256 lines
9.8 KiB
Python
256 lines
9.8 KiB
Python
# Copyright (c) 2013 Mirantis Inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
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# implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import six
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import six.moves.urllib.parse as urlparse
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from sahara import conductor as c
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from sahara import context
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from sahara.plugins import base as plugin_base
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from sahara.service.edp.workflow_creator import hive_workflow
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from sahara.service.edp.workflow_creator import java_workflow
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from sahara.service.edp.workflow_creator import mapreduce_workflow
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from sahara.service.edp.workflow_creator import pig_workflow
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from sahara.swift import swift_helper as sw
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from sahara.swift import utils as su
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from sahara.utils import edp
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from sahara.utils import xmlutils
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conductor = c.API
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class BaseFactory(object):
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def _separate_edp_configs(self, job_dict):
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configs = {}
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edp_configs = {}
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if 'configs' in job_dict:
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for k, v in six.iteritems(job_dict['configs']):
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if k.startswith('edp.'):
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edp_configs[k] = v
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else:
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configs[k] = v
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return configs, edp_configs
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def _prune_edp_configs(self, job_dict):
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if job_dict is None:
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return {}, {}
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# Rather than copy.copy, we make this by hand
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# to avoid FrozenClassError when we update 'configs'
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pruned_job_dict = {}
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for k, v in six.iteritems(job_dict):
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pruned_job_dict[k] = v
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# Separate out "edp." configs into its own dictionary
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configs, edp_configs = self._separate_edp_configs(job_dict)
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# Prune the new job_dict so it does not hold "edp." configs
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pruned_job_dict['configs'] = configs
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return pruned_job_dict, edp_configs
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def _update_dict(self, dest, src):
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if src is not None:
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for key, value in six.iteritems(dest):
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if hasattr(value, "update"):
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new_vals = src.get(key, {})
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value.update(new_vals)
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def inject_swift_url_suffix(self, url):
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if url.startswith("swift://"):
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u = urlparse.urlparse(url)
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if not u.netloc.endswith(su.SWIFT_URL_SUFFIX):
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return url.replace(u.netloc,
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u.netloc+"%s" % su.SWIFT_URL_SUFFIX, 1)
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return url
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def update_job_dict(self, job_dict, exec_dict):
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pruned_exec_dict, edp_configs = self._prune_edp_configs(exec_dict)
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self._update_dict(job_dict, pruned_exec_dict)
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# Add the separated "edp." configs to the job_dict
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job_dict['edp_configs'] = edp_configs
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# Args are listed, not named. Simply replace them.
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job_dict['args'] = pruned_exec_dict.get('args', [])
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# Find all swift:// paths in args, configs, and params and
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# add the .sahara suffix to the container if it is not there
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# already
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job_dict['args'] = [
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# TODO(tmckay) args for Pig can actually be -param name=value
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# and value could conceivably contain swift paths
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self.inject_swift_url_suffix(arg) for arg in job_dict['args']]
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for k, v in six.iteritems(job_dict.get('configs', {})):
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job_dict['configs'][k] = self.inject_swift_url_suffix(v)
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for k, v in six.iteritems(job_dict.get('params', {})):
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job_dict['params'][k] = self.inject_swift_url_suffix(v)
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def get_configs(self, input_data, output_data):
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configs = {}
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for src in (input_data, output_data):
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if src.type == "swift" and hasattr(src, "credentials"):
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if "user" in src.credentials:
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configs[sw.HADOOP_SWIFT_USERNAME] = src.credentials['user']
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if "password" in src.credentials:
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configs[
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sw.HADOOP_SWIFT_PASSWORD] = src.credentials['password']
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break
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return configs
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def get_params(self, input_data, output_data):
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return {'INPUT': input_data.url,
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'OUTPUT': output_data.url}
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class PigFactory(BaseFactory):
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def __init__(self, job):
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super(PigFactory, self).__init__()
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self.name = self.get_script_name(job)
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def get_script_name(self, job):
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return conductor.job_main_name(context.ctx(), job)
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def get_workflow_xml(self, cluster, execution, input_data, output_data):
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job_dict = {'configs': self.get_configs(input_data, output_data),
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'params': self.get_params(input_data, output_data),
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'args': []}
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self.update_job_dict(job_dict, execution.job_configs)
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creator = pig_workflow.PigWorkflowCreator()
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creator.build_workflow_xml(self.name,
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configuration=job_dict['configs'],
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params=job_dict['params'],
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arguments=job_dict['args'])
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return creator.get_built_workflow_xml()
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class HiveFactory(BaseFactory):
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def __init__(self, job):
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super(HiveFactory, self).__init__()
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self.name = self.get_script_name(job)
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def get_script_name(self, job):
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return conductor.job_main_name(context.ctx(), job)
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def get_workflow_xml(self, cluster, execution, input_data, output_data):
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job_dict = {'configs': self.get_configs(input_data, output_data),
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'params': self.get_params(input_data, output_data)}
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self.update_job_dict(job_dict, execution.job_configs)
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plugin = plugin_base.PLUGINS.get_plugin(cluster.plugin_name)
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hdfs_user = plugin.get_hdfs_user()
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creator = hive_workflow.HiveWorkflowCreator()
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creator.build_workflow_xml(self.name,
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edp.get_hive_shared_conf_path(hdfs_user),
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configuration=job_dict['configs'],
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params=job_dict['params'])
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return creator.get_built_workflow_xml()
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class MapReduceFactory(BaseFactory):
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def get_configs(self, input_data, output_data):
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configs = super(MapReduceFactory, self).get_configs(input_data,
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output_data)
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configs['mapred.input.dir'] = input_data.url
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configs['mapred.output.dir'] = output_data.url
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return configs
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def _get_streaming(self, job_dict):
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prefix = 'edp.streaming.'
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return dict((k[len(prefix):], v) for (k, v) in six.iteritems(
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job_dict['edp_configs']) if k.startswith(prefix))
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def get_workflow_xml(self, cluster, execution, input_data, output_data):
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job_dict = {'configs': self.get_configs(input_data, output_data)}
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self.update_job_dict(job_dict, execution.job_configs)
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creator = mapreduce_workflow.MapReduceWorkFlowCreator()
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creator.build_workflow_xml(configuration=job_dict['configs'],
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streaming=self._get_streaming(job_dict))
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return creator.get_built_workflow_xml()
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class JavaFactory(BaseFactory):
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def _get_java_configs(self, job_dict):
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main_class = job_dict['edp_configs']['edp.java.main_class']
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java_opts = job_dict['edp_configs'].get('edp.java.java_opts', None)
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return main_class, java_opts
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def get_workflow_xml(self, cluster, execution, *args, **kwargs):
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job_dict = {'configs': {},
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'args': []}
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self.update_job_dict(job_dict, execution.job_configs)
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main_class, java_opts = self._get_java_configs(job_dict)
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creator = java_workflow.JavaWorkflowCreator()
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creator.build_workflow_xml(main_class,
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configuration=job_dict['configs'],
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java_opts=java_opts,
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arguments=job_dict['args'])
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return creator.get_built_workflow_xml()
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def get_creator(job):
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def make_PigFactory():
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return PigFactory(job)
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def make_HiveFactory():
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return HiveFactory(job)
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type_map = {
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edp.JOB_TYPE_HIVE: make_HiveFactory,
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edp.JOB_TYPE_JAVA: JavaFactory,
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edp.JOB_TYPE_MAPREDUCE: MapReduceFactory,
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edp.JOB_TYPE_MAPREDUCE_STREAMING: MapReduceFactory,
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edp.JOB_TYPE_PIG: make_PigFactory
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}
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return type_map[job.type]()
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def get_possible_job_config(job_type):
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if not edp.compare_job_type(job_type, *edp.JOB_TYPES_ALL):
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return None
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if edp.compare_job_type(job_type, edp.JOB_TYPE_JAVA):
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return {'job_config': {'configs': [], 'args': []}}
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if edp.compare_job_type(job_type,
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edp.JOB_TYPE_MAPREDUCE, edp.JOB_TYPE_PIG):
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#TODO(nmakhotkin) Here we should return config based on specific plugin
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cfg = xmlutils.load_hadoop_xml_defaults(
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'plugins/vanilla/v1_2_1/resources/mapred-default.xml')
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if edp.compare_job_type(job_type, edp.JOB_TYPE_MAPREDUCE):
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cfg += xmlutils.load_hadoop_xml_defaults(
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'service/edp/resources/mapred-job-config.xml')
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elif edp.compare_job_type(job_type, edp.JOB_TYPE_HIVE):
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#TODO(nmakhotkin) Here we should return config based on specific plugin
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cfg = xmlutils.load_hadoop_xml_defaults(
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'plugins/vanilla/v1_2_1/resources/hive-default.xml')
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# TODO(tmckay): args should be a list when bug #269968
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# is fixed on the UI side
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config = {'configs': cfg, "args": {}}
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if not edp.compare_job_type(edp.JOB_TYPE_MAPREDUCE, edp.JOB_TYPE_JAVA):
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config.update({'params': {}})
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return {'job_config': config}
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