457 lines
14 KiB
Python
457 lines
14 KiB
Python
from __future__ import unicode_literals
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import boto
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from boto.emr.instance_group import InstanceGroup
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from boto.emr.step import StreamingStep
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import sure # noqa
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from moto import mock_emr
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from tests.helpers import requires_boto_gte
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@mock_emr
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def test_create_job_flow_in_multiple_regions():
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step = StreamingStep(
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name='My wordcount example',
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mapper='s3n://elasticmapreduce/samples/wordcount/wordSplitter.py',
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reducer='aggregate',
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input='s3n://elasticmapreduce/samples/wordcount/input',
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output='s3n://output_bucket/output/wordcount_output'
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)
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west1_conn = boto.emr.connect_to_region('us-east-1')
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west1_job_id = west1_conn.run_jobflow(
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name='us-east-1',
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log_uri='s3://some_bucket/jobflow_logs',
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master_instance_type='m1.medium',
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slave_instance_type='m1.small',
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steps=[step],
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)
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west2_conn = boto.emr.connect_to_region('eu-west-1')
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west2_job_id = west2_conn.run_jobflow(
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name='eu-west-1',
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log_uri='s3://some_bucket/jobflow_logs',
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master_instance_type='m1.medium',
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slave_instance_type='m1.small',
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steps=[step],
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)
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west1_job_flow = west1_conn.describe_jobflow(west1_job_id)
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west1_job_flow.name.should.equal('us-east-1')
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west2_job_flow = west2_conn.describe_jobflow(west2_job_id)
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west2_job_flow.name.should.equal('eu-west-1')
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@mock_emr
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def test_create_job_flow():
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conn = boto.connect_emr()
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step1 = StreamingStep(
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name='My wordcount example',
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mapper='s3n://elasticmapreduce/samples/wordcount/wordSplitter.py',
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reducer='aggregate',
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input='s3n://elasticmapreduce/samples/wordcount/input',
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output='s3n://output_bucket/output/wordcount_output'
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)
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step2 = StreamingStep(
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name='My wordcount example2',
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mapper='s3n://elasticmapreduce/samples/wordcount/wordSplitter2.py',
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reducer='aggregate',
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input='s3n://elasticmapreduce/samples/wordcount/input2',
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output='s3n://output_bucket/output/wordcount_output2'
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)
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job_id = conn.run_jobflow(
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name='My jobflow',
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log_uri='s3://some_bucket/jobflow_logs',
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master_instance_type='m1.medium',
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slave_instance_type='m1.small',
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steps=[step1, step2],
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)
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job_flow = conn.describe_jobflow(job_id)
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job_flow.state.should.equal('STARTING')
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job_flow.jobflowid.should.equal(job_id)
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job_flow.name.should.equal('My jobflow')
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job_flow.masterinstancetype.should.equal('m1.medium')
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job_flow.slaveinstancetype.should.equal('m1.small')
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job_flow.loguri.should.equal('s3://some_bucket/jobflow_logs')
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job_flow.visibletoallusers.should.equal('False')
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int(job_flow.normalizedinstancehours).should.equal(0)
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job_step = job_flow.steps[0]
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job_step.name.should.equal('My wordcount example')
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job_step.state.should.equal('STARTING')
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args = [arg.value for arg in job_step.args]
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args.should.equal([
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'-mapper',
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's3n://elasticmapreduce/samples/wordcount/wordSplitter.py',
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'-reducer',
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'aggregate',
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'-input',
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's3n://elasticmapreduce/samples/wordcount/input',
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'-output',
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's3n://output_bucket/output/wordcount_output',
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])
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job_step2 = job_flow.steps[1]
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job_step2.name.should.equal('My wordcount example2')
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job_step2.state.should.equal('PENDING')
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args = [arg.value for arg in job_step2.args]
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args.should.equal([
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'-mapper',
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's3n://elasticmapreduce/samples/wordcount/wordSplitter2.py',
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'-reducer',
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'aggregate',
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'-input',
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's3n://elasticmapreduce/samples/wordcount/input2',
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'-output',
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's3n://output_bucket/output/wordcount_output2',
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])
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@requires_boto_gte("2.8")
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@mock_emr
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def test_create_job_flow_with_new_params():
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# Test that run_jobflow works with newer params
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conn = boto.connect_emr()
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conn.run_jobflow(
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name='My jobflow',
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log_uri='s3://some_bucket/jobflow_logs',
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master_instance_type='m1.medium',
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slave_instance_type='m1.small',
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job_flow_role='some-role-arn',
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steps=[],
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)
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@requires_boto_gte("2.8")
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@mock_emr
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def test_create_job_flow_visible_to_all_users():
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conn = boto.connect_emr()
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job_id = conn.run_jobflow(
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name='My jobflow',
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log_uri='s3://some_bucket/jobflow_logs',
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steps=[],
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visible_to_all_users=True,
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)
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job_flow = conn.describe_jobflow(job_id)
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job_flow.visibletoallusers.should.equal('True')
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@requires_boto_gte("2.8")
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@mock_emr
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def test_create_job_flow_with_instance_groups():
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conn = boto.connect_emr()
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instance_groups = [InstanceGroup(6, 'TASK', 'c1.medium', 'SPOT', 'spot-0.07', '0.07'),
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InstanceGroup(6, 'TASK', 'c1.medium', 'SPOT', 'spot-0.07', '0.07')]
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job_id = conn.run_jobflow(
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name='My jobflow',
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log_uri='s3://some_bucket/jobflow_logs',
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steps=[],
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instance_groups=instance_groups
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)
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job_flow = conn.describe_jobflow(job_id)
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int(job_flow.instancecount).should.equal(12)
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instance_group = job_flow.instancegroups[0]
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int(instance_group.instancerunningcount).should.equal(6)
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@mock_emr
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def test_terminate_job_flow():
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conn = boto.connect_emr()
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job_id = conn.run_jobflow(
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name='My jobflow',
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log_uri='s3://some_bucket/jobflow_logs',
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steps=[]
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)
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flow = conn.describe_jobflows()[0]
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flow.state.should.equal('STARTING')
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conn.terminate_jobflow(job_id)
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flow = conn.describe_jobflows()[0]
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flow.state.should.equal('TERMINATED')
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@mock_emr
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def test_describe_job_flows():
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conn = boto.connect_emr()
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job1_id = conn.run_jobflow(
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name='My jobflow',
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log_uri='s3://some_bucket/jobflow_logs',
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steps=[]
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)
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job2_id = conn.run_jobflow(
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name='My jobflow',
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log_uri='s3://some_bucket/jobflow_logs',
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steps=[]
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)
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jobs = conn.describe_jobflows()
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jobs.should.have.length_of(2)
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jobs = conn.describe_jobflows(jobflow_ids=[job2_id])
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jobs.should.have.length_of(1)
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jobs[0].jobflowid.should.equal(job2_id)
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first_job = conn.describe_jobflow(job1_id)
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first_job.jobflowid.should.equal(job1_id)
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@mock_emr
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def test_add_steps_to_flow():
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conn = boto.connect_emr()
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step1 = StreamingStep(
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name='My wordcount example',
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mapper='s3n://elasticmapreduce/samples/wordcount/wordSplitter.py',
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reducer='aggregate',
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input='s3n://elasticmapreduce/samples/wordcount/input',
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output='s3n://output_bucket/output/wordcount_output'
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)
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job_id = conn.run_jobflow(
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name='My jobflow',
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log_uri='s3://some_bucket/jobflow_logs',
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steps=[step1]
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)
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job_flow = conn.describe_jobflow(job_id)
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job_flow.state.should.equal('STARTING')
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job_flow.jobflowid.should.equal(job_id)
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job_flow.name.should.equal('My jobflow')
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job_flow.loguri.should.equal('s3://some_bucket/jobflow_logs')
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step2 = StreamingStep(
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name='My wordcount example2',
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mapper='s3n://elasticmapreduce/samples/wordcount/wordSplitter2.py',
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reducer='aggregate',
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input='s3n://elasticmapreduce/samples/wordcount/input2',
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output='s3n://output_bucket/output/wordcount_output2'
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)
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conn.add_jobflow_steps(job_id, [step2])
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job_flow = conn.describe_jobflow(job_id)
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job_step = job_flow.steps[0]
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job_step.name.should.equal('My wordcount example')
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job_step.state.should.equal('STARTING')
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args = [arg.value for arg in job_step.args]
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args.should.equal([
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'-mapper',
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's3n://elasticmapreduce/samples/wordcount/wordSplitter.py',
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'-reducer',
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'aggregate',
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'-input',
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's3n://elasticmapreduce/samples/wordcount/input',
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'-output',
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's3n://output_bucket/output/wordcount_output',
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])
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job_step2 = job_flow.steps[1]
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job_step2.name.should.equal('My wordcount example2')
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job_step2.state.should.equal('PENDING')
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args = [arg.value for arg in job_step2.args]
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args.should.equal([
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'-mapper',
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's3n://elasticmapreduce/samples/wordcount/wordSplitter2.py',
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'-reducer',
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'aggregate',
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'-input',
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's3n://elasticmapreduce/samples/wordcount/input2',
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'-output',
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's3n://output_bucket/output/wordcount_output2',
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])
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@mock_emr
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def test_create_instance_groups():
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conn = boto.connect_emr()
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step1 = StreamingStep(
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name='My wordcount example',
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mapper='s3n://elasticmapreduce/samples/wordcount/wordSplitter.py',
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reducer='aggregate',
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input='s3n://elasticmapreduce/samples/wordcount/input',
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output='s3n://output_bucket/output/wordcount_output'
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)
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job_id = conn.run_jobflow(
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name='My jobflow',
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log_uri='s3://some_bucket/jobflow_logs',
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steps=[step1],
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)
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instance_group = InstanceGroup(6, 'TASK', 'c1.medium', 'SPOT', 'spot-0.07', '0.07')
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instance_group = conn.add_instance_groups(job_id, [instance_group])
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instance_group_id = instance_group.instancegroupids
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job_flow = conn.describe_jobflows()[0]
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int(job_flow.instancecount).should.equal(6)
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instance_group = job_flow.instancegroups[0]
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instance_group.instancegroupid.should.equal(instance_group_id)
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int(instance_group.instancerunningcount).should.equal(6)
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instance_group.instancerole.should.equal('TASK')
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instance_group.instancetype.should.equal('c1.medium')
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instance_group.market.should.equal('SPOT')
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instance_group.name.should.equal('spot-0.07')
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instance_group.bidprice.should.equal('0.07')
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@mock_emr
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def test_modify_instance_groups():
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conn = boto.connect_emr()
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step1 = StreamingStep(
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name='My wordcount example',
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mapper='s3n://elasticmapreduce/samples/wordcount/wordSplitter.py',
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reducer='aggregate',
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input='s3n://elasticmapreduce/samples/wordcount/input',
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output='s3n://output_bucket/output/wordcount_output'
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)
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job_id = conn.run_jobflow(
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name='My jobflow',
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log_uri='s3://some_bucket/jobflow_logs',
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steps=[step1]
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)
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instance_group1 = InstanceGroup(6, 'TASK', 'c1.medium', 'SPOT', 'spot-0.07', '0.07')
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instance_group2 = InstanceGroup(6, 'TASK', 'c1.medium', 'SPOT', 'spot-0.07', '0.07')
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instance_group = conn.add_instance_groups(job_id, [instance_group1, instance_group2])
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instance_group_ids = instance_group.instancegroupids.split(",")
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job_flow = conn.describe_jobflows()[0]
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int(job_flow.instancecount).should.equal(12)
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instance_group = job_flow.instancegroups[0]
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int(instance_group.instancerunningcount).should.equal(6)
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conn.modify_instance_groups(instance_group_ids, [2, 3])
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job_flow = conn.describe_jobflows()[0]
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int(job_flow.instancecount).should.equal(5)
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instance_group1 = [
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group for group
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in job_flow.instancegroups
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if group.instancegroupid == instance_group_ids[0]
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][0]
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int(instance_group1.instancerunningcount).should.equal(2)
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instance_group2 = [
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group for group
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in job_flow.instancegroups
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if group.instancegroupid == instance_group_ids[1]
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][0]
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int(instance_group2.instancerunningcount).should.equal(3)
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@requires_boto_gte("2.8")
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@mock_emr
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def test_set_visible_to_all_users():
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conn = boto.connect_emr()
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job_id = conn.run_jobflow(
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name='My jobflow',
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log_uri='s3://some_bucket/jobflow_logs',
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steps=[],
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visible_to_all_users=False,
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)
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job_flow = conn.describe_jobflow(job_id)
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job_flow.visibletoallusers.should.equal('False')
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conn.set_visible_to_all_users(job_id, True)
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job_flow = conn.describe_jobflow(job_id)
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job_flow.visibletoallusers.should.equal('True')
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conn.set_visible_to_all_users(job_id, False)
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job_flow = conn.describe_jobflow(job_id)
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job_flow.visibletoallusers.should.equal('False')
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@requires_boto_gte("2.8")
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@mock_emr
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def test_set_termination_protection():
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conn = boto.connect_emr()
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job_id = conn.run_jobflow(
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name='My jobflow',
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log_uri='s3://some_bucket/jobflow_logs',
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steps=[]
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)
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job_flow = conn.describe_jobflow(job_id)
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job_flow.terminationprotected.should.equal(u'None')
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conn.set_termination_protection(job_id, True)
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job_flow = conn.describe_jobflow(job_id)
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job_flow.terminationprotected.should.equal('true')
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conn.set_termination_protection(job_id, False)
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job_flow = conn.describe_jobflow(job_id)
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job_flow.terminationprotected.should.equal('false')
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@mock_emr
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def test_list_clusters():
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conn = boto.connect_emr()
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conn.run_jobflow(
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name='My jobflow',
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log_uri='s3://some_bucket/jobflow_logs',
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steps=[],
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)
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summary = conn.list_clusters()
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clusters = summary.clusters
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clusters.should.have.length_of(1)
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cluster = clusters[0]
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cluster.name.should.equal("My jobflow")
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cluster.normalizedinstancehours.should.equal('0')
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cluster.status.state.should.equal("RUNNING")
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@mock_emr
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def test_describe_cluster():
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conn = boto.connect_emr()
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job_id = conn.run_jobflow(
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name='My jobflow',
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log_uri='s3://some_bucket/jobflow_logs',
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steps=[],
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)
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cluster = conn.describe_cluster(job_id)
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cluster.name.should.equal("My jobflow")
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cluster.normalizedinstancehours.should.equal('0')
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cluster.status.state.should.equal("RUNNING")
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@mock_emr
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def test_cluster_tagging():
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conn = boto.connect_emr()
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job_id = conn.run_jobflow(
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name='My jobflow',
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log_uri='s3://some_bucket/jobflow_logs',
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steps=[],
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)
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cluster_id = job_id
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conn.add_tags(cluster_id, {"tag1": "val1", "tag2": "val2"})
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cluster = conn.describe_cluster(cluster_id)
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cluster.tags.should.have.length_of(2)
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tags = dict((tag.key, tag.value) for tag in cluster.tags)
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tags['tag1'].should.equal('val1')
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tags['tag2'].should.equal('val2')
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# Remove a tag
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conn.remove_tags(cluster_id, ["tag1"])
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cluster = conn.describe_cluster(cluster_id)
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cluster.tags.should.have.length_of(1)
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tags = dict((tag.key, tag.value) for tag in cluster.tags)
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tags['tag2'].should.equal('val2')
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