示例#1
0
文件: helper.py 项目: StochSS/stochss
def start_celery_on_vm(instance_type, ip, key_file, agent_type,
                       worker_name='%h', username="******", prepend_commands=None, log_level='info'):
    copy_celery_config_to_vm(instance_type=instance_type, ip=ip, key_file=key_file,
                             agent_type=agent_type, username=username)

    commands = prepend_commands if prepend_commands is not None else []

    python_path_list = [TaskConfig.STOCHSS_HOME,
                        TaskConfig.PYURDME_DIR,
                        os.path.join(TaskConfig.STOCHSS_HOME, 'app'),
                        os.path.join(TaskConfig.STOCHSS_HOME, 'app', 'backend'),
                        os.path.join(TaskConfig.STOCHSS_HOME, 'app', 'lib', 'cloudtracker')]
    python_path = 'export PYTHONPATH={0}'.format(':'.join(python_path_list))
    commands.append(python_path)


    # Start the shutdown-monitor
    if agent_type == AgentTypes.EC2:
        commands.append('python /home/ubuntu/stochss/app/backend/tasks.py shutdown-monitor &' + \
                        "celery -A tasks worker -Q {q1},{q2} -n {worker_name} --autoreload --loglevel={log_level} --workdir /home/{username} > /home/{username}/celery.log 2>&1".format(
                            q1=CeleryConfig.get_queue_name(agent_type=agent_type),
                            q2=CeleryConfig.get_queue_name(agent_type=agent_type, instance_type=instance_type),
                            log_level=log_level,
                            worker_name=worker_name,
                            username=username)
        )
    else:
        commands.append(
            "celery -A tasks worker -Q {q1},{q2} -n {worker_name} --autoreload --loglevel={log_level} --workdir /home/{username} > /home/{username}/celery.log 2>&1".format(
                q1=CeleryConfig.get_queue_name(agent_type=agent_type),
                q2=CeleryConfig.get_queue_name(agent_type=agent_type, instance_type=instance_type),
                log_level=log_level,
                worker_name=worker_name,
                username=username)
        )

    command = ';'.join(commands)

    # start_celery_str = "celery -A tasks worker --autoreload --loglevel=info --workdir /home/ubuntu > /home/ubuntu/celery.log 2>&1"
    # PyURDME must be run inside a 'screen' terminal as part of the FEniCS code depends on the ability to
    # write to the process' terminal, screen provides this terminal.
    celery_cmd = "sudo screen -d -m bash -c '{0}'".format(command)

#    cmd = "ssh -o 'StrictHostKeyChecking no' -i {key_file} {username}@{ip} \"{cmd}\"".format(key_file=key_file,
#                                                                                             ip=ip,
#                                                                                             username=username,
#                                                                                            cmd=celery_cmd)
    cmd = get_remote_command(username, ip, key_file, celery_cmd)
    logging.info(cmd)
    success = os.system(cmd)
    logging.debug("success = {0}".format(success))
    return success
示例#2
0
def update_celery_config_with_queue_head_ip(queue_head_ip, agent_type):
    '''
    Method used for updating celery config file. It should have the correct IP
    of the queue head node, which should already be running.

    Args
        queue_head_ip    The ip that is going to be written in the celery configuration file
    '''
    logging.debug("queue_head_ip = {0}".format(queue_head_ip))

    with open(CeleryConfig.CONFIG_TEMPLATE_FILENAME,
              'r') as celery_config_file:
        celery_config_lines = celery_config_file.readlines()
    with open(CeleryConfig.get_config_filename(agent_type=agent_type),
              'w') as celery_config_file:
        for line in celery_config_lines:
            if line.strip().startswith('BROKER_URL'):
                celery_config_file.write(
                    'BROKER_URL = "amqp://*****:*****@{0}:5672/"\n'.format(
                        queue_head_ip))
            else:
                celery_config_file.write(line)

    # Now update the actual Celery app....
    # TODO: Doesnt seem to work in GAE until next request comes in to server
    tasks.CelerySingleton().configure()
示例#3
0
文件: helper.py 项目: StochSS/stochss
def copy_celery_config_to_vm(instance_type, ip, key_file, agent_type, username):
    celery_config_filename = CeleryConfig.get_config_filename(agent_type=agent_type)
    if not os.path.exists(celery_config_filename):
        raise Exception("celery config file not found: {0}".format(celery_config_filename))

    config_celery_queues(agent_type=agent_type, instance_types=[instance_type])
    cmd = get_scp_command(keyfile=key_file, source=celery_config_filename,
                        target="{user}@{ip}:~/celeryconfig.py".format(user=username, ip=ip))
    logging.info(cmd)
    success = os.system(cmd)
    if success == 0:
        logging.info("scp success!")
        logging.info(" {0} transfered to {1}".format(celery_config_filename, ip))
    else:
        raise Exception("scp failure: {0} not transfered to {1}".format(celery_config_filename, ip))
示例#4
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def config_celery_queues(agent_type, instance_types):
    exchange = "exchange = Exchange('{0}', type='direct')".format(
        CeleryConfig.get_exchange_name(agent_type=agent_type))
    logging.debug(exchange)

    queue_list = map(
        lambda instance_type: "Queue('{0}', exchange, routing_key='{1}')".
        format(
            CeleryConfig.get_queue_name(agent_type=agent_type,
                                        instance_type=instance_type),
            CeleryConfig.get_routing_key_name(agent_type=agent_type,
                                              instance_type=instance_type)),
        instance_types)

    agent_queue_name = CeleryConfig.get_queue_name(agent_type=agent_type)
    agent_routing_key = CeleryConfig.get_routing_key_name(
        agent_type=agent_type)
    queue_list.insert(
        0, "Queue('{0}', exchange, routing_key='{1}')".format(
            agent_queue_name, agent_routing_key))
    logging.debug(pprint.pformat(queue_list))

    queues_string = 'CELERY_QUEUES = ({0})'.format(', '.join(queue_list))
    logging.debug(queues_string)

    with open(CeleryConfig.get_config_filename(agent_type=agent_type),
              'r') as f:
        lines = f.readlines()

    f = open(CeleryConfig.get_config_filename(agent_type=agent_type), 'w')
    clear_following = False
    for line in lines:
        if clear_following:
            f.write("")
        elif line.strip().startswith('exchange'):
            f.write(exchange + "\n")
        elif line.strip().startswith('CELERY_QUEUES'):
            f.write(queues_string + "\n")
            clear_following = True
        else:
            f.write(line)
    f.close()

    # reload the celery configuration
    tasks.CelerySingleton().configure()
示例#5
0
文件: helper.py 项目: StochSS/stochss
def update_celery_config_with_queue_head_ip(queue_head_ip, agent_type):
    '''
    Method used for updating celery config file. It should have the correct IP
    of the queue head node, which should already be running.

    Args
        queue_head_ip    The ip that is going to be written in the celery configuration file
    '''
    logging.debug("queue_head_ip = {0}".format(queue_head_ip))

    with open(CeleryConfig.CONFIG_TEMPLATE_FILENAME, 'r') as celery_config_file:
        celery_config_lines = celery_config_file.readlines()
    with open(CeleryConfig.get_config_filename(agent_type=agent_type), 'w') as celery_config_file:
        for line in celery_config_lines:
            if line.strip().startswith('BROKER_URL'):
                celery_config_file.write('BROKER_URL = "amqp://*****:*****@{0}:5672/"\n'.format(queue_head_ip))
            else:
                celery_config_file.write(line)

    # Now update the actual Celery app....
    # TODO: Doesnt seem to work in GAE until next request comes in to server
    tasks.CelerySingleton().configure()
示例#6
0
def copy_celery_config_to_vm(instance_type, ip, key_file, agent_type,
                             username):
    celery_config_filename = CeleryConfig.get_config_filename(
        agent_type=agent_type)
    if not os.path.exists(celery_config_filename):
        raise Exception(
            "celery config file not found: {0}".format(celery_config_filename))

    config_celery_queues(agent_type=agent_type, instance_types=[instance_type])
    cmd = get_scp_command(keyfile=key_file,
                          source=celery_config_filename,
                          target="{user}@{ip}:~/celeryconfig.py".format(
                              user=username, ip=ip))
    logging.info(cmd)
    success = os.system(cmd)
    if success == 0:
        logging.info("scp success!")
        logging.info(" {0} transfered to {1}".format(celery_config_filename,
                                                     ip))
    else:
        raise Exception("scp failure: {0} not transfered to {1}".format(
            celery_config_filename, ip))
示例#7
0
文件: helper.py 项目: StochSS/stochss
def config_celery_queues(agent_type, instance_types):
    exchange = "exchange = Exchange('{0}', type='direct')".format(CeleryConfig.get_exchange_name(agent_type=agent_type))
    logging.debug(exchange)

    queue_list = map(lambda instance_type: "Queue('{0}', exchange, routing_key='{1}')".format(
        CeleryConfig.get_queue_name(agent_type=agent_type, instance_type=instance_type),
        CeleryConfig.get_routing_key_name(agent_type=agent_type, instance_type=instance_type)),
                     instance_types)

    agent_queue_name = CeleryConfig.get_queue_name(agent_type=agent_type)
    agent_routing_key = CeleryConfig.get_routing_key_name(agent_type=agent_type)
    queue_list.insert(0, "Queue('{0}', exchange, routing_key='{1}')".format(agent_queue_name, agent_routing_key))
    logging.debug(pprint.pformat(queue_list))

    queues_string = 'CELERY_QUEUES = ({0})'.format(', '.join(queue_list))
    logging.debug(queues_string)

    with open(CeleryConfig.get_config_filename(agent_type=agent_type), 'r') as f:
        lines = f.readlines()

    f = open(CeleryConfig.get_config_filename(agent_type=agent_type), 'w')
    clear_following = False
    for line in lines:
        if clear_following:
            f.write("")
        elif line.strip().startswith('exchange'):
            f.write(exchange + "\n")
        elif line.strip().startswith('CELERY_QUEUES'):
            f.write(queues_string + "\n")
            clear_following = True
        else:
            f.write(line)
    f.close()

    # reload the celery configuration
    tasks.CelerySingleton().configure()
示例#8
0
文件: helper.py 项目: StochSS/stochss
def execute_cloud_task(params, agent_type, ec2_access_key, ec2_secret_key,
                       task_id, instance_type, cost_replay, database, storage_agent):
    '''
    This method instantiates celery tasks in the cloud.
    Returns return value from celery async call and the task ID
    '''
    if 'bucketname' not in params:
        params['bucketname'] = ''
    logging.debug('execute_cloud_task: params =\n\n{0}'.format(pprint.pformat(params)))
    logging.debug('agent_type = {}'.format(agent_type))

    celery_config = tasks.CelerySingleton()
    celery_config.configure()
    celery_config.print_celery_queue_config()

    celery_queue_name = CeleryConfig.get_queue_name(agent_type=agent_type, instance_type=instance_type)
    celery_exchange = CeleryConfig.get_exchange_name(agent_type=agent_type, instance_type=instance_type)
    celery_routing_key = CeleryConfig.get_routing_key_name(agent_type=agent_type, instance_type=instance_type)

    logging.info('Deliver the task to the queue: {0}, routing key: {1}'.format(celery_queue_name, celery_routing_key))

    try:
        # Need to make sure that the queue is actually reachable because
        # we don't want the user to try to submit a task and have it
        # timeout because the broker server isn't up yet.
        is_broker_up, exc, trace = check_broker_status()
        if is_broker_up == False:
            return {
                "success": False,
                "reason": "Cloud instances unavailable. Please wait a minute for their initialization to complete.",
                "exception": str(exc),
                "traceback": trace
            }

        # create a celery task
        logging.debug("execute_cloud_task : executing task with uuid : %s ", task_id)

        start_time = datetime.now()
        data = {
            'status': "pending",
            "start_time": start_time.strftime('%Y-%m-%d %H:%M:%S'),
            'message': "Task sent to Cloud",
            'uuid': task_id,
            'infrastructure': agent_type
        }

        if params["job_type"] == JobTypes.STOCHOPTIM:
            result = __execute_cloud_stochoptim_task(params=params, data=data,
                                                     database=database, task_id=task_id,
                                                     celery_queue_name=celery_queue_name,
                                                     celery_routing_key=celery_routing_key,
                                                     storage_agent=storage_agent)

        else:
            # if this is the cost analysis and agent is ec2 replay then update the stochss-cost-analysis table
            if cost_replay:
                if agent_type in JobConfig.SUPPORTED_AGENT_TYPES_FOR_COST_ANALYSIS:
                    result = __execute_cloud_cost_analysis_task(params=params, agent_type=agent_type,
                                                                instance_type=instance_type,
                                                                task_id=task_id, database=database,
                                                                ec2_access_key=ec2_access_key,
                                                                ec2_secret_key=ec2_secret_key, start_time=start_time,
                                                                celery_queue_name=celery_queue_name,
                                                                celery_routing_key=celery_routing_key,
                                                                storage_agent=storage_agent)
                else:
                    raise Exception("cost replay not supported for agent type = {0}".format(agent_type))

            else:
                result = {}
                result["db_id"] = task_id

                params["db_table"] = JobDatabaseConfig.TABLE_NAME
                params["cost_analysis_table"] = JobDatabaseConfig.COST_ANALYSIS_TABLE_NAME
                database.updateEntry(taskid=task_id, data=data, tablename=params["db_table"])

                if ec2_access_key is None:
                    ec2_access_key = ''
                if ec2_secret_key is None:
                    ec2_secret_key = ''

                celery_task = tasks.task.apply_async(
                    args=[task_id, params, agent_type, database, storage_agent, ec2_access_key, ec2_secret_key],
                    queue=celery_queue_name, routing_key=celery_routing_key)

                logging.info('celery_task.ready() = {}'.format(celery_task.ready()))
                logging.info('celery_task.id = {}'.format(celery_task.id))

                result["celery_pid"] = celery_task.id

                logging.info("execute_cloud_task: result of task with task_id {0} : \n{1}".format(task_id,
                                                                                                  pprint.pformat(
                                                                                                      result)))
                result["success"] = True
        result['resource'] = params['resource']
        return result

    except Exception as e:
        logging.exception(e)

        return {
            "success": False,
            "reason": str(e),
            "exception": str(e),
        }
示例#9
0
def start_celery_on_vm(instance_type,
                       ip,
                       key_file,
                       agent_type,
                       worker_name='%h',
                       username="******",
                       prepend_commands=None,
                       log_level='info'):
    copy_celery_config_to_vm(instance_type=instance_type,
                             ip=ip,
                             key_file=key_file,
                             agent_type=agent_type,
                             username=username)

    commands = prepend_commands if prepend_commands is not None else []

    python_path_list = [
        TaskConfig.STOCHSS_HOME, TaskConfig.PYURDME_DIR,
        os.path.join(TaskConfig.STOCHSS_HOME, 'app'),
        os.path.join(TaskConfig.STOCHSS_HOME, 'app', 'backend'),
        os.path.join(TaskConfig.STOCHSS_HOME, 'app', 'lib', 'cloudtracker')
    ]
    python_path = 'export PYTHONPATH={0}'.format(':'.join(python_path_list))
    commands.append(python_path)

    # Start the shutdown-monitor
    if agent_type == AgentTypes.EC2:
        commands.append('python /home/ubuntu/stochss/app/backend/tasks.py shutdown-monitor &' + \
                        "celery -A tasks worker -Q {q1},{q2} -n {worker_name} --autoreload --loglevel={log_level} --workdir /home/{username} > /home/{username}/celery.log 2>&1".format(
                            q1=CeleryConfig.get_queue_name(agent_type=agent_type),
                            q2=CeleryConfig.get_queue_name(agent_type=agent_type, instance_type=instance_type),
                            log_level=log_level,
                            worker_name=worker_name,
                            username=username)
        )
    else:
        commands.append(
            "celery -A tasks worker -Q {q1},{q2} -n {worker_name} --autoreload --loglevel={log_level} --workdir /home/{username} > /home/{username}/celery.log 2>&1"
            .format(q1=CeleryConfig.get_queue_name(agent_type=agent_type),
                    q2=CeleryConfig.get_queue_name(
                        agent_type=agent_type, instance_type=instance_type),
                    log_level=log_level,
                    worker_name=worker_name,
                    username=username))

    command = ';'.join(commands)

    # start_celery_str = "celery -A tasks worker --autoreload --loglevel=info --workdir /home/ubuntu > /home/ubuntu/celery.log 2>&1"
    # PyURDME must be run inside a 'screen' terminal as part of the FEniCS code depends on the ability to
    # write to the process' terminal, screen provides this terminal.
    celery_cmd = "sudo screen -d -m bash -c '{0}'".format(command)

    #    cmd = "ssh -o 'StrictHostKeyChecking no' -i {key_file} {username}@{ip} \"{cmd}\"".format(key_file=key_file,
    #                                                                                             ip=ip,
    #                                                                                             username=username,
    #                                                                                            cmd=celery_cmd)
    cmd = get_remote_command(username, ip, key_file, celery_cmd)
    logging.info(cmd)
    success = os.system(cmd)
    logging.debug("success = {0}".format(success))
    return success
示例#10
0
def execute_cloud_task(params, agent_type, ec2_access_key, ec2_secret_key,
                       task_id, instance_type, cost_replay, database,
                       storage_agent):
    '''
    This method instantiates celery tasks in the cloud.
    Returns return value from celery async call and the task ID
    '''
    if 'bucketname' not in params:
        params['bucketname'] = ''
    logging.debug('execute_cloud_task: params =\n\n{0}'.format(
        pprint.pformat(params)))
    logging.debug('agent_type = {}'.format(agent_type))

    celery_config = tasks.CelerySingleton()
    celery_config.configure()
    celery_config.print_celery_queue_config()

    celery_queue_name = CeleryConfig.get_queue_name(
        agent_type=agent_type, instance_type=instance_type)
    celery_exchange = CeleryConfig.get_exchange_name(
        agent_type=agent_type, instance_type=instance_type)
    celery_routing_key = CeleryConfig.get_routing_key_name(
        agent_type=agent_type, instance_type=instance_type)

    logging.info('Deliver the task to the queue: {0}, routing key: {1}'.format(
        celery_queue_name, celery_routing_key))

    try:
        # Need to make sure that the queue is actually reachable because
        # we don't want the user to try to submit a task and have it
        # timeout because the broker server isn't up yet.
        is_broker_up, exc, trace = check_broker_status()
        if is_broker_up == False:
            return {
                "success": False,
                "reason":
                "Cloud instances unavailable. Please wait a minute for their initialization to complete.",
                "exception": str(exc),
                "traceback": trace
            }

        # create a celery task
        logging.debug("execute_cloud_task : executing task with uuid : %s ",
                      task_id)

        start_time = datetime.now()
        data = {
            'status': "pending",
            "start_time": start_time.strftime('%Y-%m-%d %H:%M:%S'),
            'message': "Task sent to Cloud",
            'uuid': task_id,
            'infrastructure': agent_type
        }

        if params["job_type"] == JobTypes.STOCHOPTIM:
            result = __execute_cloud_stochoptim_task(
                params=params,
                data=data,
                database=database,
                task_id=task_id,
                celery_queue_name=celery_queue_name,
                celery_routing_key=celery_routing_key,
                storage_agent=storage_agent)

        else:
            # if this is the cost analysis and agent is ec2 replay then update the stochss-cost-analysis table
            if cost_replay:
                if agent_type in JobConfig.SUPPORTED_AGENT_TYPES_FOR_COST_ANALYSIS:
                    result = __execute_cloud_cost_analysis_task(
                        params=params,
                        agent_type=agent_type,
                        instance_type=instance_type,
                        task_id=task_id,
                        database=database,
                        ec2_access_key=ec2_access_key,
                        ec2_secret_key=ec2_secret_key,
                        start_time=start_time,
                        celery_queue_name=celery_queue_name,
                        celery_routing_key=celery_routing_key,
                        storage_agent=storage_agent)
                else:
                    raise Exception(
                        "cost replay not supported for agent type = {0}".
                        format(agent_type))

            else:
                result = {}
                result["db_id"] = task_id

                params["db_table"] = JobDatabaseConfig.TABLE_NAME
                params[
                    "cost_analysis_table"] = JobDatabaseConfig.COST_ANALYSIS_TABLE_NAME
                database.updateEntry(taskid=task_id,
                                     data=data,
                                     tablename=params["db_table"])

                if ec2_access_key is None:
                    ec2_access_key = ''
                if ec2_secret_key is None:
                    ec2_secret_key = ''

                celery_task = tasks.task.apply_async(
                    args=[
                        task_id, params, agent_type, database, storage_agent,
                        ec2_access_key, ec2_secret_key
                    ],
                    queue=celery_queue_name,
                    routing_key=celery_routing_key)

                logging.info('celery_task.ready() = {}'.format(
                    celery_task.ready()))
                logging.info('celery_task.id = {}'.format(celery_task.id))

                result["celery_pid"] = celery_task.id

                logging.info(
                    "execute_cloud_task: result of task with task_id {0} : \n{1}"
                    .format(task_id, pprint.pformat(result)))
                result["success"] = True
        result['resource'] = params['resource']
        return result

    except Exception as e:
        logging.exception(e)

        return {
            "success": False,
            "reason": str(e),
            "exception": str(e),
        }