def main():
args_dict = parse_cli_args(create_parser())
print("Args: ", args_dict)
numeric_level = getattr(logging, args_dict['log_level'], None)
logging.basicConfig(format=LOGFORMAT)
logger.setLevel(numeric_level)
client = boto3.client('emr', region_name=args_dict['aws_region'])
s3 = boto3.resource('s3')
cluster_id = args_dict.get('cluster_id')
if cluster_id is None:
logger.info("Launching cluster...")
ec2_client = boto3.client('ec2', region_name=args_dict['aws_region'])
pricing_client = boto3.client('pricing',
region_name=args_dict['aws_region'])
args_dict = determine_prices(args_dict, ec2_client, pricing_client)
cluster_config = cluster.emr_config(**args_dict)
response = client.run_job_flow(**cluster_config)
cluster_id = response['JobFlowId']
logger.info("Cluster ID: %s", cluster_id)
emr_steps = steps.setup_steps(s3, args_dict['s3_bucket'], args_dict['app'],
args_dict['submit_args'],
args_dict['app_args'], args_dict['uploads'],
args_dict['s3_dist_cp'])
response = client.add_job_flow_steps(JobFlowId=cluster_id, Steps=emr_steps)
try:
step_ids = json.dumps(response['StepIds'])
except KeyError:
step_ids = 'Invalid response'
logger.info("Step IDs: %s", step_ids)
def main():
parser = create_parser()
args = parser.parse_args()
print("Args: ", args)
numeric_level = getattr(logging, args.log_level, None)
logging.basicConfig(format=LOGFORMAT)
logger.setLevel(numeric_level)
client = boto3.client('emr', region_name=args.aws_region)
s3 = boto3.resource('s3')
cluster_id = args.cluster_id
if cluster_id is None:
logger.info("Launching cluster...")
args_dict = vars(args)
if args.dynamic_pricing:
ec2 = boto3.client('ec2', region_name=args.aws_region)
bid_px, is_spot = pricing.get_bid_price(ec2, args.slave)
args_dict['bid_price'] = str(bid_px)
if is_spot:
logger.info("Using spot pricing with bid price $%d", bid_px)
else:
logger.info("Spot price too high. Using on-demand %d", bid_px)
cluster_config = cluster.emr_config(**args_dict)
response = client.run_job_flow(**cluster_config)
cluster_id = response['JobFlowId']
logger.info("Cluster ID: %s", cluster_id)
emr_steps = steps.setup_steps(s3, args.s3_bucket, args.app,
args.submit_args, args.app_args,
args.uploads, args.s3_dist_cp)
client.add_job_flow_steps(JobFlowId=cluster_id, Steps=emr_steps)
def test_emr_cluster_config_with_defaults():
config = emr_config('emr-5.2.0',
instance_type_master='m4.large',
keep_alive=False,
instance_type_core='m4.2xlarge',
instance_type_task='m4.2xlarge',
num_core=1,
num_task=1,
bid_price_task='0.1',
name="Test SparkSteps",
defaults=['spark-defaults', 'spark.speculation=false',
'yarn-site', 'yarn.nodemanager.vmem-check-enabled=true'])
print(config['Configurations'])
assert config == {'Instances':
{'InstanceGroups': [{'InstanceCount': 1, # NOQA: E127
'InstanceRole': 'MASTER',
'InstanceType': 'm4.large',
'Market': 'ON_DEMAND',
'Name': 'Master Node'},
{'InstanceCount': 1,
'InstanceRole': 'CORE',
'InstanceType': 'm4.2xlarge',
'Market': 'ON_DEMAND',
'Name': 'Core Nodes'},
{'BidPrice': '0.1',
'InstanceCount': 1,
'InstanceRole': 'TASK',
'InstanceType': 'm4.2xlarge',
'Market': 'SPOT',
'Name': 'Task Nodes'}],
'KeepJobFlowAliveWhenNoSteps': False,
'TerminationProtected': False
},
'Applications': [{'Name': 'Hadoop'}, {'Name': 'Spark'}],
'Configurations': [
{
'Classification': 'spark-defaults',
'Properties': {
'spark.speculation': 'false'
}
},
{
'Classification': 'yarn-site',
'Properties': {
'yarn.nodemanager.vmem-check-enabled': 'true'
}
}
],
'Name': 'Test SparkSteps',
'JobFlowRole': 'EMR_EC2_DefaultRole',
'ReleaseLabel': 'emr-5.2.0',
'VisibleToAllUsers': True,
'ServiceRole': 'EMR_DefaultRole'}
client = boto3.client('emr', region_name=AWS_REGION_NAME)
client.run_job_flow(**config)
def test_emr_cluster_config():
config = emr_config('emr-5.2.0',
master='m4.large',
keep_alive=False,
slave='m4.2xlarge',
num_core=1,
num_task=1,
bid_price='0.1',
name="Test SparkSteps")
assert config == {
'Instances': {
'InstanceGroups': [
{
'InstanceCount': 1, # NOQA: E127
'InstanceRole': 'MASTER',
'InstanceType': 'm4.large',
'Market': 'ON_DEMAND',
'Name': 'Master Node'
},
{
'InstanceCount': 1,
'InstanceRole': 'CORE',
'InstanceType': 'm4.2xlarge',
'Market': 'ON_DEMAND',
'Name': 'Core Nodes'
},
{
'BidPrice': '0.1',
'InstanceCount': 1,
'InstanceRole': 'TASK',
'InstanceType': 'm4.2xlarge',
'Market': 'SPOT',
'Name': 'Task Nodes'
}
],
'KeepJobFlowAliveWhenNoSteps':
False,
'TerminationProtected':
False
},
'Applications': [{
'Name': 'Hadoop'
}, {
'Name': 'Spark'
}],
'Name': 'Test SparkSteps',
'JobFlowRole': 'EMR_EC2_DefaultRole',
'ReleaseLabel': 'emr-5.2.0',
'VisibleToAllUsers': True,
'ServiceRole': 'EMR_DefaultRole'
}
client = boto3.client('emr', region_name=AWS_REGION_NAME)
client.run_job_flow(**config)
def test_is_step_complete(emr_client, s3_client):
"""
Ensure is_step_complete returns expected boolean value
"""
cluster_config = emr_config('emr-5.2.0',
instance_type_master='m4.large',
jobflow_role='MyCustomRole',
keep_alive=False,
instance_type_core='m4.2xlarge',
instance_type_task='m4.2xlarge',
num_core=1,
num_task=1,
bid_price_task='0.1',
maximize_resource_allocation=True,
name='Test SparkSteps',
app_list=['hadoop', 'hive', 'spark'])
response = emr_client.run_job_flow(**cluster_config)
cluster_id = response['JobFlowId']
test_step = {
'Name': 'test-step',
'ActionOnFailure': 'CANCEL_AND_WAIT',
'HadoopJarStep': {
'Jar': 'command-runner.jar',
'Args': ['state-pusher-script']
}
}
response = emr_client.add_job_flow_steps(JobFlowId=cluster_id,
Steps=[test_step])
last_step_id = response['StepIds'][-1]
# while the step state is non-terminal is_step_complete should return False
for state in ['PENDING', 'RUNNING', 'CONTINUE', 'CANCEL_PENDING']:
set_step_state(last_step_id, cluster_id, state)
assert not is_step_complete(emr_client, cluster_id, last_step_id), \
'Expected last step to not be complete when step state is {}'.format(state)
# when last step is in a terminal state (completed), is_step_complete should return True
set_step_state(last_step_id, cluster_id, 'COMPLETED')
assert is_step_complete(emr_client, cluster_id, last_step_id), \
'Expected last step to be complete when last step state is {}'.format('COMPLETED')
# when last step is in a failed state, is_step_complete should raise a helpful exception
for state in ['CANCELLED', 'FAILED', 'INTERRUPTED']:
set_step_state(last_step_id, cluster_id, state)
try:
is_step_complete(emr_client, cluster_id, last_step_id)
assert False, \
'Expected an exception to be raised when the last step is in {} state'.format(state)
except Exception as e:
assert 'EMR job failed' == str(
e), 'Exception message not as expected'
def main():
args_dict = parse_cli_args(create_parser())
print("Args: ", args_dict)
numeric_level = getattr(logging, args_dict['log_level'], None)
logging.basicConfig(format=LOGFORMAT)
logging.getLogger('sparksteps').setLevel(numeric_level)
client = boto3.client('emr', region_name=args_dict['aws_region'])
s3 = boto3.resource('s3')
cluster_id = args_dict.get('cluster_id')
if cluster_id is None:
logger.info("Launching cluster...")
ec2_client = boto3.client('ec2', region_name=args_dict['aws_region'])
pricing_client = boto3.client('pricing',
region_name=args_dict['aws_region'])
args_dict = determine_prices(args_dict, ec2_client, pricing_client)
cluster_config = cluster.emr_config(**args_dict)
response = client.run_job_flow(**cluster_config)
cluster_id = response['JobFlowId']
logger.info("Cluster ID: %s", cluster_id)
emr_steps = steps.setup_steps(s3, args_dict['s3_bucket'],
args_dict['s3_path'], args_dict['app'],
args_dict['submit_args'],
args_dict['app_args'], args_dict['uploads'],
args_dict['s3_dist_cp'])
response = client.add_job_flow_steps(JobFlowId=cluster_id, Steps=emr_steps)
try:
step_ids = json.dumps(response['StepIds'])
except KeyError:
step_ids = 'Invalid response'
args_dict['wait'] = False
logger.info("Step IDs: %s", step_ids)
sleep_interval = args_dict.get('wait')
if sleep_interval:
last_step_id = response['StepIds'][-1]
logger.info(
'Polling until step {last_step} is complete using a sleep interval of {interval} seconds...'
.format(last_step=last_step_id, interval=sleep_interval))
wait_for_step_complete(client,
cluster_id,
last_step_id,
sleep_interval_s=int(sleep_interval))
def test_emr_cluster_config():
config = emr_config('emr-5.2.0',
instance_type_master='m4.large',
jobflow_role='MyCustomRole',
service_role='MyServiceRole',
keep_alive=False,
instance_type_core='m4.2xlarge',
instance_type_task='m4.2xlarge',
num_core=1,
num_task=1,
bid_price_task='0.1',
maximize_resource_allocation=True,
name="Test SparkSteps",
app_list=['hadoop', 'hive', 'spark'])
assert config == {'Instances':
{'InstanceGroups': [{'InstanceCount': 1, # NOQA: E127
'InstanceRole': 'MASTER',
'InstanceType': 'm4.large',
'Market': 'ON_DEMAND',
'Name': 'Master Node'},
{'InstanceCount': 1,
'InstanceRole': 'CORE',
'InstanceType': 'm4.2xlarge',
'Market': 'ON_DEMAND',
'Name': 'Core Nodes'},
{'BidPrice': '0.1',
'InstanceCount': 1,
'InstanceRole': 'TASK',
'InstanceType': 'm4.2xlarge',
'Market': 'SPOT',
'Name': 'Task Nodes'}],
'KeepJobFlowAliveWhenNoSteps': False,
'TerminationProtected': False
},
'Applications': [{'Name': 'Hadoop'}, {'Name': 'Hive'}, {'Name': 'Spark'}],
'Name': 'Test SparkSteps',
'JobFlowRole': 'MyCustomRole',
'ServiceRole': 'MyServiceRole',
'ReleaseLabel': 'emr-5.2.0',
'VisibleToAllUsers': True,
'Configurations': [{'Classification': 'spark',
'Properties': {'maximizeResourceAllocation': 'true'}}]
}
client = boto3.client('emr', region_name=AWS_REGION_NAME)
client.run_job_flow(**config)
def test_emr_cluster_config():
config = emr_config('emr-5.2.0',
instance_type_master='m4.large',
keep_alive=False,
instance_type_core='m4.2xlarge',
instance_type_task='m4.2xlarge',
num_core=1,
num_task=1,
bid_price_task='0.1',
maximize_resource_allocation=True,
name="Test SparkSteps")
assert config == {'Instances':
{'InstanceGroups': [{'InstanceCount': 1, # NOQA: E127
'InstanceRole': 'MASTER',
'InstanceType': 'm4.large',
'Market': 'ON_DEMAND',
'Name': 'Master Node'},
{'InstanceCount': 1,
'InstanceRole': 'CORE',
'InstanceType': 'm4.2xlarge',
'Market': 'ON_DEMAND',
'Name': 'Core Nodes'},
{'BidPrice': '0.1',
'InstanceCount': 1,
'InstanceRole': 'TASK',
'InstanceType': 'm4.2xlarge',
'Market': 'SPOT',
'Name': 'Task Nodes'}],
'KeepJobFlowAliveWhenNoSteps': False,
'TerminationProtected': False
},
'Applications': [{'Name': 'Hadoop'}, {'Name': 'Spark'}],
'Name': 'Test SparkSteps',
'JobFlowRole': 'EMR_EC2_DefaultRole',
'ReleaseLabel': 'emr-5.2.0',
'VisibleToAllUsers': True,
'ServiceRole': 'EMR_DefaultRole',
'Configurations': [{'Classification': 'spark',
'Properties': {'maximizeResourceAllocation': 'true'}}]
}
client = boto3.client('emr', region_name=AWS_REGION_NAME)
client.run_job_flow(**config)
def test_emr_spot_cluster():
config = emr_config('emr-5.2.0',
instance_type_master='m4.large',
keep_alive=False,
instance_type_core='c3.8xlarge',
instance_type_task='c3.8xlarge',
num_core=2,
num_task=4,
bid_price_master='0.05',
bid_price_core='0.25',
bid_price_task='0.1',
name="Test SparkSteps",
bootstrap_script='s3://bucket/bootstrap-actions.sh')
assert config == {'Instances':
{'InstanceGroups': [{'InstanceCount': 1, # NOQA: E127
'InstanceRole': 'MASTER',
'InstanceType': 'm4.large',
'Market': 'SPOT',
'BidPrice': '0.05',
'Name': 'Master Node'},
{'BidPrice': '0.25',
'InstanceCount': 2,
'InstanceRole': 'CORE',
'InstanceType': 'c3.8xlarge',
'Market': 'SPOT',
'Name': 'Core Nodes'},
{'BidPrice': '0.1',
'InstanceCount': 4,
'InstanceRole': 'TASK',
'InstanceType': 'c3.8xlarge',
'Market': 'SPOT',
'Name': 'Task Nodes'}],
'KeepJobFlowAliveWhenNoSteps': False,
'TerminationProtected': False
},
'Applications': [{'Name': 'Hadoop'}, {'Name': 'Spark'}],
'BootstrapActions': [{'Name': 'bootstrap',
'ScriptBootstrapAction': {'Path': 's3://bucket/bootstrap-actions.sh'}}],
'Name': 'Test SparkSteps',
'JobFlowRole': 'EMR_EC2_DefaultRole',
'ReleaseLabel': 'emr-5.2.0',
'VisibleToAllUsers': True,
'ServiceRole': 'EMR_DefaultRole'}
def test_emr_spot_cluster():
config = emr_config('emr-5.2.0',
instance_type_master='m4.large',
keep_alive=False,
instance_type_core='c3.8xlarge',
instance_type_task='c3.8xlarge',
num_core=2,
num_task=4,
bid_price_master='0.05',
bid_price_core='0.25',
bid_price_task='0.1',
name="Test SparkSteps",
bootstrap_script='s3://bucket/bootstrap-actions.sh')
assert config == {'Instances':
{'InstanceGroups': [{'InstanceCount': 1, # NOQA: E127
'InstanceRole': 'MASTER',
'InstanceType': 'm4.large',
'Market': 'SPOT',
'BidPrice': '0.05',
'Name': 'Master Node'},
{'BidPrice': '0.25',
'InstanceCount': 2,
'InstanceRole': 'CORE',
'InstanceType': 'c3.8xlarge',
'Market': 'SPOT',
'Name': 'Core Nodes'},
{'BidPrice': '0.1',
'InstanceCount': 4,
'InstanceRole': 'TASK',
'InstanceType': 'c3.8xlarge',
'Market': 'SPOT',
'Name': 'Task Nodes'}],
'KeepJobFlowAliveWhenNoSteps': False,
'TerminationProtected': False
},
'Applications': [{'Name': 'Hadoop'}, {'Name': 'Spark'}],
'BootstrapActions': [{'Name': 'bootstrap',
'ScriptBootstrapAction': {'Path': 's3://bucket/bootstrap-actions.sh'}}],
'Name': 'Test SparkSteps',
'JobFlowRole': 'EMR_EC2_DefaultRole',
'ReleaseLabel': 'emr-5.2.0',
'VisibleToAllUsers': True,
'ServiceRole': 'EMR_DefaultRole'}
def test_emr_cluster_config_with_bootstrap():
config = emr_config('emr-5.2.0',
instance_type_master='m4.large',
keep_alive=False,
instance_type_core='m4.2xlarge',
instance_type_task='m4.2xlarge',
num_core=1,
num_task=1,
bid_price_task='0.1',
name="Test SparkSteps",
bootstrap_script='s3://bucket/bootstrap-actions.sh')
assert config == {'Instances':
{'InstanceGroups': [{'InstanceCount': 1, # NOQA: E127
'InstanceRole': 'MASTER',
'InstanceType': 'm4.large',
'Market': 'ON_DEMAND',
'Name': 'Master Node'},
{'InstanceCount': 1,
'InstanceRole': 'CORE',
'InstanceType': 'm4.2xlarge',
'Market': 'ON_DEMAND',
'Name': 'Core Nodes'},
{'BidPrice': '0.1',
'InstanceCount': 1,
'InstanceRole': 'TASK',
'InstanceType': 'm4.2xlarge',
'Market': 'SPOT',
'Name': 'Task Nodes'}],
'KeepJobFlowAliveWhenNoSteps': False,
'TerminationProtected': False
},
'Applications': [{'Name': 'Hadoop'}, {'Name': 'Spark'}],
'BootstrapActions': [{'Name': 'bootstrap',
'ScriptBootstrapAction': {'Path': 's3://bucket/bootstrap-actions.sh'}}],
'Name': 'Test SparkSteps',
'JobFlowRole': 'EMR_EC2_DefaultRole',
'ReleaseLabel': 'emr-5.2.0',
'VisibleToAllUsers': True,
'ServiceRole': 'EMR_DefaultRole'}
client = boto3.client('emr', region_name=AWS_REGION_NAME)
client.run_job_flow(**config)
def main():
args_dict = parse_cli_args(create_parser())
print("Args: ", args_dict)
numeric_level = getattr(logging, args_dict['log_level'], None)
logging.basicConfig(format=LOGFORMAT)
logger.setLevel(numeric_level)
client = boto3.client('emr', region_name=args_dict['aws_region'])
s3 = boto3.resource('s3')
cluster_id = args_dict.get('cluster_id')
if cluster_id is None:
logger.info("Launching cluster...")
ec2_client = boto3.client('ec2', region_name=args_dict['aws_region'])
pricing_client = boto3.client('pricing', region_name=args_dict['aws_region'])
args_dict = determine_prices(args_dict, ec2_client, pricing_client)
cluster_config = cluster.emr_config(**args_dict)
response = client.run_job_flow(**cluster_config)
cluster_id = response['JobFlowId']
logger.info("Cluster ID: %s", cluster_id)
emr_steps = steps.setup_steps(s3,
args_dict['s3_bucket'],
args_dict['app'],
args_dict['submit_args'],
args_dict['app_args'],
args_dict['uploads'],
args_dict['s3_dist_cp'])
response = client.add_job_flow_steps(JobFlowId=cluster_id, Steps=emr_steps)
try:
step_ids = json.dumps(response['StepIds'])
except KeyError:
step_ids = 'Invalid response'
logger.info("Step IDs: %s", step_ids)
def test_emr_ebs_storage():
config = emr_config('emr-5.2.0',
instance_type_master='m4.large',
keep_alive=False,
instance_type_core='c3.8xlarge',
instance_type_task='c3.8xlarge',
ebs_volume_size_core=100,
ebs_volume_type_core='gp2',
ebs_volumes_per_core=2,
ebs_volume_size_task=10,
ebs_volume_type_task='io1',
ebs_optimized_task=True,
num_core=2,
num_task=4,
bid_price_master='0.05',
bid_price_core='0.25',
bid_price_task='0.1',
name="Test SparkSteps",
bootstrap_script='s3://bucket/bootstrap-actions.sh')
assert config == {'Instances':
{'InstanceGroups': [{'InstanceCount': 1, # NOQA: E127
'InstanceRole': 'MASTER',
'InstanceType': 'm4.large',
'Market': 'SPOT',
'BidPrice': '0.05',
'Name': 'Master Node'},
{'BidPrice': '0.25',
'InstanceCount': 2,
'InstanceRole': 'CORE',
'InstanceType': 'c3.8xlarge',
'Market': 'SPOT',
'Name': 'Core Nodes',
'EbsConfiguration': {
'EbsBlockDeviceConfigs': [{
'VolumeSpecification': {
'VolumeType': 'gp2',
'SizeInGB': 100
},
'VolumesPerInstance': 2
}],
'EbsOptimized': False
}},
{'BidPrice': '0.1',
'InstanceCount': 4,
'InstanceRole': 'TASK',
'InstanceType': 'c3.8xlarge',
'Market': 'SPOT',
'Name': 'Task Nodes',
'EbsConfiguration': {
'EbsBlockDeviceConfigs': [{
'VolumeSpecification': {
'VolumeType': 'io1',
'SizeInGB': 10
},
'VolumesPerInstance': 1
}],
'EbsOptimized': True
}}],
'KeepJobFlowAliveWhenNoSteps': False,
'TerminationProtected': False
},
'Applications': [{'Name': 'Hadoop'}, {'Name': 'Spark'}],
'BootstrapActions': [{'Name': 'bootstrap',
'ScriptBootstrapAction': {'Path': 's3://bucket/bootstrap-actions.sh'}}],
'Name': 'Test SparkSteps',
'JobFlowRole': 'EMR_EC2_DefaultRole',
'ReleaseLabel': 'emr-5.2.0',
'VisibleToAllUsers': True,
'ServiceRole': 'EMR_DefaultRole'}
def test_emr_ebs_storage():
config = emr_config('emr-5.2.0',
instance_type_master='m4.large',
keep_alive=False,
instance_type_core='c3.8xlarge',
instance_type_task='c3.8xlarge',
ebs_volume_size_core=100,
ebs_volume_type_core='gp2',
ebs_volumes_per_core=2,
ebs_volume_size_task=10,
ebs_volume_type_task='io1',
ebs_optimized_task=True,
num_core=2,
num_task=4,
bid_price_master='0.05',
bid_price_core='0.25',
bid_price_task='0.1',
name="Test SparkSteps",
bootstrap_script='s3://bucket/bootstrap-actions.sh')
assert config == {'Instances':
{'InstanceGroups': [{'InstanceCount': 1, # NOQA: E127
'InstanceRole': 'MASTER',
'InstanceType': 'm4.large',
'Market': 'SPOT',
'BidPrice': '0.05',
'Name': 'Master Node'},
{'BidPrice': '0.25',
'InstanceCount': 2,
'InstanceRole': 'CORE',
'InstanceType': 'c3.8xlarge',
'Market': 'SPOT',
'Name': 'Core Nodes',
'EbsConfiguration': {
'EbsBlockDeviceConfigs': [{
'VolumeSpecification': {
'VolumeType': 'gp2',
'SizeInGB': 100
},
'VolumesPerInstance': 2
}],
'EbsOptimized': False
}},
{'BidPrice': '0.1',
'InstanceCount': 4,
'InstanceRole': 'TASK',
'InstanceType': 'c3.8xlarge',
'Market': 'SPOT',
'Name': 'Task Nodes',
'EbsConfiguration': {
'EbsBlockDeviceConfigs': [{
'VolumeSpecification': {
'VolumeType': 'io1',
'SizeInGB': 10
},
'VolumesPerInstance': 1
}],
'EbsOptimized': True
}}],
'KeepJobFlowAliveWhenNoSteps': False,
'TerminationProtected': False
},
'Applications': [{'Name': 'Hadoop'}, {'Name': 'Spark'}],
'BootstrapActions': [{'Name': 'bootstrap',
'ScriptBootstrapAction': {'Path': 's3://bucket/bootstrap-actions.sh'}}],
'Name': 'Test SparkSteps',
'JobFlowRole': 'EMR_EC2_DefaultRole',
'ReleaseLabel': 'emr-5.2.0',
'VisibleToAllUsers': True,
'ServiceRole': 'EMR_DefaultRole'}
