Support Spark 1.3.1
Add version "1.3.1" to the list of supported versions, in tandem with https://review.openstack.org/#/c/195054/ that adds support in the DIB. This one-liner is sufficient, from Sahara's point of view Spark 1.0 and 1.3 are the same. This patch set Updates also the Spark plugin documentation and the tests. Change-Id: I8fa482b6d1d6abaa6633aec309a3ba826a8b7ebb Implements: blueprint support-spark-1-3
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@ -14,8 +14,8 @@ has been developed and tested with the images generated by sahara-image-elements
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* https://github.com/openstack/sahara-image-elements
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Those Ubuntu images already have Cloudera CDH4 HDFS and Apache Spark installed.
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A prepared image can be found at the following location:
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Those Ubuntu images already have Cloudera CDH5 HDFS and Apache Spark installed.
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A prepared image for Spark 1.0 and CDH4 HDFS can be found at the following location:
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* http://sahara-files.mirantis.com/sahara-juno-spark-1.0.0-ubuntu-14.04.qcow2
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@ -23,7 +23,8 @@ The Spark plugin requires an image to be tagged in Sahara Image Registry with
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two tags: 'spark' and '<Spark version>' (e.g. '1.0.0').
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Also you should specify the username of the default cloud-user used in the image. For
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images generated with the DIB it is 'ubuntu'.
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the images available at the URLs listed above and for all the ones generated with the
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DIB it is 'ubuntu'.
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Note that the Spark cluster is deployed using the scripts available in the
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Spark distribution, which allow to start all services (master and slaves), stop
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32
etc/scenario/sahara-ci/spark-1.3.1.yaml
Normal file
32
etc/scenario/sahara-ci/spark-1.3.1.yaml
Normal file
@ -0,0 +1,32 @@
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clusters:
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- plugin_name: spark
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plugin_version: 1.3.1
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image: %spark_image%
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node_group_templates:
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- name: master
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flavor_id: %ci_flavor_id%
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node_processes:
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- master
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- namenode
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auto_security_group: true
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- name: worker
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flavor_id: %ci_flavor_id%
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node_processes:
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- datanode
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- slave
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auto_security_group: true
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cluster_template:
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name: spark131
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node_group_templates:
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master: 1
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worker: 1
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cluster_configs:
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HDFS:
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dfs.replication: 1
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cluster:
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name: %cluster_name%
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scaling:
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- operation: add
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node_group: worker
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size: 1
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edp_jobs_flow: spark_edp
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@ -56,7 +56,7 @@ class SparkProvider(p.ProvisioningPluginBase):
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"CDH cluster without any management consoles.")
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def get_versions(self):
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return ['1.0.0', '0.9.1']
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return ['1.3.1', '1.0.0', '0.9.1']
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def get_configs(self, hadoop_version):
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return c_helper.get_plugin_configs()
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@ -594,7 +594,7 @@ SPARK_CONFIG_OPTS = [
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help='A list of processes that will be launched '
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'on worker nodes'),
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cfg.StrOpt('HADOOP_VERSION',
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default='1.0.0',
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default='1.3.1',
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help='Version of Spark (even though it says "HADOOP".'),
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cfg.StrOpt('HADOOP_USER',
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default='hdfs',
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@ -66,6 +66,19 @@ class SparkPluginTest(base.SaharaWithDbTestCase):
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plugin.get_edp_engine(cluster, edp.JOB_TYPE_SPARK),
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engine.SparkJobEngine)
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def test_plugin13_edp_engine(self):
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cluster_dict = {
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'name': 'cluster',
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'plugin_name': 'spark',
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'hadoop_version': '1.3.1',
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'default_image_id': 'image'}
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cluster = conductor.cluster_create(context.ctx(), cluster_dict)
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plugin = pb.PLUGINS.get_plugin(cluster.plugin_name)
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self.assertIsInstance(
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plugin.get_edp_engine(cluster, edp.JOB_TYPE_SPARK),
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engine.SparkJobEngine)
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def test_cleanup_configs(self):
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remote = mock.Mock()
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instance = mock.Mock()
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