openstack/deb-sahara
Code Issues Proposed changes
0204314c41
deb-sahara/sahara/plugins/spark/config_helper.py
Michael Ionkin b5bb9f97dc Add hadoop openstack swift jar to ambari cluster 
This patch adds our custom hadoop swiftfs implementation to Ambari
cluster instances after their start in order to allow usage of
swift with Keystone API v3.
p.s. required jar file should be previously saved in the
     /opt folder of the base images.

Closes-bug: 1558064
Change-Id: Ie6df4a542a16b4417b505b4a621e8b4b921364d3
2016-03-25 12:53:14 +03:00

518 lines
19 KiB
Python
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# Copyright (c) 2014 Hoang Do, Phuc Vo, P. Michiardi, D. Venzano
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
# implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from oslo_config import cfg
from oslo_log import log as logging
import six
from sahara import conductor as c
from sahara.plugins import provisioning as p
from sahara.plugins import utils
from sahara.swift import swift_helper as swift
from sahara.topology import topology_helper as topology
from sahara.utils import files as f
from sahara.utils import types as types
from sahara.utils import xmlutils as x
conductor = c.API
LOG = logging.getLogger(__name__)
CONF = cfg.CONF
CORE_DEFAULT = x.load_hadoop_xml_defaults(
'plugins/spark/resources/core-default.xml')
HDFS_DEFAULT = x.load_hadoop_xml_defaults(
'plugins/spark/resources/hdfs-default.xml')
SWIFT_DEFAULTS = swift.read_default_swift_configs()
XML_CONFS = {
"HDFS": [CORE_DEFAULT, HDFS_DEFAULT, SWIFT_DEFAULTS]
}
_default_executor_classpath = ":".join(
['/usr/lib/hadoop-mapreduce/hadoop-openstack.jar'])
SPARK_CONFS = {
'Spark': {
"OPTIONS": [
{
'name': 'Executor extra classpath',
'description': 'Value for spark.executor.extraClassPath'
' in spark-defaults.conf'
' (default: %s)' % _default_executor_classpath,
'default': '%s' % _default_executor_classpath,
'priority': 2,
},
{
'name': 'Master port',
'description': 'Start the master on a different port'
' (default: 7077)',
'default': '7077',
'priority': 2,
},
{
'name': 'Worker port',
'description': 'Start the Spark worker on a specific port'
' (default: random)',
'default': 'random',
'priority': 2,
},
{
'name': 'Master webui port',
'description': 'Port for the master web UI (default: 8080)',
'default': '8080',
'priority': 1,
},
{
'name': 'Worker webui port',
'description': 'Port for the worker web UI (default: 8081)',
'default': '8081',
'priority': 1,
},
{
'name': 'Worker cores',
'description': 'Total number of cores to allow Spark'
' applications to use on the machine'
' (default: all available cores)',
'default': 'all',
'priority': 2,
},
{
'name': 'Worker memory',
'description': 'Total amount of memory to allow Spark'
' applications to use on the machine, e.g. 1000m,'
' 2g (default: total memory minus 1 GB)',
'default': 'all',
'priority': 1,
},
{
'name': 'Worker instances',
'description': 'Number of worker instances to run on each'
' machine (default: 1)',
'default': '1',
'priority': 2,
},
{
'name': 'Spark home',
'description': 'The location of the spark installation'
' (default: /opt/spark)',
'default': '/opt/spark',
'priority': 2,
},
{
'name': 'Minimum cleanup seconds',
'description': 'Job data will never be purged before this'
' amount of time elapses (default: 86400 = 1 day)',
'default': '86400',
'priority': 2,
},
{
'name': 'Maximum cleanup seconds',
'description': 'Job data will always be purged after this'
' amount of time elapses (default: 1209600 = 14 days)',
'default': '1209600',
'priority': 2,
},
{
'name': 'Minimum cleanup megabytes',
'description': 'No job data will be purged unless the total'
' job data exceeds this size (default: 4096 = 4GB)',
'default': '4096',
'priority': 2,
},
]
}
}
HADOOP_CONF_DIR = "/etc/hadoop/conf"
ENV_CONFS = {
"HDFS": {
'Name Node Heap Size': 'HADOOP_NAMENODE_OPTS=\\"-Xmx%sm\\"',
'Data Node Heap Size': 'HADOOP_DATANODE_OPTS=\\"-Xmx%sm\\"'
}
}
ENABLE_DATA_LOCALITY = p.Config('Enable Data Locality', 'general', 'cluster',
config_type="bool", priority=1,
default_value=True, is_optional=True)
ENABLE_SWIFT = p.Config('Enable Swift', 'general', 'cluster',
config_type="bool", priority=1,
default_value=True, is_optional=False)
DATANODES_STARTUP_TIMEOUT = p.Config(
'DataNodes startup timeout', 'general', 'cluster', config_type='int',
priority=1, default_value=10800, is_optional=True,
description='Timeout for DataNodes startup, in seconds')
# Default set to 1 day, which is the default Keystone token
# expiration time. After the token is expired we can't continue
# scaling anyway.
DECOMMISSIONING_TIMEOUT = p.Config('Decommissioning Timeout', 'general',
'cluster', config_type='int', priority=1,
default_value=86400, is_optional=True,
description='Timeout for datanode'
' decommissioning operation'
' during scaling, in seconds')
HIDDEN_CONFS = ['fs.defaultFS', 'dfs.namenode.name.dir',
'dfs.datanode.data.dir']
CLUSTER_WIDE_CONFS = ['dfs.block.size', 'dfs.permissions', 'dfs.replication',
'dfs.replication.min', 'dfs.replication.max',
'io.file.buffer.size']
PRIORITY_1_CONFS = ['dfs.datanode.du.reserved',
'dfs.datanode.failed.volumes.tolerated',
'dfs.datanode.max.xcievers', 'dfs.datanode.handler.count',
'dfs.namenode.handler.count']
# for now we have not so many cluster-wide configs
# lets consider all of them having high priority
PRIORITY_1_CONFS += CLUSTER_WIDE_CONFS
def _initialise_configs():
configs = []
for service, config_lists in six.iteritems(XML_CONFS):
for config_list in config_lists:
for config in config_list:
if config['name'] not in HIDDEN_CONFS:
cfg = p.Config(config['name'], service, "node",
is_optional=True, config_type="string",
default_value=str(config['value']),
description=config['description'])
if cfg.default_value in ["true", "false"]:
cfg.config_type = "bool"
cfg.default_value = (cfg.default_value == 'true')
elif types.is_int(cfg.default_value):
cfg.config_type = "int"
cfg.default_value = int(cfg.default_value)
if config['name'] in CLUSTER_WIDE_CONFS:
cfg.scope = 'cluster'
if config['name'] in PRIORITY_1_CONFS:
cfg.priority = 1
configs.append(cfg)
for service, config_items in six.iteritems(ENV_CONFS):
for name, param_format_str in six.iteritems(config_items):
configs.append(p.Config(name, service, "node",
default_value=1024, priority=1,
config_type="int"))
for service, config_items in six.iteritems(SPARK_CONFS):
for item in config_items['OPTIONS']:
cfg = p.Config(name=item["name"],
description=item["description"],
default_value=item["default"],
applicable_target=service,
scope="cluster", is_optional=True,
priority=item["priority"])
configs.append(cfg)
configs.append(DECOMMISSIONING_TIMEOUT)
configs.append(ENABLE_SWIFT)
configs.append(DATANODES_STARTUP_TIMEOUT)
if CONF.enable_data_locality:
configs.append(ENABLE_DATA_LOCALITY)
return configs
# Initialise plugin Hadoop configurations
PLUGIN_CONFIGS = _initialise_configs()
def get_plugin_configs():
return PLUGIN_CONFIGS
def generate_cfg_from_general(cfg, configs, general_config,
rest_excluded=False):
if 'general' in configs:
for nm in general_config:
if nm not in configs['general'] and not rest_excluded:
configs['general'][nm] = general_config[nm]['default_value']
for name, value in configs['general'].items():
if value:
cfg = _set_config(cfg, general_config, name)
LOG.debug("Applying config: {name}".format(name=name))
else:
cfg = _set_config(cfg, general_config)
return cfg
def _get_hostname(service):
return service.hostname() if service else None
def generate_xml_configs(configs, storage_path, nn_hostname, hadoop_port):
if hadoop_port is None:
hadoop_port = 8020
cfg = {
'fs.defaultFS': 'hdfs://%s:%s' % (nn_hostname, str(hadoop_port)),
'dfs.namenode.name.dir': extract_hadoop_path(storage_path,
'/dfs/nn'),
'dfs.datanode.data.dir': extract_hadoop_path(storage_path,
'/dfs/dn'),
'dfs.hosts': '/etc/hadoop/dn.incl',
'dfs.hosts.exclude': '/etc/hadoop/dn.excl'
}
# inserting user-defined configs
for key, value in extract_hadoop_xml_confs(configs):
cfg[key] = value
# Add the swift defaults if they have not been set by the user
swft_def = []
if is_swift_enabled(configs):
swft_def = SWIFT_DEFAULTS
swift_configs = extract_name_values(swift.get_swift_configs())
for key, value in six.iteritems(swift_configs):
if key not in cfg:
cfg[key] = value
# invoking applied configs to appropriate xml files
core_all = CORE_DEFAULT + swft_def
if CONF.enable_data_locality:
cfg.update(topology.TOPOLOGY_CONFIG)
# applying vm awareness configs
core_all += topology.vm_awareness_core_config()
xml_configs = {
'core-site': x.create_hadoop_xml(cfg, core_all),
'hdfs-site': x.create_hadoop_xml(cfg, HDFS_DEFAULT)
}
return xml_configs
def _get_spark_opt_default(opt_name):
for opt in SPARK_CONFS["Spark"]["OPTIONS"]:
if opt_name == opt["name"]:
return opt["default"]
return None
def generate_spark_env_configs(cluster):
configs = []
# master configuration
sp_master = utils.get_instance(cluster, "master")
configs.append('SPARK_MASTER_IP=' + sp_master.hostname())
# point to the hadoop conf dir so that Spark can read things
# like the swift configuration without having to copy core-site
# to /opt/spark/conf
configs.append('HADOOP_CONF_DIR=' + HADOOP_CONF_DIR)
masterport = utils.get_config_value_or_default("Spark",
"Master port",
cluster)
if masterport and masterport != _get_spark_opt_default("Master port"):
configs.append('SPARK_MASTER_PORT=' + str(masterport))
masterwebport = utils.get_config_value_or_default("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 = utils.get_config_value_or_default("Spark",
"Worker cores",
cluster)
if workercores and workercores != _get_spark_opt_default("Worker cores"):
configs.append('SPARK_WORKER_CORES=' + str(workercores))
workermemory = utils.get_config_value_or_default("Spark",
"Worker memory",
cluster)
if (workermemory and
workermemory != _get_spark_opt_default("Worker memory")):
configs.append('SPARK_WORKER_MEMORY=' + str(workermemory))
workerport = utils.get_config_value_or_default("Spark",
"Worker port",
cluster)
if workerport and workerport != _get_spark_opt_default("Worker port"):
configs.append('SPARK_WORKER_PORT=' + str(workerport))
workerwebport = utils.get_config_value_or_default("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 = utils.get_config_value_or_default("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)
# workernames need to be a list of woker names
def generate_spark_slaves_configs(workernames):
return '\n'.join(workernames)
def generate_spark_executor_classpath(cluster):
cp = utils.get_config_value_or_default("Spark",
"Executor extra classpath",
cluster)
if cp:
return "spark.executor.extraClassPath " + cp
return "\n"
def extract_hadoop_environment_confs(configs):
"""Returns environment specific Hadoop configurations.
:returns list of Hadoop parameters which should be passed via environment
"""
lst = []
for service, srv_confs in configs.items():
if ENV_CONFS.get(service):
for param_name, param_value in srv_confs.items():
for cfg_name, cfg_format_str in ENV_CONFS[service].items():
if param_name == cfg_name and param_value is not None:
lst.append(cfg_format_str % param_value)
return lst
def extract_hadoop_xml_confs(configs):
"""Returns xml specific Hadoop configurations.
:returns list of Hadoop parameters which should be passed into general
configs like core-site.xml
"""
lst = []
for service, srv_confs in configs.items():
if XML_CONFS.get(service):
for param_name, param_value in srv_confs.items():
for cfg_list in XML_CONFS[service]:
names = [cfg['name'] for cfg in cfg_list]
if param_name in names and param_value is not None:
lst.append((param_name, param_value))
return lst
def generate_hadoop_setup_script(storage_paths, env_configs):
script_lines = ["#!/bin/bash -x"]
script_lines.append("echo -n > /tmp/hadoop-env.sh")
for line in env_configs:
if 'HADOOP' in line:
script_lines.append('echo "%s" >> /tmp/hadoop-env.sh' % line)
script_lines.append("cat /etc/hadoop/hadoop-env.sh >> /tmp/hadoop-env.sh")
script_lines.append("cp /tmp/hadoop-env.sh /etc/hadoop/hadoop-env.sh")
hadoop_log = storage_paths[0] + "/log/hadoop/\$USER/"
script_lines.append('sed -i "s,export HADOOP_LOG_DIR=.*,'
'export HADOOP_LOG_DIR=%s," /etc/hadoop/hadoop-env.sh'
% hadoop_log)
hadoop_log = storage_paths[0] + "/log/hadoop/hdfs"
script_lines.append('sed -i "s,export HADOOP_SECURE_DN_LOG_DIR=.*,'
'export HADOOP_SECURE_DN_LOG_DIR=%s," '
'/etc/hadoop/hadoop-env.sh' % hadoop_log)
for path in storage_paths:
script_lines.append("chown -R hadoop:hadoop %s" % path)
script_lines.append("chmod -f -R 755 %s ||"
"echo 'Permissions unchanged'" % path)
return "\n".join(script_lines)
def generate_job_cleanup_config(cluster):
args = {
'minimum_cleanup_megabytes': utils.get_config_value_or_default(
"Spark", "Minimum cleanup megabytes", cluster),
'minimum_cleanup_seconds': utils.get_config_value_or_default(
"Spark", "Minimum cleanup seconds", cluster),
'maximum_cleanup_seconds': utils.get_config_value_or_default(
"Spark", "Maximum cleanup seconds", cluster)
}
job_conf = {'valid': (args['maximum_cleanup_seconds'] > 0 and
(args['minimum_cleanup_megabytes'] > 0
and args['minimum_cleanup_seconds'] > 0))}
if job_conf['valid']:
job_conf['cron'] = f.get_file_text(
'plugins/spark/resources/spark-cleanup.cron'),
job_cleanup_script = f.get_file_text(
'plugins/spark/resources/tmp-cleanup.sh.template')
job_conf['script'] = job_cleanup_script.format(**args)
return job_conf
def extract_name_values(configs):
return {cfg['name']: cfg['value'] for cfg in configs}
def make_hadoop_path(base_dirs, suffix):
return [base_dir + suffix for base_dir in base_dirs]
def extract_hadoop_path(lst, hadoop_dir):
if lst:
return ",".join(make_hadoop_path(lst, hadoop_dir))
def _set_config(cfg, gen_cfg, name=None):
if name in gen_cfg:
cfg.update(gen_cfg[name]['conf'])
if name is None:
for name in gen_cfg:
cfg.update(gen_cfg[name]['conf'])
return cfg
def _get_general_config_value(conf, option):
if 'general' in conf and option.name in conf['general']:
return conf['general'][option.name]
return option.default_value
def _get_general_cluster_config_value(cluster, option):
return _get_general_config_value(cluster.cluster_configs, option)
def is_data_locality_enabled(cluster):
if not CONF.enable_data_locality:
return False
return _get_general_cluster_config_value(cluster, ENABLE_DATA_LOCALITY)
def is_swift_enabled(configs):
return _get_general_config_value(configs, ENABLE_SWIFT)
def get_decommissioning_timeout(cluster):
return _get_general_cluster_config_value(cluster, DECOMMISSIONING_TIMEOUT)
def get_port_from_config(service, name, cluster=None):
address = utils.get_config_value_or_default(service, name, cluster)
return utils.get_port_from_address(address)
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