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aws.py
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aws.py
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# -*- coding: utf-8 -*-
"""
buildstockbatch.aws
~~~~~~~~~~~~~~~
This class contains the object & methods that allow for usage of the library with AWS Batch
:author: Noel Merket
:copyright: (c) 2018 by The Alliance for Sustainable Energy
:license: BSD-3
"""
import argparse
from awsretry import AWSRetry
import base64
import boto3
from botocore.exceptions import ClientError
import gzip
from joblib import Parallel, delayed
import json
import logging
import os
import pathlib
import random
from s3fs import S3FileSystem
import tarfile
import re
import time
import io
import zipfile
from buildstockbatch.aws.awsbase import AwsJobBase
from buildstockbatch.base import ValidationError
from buildstockbatch.cloud.docker_base import DockerBatchBase
from buildstockbatch.utils import log_error_details, get_project_configuration
logger = logging.getLogger(__name__)
def upload_file_to_s3(*args, **kwargs):
s3 = boto3.client("s3")
s3.upload_file(*args, **kwargs)
def upload_directory_to_s3(local_directory, bucket, prefix):
local_dir_abs = pathlib.Path(local_directory).absolute()
def filename_generator():
for dirpath, dirnames, filenames in os.walk(local_dir_abs):
for filename in filenames:
if filename.startswith("."):
continue
local_filepath = pathlib.Path(dirpath, filename)
s3_key = pathlib.PurePosixPath(prefix, local_filepath.relative_to(local_dir_abs))
yield local_filepath, s3_key
logger.debug("Uploading {} => {}/{}".format(local_dir_abs, bucket, prefix))
Parallel(n_jobs=-1, verbose=9)(
delayed(upload_file_to_s3)(str(local_file), bucket, s3_key.as_posix())
for local_file, s3_key in filename_generator()
)
def copy_s3_file(src_bucket, src_key, dest_bucket, dest_key):
s3 = boto3.client("s3")
s3.copy({"Bucket": src_bucket, "Key": src_key}, dest_bucket, dest_key)
class AwsBatchEnv(AwsJobBase):
"""
Class to manage the AWS Batch environment and Step Function controller.
"""
def __init__(self, job_name, aws_config, boto3_session):
"""
Initialize the Batch environment.
:param job_name: Name of the job being run
"""
super().__init__(job_name, aws_config, boto3_session)
self.batch = self.session.client("batch")
self.ec2 = self.session.client("ec2")
self.ec2r = self.session.resource("ec2")
self.emr = self.session.client("emr")
self.step_functions = self.session.client("stepfunctions")
self.aws_lambda = self.session.client("lambda")
self.s3 = self.session.client("s3")
self.s3_res = self.session.resource("s3")
self.task_role_arn = None
self.job_definition_arn = None
self.instance_role_arn = None
self.spot_service_role_arn = None
self.service_role_arn = None
self.instance_profile_arn = None
self.job_queue_arn = None
logger.propagate = False
def __repr__(self):
return super().__repr__()
def create_emr_lambda_roles(self):
"""
Create supporting IAM roles for Lambda support.
"""
# EMR
lambda_policy = {
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": "logs:CreateLogGroup",
"Resource": f"arn:aws:logs:{self.region}:{self.account}:*",
},
{
"Effect": "Allow",
"Action": ["logs:CreateLogStream", "logs:PutLogEvents"],
"Resource": [f"arn:aws:logs:{self.region}:{self.account}:log-group:/aws/lambda/launchemr:*"],
},
{
"Effect": "Allow",
"Action": "elasticmapreduce:RunJobFlow",
"Resource": "*",
},
{
"Effect": "Allow",
"Action": "iam:PassRole",
"Resource": [
f"arn:aws:iam::{self.account}:role/EMR_DefaultRole",
f"arn:aws:iam::{self.account}:role/EMR_EC2_DefaultRole",
f"arn:aws:iam::{self.account}:role/EMR_AutoScaling_DefaultRole",
self.emr_job_flow_role_arn,
self.emr_service_role_arn,
],
},
{
"Effect": "Allow",
"Action": "s3:GetObject",
"Resource": [f"arn:aws:s3:::{self.s3_bucket}/*"],
},
],
}
self.lambda_emr_job_step_execution_role_arn = self.iam_helper.role_stitcher(
self.lambda_emr_job_step_execution_role,
"lambda",
f"Lambda execution role for {self.lambda_emr_job_step_function_name}",
policies_list=[json.dumps(lambda_policy, indent=4)],
)
def create_vpc(self):
cidrs_in_use = set()
vpc_response = AWSRetry.backoff()(self.ec2.describe_vpcs)()
for vpc in vpc_response["Vpcs"]:
cidrs_in_use.add(vpc["CidrBlock"])
for cidr_assoc in vpc["CidrBlockAssociationSet"]:
cidrs_in_use.add(cidr_assoc["CidrBlock"])
need_to_find_cidr = True
while need_to_find_cidr:
self.vpc_cidr = "172.{}.0.0/16".format(random.randrange(100, 200))
need_to_find_cidr = self.vpc_cidr in cidrs_in_use
self.pub_subnet_cidr = self.vpc_cidr.replace("/16", "/17")
self.priv_subnet_cidr_1 = self.vpc_cidr.replace(".0.0/16", ".128.0/18")
self.priv_subnet_cidr_2 = self.vpc_cidr.replace(".0.0/16", ".192.0/18")
# Create the VPC
response = self.ec2.create_vpc(
CidrBlock=self.vpc_cidr,
AmazonProvidedIpv6CidrBlock=False,
InstanceTenancy="default",
)
self.vpc_id = response["Vpc"]["VpcId"]
logger.info(f"VPC {self.vpc_id} created")
while True:
try:
self.ec2.create_tags(
Resources=[self.vpc_id],
Tags=[{"Key": "Name", "Value": self.job_identifier}],
)
break
except Exception as e:
if "InvalidVpcID.NotFound" in str(e):
logger.info("Cannot tag VPC. VPC not yet created. Sleeping...")
time.sleep(5)
else:
raise
# Find the default security group
sec_response = self.ec2.describe_security_groups(
Filters=[
{"Name": "vpc-id", "Values": [self.vpc_id]},
]
)
self.batch_security_group = sec_response["SecurityGroups"][0]["GroupId"]
logger.info(f"Security group {self.batch_security_group} created for vpc/job.")
response = self.ec2.authorize_security_group_ingress(
GroupId=self.batch_security_group,
IpPermissions=[
{
"FromPort": 0,
"IpProtocol": "tcp",
"IpRanges": [
{"CidrIp": "0.0.0.0/0"},
],
"ToPort": 65535,
},
],
)
# Create the private subnets
priv_response_1 = self.ec2.create_subnet(
CidrBlock=self.priv_subnet_cidr_1,
AvailabilityZone=f"{self.region}a",
VpcId=self.vpc_id,
)
self.priv_vpc_subnet_id_1 = priv_response_1["Subnet"]["SubnetId"]
logger.info("Private subnet created.")
priv_response_2 = self.ec2.create_subnet(
CidrBlock=self.priv_subnet_cidr_2,
AvailabilityZone=f"{self.region}b",
VpcId=self.vpc_id,
)
self.priv_vpc_subnet_id_2 = priv_response_2["Subnet"]["SubnetId"]
logger.info("Private subnet created.")
self.ec2.create_tags(
Resources=[self.priv_vpc_subnet_id_1],
Tags=[{"Key": "Name", "Value": self.job_identifier}],
)
self.ec2.create_tags(
Resources=[self.priv_vpc_subnet_id_2],
Tags=[{"Key": "Name", "Value": self.job_identifier}],
)
ig_response = self.ec2.create_internet_gateway()
self.internet_gateway_id = ig_response["InternetGateway"]["InternetGatewayId"]
AWSRetry.backoff()(self.ec2.create_tags)(
Resources=[self.internet_gateway_id],
Tags=[{"Key": "Name", "Value": self.job_identifier}],
)
logger.info(f"Internet gateway {self.internet_gateway_id} created.")
# Create the public subnet
pub_response = self.ec2.create_subnet(CidrBlock=self.pub_subnet_cidr, VpcId=self.vpc_id)
logger.info("EIP allocated.")
self.pub_vpc_subnet_id = pub_response["Subnet"]["SubnetId"]
self.ec2.create_tags(
Resources=[self.pub_vpc_subnet_id],
Tags=[{"Key": "Name", "Value": self.job_identifier}],
)
# Create and elastic IP for the NAT Gateway
try:
ip_response = self.ec2.allocate_address(Domain="vpc")
self.nat_ip_allocation = ip_response["AllocationId"]
logger.info("EIP allocated.")
self.ec2.create_tags(
Resources=[self.nat_ip_allocation],
Tags=[{"Key": "Name", "Value": self.job_identifier}],
)
except Exception as e:
if "AddressLimitExceeded" in str(e):
raise
# Create an internet gateway
self.ec2.attach_internet_gateway(InternetGatewayId=self.internet_gateway_id, VpcId=self.vpc_id)
logger.info("Internet Gateway attached.")
# Find the only/default route table
drt_response = self.ec2.describe_route_tables(
Filters=[
{"Name": "vpc-id", "Values": [self.vpc_id]},
]
)
self.pub_route_table_id = drt_response["RouteTables"][0]["RouteTableId"]
# Modify the default route table to be used as the public route
while True:
try:
self.ec2.create_route(
DestinationCidrBlock="0.0.0.0/0",
GatewayId=self.internet_gateway_id,
RouteTableId=self.pub_route_table_id,
)
logger.info("Route created for Internet Gateway.")
break
except Exception as e:
if "NotFound" in str(e):
time.sleep(5)
logger.info("Internet Gateway not yet created. Sleeping...")
else:
raise
# Create a NAT Gateway
nat_response = self.ec2.create_nat_gateway(AllocationId=self.nat_ip_allocation, SubnetId=self.pub_vpc_subnet_id)
self.nat_gateway_id = nat_response["NatGateway"]["NatGatewayId"]
logger.info("NAT Gateway created.")
# Create a new private route table
prt_response = self.ec2.create_route_table(VpcId=self.vpc_id)
self.priv_route_table_id = prt_response["RouteTable"]["RouteTableId"]
logger.info("Route table created.")
AWSRetry.backoff()(self.ec2.create_tags)(
Resources=[self.priv_route_table_id],
Tags=[{"Key": "Name", "Value": self.job_identifier}],
)
# Associate the private route to the private subnet
self.ec2.associate_route_table(RouteTableId=self.priv_route_table_id, SubnetId=self.priv_vpc_subnet_id_1)
logger.info("Route table associated with subnet.")
self.ec2.associate_route_table(RouteTableId=self.priv_route_table_id, SubnetId=self.priv_vpc_subnet_id_2)
logger.info("Route table associated with subnet.")
# Associate the NAT gateway with the private route
while True:
try:
self.ec2.create_route(
DestinationCidrBlock="0.0.0.0/0",
NatGatewayId=self.nat_gateway_id,
RouteTableId=self.priv_route_table_id,
)
logger.info("Route created for subnet.")
break
except Exception as e:
if "InvalidNatGatewayID.NotFound" in str(e):
time.sleep(5)
logger.info("Nat Gateway not yet created. Sleeping...")
else:
raise
def generate_name_value_inputs(self, var_dictionary):
"""
Helper to properly format more easily used dictionaries.
:param var_dictionary: a dictionary of key/values to be transformed
:return: list of dictionaries in name: and value: outputs
"""
name_vals = []
for k, v in var_dictionary.items():
name_vals.append(dict(name=k, value=v))
return name_vals
def create_batch_service_roles(self):
"""
Creates the IAM roles used in the various areas of the batch service.
This currently will not try to overwrite or update existing roles.
"""
self.service_role_arn = self.iam_helper.role_stitcher(
self.batch_service_role_name,
"batch",
f"Service role for Batch environment {self.job_identifier}",
managed_policie_arns=["arn:aws:iam::aws:policy/service-role/AWSBatchServiceRole"],
)
# Instance Role for Batch compute environment
self.instance_role_arn = self.iam_helper.role_stitcher(
self.batch_instance_role_name,
"ec2",
f"Instance role for Batch compute environment {self.job_identifier}",
managed_policie_arns=["arn:aws:iam::aws:policy/service-role/AmazonEC2ContainerServiceforEC2Role"],
)
# Instance Profile
try:
response = self.iam.create_instance_profile(InstanceProfileName=self.batch_instance_profile_name)
self.instance_profile_arn = response["InstanceProfile"]["Arn"]
logger.info("Instance Profile created")
response = self.iam.add_role_to_instance_profile(
InstanceProfileName=self.batch_instance_profile_name,
RoleName=self.batch_instance_role_name,
)
except Exception as e:
if "EntityAlreadyExists" in str(e):
logger.info("ECS Instance Profile not created - already exists")
response = self.iam.get_instance_profile(InstanceProfileName=self.batch_instance_profile_name)
self.instance_profile_arn = response["InstanceProfile"]["Arn"]
# ECS Task Policy
task_permissions_policy = f"""{{
"Version": "2012-10-17",
"Statement": [
{{
"Sid": "VisualEditor0",
"Effect": "Allow",
"Action": [
"s3:PutAnalyticsConfiguration",
"s3:GetObjectVersionTagging",
"s3:CreateBucket",
"s3:ReplicateObject",
"s3:GetObjectAcl",
"s3:DeleteBucketWebsite",
"s3:PutLifecycleConfiguration",
"s3:GetObjectVersionAcl",
"s3:PutObjectTagging",
"s3:DeleteObject",
"s3:GetIpConfiguration",
"s3:DeleteObjectTagging",
"s3:GetBucketWebsite",
"s3:PutReplicationConfiguration",
"s3:DeleteObjectVersionTagging",
"s3:GetBucketNotification",
"s3:PutBucketCORS",
"s3:GetReplicationConfiguration",
"s3:ListMultipartUploadParts",
"s3:PutObject",
"s3:GetObject",
"s3:PutBucketNotification",
"s3:PutBucketLogging",
"s3:GetAnalyticsConfiguration",
"s3:GetObjectVersionForReplication",
"s3:GetLifecycleConfiguration",
"s3:ListBucketByTags",
"s3:GetInventoryConfiguration",
"s3:GetBucketTagging",
"s3:PutAccelerateConfiguration",
"s3:DeleteObjectVersion",
"s3:GetBucketLogging",
"s3:ListBucketVersions",
"s3:ReplicateTags",
"s3:RestoreObject",
"s3:ListBucket",
"s3:GetAccelerateConfiguration",
"s3:GetBucketPolicy",
"s3:PutEncryptionConfiguration",
"s3:GetEncryptionConfiguration",
"s3:GetObjectVersionTorrent",
"s3:AbortMultipartUpload",
"s3:PutBucketTagging",
"s3:GetBucketRequestPayment",
"s3:GetObjectTagging",
"s3:GetMetricsConfiguration",
"s3:DeleteBucket",
"s3:PutBucketVersioning",
"s3:ListBucketMultipartUploads",
"s3:PutMetricsConfiguration",
"s3:PutObjectVersionTagging",
"s3:GetBucketVersioning",
"s3:GetBucketAcl",
"s3:PutInventoryConfiguration",
"s3:PutIpConfiguration",
"s3:GetObjectTorrent",
"s3:PutBucketWebsite",
"s3:PutBucketRequestPayment",
"s3:GetBucketCORS",
"s3:GetBucketLocation",
"s3:ReplicateDelete",
"s3:GetObjectVersion"
],
"Resource": [
"{self.s3_bucket_arn}",
"{self.s3_bucket_arn}/*"
]
}},
{{
"Sid": "VisualEditor1",
"Effect": "Allow",
"Action": [
"s3:ListAllMyBuckets",
"s3:HeadBucket"
],
"Resource": "*"
}}
]
}}"""
self.task_role_arn = self.iam_helper.role_stitcher(
self.batch_ecs_task_role_name,
"ecs-tasks",
f"Task role for Batch job {self.job_identifier}",
policies_list=[task_permissions_policy],
)
if self.batch_use_spot:
# Spot Fleet Role
self.spot_service_role_arn = self.iam_helper.role_stitcher(
self.batch_spot_service_role_name,
"spotfleet",
f"Spot Fleet role for Batch compute environment {self.job_identifier}",
managed_policie_arns=["arn:aws:iam::aws:policy/service-role/AmazonEC2SpotFleetTaggingRole"],
)
def create_compute_environment(self, maxCPUs=10000):
"""
Creates a compute environment suffixed with the job name
:param subnets: list of subnet IDs
:param maxCPUs: numeric value for max VCPUs for the envionment
"""
try:
compute_resources = {
"minvCpus": 0,
"maxvCpus": maxCPUs,
"desiredvCpus": 0,
"instanceTypes": [
"optimal",
],
"imageId": self.batch_compute_environment_ami,
"subnets": [self.priv_vpc_subnet_id_1, self.priv_vpc_subnet_id_2],
"securityGroupIds": [self.batch_security_group],
"instanceRole": self.instance_profile_arn,
}
if self.batch_use_spot:
compute_resources.update(
{
"type": "SPOT",
"bidPercentage": 100,
"spotIamFleetRole": self.spot_service_role_arn,
}
)
else:
compute_resources["type"] = "EC2"
self.batch.create_compute_environment(
computeEnvironmentName=self.batch_compute_environment_name,
type="MANAGED",
state="ENABLED",
computeResources=compute_resources,
serviceRole=self.service_role_arn,
)
logger.info(f"Compute environment {self.batch_compute_environment_name} created.")
except Exception as e:
if "Object already exists" in str(e):
logger.info(f"Compute environment {self.batch_compute_environment_name} not created - already exists")
else:
raise
def create_job_queue(self):
"""
Creates a job queue based on the Batch environment definition
"""
while True:
try:
response = self.batch.create_job_queue(
jobQueueName=self.batch_job_queue_name,
state="ENABLED",
priority=1,
computeEnvironmentOrder=[
{
"order": 1,
"computeEnvironment": self.batch_compute_environment_name,
},
],
)
# print("JOB QUEUE")
# print(response)
self.job_queue_arn = response["jobQueueArn"]
logger.info(f"Job queue {self.batch_job_queue_name} created")
break
except Exception as e:
if "Object already exists" in str(e):
logger.info(f"Job queue {self.batch_job_queue_name} not created - already exists")
response = self.batch.describe_job_queues(
jobQueues=[
self.batch_job_queue_name,
]
)
self.job_queue_arn = response["jobQueues"][0]["jobQueueArn"]
break
elif "is not valid" in str(e):
# Need to wait a second for the compute environment to complete registration
logger.warning(
"5 second sleep initiated to wait for compute environment creation due to error: " + str(e)
)
time.sleep(5)
else:
raise
def create_job_definition(self, docker_image, vcpus, memory, command, env_vars):
"""
Creates a job definition to run in the Batch environment. This will create a new version with every execution.
:param docker_image: The image ID from the related ECR enviornment
:param vcpus: Numeric value of the vcpus dedicated to each container
:param memory: Numeric value of the memory MBs dedicated to each container
:param command: Command to run in the container
:param env_vars: Dictionary of key/value environment variables to include in the job
"""
response = self.batch.register_job_definition(
jobDefinitionName=self.job_identifier,
type="container",
# parameters={
# 'string': 'string'
# },
containerProperties={
"image": docker_image,
"vcpus": vcpus,
"memory": memory,
"command": command,
"jobRoleArn": self.task_role_arn,
"environment": self.generate_name_value_inputs(env_vars),
},
retryStrategy={"attempts": 2},
)
self.job_definition_arn = response["jobDefinitionArn"]
def submit_job(self, array_size=4):
"""
Submits the created job definition and version to be run.
"""
while True:
try:
self.batch.submit_job(
jobName=self.job_identifier,
jobQueue=self.batch_job_queue_name,
arrayProperties={"size": array_size},
jobDefinition=self.job_definition_arn,
)
logger.info(f"Job {self.job_identifier} submitted.")
break
except Exception as e:
if "not in VALID state" in str(e):
# Need to wait a second for the compute environment to complete registration
logger.warning("5 second sleep initiated to wait for job queue creation due to error: " + str(e))
time.sleep(5)
else:
raise
def create_state_machine_roles(self):
lambda_policy = f"""{{
"Version": "2012-10-17",
"Statement": [
{{
"Effect": "Allow",
"Action": [
"lambda:InvokeFunction"
],
"Resource": [
"arn:aws:lambda:*:*:function:{self.lambda_emr_job_step_function_name}"
]
}}
]
}}
"""
batch_policy = """{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"batch:SubmitJob",
"batch:DescribeJobs",
"batch:TerminateJob"
],
"Resource": "*"
},
{
"Effect": "Allow",
"Action": [
"events:PutTargets",
"events:PutRule",
"events:DescribeRule"
],
"Resource": [
"arn:aws:events:*:*:rule/StepFunctionsGetEventsForBatchJobsRule"
]
}
]
}
"""
sns_policy = f"""{{
"Version": "2012-10-17",
"Statement": [
{{
"Effect": "Allow",
"Action": [
"sns:Publish"
],
"Resource": "arn:aws:sns:*:*:{self.sns_state_machine_topic}"
}}
]
}}
"""
policies_list = [lambda_policy, batch_policy, sns_policy]
self.state_machine_role_arn = self.iam_helper.role_stitcher(
self.state_machine_role_name,
"states",
"Permissions for statemachine to run jobs",
policies_list=policies_list,
)
def create_state_machine(self):
job_definition = f"""{{
"Comment": "An example of the Amazon States Language for notification on an AWS Batch job completion",
"StartAt": "Submit Batch Job",
"States": {{
"Submit Batch Job": {{
"Type": "Task",
"Resource": "arn:aws:states:::batch:submitJob.sync",
"Parameters": {{
"JobDefinition": "{self.job_definition_arn}",
"JobName": "{self.job_identifier}",
"JobQueue": "{self.job_queue_arn}",
"ArrayProperties": {{
"Size.$": "$.array_size"
}}
}},
"Next": "Notify Batch Success",
"Catch": [
{{
"ErrorEquals": [ "States.ALL" ],
"Next": "Notify Batch Failure"
}}
]
}},
"Notify Batch Success": {{
"Type": "Task",
"Resource": "arn:aws:states:::sns:publish",
"Parameters": {{
"Message": "Batch job submitted through Step Functions succeeded",
"TopicArn": "arn:aws:sns:{self.region}:{self.account}:{self.sns_state_machine_topic}"
}},
"Next": "Run EMR Job"
}},
"Notify Batch Failure": {{
"Type": "Task",
"Resource": "arn:aws:states:::sns:publish",
"Parameters": {{
"Message": "Batch job submitted through Step Functions failed",
"TopicArn": "arn:aws:sns:{self.region}:{self.account}:{self.sns_state_machine_topic}"
}},
"Next": "Job Failure"
}},
"Run EMR Job": {{
"Type": "Task",
"Resource": "arn:aws:lambda:{self.region}:{self.account}:function:{self.lambda_emr_job_step_function_name}",
"Next": "Notify EMR Job Success",
"Catch": [
{{
"ErrorEquals": [ "States.ALL" ],
"Next": "Notify EMR Job Failure"
}}
]
}},
"Notify EMR Job Success": {{
"Type": "Task",
"Resource": "arn:aws:states:::sns:publish",
"Parameters": {{
"Message": "EMR Job succeeded",
"TopicArn": "arn:aws:sns:{self.region}:{self.account}:{self.sns_state_machine_topic}"
}},
"End": true
}},
"Notify EMR Job Failure": {{
"Type": "Task",
"Resource": "arn:aws:states:::sns:publish",
"Parameters": {{
"Message": "EMR job failed",
"TopicArn": "arn:aws:sns:{self.region}:{self.account}:{self.sns_state_machine_topic}"
}},
"Next": "Job Failure"
}},
"Job Failure": {{
"Type": "Fail"
}}
}}
}}
"""
while True:
try:
response = self.step_functions.create_state_machine(
name=self.state_machine_name,
definition=job_definition,
roleArn=self.state_machine_role_arn,
)
# print(response)
self.state_machine_arn = response["stateMachineArn"]
logger.info(f"State machine {self.state_machine_name} created.")
break
except Exception as e:
if "AccessDeniedException" in str(e):
logger.info("State machine role not yet registered, sleeping...")
time.sleep(5)
elif "StateMachineAlreadyExists" in str(e):
logger.info("State machine already exists, skipping...")
self.state_machine_arn = f"arn:aws:states:{self.region}:{self.account}:stateMachine:{self.state_machine_name}" # noqa E501
break
else:
raise
def start_state_machine_execution(self, array_size):
self.step_functions.start_execution(
stateMachineArn=self.state_machine_arn,
name=f"{self.state_machine_name}_execution_{int(time.time())}",
input=f'{{"array_size": {array_size}}}',
)
logger.info(f"Starting state machine {self.state_machine_name}.")
def clean(self):
# Get our vpc:
response = self.ec2.describe_vpcs(
Filters=[
{
"Name": "tag:Name",
"Values": [
self.vpc_name,
],
},
]
)
try:
self.vpc_id = response["Vpcs"][0]["VpcId"]
except (KeyError, IndexError):
self.vpc_id = None
logger.info("Cleaning up EMR.")
try:
self.emr.terminate_job_flows(JobFlowIds=[self.emr_cluster_name])
logger.info(f"EMR cluster {self.emr_cluster_name} deleted.")
except Exception as e:
if "ResourceNotFoundException" in str(e):
logger.info(f"EMR cluster {self.emr_cluster_name} already MIA - skipping...")
self.iam_helper.remove_role_from_instance_profile(self.emr_instance_profile_name)
self.iam_helper.delete_instance_profile(self.emr_instance_profile_name)
self.iam_helper.delete_role(self.emr_job_flow_role_name)
self.iam_helper.delete_role(self.emr_service_role_name)
logger.info(f"EMR clean complete. Results bucket and data {self.s3_bucket} have not been deleted.")
logger.info(f"Deleting Security group {self.emr_cluster_security_group_name}.")
default_sg_response = self.ec2.describe_security_groups(
Filters=[
{
"Name": "group-name",
"Values": [
"default",
],
},
]
)
logger.info("Removing egress from default security group.")
for group in default_sg_response["SecurityGroups"]:
if group["VpcId"] == self.vpc_id:
default_group_id = group["GroupId"]
dsg = self.ec2r.SecurityGroup(default_group_id)
if len(dsg.ip_permissions_egress):
response = dsg.revoke_egress(IpPermissions=dsg.ip_permissions_egress)
sg_response = AWSRetry.backoff()(self.ec2.describe_security_groups)(
Filters=[
{
"Name": "group-name",
"Values": [
self.emr_cluster_security_group_name,
],
},
]
)
try:
group_id = sg_response["SecurityGroups"][0]["GroupId"]
sg = self.ec2r.SecurityGroup(group_id)
if len(sg.ip_permissions):
sg.revoke_ingress(IpPermissions=sg.ip_permissions)
while True:
try:
self.ec2.delete_security_group(GroupId=group_id)
break
except ClientError:
logger.info("Waiting for security group ingress rules to be removed ...")
time.sleep(5)
logger.info(f"Deleted security group {self.emr_cluster_security_group_name}.")
except Exception as e:
if "does not exist" in str(e) or "list index out of range" in str(e):
logger.info(f"Security group {self.emr_cluster_security_group_name} does not exist - skipping...")
else:
raise
try:
self.aws_lambda.delete_function(FunctionName=self.lambda_emr_job_step_function_name)
except Exception as e:
if "Function not found" in str(e):
logger.info(f"Function {self.lambda_emr_job_step_function_name} not found, skipping...")
else:
raise
try:
self.s3.delete_object(Bucket=self.s3_bucket, Key=self.s3_lambda_code_emr_cluster_key)
logger.info(
f"S3 object {self.s3_lambda_code_emr_cluster_key} for bucket {self.s3_bucket} deleted." # noqa E501
)
except Exception as e:
if "NoSuchBucket" in str(e):
logger.info(
f"S3 object {self.s3_lambda_code_emr_cluster_key} for bucket {self.s3_bucket} missing - not deleted." # noqa E501
)
else:
raise
self.iam_helper.delete_role(self.lambda_emr_job_step_execution_role)
state_machines = self.step_functions.list_state_machines()
for sm in state_machines["stateMachines"]:
if sm["name"] == self.state_machine_name:
self.state_machine_arn = sm["stateMachineArn"]
self.step_functions.delete_state_machine(stateMachineArn=self.state_machine_arn)
logger.info(f"Deleted state machine {self.state_machine_name}.")
break
self.iam_helper.delete_role(self.state_machine_role_name)
try:
self.batch.update_job_queue(jobQueue=self.batch_job_queue_name, state="DISABLED")
while True:
try:
response = self.batch.delete_job_queue(jobQueue=self.batch_job_queue_name)
logger.info(f"Job queue {self.batch_job_queue_name} deleted.")
break
except Exception as e:
if "Cannot delete, resource is being modified" in str(e):
logger.info("Job queue being modified - sleeping until ready...")
time.sleep(5)
else:
raise
except Exception as e:
if "does not exist" in str(e):