")
spark_master = utils.get_instance(cluster, "master")
if decommission_sls:
sc.decommission_sl(spark_master, instances, sls)
if decommission_dns:
sc.decommission_dn(nn, instances, dns)
def decommission_nodes(self, cluster, instances):
sls = utils.get_instances(cluster, "slave")
dns = utils.get_instances(cluster, "datanode")
decommission_dns = False
decommission_sls = False
for i in instances:
if 'datanode' in i.node_group.node_processes:
dns.remove(i)
decommission_dns = True
if 'slave' in i.node_group.node_processes:
sls.remove(i)
decommission_sls = True
nn = utils.get_instance(cluster, "namenode")
spark_master = utils.get_instance(cluster, "master")
if decommission_sls:
sc.decommission_sl(spark_master, instances, sls)
if decommission_dns:
sc.decommission_dn(nn, instances, dns)
def _set_cluster_info(self, cluster):
nn = utils.get_instance(cluster, "namenode")
sp_master = utils.get_instance(cluster, "master")
info = {}
if nn:
address = c_helper.get_config_value('HDFS', 'dfs.http.address',
cluster)
port = address[address.rfind(':') + 1:]
info['HDFS'] = {
'Web UI': 'http://%s:%s' % (nn.management_ip, port)
}
info['HDFS']['NameNode'] = 'hdfs://%s:8020' % nn.hostname()
if sp_master:
port = c_helper.get_config_value('Spark', 'Master webui port',
cluster)
if port is not None:
info['Spark'] = {
'Web UI': 'http://%s:%s' % (sp_master.management_ip, port)
}
ctx = context.ctx()
conductor.cluster_update(ctx, cluster, {'info': info})
def _set_cluster_info(self, cluster):
nn = utils.get_instance(cluster, "namenode")
sp_master = utils.get_instance(cluster, "master")
info = {}
if nn:
address = c_helper.get_config_value(
'HDFS', 'dfs.http.address', cluster)
port = address[address.rfind(':') + 1:]
info['HDFS'] = {
'Web UI': 'http://%s:%s' % (nn.management_ip, port)
}
info['HDFS']['NameNode'] = 'hdfs://%s:8020' % nn.hostname()
if sp_master:
port = c_helper.get_config_value(
'Spark', 'Master webui port', cluster)
if port is not None:
info['Spark'] = {
'Web UI': 'http://%s:%s' % (sp_master.management_ip, port)
}
ctx = context.ctx()
conductor.cluster_update(ctx, cluster, {'info': info})
def start_cluster(self, cluster):
sm_instance = utils.get_instance(cluster, "master")
sl_instances = utils.get_instances(cluster, "slave")
# start storm master
if sm_instance:
with remote.get_remote(sm_instance) as r:
run.start_storm_master(r)
LOG.info("Storm master at '%s' has been started",
sm_instance.hostname())
# start storm slaves
self._start_slave_processes(sl_instances)
LOG.info('Cluster %s has been started successfully' % cluster.name)
self._set_cluster_info(cluster)
def start_cluster(cluster):
client = c.IntelClient(u.get_instance(cluster, 'manager'), cluster.name)
LOG.debug("Starting hadoop services")
client.services.hdfs.start()
if u.get_jobtracker(cluster):
client.services.mapred.start()
if u.get_hiveserver(cluster):
client.services.hive.start()
if u.get_oozie(cluster):
LOG.info("Setup oozie")
_setup_oozie(cluster)
client.services.oozie.start()
def start_cluster(cluster):
client = c.IntelClient(u.get_instance(cluster, 'manager'), cluster.name)
LOG.debug("Starting hadoop services")
client.services.hdfs.start()
if u.get_jobtracker(cluster):
client.services.mapred.start()
if u.get_hiveserver(cluster):
client.services.hive.start()
if u.get_oozie(cluster):
LOG.info("Setup oozie")
_setup_oozie(cluster)
client.services.oozie.start()
def scale_cluster(cluster, instances):
scale_ins_hosts = [i.fqdn() for i in instances]
dn_hosts = [dn.fqdn() for dn in u.get_datanodes(cluster)]
nm_hosts = [nm.fqdn() for nm in u.get_nodemanagers(cluster)]
to_scale_dn = []
to_scale_nm = []
for i in scale_ins_hosts:
if i in dn_hosts:
to_scale_dn.append(i)
if i in nm_hosts:
to_scale_nm.append(i)
client = c.IntelClient(u.get_instance(cluster, 'manager'), cluster.name)
rack = '/Default'
client.nodes.add(scale_ins_hosts, rack, 'hadoop',
'/home/hadoop/.ssh/id_rsa')
client.cluster.install_software(scale_ins_hosts)
if to_scale_nm:
client.services.yarn.add_nodes('NodeManager', to_scale_nm)
if to_scale_dn:
client.services.hdfs.add_nodes('DataNode', to_scale_dn)
# IDH 3.0.2 reset cluster parameters (bug #1300603)
# Restoring them back
LOG.info("Provisioning configs")
# cinder and ephemeral drive support
_configure_storage(client, cluster)
# swift support
_configure_swift(client, cluster)
# user configs
_add_user_params(client, cluster)
client.nodes.config()
if to_scale_dn:
client.services.hdfs.start()
if to_scale_nm:
client.services.yarn.start()
def generate_spark_env_configs(cluster):
configs = []
# master configuration
sp_master = utils.get_instance(cluster, "master")
configs.append('SPARK_MASTER_IP=' + sp_master.hostname())
masterport = get_config_value("Spark", "Master port", cluster)
if masterport and masterport != _get_spark_opt_default("Master port"):
configs.append('SPARK_MASTER_PORT=' + str(masterport))
masterwebport = get_config_value("Spark", "Master webui port", cluster)
if masterwebport and \
masterwebport != _get_spark_opt_default("Master webui port"):
configs.append('SPARK_MASTER_WEBUI_PORT=' + str(masterwebport))
# configuration for workers
workercores = get_config_value("Spark", "Worker cores", cluster)
if workercores and workercores != _get_spark_opt_default("Worker cores"):
configs.append('SPARK_WORKER_CORES=' + str(workercores))
workermemory = get_config_value("Spark", "Worker memory", cluster)
if workermemory and \
workermemory != _get_spark_opt_default("Worker memory"):
configs.append('SPARK_WORKER_MEMORY=' + str(workermemory))
workerport = get_config_value("Spark", "Worker port", cluster)
if workerport and workerport != _get_spark_opt_default("Worker port"):
configs.append('SPARK_WORKER_PORT=' + str(workerport))
workerwebport = get_config_value("Spark", "Worker webui port", cluster)
if workerwebport and \
workerwebport != _get_spark_opt_default("Worker webui port"):
configs.append('SPARK_WORKER_WEBUI_PORT=' + str(workerwebport))
workerinstances = get_config_value("Spark", "Worker instances", cluster)
if workerinstances and \
workerinstances != _get_spark_opt_default("Worker instances"):
configs.append('SPARK_WORKER_INSTANCES=' + str(workerinstances))
return '\n'.join(configs)
def generate_spark_env_configs(cluster):
configs = []
# master configuration
sp_master = utils.get_instance(cluster, "master")
configs.append('SPARK_MASTER_IP=' + sp_master.hostname())
masterport = get_config_value("Spark", "Master port", cluster)
if masterport and masterport != _get_spark_opt_default("Master port"):
configs.append('SPARK_MASTER_PORT=' + str(masterport))
masterwebport = get_config_value("Spark", "Master webui port", cluster)
if (masterwebport and
masterwebport != _get_spark_opt_default("Master webui port")):
configs.append('SPARK_MASTER_WEBUI_PORT=' + str(masterwebport))
# configuration for workers
workercores = get_config_value("Spark", "Worker cores", cluster)
if workercores and workercores != _get_spark_opt_default("Worker cores"):
configs.append('SPARK_WORKER_CORES=' + str(workercores))
workermemory = get_config_value("Spark", "Worker memory", cluster)
if (workermemory and
workermemory != _get_spark_opt_default("Worker memory")):
configs.append('SPARK_WORKER_MEMORY=' + str(workermemory))
workerport = get_config_value("Spark", "Worker port", cluster)
if workerport and workerport != _get_spark_opt_default("Worker port"):
configs.append('SPARK_WORKER_PORT=' + str(workerport))
workerwebport = get_config_value("Spark", "Worker webui port", cluster)
if (workerwebport and
workerwebport != _get_spark_opt_default("Worker webui port")):
configs.append('SPARK_WORKER_WEBUI_PORT=' + str(workerwebport))
workerinstances = get_config_value("Spark", "Worker instances", cluster)
if (workerinstances and
workerinstances != _get_spark_opt_default("Worker instances")):
configs.append('SPARK_WORKER_INSTANCES=' + str(workerinstances))
return '\n'.join(configs)
def _extract_configs_to_extra(self, cluster):
st_master = utils.get_instance(cluster, "master")
st_slaves = utils.get_instances(cluster, "slave")
zk_servers = utils.get_instances(cluster, "zookeeper")
extra = dict()
config_instances = ''
if st_master is not None:
if zk_servers is not None:
zknames = []
for zk in zk_servers:
zknames.append(zk.hostname())
config_master = c_helper.generate_storm_config(cluster,
st_master.hostname(),
zknames)
# FIGURE OUT HOW TO GET IPS
for ng in cluster.node_groups:
extra[ng.id] = {
'setup_script': c_helper.generate_hosts_setup_script(
ng.storage_paths(),
c_helper.extract_hadoop_environment_confs(
ng.configuration())
),
'sp_master': config_master,
'sp_slaves': config_slaves
}
if c_helper.is_data_locality_enabled(cluster):
topology_data = th.generate_topology_map(
cluster, CONF.enable_hypervisor_awareness)
extra['topology_data'] = "\n".join(
[k + " " + v for k, v in topology_data.items()]) + "\n"
return extra
def get_resourcemanager(cluster):
return u.get_instance(cluster, 'RESOURCEMANAGER')
def install_manager(cluster):
LOG.info("Starting Install Manager Process")
mng_instance = u.get_instance(cluster, 'manager')
idh_tarball_path = c_helper.get_config_value(
cluster.cluster_configs.get('general'), c_helper.IDH_TARBALL_URL)
idh_tarball_filename = idh_tarball_path.rsplit('/', 1)[-1]
idh_dir = idh_tarball_filename[:idh_tarball_filename.find('.tar.gz')]
LOG.info("IDH tgz will be retrieved from: \'%s\'", idh_tarball_path)
idh_repo = c_helper.get_config_value(
cluster.cluster_configs.get('general'), c_helper.IDH_REPO_URL)
os_repo = c_helper.get_config_value(cluster.cluster_configs.get('general'),
c_helper.OS_REPO_URL)
idh_install_cmd = 'sudo ./%s/install.sh --mode=silent 2>&1' % idh_dir
with mng_instance.remote() as r:
LOG.info("Download IDH manager ")
try:
r.execute_command('curl -O %s 2>&1' % idh_tarball_path)
except Exception as e:
raise RuntimeError(
"Unable to download IDH manager from %s" % idh_tarball_path, e)
# unpack archive
LOG.info("Unpack manager %s ", idh_tarball_filename)
try:
r.execute_command('tar xzf %s 2>&1' % idh_tarball_filename)
except Exception as e:
raise RuntimeError("Unable to unpack tgz %s", idh_tarball_filename,
e)
# install idh
LOG.debug("Install manager with %s : ", idh_install_cmd)
inst_conf = _INST_CONF_TEMPLATE % (os_repo, idh_repo)
r.write_file_to('%s/ui-installer/conf' % idh_dir, inst_conf)
#TODO(alazarev) make timeout configurable (bug #1262897)
r.execute_command(idh_install_cmd, timeout=3600)
# fix nginx persimmions bug
r.execute_command('sudo chmod o+x /var/lib/nginx/ /var/lib/nginx/tmp '
'/var/lib/nginx/tmp/client_body')
# waiting start idh manager
#TODO(alazarev) make timeout configurable (bug #1262897)
timeout = 600
LOG.debug("Waiting %s seconds for Manager to start : ", timeout)
while timeout:
try:
telnetlib.Telnet(mng_instance.management_ip, 9443)
break
except IOError:
timeout -= 2
context.sleep(2)
else:
message = ("IDH Manager failed to start in %s minutes on node '%s' "
"of cluster '%s'" %
(timeout / 60, mng_instance.management_ip, cluster.name))
LOG.error(message)
raise iex.IntelPluginException(message)
def run_job(self, job_execution):
ctx = context.ctx()
job = conductor.job_get(ctx, job_execution.job_id)
proxy_configs = job_execution.job_configs.get('proxy_configs')
# We'll always run the driver program on the master
master = plugin_utils.get_instance(self.cluster, "master")
# TODO(tmckay): wf_dir should probably be configurable.
# The only requirement is that the dir is writable by the image user
wf_dir = job_utils.create_workflow_dir(master, '/tmp/spark-edp', job,
job_execution.id)
paths = job_utils.upload_job_files(master,
wf_dir,
job,
libs_subdir=False,
proxy_configs=proxy_configs)
# We can shorten the paths in this case since we'll run out of wf_dir
paths = [os.path.basename(p) for p in paths]
# TODO(tmckay): for now, paths[0] is always assumed to be the app
# jar and we generate paths in order (mains, then libs).
# When we have a Spark job type, we can require a "main" and set
# the app jar explicitly to be "main"
app_jar = paths.pop(0)
# The rest of the paths will be passed with --jars
additional_jars = ",".join(paths)
if additional_jars:
additional_jars = "--jars " + additional_jars
# Launch the spark job using spark-submit and deploy_mode = client
host = master.hostname()
port = c_helper.get_config_value("Spark", "Master port", self.cluster)
spark_submit = os.path.join(
c_helper.get_config_value("Spark", "Spark home", self.cluster),
"bin/spark-submit")
job_class = job_execution.job_configs.configs["edp.java.main_class"]
# TODO(tmckay): we need to clean up wf_dirs on long running clusters
# TODO(tmckay): probably allow for general options to spark-submit
args = " ".join(job_execution.job_configs.get('args', []))
# The redirects of stdout and stderr will preserve output in the wf_dir
cmd = "%s %s --class %s %s --master spark://%s:%s %s" % (
spark_submit, app_jar, job_class, additional_jars, host, port,
args)
# If an exception is raised here, the job_manager will mark
# the job failed and log the exception
with remote.get_remote(master) as r:
# Upload the command launch script
launch = os.path.join(wf_dir, "launch_command")
r.write_file_to(launch, self._job_script())
r.execute_command("chmod +x %s" % launch)
ret, stdout = r.execute_command(
"cd %s; ./launch_command %s > /dev/null 2>&1 & echo $!" %
(wf_dir, cmd))
if ret == 0:
# Success, we'll add the wf_dir in job_execution.extra and store
# pid@instance_id as the job id
# We know the job is running so return "RUNNING"
return (stdout.strip() + "@" + master.id, edp.JOB_STATUS_RUNNING, {
'spark-path': wf_dir
})
# Hmm, no execption but something failed.
# Since we're using backgrounding with redirect, this is unlikely.
raise e.EDPError(
_("Spark job execution failed. Exit status = "
"%(status)s, stdout = %(stdout)s") % {
'status': ret,
'stdout': stdout
})
def get_oozie(cluster):
return u.get_instance(cluster, 'OOZIE_SERVER')
def get_historyserver(cluster):
return u.get_instance(cluster, 'historyserver')
def get_manager(cluster):
return u.get_instance(cluster, 'MANAGER')
def get_jobtracker(cluster):
instance = u.get_instance(cluster, "jobtracker")
return instance
def get_oozie(cluster):
return u.get_instance(cluster, "oozie")
def get_namenode(cluster):
return u.get_instance(cluster, "namenode")
def get_jobtracker(cluster):
instance = u.get_instance(cluster, "jobtracker")
return instance
def install_manager(cluster):
LOG.info("Starting Install Manager Process")
mng_instance = u.get_instance(cluster, 'manager')
idh_tarball_path = c_helper.get_config_value(
cluster.cluster_configs.get('general'), c_helper.IDH_TARBALL_URL)
idh_tarball_filename = idh_tarball_path.rsplit('/', 1)[-1]
idh_dir = idh_tarball_filename[:idh_tarball_filename.find('.tar.gz')]
LOG.info("IDH tgz will be retrieved from: \'%s\'", idh_tarball_path)
idh_repo = c_helper.get_config_value(
cluster.cluster_configs.get('general'), c_helper.IDH_REPO_URL)
os_repo = c_helper.get_config_value(
cluster.cluster_configs.get('general'), c_helper.OS_REPO_URL)
idh_install_cmd = 'sudo ./%s/install.sh --mode=silent 2>&1' % idh_dir
with mng_instance.remote() as r:
LOG.info("Download IDH manager ")
try:
r.execute_command('curl -O %s 2>&1' % idh_tarball_path)
except Exception as e:
raise RuntimeError("Unable to download IDH manager from %s" %
idh_tarball_path, e)
# unpack archive
LOG.info("Unpack manager %s ", idh_tarball_filename)
try:
r.execute_command('tar xzf %s 2>&1' % idh_tarball_filename)
except Exception as e:
raise RuntimeError("Unable to unpack tgz %s",
idh_tarball_filename, e)
# install idh
LOG.debug("Install manager with %s : ", idh_install_cmd)
inst_conf = _INST_CONF_TEMPLATE % (os_repo, idh_repo)
r.write_file_to('%s/ui-installer/conf' % idh_dir, inst_conf)
#TODO(alazarev) make timeout configurable (bug #1262897)
r.execute_command(idh_install_cmd, timeout=3600)
# fix nginx persimmions bug
r.execute_command('sudo chmod o+x /var/lib/nginx/ /var/lib/nginx/tmp '
'/var/lib/nginx/tmp/client_body')
# waiting start idh manager
#TODO(alazarev) make timeout configurable (bug #1262897)
timeout = 600
LOG.debug("Waiting %s seconds for Manager to start : ", timeout)
while timeout:
try:
telnetlib.Telnet(mng_instance.management_ip, 9443)
break
except IOError:
timeout -= 2
context.sleep(2)
else:
message = ("IDH Manager failed to start in %s minutes on node '%s' "
"of cluster '%s'"
% (timeout / 60, mng_instance.management_ip, cluster.name))
LOG.error(message)
raise iex.IntelPluginException(message)
def get_oozie_server(self, cluster):
return u.get_instance(cluster, "oozie")
def run_job(self, job_execution):
ctx = context.ctx()
job = conductor.job_get(ctx, job_execution.job_id)
# We'll always run the driver program on the master
master = plugin_utils.get_instance(self.cluster, "master")
# TODO(tmckay): wf_dir should probably be configurable.
# The only requirement is that the dir is writable by the image user
wf_dir = job_utils.create_workflow_dir(master, '/tmp/spark-edp', job,
job_execution.id)
paths = job_utils.upload_job_files(master, wf_dir, job,
libs_subdir=False)
# We can shorten the paths in this case since we'll run out of wf_dir
paths = [os.path.basename(p) for p in paths]
# TODO(tmckay): for now, paths[0] is always assumed to be the app
# jar and we generate paths in order (mains, then libs).
# When we have a Spark job type, we can require a "main" and set
# the app jar explicitly to be "main"
app_jar = paths.pop(0)
# The rest of the paths will be passed with --jars
additional_jars = ",".join(paths)
if additional_jars:
additional_jars = "--jars " + additional_jars
# Launch the spark job using spark-submit and deploy_mode = client
host = master.hostname()
port = c_helper.get_config_value("Spark", "Master port", self.cluster)
spark_submit = os.path.join(
c_helper.get_config_value("Spark",
"Spark home",
self.cluster),
"bin/spark-submit")
job_class = job_execution.job_configs.configs["edp.java.main_class"]
# TODO(tmckay): we need to clean up wf_dirs on long running clusters
# TODO(tmckay): probably allow for general options to spark-submit
args = " ".join(job_execution.job_configs.get('args', []))
# The redirects of stdout and stderr will preserve output in the wf_dir
cmd = "%s %s --class %s %s --master spark://%s:%s %s" % (
spark_submit,
app_jar,
job_class,
additional_jars,
host,
port,
args)
# If an exception is raised here, the job_manager will mark
# the job failed and log the exception
with remote.get_remote(master) as r:
# Upload the command launch script
launch = os.path.join(wf_dir, "launch_command")
r.write_file_to(launch, self._job_script())
r.execute_command("chmod +x %s" % launch)
ret, stdout = r.execute_command(
"cd %s; ./launch_command %s > /dev/null 2>&1 & echo $!"
% (wf_dir, cmd))
if ret == 0:
# Success, we'll add the wf_dir in job_execution.extra and store
# pid@instance_id as the job id
# We know the job is running so return "RUNNING"
return (stdout.strip() + "@" + master.id,
edp.JOB_STATUS_RUNNING,
{'spark-path': wf_dir})
# Hmm, no execption but something failed.
# Since we're using backgrounding with redirect, this is unlikely.
raise e.EDPError("Spark job execution failed. Exit status = %s, "
"stdout = %s" % (ret, stdout))
def get_namenode(cluster):
return u.get_instance(cluster, "namenode")
def decommission_nodes(cluster, instances):
dec_hosts = [i.fqdn() for i in instances]
dn_hosts = [dn.fqdn() for dn in u.get_datanodes(cluster)]
tt_hosts = [dn.fqdn() for dn in u.get_tasktrackers(cluster)]
client = c.IntelClient(u.get_instance(cluster, 'manager'), cluster.name)
dec_dn_hosts = []
for dec_host in dec_hosts:
if dec_host in dn_hosts:
dec_dn_hosts.append(dec_host)
if dec_dn_hosts:
client.services.hdfs.decommission_nodes(dec_dn_hosts)
#TODO(alazarev) make timeout configurable (bug #1262897)
timeout = 14400 # 4 hours
cur_time = 0
for host in dec_dn_hosts:
while cur_time < timeout:
if client.services.hdfs.get_datanode_status(
host) == 'Decomissioned':
break
context.sleep(5)
cur_time += 5
else:
LOG.warn("Failed to decomission node '%s' of cluster '%s' "
"in %s minutes" % (host, cluster.name, timeout / 60))
client.nodes.stop(dec_hosts)
# wait stop services
#TODO(alazarev) make timeout configurable (bug #1262897)
timeout = 600 # 10 minutes
cur_time = 0
for instance in instances:
while cur_time < timeout:
stopped = True
if instance.fqdn() in dn_hosts:
code, out = instance.remote().execute_command(
'sudo /sbin/service hadoop-datanode status',
raise_when_error=False)
if out.strip() != 'datanode is stopped':
stopped = False
if out.strip() == 'datanode dead but pid file exists':
instance.remote().execute_command(
'sudo rm -f '
'/var/run/hadoop/hadoop-hadoop-datanode.pid')
if instance.fqdn() in tt_hosts:
code, out = instance.remote().execute_command(
'sudo /sbin/service hadoop-tasktracker status',
raise_when_error=False)
if out.strip() != 'tasktracker is stopped':
stopped = False
if stopped:
break
else:
context.sleep(5)
cur_time += 5
else:
LOG.warn("Failed to stop services on node '%s' of cluster '%s' "
"in %s minutes" % (instance, cluster.name, timeout / 60))
for node in dec_hosts:
LOG.info("Deleting node '%s' on cluster '%s'" % (node, cluster.name))
client.nodes.delete(node)
def get_resourcemanager(cluster):
return u.get_instance(cluster, 'resourcemanager')
def get_oozie_server(self, cluster):
return u.get_instance(cluster, "oozie_server")
def get_hiveserver(cluster):
return u.get_instance(cluster, "hiveserver")
def get_historyserver(cluster):
return u.get_instance(cluster, 'JOBHISTORY')
def get_namenode(cluster):
return u.get_instance(cluster, "NAMENODE")
def get_secondarynamenode(cluster):
return u.get_instance(cluster, 'SECONDARYNAMENODE')
def get_resourcemanager(cluster):
return u.get_instance(cluster, 'resourcemanager')
def test_get_instance(self):
self.assertIsNone(u.get_instance(self.c1, 'wrong-process'))
self.assertEqual(u.get_instance(self.c1, 'nn'),
self.ng1.instances[0])
with testtools.ExpectedException(ex.InvalidComponentCountException):
u.get_instance(self.c1, 'dn')
def get_oozie(cluster):
return u.get_instance(cluster, "oozie")
def get_hiveserver(cluster):
return u.get_instance(cluster, "hiveserver")
def decommission_nodes(cluster, instances):
dec_hosts = [i.fqdn() for i in instances]
dn_hosts = [dn.fqdn() for dn in u.get_datanodes(cluster)]
tt_hosts = [dn.fqdn() for dn in u.get_tasktrackers(cluster)]
client = c.IntelClient(u.get_instance(cluster, 'manager'), cluster.name)
dec_dn_hosts = []
for dec_host in dec_hosts:
if dec_host in dn_hosts:
dec_dn_hosts.append(dec_host)
if dec_dn_hosts:
client.services.hdfs.decommission_nodes(dec_dn_hosts)
#TODO(alazarev) make timeout configurable (bug #1262897)
timeout = 14400 # 4 hours
cur_time = 0
for host in dec_dn_hosts:
while cur_time < timeout:
if client.services.hdfs.get_datanode_status(
host) == 'Decomissioned':
break
context.sleep(5)
cur_time += 5
else:
LOG.warn("Failed to decomission node '%s' of cluster '%s' "
"in %s minutes" % (host, cluster.name, timeout / 60))
client.nodes.stop(dec_hosts)
# wait stop services
#TODO(alazarev) make timeout configurable (bug #1262897)
timeout = 600 # 10 minutes
cur_time = 0
for instance in instances:
while cur_time < timeout:
stopped = True
if instance.fqdn() in dn_hosts:
code, out = instance.remote().execute_command(
'sudo /sbin/service hadoop-datanode status',
raise_when_error=False)
if out.strip() != 'datanode is stopped':
stopped = False
if out.strip() == 'datanode dead but pid file exists':
instance.remote().execute_command(
'sudo rm -f '
'/var/run/hadoop/hadoop-hadoop-datanode.pid')
if instance.fqdn() in tt_hosts:
code, out = instance.remote().execute_command(
'sudo /sbin/service hadoop-tasktracker status',
raise_when_error=False)
if out.strip() != 'tasktracker is stopped':
stopped = False
if stopped:
break
else:
context.sleep(5)
cur_time += 5
else:
LOG.warn("Failed to stop services on node '%s' of cluster '%s' "
"in %s minutes" % (instance, cluster.name, timeout / 60))
for node in dec_hosts:
LOG.info("Deleting node '%s' on cluster '%s'" % (node, cluster.name))
client.nodes.delete(node)
def get_historyserver(cluster):
return u.get_instance(cluster, 'historyserver')
def get_oozie_server(self, cluster):
return u.get_instance(cluster, "OOZIE_SERVER")
def get_oozie_server(self, cluster):
return u.get_instance(cluster, "OOZIE_SERVER")
