| #!/usr/bin/python3 |
| |
| # ***************************************************************************** |
| # |
| # Licensed to the Apache Software Foundation (ASF) under one |
| # or more contributor license agreements. See the NOTICE file |
| # distributed with this work for additional information |
| # regarding copyright ownership. The ASF licenses this file |
| # to you under the Apache License, Version 2.0 (the |
| # "License"); you may not use this file except in compliance |
| # with the License. You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, |
| # software distributed under the License is distributed on an |
| # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
| # KIND, either express or implied. See the License for the |
| # specific language governing permissions and limitations |
| # under the License. |
| # |
| # ****************************************************************************** |
| |
| import datalab.actions_lib |
| import datalab.fab |
| import datalab.meta_lib |
| import datalab.notebook_lib |
| import json |
| import logging |
| import multiprocessing |
| import os |
| import sys |
| import traceback |
| from fabric.api import * |
| |
| |
| def configure_dataengine_service(instance, dataproc_conf): |
| dataproc_conf['instance_ip'] = GCPMeta.get_private_ip_address(instance) |
| # configuring proxy on Data Engine service |
| try: |
| logging.info('[CONFIGURE PROXY ON DATAENGINE SERVICE]') |
| print('[CONFIGURE PROXY ON DATAENGINE SERVICE]') |
| additional_config = {"proxy_host": dataproc_conf['edge_instance_name'], "proxy_port": "3128"} |
| params = "--hostname {} --instance_name {} --keyfile {} --additional_config '{}' --os_user {}" \ |
| .format(dataproc_conf['instance_ip'], dataproc_conf['cluster_name'], dataproc_conf['key_path'], |
| json.dumps(additional_config), dataproc_conf['datalab_ssh_user']) |
| try: |
| local("~/scripts/{}.py {}".format('common_configure_proxy', params)) |
| except: |
| traceback.print_exc() |
| raise Exception |
| except Exception as err: |
| datalab.fab.append_result("Failed to configure proxy.", str(err)) |
| GCPActions.delete_dataproc_cluster(dataproc_conf['cluster_name'], os.environ['gcp_region']) |
| sys.exit(1) |
| |
| try: |
| logging.info('[CONFIGURE DATAENGINE SERVICE]') |
| print('[CONFIGURE DATAENGINE SERVICE]') |
| try: |
| env['connection_attempts'] = 100 |
| env.key_filename = "{}".format(dataproc_conf['key_path']) |
| env.host_string = dataproc_conf['datalab_ssh_user'] + '@' + dataproc_conf['instance_ip'] |
| datalab.notebook_lib.install_os_pkg([['python3-pip', 'N/A']]) |
| datalab.fab.configure_data_engine_service_pip(dataproc_conf['instance_ip'], |
| dataproc_conf['datalab_ssh_user'], |
| dataproc_conf['key_path']) |
| except: |
| traceback.print_exc() |
| raise Exception |
| except Exception as err: |
| datalab.fab.append_result("Failed to configure dataengine service.", str(err)) |
| GCPActions.delete_dataproc_cluster(dataproc_conf['cluster_name'], os.environ['gcp_region']) |
| sys.exit(1) |
| |
| try: |
| print('[SETUP EDGE REVERSE PROXY TEMPLATE]') |
| logging.info('[SETUP EDGE REVERSE PROXY TEMPLATE]') |
| slaves = [] |
| for idx, instance in enumerate(dataproc_conf['cluster_core_instances']): |
| slave_ip = GCPMeta.get_private_ip_address(instance) |
| slave = { |
| 'name': 'datanode{}'.format(idx + 1), |
| 'ip': slave_ip, |
| 'dns': "{0}.c.{1}.internal".format(instance, os.environ['gcp_project_id']) |
| } |
| slaves.append(slave) |
| additional_info = { |
| "computational_name": dataproc_conf['computational_name'], |
| "master_ip": dataproc_conf['master_ip'], |
| "master_dns": "{0}.c.{1}.internal".format(dataproc_conf['master_name'], os.environ['gcp_project_id']), |
| "slaves": slaves, |
| "tensor": False |
| } |
| params = "--edge_hostname {} " \ |
| "--keyfile {} " \ |
| "--os_user {} " \ |
| "--type {} " \ |
| "--exploratory_name {} " \ |
| "--additional_info '{}'"\ |
| .format(dataproc_conf['edge_instance_hostname'], |
| dataproc_conf['key_path'], |
| dataproc_conf['datalab_ssh_user'], |
| 'dataengine-service', |
| dataproc_conf['exploratory_name'], |
| json.dumps(additional_info)) |
| try: |
| local("~/scripts/{}.py {}".format('common_configure_reverse_proxy', params)) |
| except: |
| datalab.fab.append_result("Failed edge reverse proxy template") |
| raise Exception |
| except Exception as err: |
| datalab.fab.append_result("Failed to configure reverse proxy.", str(err)) |
| GCPActions.delete_dataproc_cluster(dataproc_conf['cluster_name'], os.environ['gcp_region']) |
| sys.exit(1) |
| |
| |
| if __name__ == "__main__": |
| local_log_filename = "{}_{}_{}.log".format(os.environ['conf_resource'], os.environ['project_name'], |
| os.environ['request_id']) |
| local_log_filepath = "/logs/" + os.environ['conf_resource'] + "/" + local_log_filename |
| logging.basicConfig(format='%(levelname)-8s [%(asctime)s] %(message)s', |
| level=logging.INFO, |
| filename=local_log_filepath) |
| try: |
| GCPMeta = datalab.meta_lib.GCPMeta() |
| GCPActions = datalab.actions_lib.GCPActions() |
| print('Generating infrastructure names and tags') |
| dataproc_conf = dict() |
| if 'exploratory_name' in os.environ: |
| dataproc_conf['exploratory_name'] = os.environ['exploratory_name'].replace('_', '-').lower() |
| else: |
| dataproc_conf['exploratory_name'] = '' |
| if 'computational_name' in os.environ: |
| dataproc_conf['computational_name'] = os.environ['computational_name'].replace('_', '-').lower() |
| else: |
| dataproc_conf['computational_name'] = '' |
| dataproc_conf['service_base_name'] = (os.environ['conf_service_base_name']) |
| dataproc_conf['edge_user_name'] = (os.environ['edge_user_name']) |
| dataproc_conf['project_name'] = (os.environ['project_name']).replace('_', '-').lower() |
| dataproc_conf['endpoint_name'] = (os.environ['endpoint_name']).replace('_', '-').lower() |
| dataproc_conf['key_name'] = os.environ['conf_key_name'] |
| dataproc_conf['key_path'] = '{0}{1}.pem'.format(os.environ['conf_key_dir'], os.environ['conf_key_name']) |
| dataproc_conf['region'] = os.environ['gcp_region'] |
| dataproc_conf['zone'] = os.environ['gcp_zone'] |
| dataproc_conf['subnet'] = '{0}-{1}-{2}-subnet'.format(dataproc_conf['service_base_name'], |
| dataproc_conf['project_name'], |
| dataproc_conf['endpoint_name']) |
| dataproc_conf['cluster_name'] = '{0}-{1}-{2}-des-{3}'.format(dataproc_conf['service_base_name'], |
| dataproc_conf['project_name'], |
| dataproc_conf['endpoint_name'], |
| dataproc_conf['computational_name']) |
| dataproc_conf['cluster_tag'] = '{0}-{1}-{2}-ps'.format(dataproc_conf['service_base_name'], |
| dataproc_conf['project_name'], |
| dataproc_conf['endpoint_name']) |
| dataproc_conf['bucket_name'] = '{0}-{1}-{2}-bucket'.format(dataproc_conf['service_base_name'], |
| dataproc_conf['project_name'], |
| dataproc_conf['endpoint_name']) |
| dataproc_conf['release_label'] = os.environ['dataproc_version'] |
| dataproc_conf['cluster_label'] = {os.environ['notebook_instance_name']: "not-configured"} |
| dataproc_conf['dataproc_service_account_name'] = '{0}-{1}-{2}-ps-sa'.format(dataproc_conf['service_base_name'], |
| dataproc_conf['project_name'], |
| dataproc_conf['endpoint_name']) |
| dataproc_conf['dataproc_unique_index'] = GCPMeta.get_index_by_service_account_name( |
| dataproc_conf['dataproc_service_account_name']) |
| service_account_email = "{}-{}@{}.iam.gserviceaccount.com".format(dataproc_conf['service_base_name'], |
| dataproc_conf['dataproc_unique_index'], |
| os.environ['gcp_project_id']) |
| |
| dataproc_conf['edge_instance_name'] = '{0}-{1}-{2}-edge'.format(dataproc_conf['service_base_name'], |
| dataproc_conf['project_name'], |
| dataproc_conf['endpoint_name']) |
| dataproc_conf['edge_instance_hostname'] = GCPMeta.get_instance_public_ip_by_name( |
| dataproc_conf['edge_instance_name']) |
| dataproc_conf['datalab_ssh_user'] = os.environ['conf_os_user'] |
| dataproc_conf['master_name'] = dataproc_conf['cluster_name'] + '-m' |
| dataproc_conf['master_ip'] = GCPMeta.get_private_ip_address(dataproc_conf['master_name']) |
| except Exception as err: |
| datalab.fab.append_result("Failed to generate variables dictionary.", str(err)) |
| GCPActions.delete_dataproc_cluster(dataproc_conf['cluster_name'], os.environ['gcp_region']) |
| sys.exit(1) |
| |
| try: |
| res = GCPMeta.get_list_instances(os.environ['gcp_zone'], dataproc_conf['cluster_name']) |
| dataproc_conf['cluster_instances'] = [i.get('name') for i in res['items']] |
| except Exception as err: |
| traceback.print_exc() |
| raise Exception |
| |
| dataproc_conf['cluster_core_instances'] = list() |
| for instance in dataproc_conf['cluster_instances']: |
| if "{}-w-".format(dataproc_conf['cluster_name']) in instance: |
| dataproc_conf['cluster_core_instances'].append(instance) |
| |
| try: |
| jobs = [] |
| for instance in dataproc_conf['cluster_instances']: |
| p = multiprocessing.Process(target=configure_dataengine_service, args=(instance, dataproc_conf)) |
| jobs.append(p) |
| p.start() |
| for job in jobs: |
| job.join() |
| for job in jobs: |
| if job.exitcode != 0: |
| raise Exception |
| except Exception as err: |
| GCPActions.delete_dataproc_cluster(dataproc_conf['cluster_name'], os.environ['gcp_region']) |
| datalab.fab.append_result("Failed to configure Dataengine-service", str(err)) |
| traceback.print_exc() |
| raise Exception |
| |
| try: |
| dataproc_master_access_url = "https://" + dataproc_conf['edge_instance_hostname'] + "/{}/".format( |
| dataproc_conf['exploratory_name'] + '_' + dataproc_conf['computational_name']) |
| logging.info('[SUMMARY]') |
| print('[SUMMARY]') |
| print("Service base name: {}".format(dataproc_conf['service_base_name'])) |
| print("Cluster name: {}".format(dataproc_conf['cluster_name'])) |
| print("Key name: {}".format(dataproc_conf['key_name'])) |
| print("Region: {}".format(dataproc_conf['region'])) |
| print("Zone: {}".format(dataproc_conf['zone'])) |
| print("Subnet: {}".format(dataproc_conf['subnet'])) |
| print("Dataproc version: {}".format(dataproc_conf['release_label'])) |
| print("Dataproc master node shape: {}".format(os.environ['dataproc_master_instance_type'])) |
| print("Dataproc slave node shape: {}".format(os.environ['dataproc_slave_instance_type'])) |
| print("Master count: {}".format(os.environ['dataproc_master_count'])) |
| print("Slave count: {}".format(os.environ['dataproc_slave_count'])) |
| print("Preemptible count: {}".format(os.environ['dataproc_preemptible_count'])) |
| print("Notebook hostname: {}".format(os.environ['notebook_instance_name'])) |
| print("Bucket name: {}".format(dataproc_conf['bucket_name'])) |
| with open("/root/result.json", 'w') as result: |
| res = {"hostname": dataproc_conf['cluster_name'], |
| "key_name": dataproc_conf['key_name'], |
| "instance_id": dataproc_conf['cluster_name'], |
| "user_own_bucket_name": dataproc_conf['bucket_name'], |
| "Action": "Create new Dataproc cluster", |
| "computational_url": [ |
| {"description": "Dataproc Master", |
| "url": dataproc_master_access_url} |
| ] |
| } |
| print(json.dumps(res)) |
| result.write(json.dumps(res)) |
| except Exception as err: |
| datalab.fab.append_result("Error with writing results", str(err)) |
| GCPActions.delete_dataproc_cluster(dataproc_conf['cluster_name'], os.environ['gcp_region']) |
| sys.exit(1) |
