def update_peers(self, node_list):
'''
This method wtill return True if the master peer was updated.
False otherwise.
'''
old_master = unitdata.kv().get('spark_master.ip', 'not_set')
master_ip = ''
if not node_list:
hookenv.log("No peers yet. Acting as master.")
master_ip = utils.resolve_private_address(hookenv.unit_private_ip())
nodes = [(hookenv.local_unit(), master_ip)]
unitdata.kv().set('spark_all_master.ips', nodes)
unitdata.kv().set('spark_master.ip', master_ip)
else:
# Use as master the node with minimum Id
# Any ordering is fine here. Lexicografical ordering too.
node_list.sort()
master_ip = utils.resolve_private_address(node_list[0][1])
unitdata.kv().set('spark_master.ip', master_ip)
unitdata.kv().set('spark_all_master.ips', node_list)
hookenv.log("Updating master ip to {}.".format(master_ip))
unitdata.kv().set('spark_master.is_set', True)
unitdata.kv().flush(True)
# Incase of an HA setup adding peers must be treated as a potential
# mastr change
if (old_master != master_ip) or unitdata.kv().get('zookeepers.available', False):
return True
else:
return False
def update_peers(self, node_list):
'''
This method wtill return True if the master peer was updated.
False otherwise.
'''
old_master = unitdata.kv().get('spark_master.ip', 'not_set')
master_ip = ''
if not node_list:
hookenv.log("No peers yet. Acting as master.")
master_ip = utils.resolve_private_address(
hookenv.unit_private_ip())
nodes = [(hookenv.local_unit(), master_ip)]
unitdata.kv().set('spark_all_master.ips', nodes)
unitdata.kv().set('spark_master.ip', master_ip)
else:
# Use as master the node with minimum Id
# Any ordering is fine here. Lexicografical ordering too.
node_list.sort()
master_ip = utils.resolve_private_address(node_list[0][1])
unitdata.kv().set('spark_master.ip', master_ip)
unitdata.kv().set('spark_all_master.ips', node_list)
hookenv.log("Updating master ip to {}.".format(master_ip))
unitdata.kv().set('spark_master.is_set', True)
unitdata.kv().flush(True)
# Incase of an HA setup adding peers must be treated as a potential
# mastr change
if (old_master != master_ip) or unitdata.kv().get(
'zookeepers.available', False):
return True
else:
return False
def hosts_map(self):
local_host_name = hookenv.local_unit().replace('/', '-')
local_ip = utils.resolve_private_address(hookenv.unit_private_ip())
result = {local_ip: local_host_name}
for conv in self.conversations():
addr = conv.get_remote('private-address', '')
ip = utils.resolve_private_address(addr)
host_name = list(conv.units)[0].replace('/', '-')
result.update({ip: host_name})
return result
def trigger_puppet(self):
# If we can't reverse resolve the hostname (like on azure), support DN
# registration by IP address.
# NB: determine this *before* updating /etc/hosts below since
# gethostbyaddr will not fail if we have an /etc/hosts entry.
reverse_dns_bad = False
try:
socket.gethostbyaddr(utils.resolve_private_address(hookenv.unit_private_ip()))
except socket.herror:
reverse_dns_bad = True
# We know java7 has MAXHOSTNAMELEN of 64 char, so we cannot rely on
# java to do a hostname lookup on clouds that have >64 char fqdns
# (gce). Force short hostname (< 64 char) into /etc/hosts as workaround.
# Better fix may be to move to java8. See http://paste.ubuntu.com/16230171/
# NB: do this before the puppet apply, which may call java stuffs
# like format namenode, which will fail if we dont get this fix
# down early.
short_host = subprocess.check_output(['facter', 'hostname']).strip().decode()
private_ip = utils.resolve_private_address(hookenv.unit_private_ip())
if short_host and private_ip:
utils.update_kv_host(private_ip, short_host)
utils.manage_etc_hosts()
charm_dir = hookenv.charm_dir()
# TODO JIRA KWM: rm does not need Hdfs_init and will fail
rm_patch = Path(charm_dir) / 'resources/patch1_rm_init_hdfs.patch'
# TODO JIRA KWM: nm should not *need* mapred role. we could patch it
# with nm_patch, or adjust nm charm to include mapred role. for now,
# we're doing the latter. todo rfc from dev@bigtop list.
# nm_patch = Path(charm_dir) / 'resources/patch2_nm_core-site.patch'
# TODO JIRA KWM: client role needs common_yarn for yarn-site.xml
client_patch = Path(charm_dir) / 'resources/patch3_client_role_use_common_yarn.patch'
with chdir("{}".format(self.bigtop_base)):
# rm patch goes first
utils.run_as('root', 'patch', '-p1', '-s', '-i', rm_patch)
# skip nm_patch for now since nm charm is including mapred role
# utils.run_as('root', 'patch', '-p1', '-s', '-i', nm_patch)
# client patch goes last
utils.run_as('root', 'patch', '-p1', '-s', '-i', client_patch)
# TODO FIX ABOVE KWM
# puppet apply needs to be ran where recipes were unpacked
with chdir("{}".format(self.bigtop_base)):
utils.run_as('root', 'puppet', 'apply', '-d',
'--modulepath="bigtop-deploy/puppet/modules:/etc/puppet/modules"',
'bigtop-deploy/puppet/manifests/site.pp')
# Do any post-puppet config on the generated config files.
if reverse_dns_bad:
hdfs_site = Path('/etc/hadoop/conf/hdfs-site.xml')
with utils.xmlpropmap_edit_in_place(hdfs_site) as props:
props['dfs.namenode.datanode.registration.ip-hostname-check'] = 'false'
def configure_kafka(self, zk_units):
# Get ip:port data from our connected zookeepers
if not zk_units:
# if we have no zookeepers, make sure kafka is stopped
self.stop()
else:
zks = []
for remote_address, port in zk_units:
ip = utils.resolve_private_address(remote_address)
zks.append("%s:%s" % (ip, port))
zks.sort()
zk_connect = ",".join(zks)
# update consumer props
cfg = self.dist_config.path('kafka_conf') / 'consumer.properties'
utils.re_edit_in_place(cfg, {
r'^zookeeper.connect=.*':
'zookeeper.connect=%s' % zk_connect,
})
# update server props
cfg = self.dist_config.path('kafka_conf') / 'server.properties'
utils.re_edit_in_place(cfg, {
r'^zookeeper.connect=.*':
'zookeeper.connect=%s' % zk_connect,
})
def hosts_map(self):
result = {}
for conv in self.conversations():
ip = utils.resolve_private_address(conv.get_remote('private-address', ''))
host_name = conv.scope.replace('/', '-')
result.update({ip: host_name})
return result
def configure_kafka(self, zk_units, network_interface=None):
# Get ip:port data from our connected zookeepers
zks = []
for unit in zk_units:
ip = utils.resolve_private_address(unit['host'])
zks.append("%s:%s" % (ip, unit['port']))
zks.sort()
zk_connect = ",".join(zks)
service, unit_num = os.environ['JUJU_UNIT_NAME'].split('/', 1)
kafka_port = self.dist_config.port('kafka')
roles = ['kafka-server']
override = {
'kafka::server::broker_id': unit_num,
'kafka::server::port': kafka_port,
'kafka::server::zookeeper_connection_string': zk_connect,
}
if network_interface:
ip = Bigtop().get_ip_for_interface(network_interface)
override['kafka::server::bind_addr'] = ip
bigtop = Bigtop()
bigtop.render_site_yaml(roles=roles, overrides=override)
bigtop.trigger_puppet()
self.set_advertise()
self.restart()
def configure_kafka(self, zk_units, network_interface=None):
# Get ip:port data from our connected zookeepers
zks = []
for unit in zk_units:
ip = utils.resolve_private_address(unit['host'])
zks.append("%s:%s" % (ip, unit['port']))
zks.sort()
zk_connect = ",".join(zks)
# update consumer props
cfg = self.dist_config.path('kafka_conf') / 'consumer.properties'
utils.re_edit_in_place(
cfg, {
r'^zookeeper.connect=.*': 'zookeeper.connect=%s' % zk_connect,
})
# update server props
cfg = self.dist_config.path('kafka_conf') / 'server.properties'
utils.re_edit_in_place(
cfg, {
r'^zookeeper.connect=.*': 'zookeeper.connect=%s' % zk_connect,
})
# Possibly bind a network interface
if network_interface:
utils.re_edit_in_place(
cfg, {
r'^#?host.name=.*':
'host.name={}'.format(
get_ip_for_interface(network_interface)),
})
def configure_kafka(self, zk_units, network_interface=None):
# Get ip:port data from our connected zookeepers
zks = []
for unit in zk_units:
ip = utils.resolve_private_address(unit['host'])
zks.append("%s:%s" % (ip, unit['port']))
zks.sort()
zk_connect = ",".join(zks)
# update consumer props
cfg = self.dist_config.path('kafka_conf') / 'consumer.properties'
utils.re_edit_in_place(cfg, {
r'^zookeeper.connect=.*': 'zookeeper.connect=%s' % zk_connect,
})
# update server props
cfg = self.dist_config.path('kafka_conf') / 'server.properties'
utils.re_edit_in_place(cfg, {
r'^zookeeper.connect=.*': 'zookeeper.connect=%s' % zk_connect,
})
# Possibly bind a network interface
if network_interface:
utils.re_edit_in_place(cfg, {
r'^#?host.name=.*': 'host.name={}'.format(
get_ip_for_interface(network_interface)),
})
def am_i_registered(self):
my_ip = utils.resolve_private_address(
hookenv.unit_get('private-address'))
my_hostname = hookenv.local_unit().replace('/', '-')
unit, data = any_ready_unit(self.relation_name)
etc_hosts = json.loads((data or {}).get('etc_hosts', '{}'))
return etc_hosts.get(my_ip, None) == my_hostname
def client_present(client):
if is_state('leadership.is_leader'):
client.set_spark_started()
spark = Spark()
master_ip = utils.resolve_private_address(hookenv.unit_private_ip())
master_url = spark.get_master_url(master_ip)
client.send_master_info(master_url, master_ip)
def get_zk_connect(self, zk_units):
zks = []
for unit in zk_units:
ip = utils.resolve_private_address(unit['host'])
zks.append(ip)
zks.sort()
return ",".join(zks)
def configure_kafka(self, zk_units, network_interface=None):
# Get ip:port data from our connected zookeepers
zks = []
for unit in zk_units:
ip = utils.resolve_private_address(unit['host'])
zks.append("%s:%s" % (ip, unit['port']))
zks.sort()
zk_connect = ",".join(zks)
service, unit_num = os.environ['JUJU_UNIT_NAME'].split('/', 1)
kafka_port = self.dist_config.port('kafka')
roles = ['kafka-server']
override = {
'kafka::server::broker_id': unit_num,
'kafka::server::port': kafka_port,
'kafka::server::zookeeper_connection_string': zk_connect,
}
if network_interface:
ip = Bigtop().get_ip_for_interface(network_interface)
override['kafka::server::bind_addr'] = ip
bigtop = Bigtop()
bigtop.render_site_yaml(roles=roles, overrides=override)
bigtop.trigger_puppet()
self.set_advertise()
self.restart()
def get_zk_connect(self, zk_units):
zks = []
for unit in zk_units:
ip = utils.resolve_private_address(unit['host'])
zks.append(ip)
zks.sort()
return ",".join(zks)
def configure_kafka(self):
# Get ip:port data from our connected zookeepers
if Zookeeper().connected_units() and Zookeeper().is_ready():
zks = []
for unit, data in Zookeeper().filtered_data().items():
ip = utils.resolve_private_address(data['private-address'])
zks.append("%s:%s" % (ip, data['port']))
zks.sort()
zk_connect = ",".join(zks)
# update consumer props
cfg = self.dist_config.path('kafka_conf') / 'consumer.properties'
utils.re_edit_in_place(cfg, {
r'^zookeeper.connect=.*':
'zookeeper.connect=%s' % zk_connect,
})
# update server props
cfg = self.dist_config.path('kafka_conf') / 'server.properties'
utils.re_edit_in_place(cfg, {
r'^zookeeper.connect=.*':
'zookeeper.connect=%s' % zk_connect,
})
else:
# if we have no zookeepers, make sure kafka is stopped
self.stop()
def nodes(self):
return [{
'host':
conv.scope.replace('/', '-'),
'ip':
utils.resolve_private_address(
conv.get_remote('private-address', '')),
} for conv in self.conversations()]
def nodes(self):
return [
{
'host': conv.scope.replace('/', '-'),
'ip': utils.resolve_private_address(conv.get_remote('private-address', '')),
}
for conv in self.conversations()
]
def configure_resourcemanager():
local_hostname = hookenv.local_unit().replace('/', '-')
private_address = hookenv.unit_get('private-address')
ip_addr = utils.resolve_private_address(private_address)
hadoop = get_hadoop_base()
yarn = YARN(hadoop)
yarn.configure_resourcemanager()
yarn.configure_jobhistory()
utils.update_kv_hosts({ip_addr: local_hostname})
set_state('resourcemanager.configured')
def configure_resourcemanager():
local_hostname = hookenv.local_unit().replace('/', '-')
private_address = hookenv.unit_get('private-address')
ip_addr = utils.resolve_private_address(private_address)
hadoop = get_hadoop_base()
yarn = YARN(hadoop)
yarn.configure_resourcemanager()
yarn.configure_jobhistory()
utils.update_kv_hosts({ip_addr: local_hostname})
set_state('resourcemanager.configured')
def get_master(self):
mode = hookenv.config()['spark_execution_mode']
master = None
if mode.startswith('local') or mode == 'yarn-cluster':
master = mode
elif mode == 'standalone':
local_ip = utils.resolve_private_address(hookenv.unit_private_ip())
master = 'spark://{}:7077'.format(local_ip)
elif mode.startswith('yarn'):
master = 'yarn-client'
return master
def get_master(self):
mode = hookenv.config()['spark_execution_mode']
master = None
if mode.startswith('local') or mode == 'yarn-cluster':
master = mode
elif mode == 'standalone':
local_ip = utils.resolve_private_address(hookenv.unit_private_ip())
master = 'spark://{}:7077'.format(local_ip)
elif mode.startswith('yarn'):
master = 'yarn-client'
return master
def setup_kafka_config(self):
'''
copy the default configuration files to kafka_conf property
defined in dist.yaml
'''
default_conf = self.dist_config.path('kafka') / 'config'
kafka_conf = self.dist_config.path('kafka_conf')
kafka_conf.rmtree_p()
default_conf.copytree(kafka_conf)
# Now remove the conf included in the tarball and symlink our real conf
# dir. we've seen issues where kafka still looks for config in
# KAFKA_HOME/config.
default_conf.rmtree_p()
kafka_conf.symlink(default_conf)
# Configure immutable bits
kafka_bin = self.dist_config.path('kafka') / 'bin'
with utils.environment_edit_in_place('/etc/environment') as env:
if kafka_bin not in env['PATH']:
env['PATH'] = ':'.join([env['PATH'], kafka_bin])
env['LOG_DIR'] = self.dist_config.path('kafka_app_logs')
# note: we set the advertised.host.name below to the public_address
# to ensure that external (non-Juju) clients can connect to Kafka
public_address = hookenv.unit_get('public-address')
private_ip = utils.resolve_private_address(
hookenv.unit_get('private-address'))
kafka_server_conf = self.dist_config.path(
'kafka_conf') / 'server.properties'
service, unit_num = os.environ['JUJU_UNIT_NAME'].split('/', 1)
utils.re_edit_in_place(
kafka_server_conf, {
r'^broker.id=.*':
'broker.id=%s' % unit_num,
r'^port=.*':
'port=%s' % self.dist_config.port('kafka'),
r'^log.dirs=.*':
'log.dirs=%s' % self.dist_config.path('kafka_data_logs'),
r'^#?advertised.host.name=.*':
'advertised.host.name=%s' % public_address,
})
kafka_log4j = self.dist_config.path('kafka_conf') / 'log4j.properties'
utils.re_edit_in_place(
kafka_log4j, {
r'^kafka.logs.dir=.*':
'kafka.logs.dir=%s' % self.dist_config.path('kafka_app_logs'),
})
# fix for lxc containers and some corner cases in manual provider
# ensure that public_address is resolvable internally by mapping it to the private IP
utils.update_kv_host(private_ip, public_address)
utils.manage_etc_hosts()
def restart_services(spark):
master_info = spark.get_master_info()
master_url = master_info['connection_string']
if data_changed('insightedge.master_url', master_url):
master_ip = master_info['master']
local_ip = utils.resolve_private_address(hookenv.unit_private_ip())
is_master = master_ip == local_ip
stop_datagrid_services()
start_datagrid_services(master_url, is_master, not is_master
or not spark.is_scaled())
set_state('insightedge.ready')
hookenv.status_set('active', 'ready')
def setup_kafka_config(self):
'''
copy the default configuration files to kafka_conf property
defined in dist.yaml
'''
default_conf = self.dist_config.path('kafka') / 'config'
kafka_conf = self.dist_config.path('kafka_conf')
kafka_conf.rmtree_p()
default_conf.copytree(kafka_conf)
# Now remove the conf included in the tarball and symlink our real conf
# dir. we've seen issues where kafka still looks for config in
# KAFKA_HOME/config.
default_conf.rmtree_p()
kafka_conf.symlink(default_conf)
# Configure immutable bits
kafka_bin = self.dist_config.path('kafka') / 'bin'
with utils.environment_edit_in_place('/etc/environment') as env:
if kafka_bin not in env['PATH']:
env['PATH'] = ':'.join([env['PATH'], kafka_bin])
env['LOG_DIR'] = self.dist_config.path('kafka_app_logs')
# note: we set the advertised.host.name below to the public_address
# to ensure that external (non-Juju) clients can connect to Kafka
public_address = hookenv.unit_get('public-address')
private_ip = utils.resolve_private_address(hookenv.unit_get('private-address'))
kafka_server_conf = self.dist_config.path('kafka_conf') / 'server.properties'
service, unit_num = os.environ['JUJU_UNIT_NAME'].split('/', 1)
utils.re_edit_in_place(kafka_server_conf, {
r'^broker.id=.*': 'broker.id=%s' % unit_num,
r'^port=.*': 'port=%s' % self.dist_config.port('kafka'),
r'^log.dirs=.*': 'log.dirs=%s' % self.dist_config.path('kafka_data_logs'),
r'^#?advertised.host.name=.*': 'advertised.host.name=%s' % public_address,
})
kafka_log4j = self.dist_config.path('kafka_conf') / 'log4j.properties'
utils.re_edit_in_place(kafka_log4j, {
r'^kafka.logs.dir=.*': 'kafka.logs.dir=%s' % self.dist_config.path('kafka_app_logs'),
})
# fix for lxc containers and some corner cases in manual provider
# ensure that public_address is resolvable internally by mapping it to the private IP
utils.update_etc_hosts({private_ip: public_address})
templating.render(
'upstart.conf',
'/etc/init/kafka.conf',
context={
'kafka_conf': self.dist_config.path('kafka_conf'),
'kafka_bin': '{}/bin'.format(self.dist_config.path('kafka'))
},
)
def configure_namenode():
local_hostname = hookenv.local_unit().replace('/', '-')
private_address = hookenv.unit_get('private-address')
ip_addr = utils.resolve_private_address(private_address)
hadoop = get_hadoop_base()
hdfs = HDFS(hadoop)
hdfs.configure_namenode()
hdfs.format_namenode()
hdfs.start_namenode()
hdfs.create_hdfs_dirs()
hadoop.open_ports('namenode')
utils.update_kv_hosts({ip_addr: local_hostname})
set_state('namenode.started')
def configure_namenode():
local_hostname = hookenv.local_unit().replace("/", "-")
private_address = hookenv.unit_get("private-address")
ip_addr = utils.resolve_private_address(private_address)
hadoop = get_hadoop_base()
hdfs = HDFS(hadoop)
hdfs.configure_namenode()
hdfs.format_namenode()
hdfs.start_namenode()
hdfs.create_hdfs_dirs()
hadoop.open_ports("namenode")
utils.update_kv_hosts({ip_addr: local_hostname})
set_state("namenode.started")
def configure_hosts_file(self):
"""
Add the unit's private-address to /etc/hosts to ensure that Java
can resolve the hostname of the server to its real IP address.
We derive our hostname from the unit_id, replacing / with -.
"""
local_ip = utils.resolve_private_address(hookenv.unit_get('private-address'))
hostname = hookenv.local_unit().replace('/', '-')
utils.update_etc_hosts({local_ip: hostname})
# update name of host to more semantically meaningful value
# (this is required on some providers; the /etc/hosts entry must match
# the /etc/hostname lest Hadoop get confused about where certain things
# should be run)
etc_hostname = Path('/etc/hostname')
etc_hostname.write_text(hostname)
check_call(['hostname', '-F', etc_hostname])
def configure(self, hosts, zk_units):
zks = []
for unit in zk_units:
ip = utils.resolve_private_address(unit["host"])
zks.append(ip)
zks.sort()
zk_connect = ",".join(zks)
roles = ["hbase-server", "hbase-master", "hbase-client"]
override = {
"hadoop_hbase::common_config::zookeeper_quorum": zk_connect,
"hadoop_hbase::deploy::auxiliary": False,
}
bigtop = Bigtop()
bigtop.render_site_yaml(hosts, roles, override)
bigtop.trigger_puppet()
def configure_ha(self, zk_units):
zks = []
for unit in zk_units:
ip = utils.resolve_private_address(unit['host'])
zks.append("%s:%s" % (ip, unit['port']))
zk_connect = ",".join(zks)
daemon_opts = ('-Dspark.deploy.recoveryMode=ZOOKEEPER '
'-Dspark.deploy.zookeeper.url={}'.format(zk_connect))
spark_env = self.dist_config.path('spark_conf') / 'spark-env.sh'
utils.re_edit_in_place(spark_env, {
r'.*SPARK_DAEMON_JAVA_OPTS.*': 'SPARK_DAEMON_JAVA_OPTS=\"{}\"'.format(daemon_opts),
r'.*SPARK_MASTER_IP.*': '# SPARK_MASTER_IP',
})
unitdata.kv().set('zookeepers.available', True)
unitdata.kv().flush(True)
def configure(self, hosts, zk_units):
zks = []
for unit in zk_units:
ip = utils.resolve_private_address(unit['host'])
zks.append(ip)
zks.sort()
zk_connect = ",".join(zks)
roles = ['hbase-server', 'hbase-master', 'hbase-client']
override = {
'hadoop_hbase::common_config::zookeeper_quorum': zk_connect,
'hadoop_hbase::deploy::auxiliary': False
}
bigtop = Bigtop()
bigtop.render_site_yaml(hosts, roles, override)
bigtop.trigger_puppet()
def trigger_puppet(self):
"""
Trigger Puppet to install the desired components.
"""
java_version = unitdata.kv().get('java_version', '')
if java_version.startswith('1.7.') and len(get_fqdn()) > 64:
# We know java7 has MAXHOSTNAMELEN of 64 char, so we cannot rely on
# java to do a hostname lookup on clouds that have >64 char FQDNs
# (e.g., gce). Attempt to work around this by putting the (hopefully
# short) hostname into /etc/hosts so that it will (hopefully) be
# used instead (see http://paste.ubuntu.com/16230171/).
# NB: do this before the puppet apply, which may call java stuffs
# like format namenode, which will fail if we dont get this fix
# down early.
short_host = subprocess.check_output(['facter', 'hostname']).strip().decode()
private_ip = utils.resolve_private_address(hookenv.unit_private_ip())
if short_host and private_ip:
utils.update_kv_host(private_ip, short_host)
utils.manage_etc_hosts()
# puppet args are bigtop-version depedent
if self.bigtop_version == '1.1.0':
puppet_args = [
'-d',
'--modulepath="bigtop-deploy/puppet/modules:/etc/puppet/modules"',
'bigtop-deploy/puppet/manifests/site.pp'
]
else:
puppet_args = [
'-d',
'--parser=future',
'--modulepath="bigtop-deploy/puppet/modules:/etc/puppet/modules"',
'bigtop-deploy/puppet/manifests'
]
# puppet apply runs from the root of the bigtop release source
with chdir(self.bigtop_base):
utils.run_as('root', 'puppet', 'apply', *puppet_args)
# Do any post-puppet config on the generated config files.
utils.re_edit_in_place('/etc/default/bigtop-utils', {
r'(# )?export JAVA_HOME.*': 'export JAVA_HOME={}'.format(
java_home()),
})
def trigger_puppet(self):
"""
Trigger Puppet to install the desired components.
"""
java_version = unitdata.kv().get('java_version', '')
if java_version.startswith('1.7.') and len(get_fqdn()) > 64:
# We know java7 has MAXHOSTNAMELEN of 64 char, so we cannot rely on
# java to do a hostname lookup on clouds that have >64 char FQDNs
# (e.g., gce). Attempt to work around this by putting the (hopefully
# short) hostname into /etc/hosts so that it will (hopefully) be
# used instead (see http://paste.ubuntu.com/16230171/).
# NB: do this before the puppet apply, which may call java stuffs
# like format namenode, which will fail if we dont get this fix
# down early.
short_host = subprocess.check_output(['facter', 'hostname']).strip().decode()
private_ip = utils.resolve_private_address(hookenv.unit_private_ip())
if short_host and private_ip:
utils.update_kv_host(private_ip, short_host)
utils.manage_etc_hosts()
# puppet args are bigtop-version depedent
if self.bigtop_version == '1.1.0':
puppet_args = [
'-d',
'--modulepath="bigtop-deploy/puppet/modules:/etc/puppet/modules"',
'bigtop-deploy/puppet/manifests/site.pp'
]
else:
puppet_args = [
'-d',
'--parser=future',
'--modulepath="bigtop-deploy/puppet/modules:/etc/puppet/modules"',
'bigtop-deploy/puppet/manifests'
]
# puppet apply runs from the root of the bigtop release source
with chdir(self.bigtop_base):
utils.run_as('root', 'puppet', 'apply', *puppet_args)
# Do any post-puppet config on the generated config files.
utils.re_edit_in_place('/etc/default/bigtop-utils', {
r'(# )?export JAVA_HOME.*': 'export JAVA_HOME={}'.format(
java_home()),
})
def configure_hosts_file(self):
"""
Add the unit's private-address to /etc/hosts to ensure that Java
can resolve the hostname of the server to its real IP address.
We derive our hostname from the unit_id, replacing / with -.
"""
local_ip = utils.resolve_private_address(
hookenv.unit_get('private-address'))
hostname = hookenv.local_unit().replace('/', '-')
utils.update_kv_hosts({local_ip: hostname})
utils.manage_etc_hosts()
# update name of host to more semantically meaningful value
# (this is required on some providers; the /etc/hosts entry must match
# the /etc/hostname lest Hadoop get confused about where certain things
# should be run)
etc_hostname = Path('/etc/hostname')
etc_hostname.write_text(hostname)
check_call(['hostname', '-F', etc_hostname])
def configure_kafka(self, zk_units):
# Get ip:port data from our connected zookeepers
zks = []
for unit in zk_units:
ip = utils.resolve_private_address(unit['host'])
zks.append("%s:%s" % (ip, unit['port']))
zks.sort()
zk_connect = ",".join(zks)
# update consumer props
cfg = self.dist_config.path('kafka_conf') / 'consumer.properties'
utils.re_edit_in_place(cfg, {
r'^zookeeper.connect=.*': 'zookeeper.connect=%s' % zk_connect,
})
# update server props
cfg = self.dist_config.path('kafka_conf') / 'server.properties'
utils.re_edit_in_place(cfg, {
r'^zookeeper.connect=.*': 'zookeeper.connect=%s' % zk_connect,
})
def configure_ha(self, zk_units):
zks = []
for unit in zk_units:
ip = utils.resolve_private_address(unit['host'])
zks.append("%s:%s" % (ip, unit['port']))
zk_connect = ",".join(zks)
daemon_opts = ('-Dspark.deploy.recoveryMode=ZOOKEEPER '
'-Dspark.deploy.zookeeper.url={}'.format(zk_connect))
spark_env = self.dist_config.path('spark_conf') / 'spark-env.sh'
utils.re_edit_in_place(
spark_env, {
r'.*SPARK_DAEMON_JAVA_OPTS.*':
'SPARK_DAEMON_JAVA_OPTS=\"{}\"'.format(daemon_opts),
r'.*SPARK_MASTER_IP.*':
'# SPARK_MASTER_IP',
})
unitdata.kv().set('zookeepers.available', True)
unitdata.kv().flush(True)
def check_reverse_dns(self):
"""
Determine if reverse DNS lookups work on a machine.
Some Hadoop services expect forward and reverse DNS to work.
Not all clouds (eg, Azure) offer a working reverse-DNS environment.
Additionally, we can assume any machine with a domainname of
'localdomain' does not have proper reverse-DNS capabilities. If either
of these scenarios are present, set appropriate unit data so we can
configure around this limitation.
NB: call this *before* any /etc/hosts changes since
gethostbyaddr will not fail if we have an /etc/hosts entry.
"""
reverse_dns_ok = True
if is_localdomain():
reverse_dns_ok = False
else:
try:
socket.gethostbyaddr(utils.resolve_private_address(hookenv.unit_private_ip()))
except socket.herror:
reverse_dns_ok = False
unitdata.kv().set('reverse_dns_ok', reverse_dns_ok)
def check_reverse_dns(self):
"""
Determine if reverse DNS lookups work on a machine.
Some Hadoop services expect forward and reverse DNS to work.
Not all clouds (eg, Azure) offer a working reverse-DNS environment.
Additionally, we can assume any machine with a domainname of
'localdomain' does not have proper reverse-DNS capabilities. If either
of these scenarios are present, set appropriate unit data so we can
configure around this limitation.
NB: call this *before* any /etc/hosts changes since
gethostbyaddr will not fail if we have an /etc/hosts entry.
"""
reverse_dns_ok = True
if is_localdomain():
reverse_dns_ok = False
else:
try:
socket.gethostbyaddr(utils.resolve_private_address(hookenv.unit_private_ip()))
except socket.herror:
reverse_dns_ok = False
unitdata.kv().set('reverse_dns_ok', reverse_dns_ok)
def configure_kafka(self):
# Get ip:port data from our connected zookeepers
if Zookeeper().connected_units() and Zookeeper().is_ready():
zks = []
for unit, data in Zookeeper().filtered_data().items():
ip = utils.resolve_private_address(data['private-address'])
zks.append("%s:%s" % (ip, data['port']))
zks.sort()
zk_connect = ",".join(zks)
# update consumer props
cfg = self.dist_config.path('kafka_conf') / 'consumer.properties'
utils.re_edit_in_place(cfg, {
r'^zookeeper.connect=.*': 'zookeeper.connect=%s' % zk_connect,
})
# update server props
cfg = self.dist_config.path('kafka_conf') / 'server.properties'
utils.re_edit_in_place(cfg, {
r'^zookeeper.connect=.*': 'zookeeper.connect=%s' % zk_connect,
})
else:
# if we have no zookeepers, make sure kafka is stopped
self.stop()
def register_connected_hosts(self):
for unit, data in self.unfiltered_data().items():
ip = utils.resolve_private_address(data['private-address'])
name = unit.replace('/', '-')
utils.update_kv_host(ip, name)
def configure(self, available_hosts, zk_units, peers, extra_libs):
"""
This is the core logic of setting up spark.
:param dict available_hosts: Hosts that Spark should know about.
:param list zk_units: List of Zookeeper dicts with host/port info.
:param list peers: List of Spark peer tuples (unit name, IP).
:param list extra_libs: List of extra lib paths for driver/executors.
"""
# Set KV based on connected applications
unitdata.kv().set('zookeeper.units', zk_units)
unitdata.kv().set('sparkpeer.units', peers)
unitdata.kv().flush(True)
# Get our config ready
dc = self.dist_config
mode = hookenv.config()['spark_execution_mode']
master_ip = utils.resolve_private_address(
available_hosts['spark-master'])
master_url = self.get_master_url(master_ip)
req_driver_mem = hookenv.config()['driver_memory']
req_executor_mem = hookenv.config()['executor_memory']
if mode.startswith('yarn'):
spark_events = 'hdfs://{}'.format(dc.path('spark_events'))
else:
spark_events = 'file://{}'.format(dc.path('spark_events'))
# handle tuning options that may be set as percentages
driver_mem = '1g'
executor_mem = '1g'
if req_driver_mem.endswith('%'):
if mode == 'standalone' or mode.startswith('local'):
mem_mb = host.get_total_ram() / 1024 / 1024
req_percentage = float(req_driver_mem.strip('%')) / 100
driver_mem = str(int(mem_mb * req_percentage)) + 'm'
else:
hookenv.log(
"driver_memory percentage in non-local mode. "
"Using 1g default.",
level=hookenv.WARNING)
else:
driver_mem = req_driver_mem
if req_executor_mem.endswith('%'):
if mode == 'standalone' or mode.startswith('local'):
mem_mb = host.get_total_ram() / 1024 / 1024
req_percentage = float(req_executor_mem.strip('%')) / 100
executor_mem = str(int(mem_mb * req_percentage)) + 'm'
else:
hookenv.log(
"executor_memory percentage in non-local mode. "
"Using 1g default.",
level=hookenv.WARNING)
else:
executor_mem = req_executor_mem
# Some spark applications look for envars in /etc/environment
with utils.environment_edit_in_place('/etc/environment') as env:
env['MASTER'] = master_url
env['SPARK_HOME'] = dc.path('spark_home')
# Setup hosts dict
hosts = {
'spark': master_ip,
}
if 'namenode' in available_hosts:
hosts['namenode'] = available_hosts['namenode']
if 'resourcemanager' in available_hosts:
hosts['resourcemanager'] = available_hosts['resourcemanager']
# Setup roles dict. We always include the history server and client.
# Determine other roles based on our execution mode.
roles = ['spark-history-server', 'spark-client']
if mode == 'standalone':
roles.append('spark-master')
roles.append('spark-worker')
elif mode.startswith('yarn'):
roles.append('spark-on-yarn')
roles.append('spark-yarn-slave')
# Setup overrides dict
override = {
'spark::common::master_url':
master_url,
'spark::common::event_log_dir':
spark_events,
'spark::common::history_log_dir':
spark_events,
'spark::common::extra_lib_dirs':
':'.join(extra_libs) if extra_libs else None,
'spark::common::driver_mem':
driver_mem,
'spark::common::executor_mem':
executor_mem,
}
if zk_units:
zks = []
for unit in zk_units:
ip = utils.resolve_private_address(unit['host'])
zks.append("%s:%s" % (ip, unit['port']))
zk_connect = ",".join(zks)
override['spark::common::zookeeper_connection_string'] = zk_connect
else:
override['spark::common::zookeeper_connection_string'] = None
# Create our site.yaml and trigger puppet.
# NB: during an upgrade, we configure the site.yaml, but do not
# trigger puppet. The user must do that with the 'reinstall' action.
bigtop = Bigtop()
bigtop.render_site_yaml(hosts, roles, override)
if unitdata.kv().get('spark.version.repo', False):
hookenv.log(
"An upgrade is available and the site.yaml has been "
"configured. Run the 'reinstall' action to continue.",
level=hookenv.INFO)
else:
bigtop.trigger_puppet()
self.patch_worker_master_url(master_ip, master_url)
# Packages don't create the event dir by default. Do it each time
# spark is (re)installed to ensure location/perms are correct.
self.configure_events_dir(mode)
# Handle examples and Spark-Bench. Do this each time this method is
# called in case we need to act on a new resource or user config.
self.configure_examples()
self.configure_sparkbench()
def is_master(self):
unit_ip = utils.resolve_private_address(hookenv.unit_private_ip())
master_ip = self.get_master_ip()
return unit_ip == master_ip
def configure(self):
'''
Configure spark environment for all users
'''
spark_home = self.dist_config.path('spark')
spark_bin = spark_home / 'bin'
# handle tuning options that may be set as percentages
driver_mem = '1g'
req_driver_mem = hookenv.config()['driver_memory']
executor_mem = '1g'
req_executor_mem = hookenv.config()['executor_memory']
if req_driver_mem.endswith('%'):
if self.is_spark_local():
mem_mb = host.get_total_ram() / 1024 / 1024
req_percentage = float(req_driver_mem.strip('%')) / 100
driver_mem = str(int(mem_mb * req_percentage)) + 'm'
else:
hookenv.log("driver_memory percentage in non-local mode. Using 1g default.",
level=None)
else:
driver_mem = req_driver_mem
if req_executor_mem.endswith('%'):
if self.is_spark_local():
mem_mb = host.get_total_ram() / 1024 / 1024
req_percentage = float(req_executor_mem.strip('%')) / 100
executor_mem = str(int(mem_mb * req_percentage)) + 'm'
else:
hookenv.log("executor_memory percentage in non-local mode. Using 1g default.",
level=None)
else:
executor_mem = req_executor_mem
# update environment variables
with utils.environment_edit_in_place('/etc/environment') as env:
if spark_bin not in env['PATH']:
env['PATH'] = ':'.join([env['PATH'], spark_bin])
env['MASTER'] = self.get_master()
env['PYSPARK_DRIVER_PYTHON'] = "ipython"
env['SPARK_CONF_DIR'] = self.dist_config.path('spark_conf')
env['SPARK_DRIVER_MEMORY'] = driver_mem
env['SPARK_EXECUTOR_MEMORY'] = executor_mem
env['SPARK_HOME'] = spark_home
env['SPARK_JAR'] = "hdfs:///user/ubuntu/share/lib/spark-assembly.jar"
# update spark config
spark_conf = self.dist_config.path('spark_conf') / 'spark-defaults.conf'
utils.re_edit_in_place(spark_conf, {
r'.*spark.master *.*': 'spark.master {}'.format(self.get_master()),
r'.*spark.eventLog.enabled *.*': 'spark.eventLog.enabled true',
r'.*spark.eventLog.dir *.*': 'spark.eventLog.dir hdfs:///user/ubuntu/directory',
})
spark_env = self.dist_config.path('spark_conf') / 'spark-env.sh'
local_ip = utils.resolve_private_address(hookenv.unit_private_ip())
utils.re_edit_in_place(spark_env, {
r'.*SPARK_DRIVER_MEMORY.*': 'SPARK_DRIVER_MEMORY={}'.format(driver_mem),
r'.*SPARK_EXECUTOR_MEMORY.*': 'SPARK_EXECUTOR_MEMORY={}'.format(executor_mem),
r'.*SPARK_LOG_DIR.*': 'SPARK_LOG_DIR={}'.format(self.dist_config.path('spark_logs')),
r'.*SPARK_MASTER_IP.*': 'SPARK_MASTER_IP={}'.format(local_ip),
r'.*SPARK_WORKER_DIR.*': 'SPARK_WORKER_DIR={}'.format(self.dist_config.path('spark_work')),
})
# manage SparkBench
install_sb = hookenv.config()['spark_bench_enabled']
sb_dir = '/home/ubuntu/spark-bench'
if install_sb:
if utils.cpu_arch() == 'ppc64le':
sb_url = hookenv.config()['spark_bench_ppc64le']
else:
# TODO: may need more arch cases (go with x86 sb for now)
sb_url = hookenv.config()['spark_bench_x86_64']
Path(sb_dir).rmtree_p()
fetcher = ArchiveUrlFetchHandler()
fetcher.install(sb_url, '/home/ubuntu')
# #####
# Handle glob if we use a .tgz that doesn't expand to sb_dir
# sb_archive_dir = glob('/home/ubuntu/spark-bench-*')[0]
# SparkBench expects to live in ~/spark-bench, so put it there
# Path(sb_archive_dir).rename(sb_dir)
# #####
# comment out mem tunings (let them come from /etc/environment)
sb_env = Path(sb_dir) / 'conf/env.sh'
utils.re_edit_in_place(sb_env, {
r'^SPARK_DRIVER_MEMORY.*': '# SPARK_DRIVER_MEMORY (use value from environment)',
r'^SPARK_EXECUTOR_MEMORY.*': '# SPARK_EXECUTOR_MEMORY (use value from environment)',
})
else:
Path(sb_dir).rmtree_p()
def configure(self, available_hosts, zk_units, peers):
"""
This is the core logic of setting up spark.
Two flags are needed:
* Namenode exists aka HDFS is ready
* Resource manager exists aka YARN is ready
both flags are infered from the available hosts.
:param dict available_hosts: Hosts that Spark should know about.
"""
# Bootstrap spark
if not unitdata.kv().get('spark.bootstrapped', False):
self.setup()
unitdata.kv().set('spark.bootstrapped', True)
# Set KV based on connected applications
unitdata.kv().set('zookeeper.units', zk_units)
unitdata.kv().set('sparkpeer.units', peers)
unitdata.kv().flush(True)
# Get our config ready
dc = self.dist_config
events_log_dir = 'file://{}'.format(dc.path('spark_events'))
mode = hookenv.config()['spark_execution_mode']
master_ip = utils.resolve_private_address(available_hosts['spark-master'])
master_url = self.get_master_url(master_ip)
# Setup hosts dict
hosts = {
'spark': master_ip,
}
if 'namenode' in available_hosts:
hosts['namenode'] = available_hosts['namenode']
events_log_dir = self.setup_hdfs_logs()
if 'resourcemanager' in available_hosts:
hosts['resourcemanager'] = available_hosts['resourcemanager']
# Setup roles dict. We always include the history server and client.
# Determine other roles based on our execution mode.
roles = ['spark-history-server', 'spark-client']
if mode == 'standalone':
roles.append('spark-master')
roles.append('spark-worker')
elif mode.startswith('yarn'):
roles.append('spark-on-yarn')
roles.append('spark-yarn-slave')
# Setup overrides dict
override = {
'spark::common::master_url': master_url,
'spark::common::event_log_dir': events_log_dir,
'spark::common::history_log_dir': events_log_dir,
}
if zk_units:
zks = []
for unit in zk_units:
ip = utils.resolve_private_address(unit['host'])
zks.append("%s:%s" % (ip, unit['port']))
zk_connect = ",".join(zks)
override['spark::common::zookeeper_connection_string'] = zk_connect
else:
override['spark::common::zookeeper_connection_string'] = None
# Create our site.yaml and trigger puppet
bigtop = Bigtop()
bigtop.render_site_yaml(hosts, roles, override)
bigtop.trigger_puppet()
# Do this after our puppet bits in case puppet overrides needed perms
if 'namenode' not in available_hosts:
# Local event dir (not in HDFS) needs to be 777 so non-spark
# users can write job history there. It needs to be g+s so
# all entries will be readable by spark (in the spark group).
# It needs to be +t so users cannot remove files they don't own.
dc.path('spark_events').chmod(0o3777)
self.patch_worker_master_url(master_ip, master_url)
# handle tuning options that may be set as percentages
driver_mem = '1g'
req_driver_mem = hookenv.config()['driver_memory']
executor_mem = '1g'
req_executor_mem = hookenv.config()['executor_memory']
if req_driver_mem.endswith('%'):
if mode == 'standalone' or mode.startswith('local'):
mem_mb = host.get_total_ram() / 1024 / 1024
req_percentage = float(req_driver_mem.strip('%')) / 100
driver_mem = str(int(mem_mb * req_percentage)) + 'm'
else:
hookenv.log("driver_memory percentage in non-local mode. Using 1g default.",
level=None)
else:
driver_mem = req_driver_mem
if req_executor_mem.endswith('%'):
if mode == 'standalone' or mode.startswith('local'):
mem_mb = host.get_total_ram() / 1024 / 1024
req_percentage = float(req_executor_mem.strip('%')) / 100
executor_mem = str(int(mem_mb * req_percentage)) + 'm'
else:
hookenv.log("executor_memory percentage in non-local mode. Using 1g default.",
level=None)
else:
executor_mem = req_executor_mem
spark_env = '/etc/spark/conf/spark-env.sh'
utils.re_edit_in_place(spark_env, {
r'.*SPARK_DRIVER_MEMORY.*': 'export SPARK_DRIVER_MEMORY={}'.format(driver_mem),
r'.*SPARK_EXECUTOR_MEMORY.*': 'export SPARK_EXECUTOR_MEMORY={}'.format(executor_mem),
}, append_non_matches=True)
# Install SB (subsequent calls will reconfigure existing install)
# SparkBench looks for the spark master in /etc/environment
with utils.environment_edit_in_place('/etc/environment') as env:
env['MASTER'] = master_url
self.install_benchmark()
def configure(self, available_hosts, zk_units, peers, extra_libs):
"""
This is the core logic of setting up spark.
:param dict available_hosts: Hosts that Spark should know about.
:param list zk_units: List of Zookeeper dicts with host/port info.
:param list peers: List of Spark peer tuples (unit name, IP).
:param list extra_libs: List of extra lib paths for driver/executors.
"""
# Set KV based on connected applications
unitdata.kv().set('zookeeper.units', zk_units)
unitdata.kv().set('sparkpeer.units', peers)
unitdata.kv().flush(True)
# Get our config ready
dc = self.dist_config
mode = hookenv.config()['spark_execution_mode']
master_ip = utils.resolve_private_address(available_hosts['spark-master'])
master_url = self.get_master_url(master_ip)
req_driver_mem = hookenv.config()['driver_memory']
req_executor_mem = hookenv.config()['executor_memory']
if mode.startswith('yarn'):
spark_events = 'hdfs://{}'.format(dc.path('spark_events'))
else:
spark_events = 'file://{}'.format(dc.path('spark_events'))
# handle tuning options that may be set as percentages
driver_mem = '1g'
executor_mem = '1g'
if req_driver_mem.endswith('%'):
if mode == 'standalone' or mode.startswith('local'):
mem_mb = host.get_total_ram() / 1024 / 1024
req_percentage = float(req_driver_mem.strip('%')) / 100
driver_mem = str(int(mem_mb * req_percentage)) + 'm'
else:
hookenv.log("driver_memory percentage in non-local mode. "
"Using 1g default.", level=hookenv.WARNING)
else:
driver_mem = req_driver_mem
if req_executor_mem.endswith('%'):
if mode == 'standalone' or mode.startswith('local'):
mem_mb = host.get_total_ram() / 1024 / 1024
req_percentage = float(req_executor_mem.strip('%')) / 100
executor_mem = str(int(mem_mb * req_percentage)) + 'm'
else:
hookenv.log("executor_memory percentage in non-local mode. "
"Using 1g default.", level=hookenv.WARNING)
else:
executor_mem = req_executor_mem
# Some spark applications look for envars in /etc/environment
with utils.environment_edit_in_place('/etc/environment') as env:
env['MASTER'] = master_url
env['SPARK_HOME'] = dc.path('spark_home')
# Setup hosts dict
hosts = {
'spark': master_ip,
}
if 'namenode' in available_hosts:
hosts['namenode'] = available_hosts['namenode']
if 'resourcemanager' in available_hosts:
hosts['resourcemanager'] = available_hosts['resourcemanager']
# Setup roles dict. We always include the history server and client.
# Determine other roles based on our execution mode.
roles = ['spark-history-server', 'spark-client']
if mode == 'standalone':
roles.append('spark-master')
roles.append('spark-worker')
elif mode.startswith('yarn'):
roles.append('spark-on-yarn')
roles.append('spark-yarn-slave')
# Setup overrides dict
override = {
'spark::common::master_url': master_url,
'spark::common::event_log_dir': spark_events,
'spark::common::history_log_dir': spark_events,
'spark::common::extra_lib_dirs':
':'.join(extra_libs) if extra_libs else None,
'spark::common::driver_mem': driver_mem,
'spark::common::executor_mem': executor_mem,
}
if zk_units:
zks = []
for unit in zk_units:
ip = utils.resolve_private_address(unit['host'])
zks.append("%s:%s" % (ip, unit['port']))
zk_connect = ",".join(zks)
override['spark::common::zookeeper_connection_string'] = zk_connect
else:
override['spark::common::zookeeper_connection_string'] = None
# Create our site.yaml and trigger puppet.
# NB: during an upgrade, we configure the site.yaml, but do not
# trigger puppet. The user must do that with the 'reinstall' action.
bigtop = Bigtop()
bigtop.render_site_yaml(hosts, roles, override)
if unitdata.kv().get('spark.version.repo', False):
hookenv.log("An upgrade is available and the site.yaml has been "
"configured. Run the 'reinstall' action to continue.",
level=hookenv.INFO)
else:
bigtop.trigger_puppet()
self.patch_worker_master_url(master_ip, master_url)
# Packages don't create the event dir by default. Do it each time
# spark is (re)installed to ensure location/perms are correct.
self.configure_events_dir(mode)
# Handle examples and Spark-Bench. Do this each time this method is
# called in case we need to act on a new resource or user config.
self.configure_examples()
self.configure_sparkbench()
def register_connected_hosts(self):
for unit, data in self.unfiltered_data().items():
ip = utils.resolve_private_address(data['private-address'])
name = unit.replace('/', '-')
utils.update_kv_host(ip, name)
def configure(self):
'''
Configure spark environment for all users
'''
spark_home = self.dist_config.path('spark')
spark_bin = spark_home / 'bin'
# handle tuning options that may be set as percentages
driver_mem = '1g'
req_driver_mem = hookenv.config()['driver_memory']
executor_mem = '1g'
req_executor_mem = hookenv.config()['executor_memory']
if req_driver_mem.endswith('%'):
if self.is_spark_local():
mem_mb = host.get_total_ram() / 1024 / 1024
req_percentage = float(req_driver_mem.strip('%')) / 100
driver_mem = str(int(mem_mb * req_percentage)) + 'm'
else:
hookenv.log(
"driver_memory percentage in non-local mode. Using 1g default.",
level=None)
else:
driver_mem = req_driver_mem
if req_executor_mem.endswith('%'):
if self.is_spark_local():
mem_mb = host.get_total_ram() / 1024 / 1024
req_percentage = float(req_executor_mem.strip('%')) / 100
executor_mem = str(int(mem_mb * req_percentage)) + 'm'
else:
hookenv.log(
"executor_memory percentage in non-local mode. Using 1g default.",
level=None)
else:
executor_mem = req_executor_mem
# update environment variables
with utils.environment_edit_in_place('/etc/environment') as env:
if spark_bin not in env['PATH']:
env['PATH'] = ':'.join([env['PATH'], spark_bin])
env['MASTER'] = self.get_master()
env['PYSPARK_DRIVER_PYTHON'] = "ipython"
env['SPARK_CONF_DIR'] = self.dist_config.path('spark_conf')
env['SPARK_DRIVER_MEMORY'] = driver_mem
env['SPARK_EXECUTOR_MEMORY'] = executor_mem
env['SPARK_HOME'] = spark_home
env['SPARK_JAR'] = "hdfs:///user/ubuntu/share/lib/spark-assembly.jar"
# update spark config
spark_conf = self.dist_config.path(
'spark_conf') / 'spark-defaults.conf'
utils.re_edit_in_place(
spark_conf, {
r'.*spark.master *.*':
'spark.master {}'.format(self.get_master()),
r'.*spark.eventLog.enabled *.*':
'spark.eventLog.enabled true',
r'.*spark.eventLog.dir *.*':
'spark.eventLog.dir hdfs:///user/ubuntu/directory',
})
spark_env = self.dist_config.path('spark_conf') / 'spark-env.sh'
local_ip = utils.resolve_private_address(hookenv.unit_private_ip())
utils.re_edit_in_place(
spark_env, {
r'.*SPARK_DRIVER_MEMORY.*':
'SPARK_DRIVER_MEMORY={}'.format(driver_mem),
r'.*SPARK_EXECUTOR_MEMORY.*':
'SPARK_EXECUTOR_MEMORY={}'.format(executor_mem),
r'.*SPARK_LOG_DIR.*':
'SPARK_LOG_DIR={}'.format(self.dist_config.path('spark_logs')),
r'.*SPARK_MASTER_IP.*':
'SPARK_MASTER_IP={}'.format(local_ip),
r'.*SPARK_WORKER_DIR.*':
'SPARK_WORKER_DIR={}'.format(
self.dist_config.path('spark_work')),
})
# manage SparkBench
install_sb = hookenv.config()['spark_bench_enabled']
sb_dir = '/home/ubuntu/spark-bench'
if install_sb:
if utils.cpu_arch() == 'ppc64le':
sb_url = hookenv.config()['spark_bench_ppc64le']
else:
# TODO: may need more arch cases (go with x86 sb for now)
sb_url = hookenv.config()['spark_bench_x86_64']
Path(sb_dir).rmtree_p()
fetcher = ArchiveUrlFetchHandler()
fetcher.install(sb_url, '/home/ubuntu')
# #####
# Handle glob if we use a .tgz that doesn't expand to sb_dir
# sb_archive_dir = glob('/home/ubuntu/spark-bench-*')[0]
# SparkBench expects to live in ~/spark-bench, so put it there
# Path(sb_archive_dir).rename(sb_dir)
# #####
# comment out mem tunings (let them come from /etc/environment)
sb_env = Path(sb_dir) / 'conf/env.sh'
utils.re_edit_in_place(
sb_env, {
r'^SPARK_DRIVER_MEMORY.*':
'# SPARK_DRIVER_MEMORY (use value from environment)',
r'^SPARK_EXECUTOR_MEMORY.*':
'# SPARK_EXECUTOR_MEMORY (use value from environment)',
})
else:
Path(sb_dir).rmtree_p()
def setup_kafka_config(self):
'''
copy the default configuration files to kafka_conf property
defined in dist.yaml
'''
default_conf = self.dist_config.path('kafka') / 'config'
kafka_conf = self.dist_config.path('kafka_conf')
kafka_conf.rmtree_p()
default_conf.copytree(kafka_conf)
# Now remove the conf included in the tarball and symlink our real conf
# dir. we've seen issues where kafka still looks for config in
# KAFKA_HOME/config.
default_conf.rmtree_p()
kafka_conf.symlink(default_conf)
# Similarly, we've seen issues where kafka wants to write to
# KAFKA_HOME/logs regardless of the LOG_DIR, so make a symlink.
default_logs = self.dist_config.path('kafka') / 'logs'
kafka_logs = self.dist_config.path('kafka_app_logs')
default_logs.rmtree_p()
kafka_logs.symlink(default_logs)
# Configure environment
kafka_bin = self.dist_config.path('kafka') / 'bin'
with utils.environment_edit_in_place('/etc/environment') as env:
if kafka_bin not in env['PATH']:
env['PATH'] = ':'.join([env['PATH'], kafka_bin])
env['LOG_DIR'] = self.dist_config.path('kafka_app_logs')
# Configure server.properties
# note: we set the advertised.host.name below to the public_address
# to ensure that external (non-Juju) clients can connect to Kafka
public_address = hookenv.unit_get('public-address')
private_ip = utils.resolve_private_address(hookenv.unit_get('private-address'))
kafka_port = self.dist_config.port('kafka')
kafka_server_conf = self.dist_config.path('kafka_conf') / 'server.properties'
service, unit_num = os.environ['JUJU_UNIT_NAME'].split('/', 1)
utils.re_edit_in_place(kafka_server_conf, {
r'^broker.id=.*': 'broker.id=%s' % unit_num,
r'^port=.*': 'port=%s' % kafka_port,
r'^log.dirs=.*': 'log.dirs=%s' % self.dist_config.path('kafka_data_logs'),
r'^#?advertised.host.name=.*': 'advertised.host.name=%s' % public_address,
})
# Configure producer.properties
# note: we set the broker list host below to the public_address
# to ensure that external (non-Juju) clients can connect to Kafka.
# It must match our advertised.host.name from above.
kafka_producer_conf = self.dist_config.path('kafka_conf') / 'producer.properties'
utils.re_edit_in_place(kafka_producer_conf, {
r'^#?metadata.broker.list=.*': 'metadata.broker.list=%s:%s' % (public_address, kafka_port),
})
# Configure log properties
kafka_log4j = self.dist_config.path('kafka_conf') / 'log4j.properties'
utils.re_edit_in_place(kafka_log4j, {
r'^kafka.logs.dir=.*': 'kafka.logs.dir=%s' % self.dist_config.path('kafka_app_logs'),
})
template_name = 'upstart.conf'
template_path = '/etc/init/kafka.conf'
if host.init_is_systemd():
template_name = 'systemd.conf'
template_path = '/etc/systemd/system/kafka.service'
templating.render(
template_name,
template_path,
context={
'kafka_conf': self.dist_config.path('kafka_conf'),
'kafka_bin': '{}/bin'.format(self.dist_config.path('kafka'))
},
)
# fix for lxc containers and some corner cases in manual provider
# ensure that public_address is resolvable internally by mapping it to the private IP
utils.update_kv_host(private_ip, public_address)
utils.manage_etc_hosts()
def is_master(self):
unit_ip = utils.resolve_private_address(hookenv.unit_private_ip())
master_ip = self.get_master_ip()
return unit_ip == master_ip
def am_i_registered(self):
my_ip = utils.resolve_private_address(hookenv.unit_get('private-address'))
my_hostname = hookenv.local_unit().replace('/', '-')
unit, data = any_ready_unit(self.relation_name)
etc_hosts = json.loads((data or {}).get('etc_hosts', '{}'))
return etc_hosts.get(my_ip, None) == my_hostname
def configure(self, available_hosts, zk_units, peers, extra_libs):
"""
This is the core logic of setting up spark.
:param dict available_hosts: Hosts that Spark should know about.
:param list zk_units: List of Zookeeper dicts with host/port info.
:param list peers: List of Spark peer tuples (unit name, IP).
:param list extra_libs: List of extra lib paths for driver/executors.
"""
# Bootstrap spark
if not unitdata.kv().get('spark.bootstrapped', False):
self.setup()
unitdata.kv().set('spark.bootstrapped', True)
# Set KV based on connected applications
unitdata.kv().set('zookeeper.units', zk_units)
unitdata.kv().set('sparkpeer.units', peers)
unitdata.kv().flush(True)
# Get our config ready
dc = self.dist_config
events_log_dir = 'file://{}'.format(dc.path('spark_events'))
mode = hookenv.config()['spark_execution_mode']
master_ip = utils.resolve_private_address(
available_hosts['spark-master'])
master_url = self.get_master_url(master_ip)
req_driver_mem = hookenv.config()['driver_memory']
req_executor_mem = hookenv.config()['executor_memory']
# handle tuning options that may be set as percentages
driver_mem = '1g'
executor_mem = '1g'
if req_driver_mem.endswith('%'):
if mode == 'standalone' or mode.startswith('local'):
mem_mb = host.get_total_ram() / 1024 / 1024
req_percentage = float(req_driver_mem.strip('%')) / 100
driver_mem = str(int(mem_mb * req_percentage)) + 'm'
else:
hookenv.log(
"driver_memory percentage in non-local mode. Using 1g default.",
level=None)
else:
driver_mem = req_driver_mem
if req_executor_mem.endswith('%'):
if mode == 'standalone' or mode.startswith('local'):
mem_mb = host.get_total_ram() / 1024 / 1024
req_percentage = float(req_executor_mem.strip('%')) / 100
executor_mem = str(int(mem_mb * req_percentage)) + 'm'
else:
hookenv.log(
"executor_memory percentage in non-local mode. Using 1g default.",
level=None)
else:
executor_mem = req_executor_mem
# Setup hosts dict
hosts = {
'spark': master_ip,
}
if 'namenode' in available_hosts:
hosts['namenode'] = available_hosts['namenode']
events_log_dir = self.setup_hdfs_logs()
else:
# Bigtop includes a default hadoop_head_node if we do not specify
# any namenode info. To ensure spark standalone doesn't get
# invalid hadoop config, set our NN to an empty string.
hosts['namenode'] = ''
if 'resourcemanager' in available_hosts:
hosts['resourcemanager'] = available_hosts['resourcemanager']
# Setup roles dict. We always include the history server and client.
# Determine other roles based on our execution mode.
roles = ['spark-history-server', 'spark-client']
if mode == 'standalone':
roles.append('spark-master')
roles.append('spark-worker')
elif mode.startswith('yarn'):
roles.append('spark-on-yarn')
roles.append('spark-yarn-slave')
# Setup overrides dict
override = {
'spark::common::master_url':
master_url,
'spark::common::event_log_dir':
events_log_dir,
'spark::common::history_log_dir':
events_log_dir,
'spark::common::extra_lib_dirs':
':'.join(extra_libs) if extra_libs else None,
'spark::common::driver_mem':
driver_mem,
'spark::common::executor_mem':
executor_mem,
}
if zk_units:
zks = []
for unit in zk_units:
ip = utils.resolve_private_address(unit['host'])
zks.append("%s:%s" % (ip, unit['port']))
zk_connect = ",".join(zks)
override['spark::common::zookeeper_connection_string'] = zk_connect
else:
override['spark::common::zookeeper_connection_string'] = None
# Create our site.yaml and trigger puppet
bigtop = Bigtop()
bigtop.render_site_yaml(hosts, roles, override)
bigtop.trigger_puppet()
# Do this after our puppet bits in case puppet overrides needed perms
if 'namenode' not in available_hosts:
# Local event dir (not in HDFS) needs to be 777 so non-spark
# users can write job history there. It needs to be g+s so
# all entries will be readable by spark (in the spark group).
# It needs to be +t so users cannot remove files they don't own.
dc.path('spark_events').chmod(0o3777)
self.patch_worker_master_url(master_ip, master_url)
# Install SB (subsequent calls will reconfigure existing install)
# SparkBench looks for the spark master in /etc/environment
with utils.environment_edit_in_place('/etc/environment') as env:
env['MASTER'] = master_url
self.install_benchmark()
def configure(self, available_hosts, zk_units, peers):
"""
This is the core logic of setting up spark.
Two flags are needed:
* Namenode exists aka HDFS is there
* Resource manager exists aka YARN is ready
both flags are infered from the available hosts.
:param dict available_hosts: Hosts that Spark should know about.
"""
unitdata.kv().set('zookeeper.units', zk_units)
unitdata.kv().set('sparkpeer.units', peers)
unitdata.kv().flush(True)
if not unitdata.kv().get('spark.bootstrapped', False):
self.setup()
unitdata.kv().set('spark.bootstrapped', True)
master_ip = utils.resolve_private_address(available_hosts['spark-master'])
hosts = {
'spark': master_ip,
}
dc = self.dist_config
events_log_dir = 'file://{}'.format(dc.path('spark_events'))
if 'namenode' in available_hosts:
hosts['namenode'] = available_hosts['namenode']
events_log_dir = self.setup_hdfs_logs()
if 'resourcemanager' in available_hosts:
hosts['resourcemanager'] = available_hosts['resourcemanager']
roles = self.get_roles()
override = {
'spark::common::master_url': self.get_master_url(master_ip),
'spark::common::event_log_dir': events_log_dir,
'spark::common::history_log_dir': events_log_dir,
}
if zk_units:
zks = []
for unit in zk_units:
ip = utils.resolve_private_address(unit['host'])
zks.append("%s:%s" % (ip, unit['port']))
zk_connect = ",".join(zks)
override['spark::common::zookeeper_connection_string'] = zk_connect
else:
override['spark::common::zookeeper_connection_string'] = ""
bigtop = Bigtop()
bigtop.render_site_yaml(hosts, roles, override)
bigtop.trigger_puppet()
# There is a race condition here.
# The work role will not start the first time we trigger puppet apply.
# The exception in /var/logs/spark:
# Exception in thread "main" org.apache.spark.SparkException: Invalid master URL: spark://:7077
# The master url is not set at the time the worker start the first time.
# TODO(kjackal): ...do the needed... (investiate,debug,submit patch)
bigtop.trigger_puppet()
if 'namenode' not in available_hosts:
# Local event dir (not in HDFS) needs to be 777 so non-spark
# users can write job history there. It needs to be g+s so
# all entries will be readable by spark (in the spark group).
# It needs to be +t so users cannot remove files they don't own.
dc.path('spark_events').chmod(0o3777)
self.patch_worker_master_url(master_ip)
# SparkBench looks for the spark master in /etc/environment
with utils.environment_edit_in_place('/etc/environment') as env:
env['MASTER'] = self.get_master_url(master_ip)
# Install SB (subsequent calls will reconfigure existing install)
self.install_benchmark()
