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Quickstart

This page shows you how to create a Cloud Composer environment in the Google Cloud Platform Console and run a simple Apache Airflow DAG (also called a workflow).

Before you begin

  1. Faça login na sua Conta do Google.

    Se você ainda não tiver uma, inscreva-se.

  2. Selecione ou crie um projeto do GCP.

    Acessar a página Gerenciar recursos

  3. Verifique se o faturamento foi ativado para o projeto.

    Saiba como ativar o faturamento

  4. Ativar Cloud Composer API.

    Ativar a API

Creating an environment

  1. In the GCP Console, go to the Create environment page.

    Open the Create environment page

  2. In the Name field, enter example-environment.

  3. In the Location drop-down list, select a region for the Cloud Composer environment. See Available regions for information on selecting a region.

  4. For other environment configuration options, use the provided defaults.

  5. To create the environment, click Create.

  6. Wait until environment creation is completed. When done, the green check mark displays to the left of the environment name.

Viewing environment details

After environment creation is completed, you can view your environment's deployment information, such as the Cloud Composer version, the URL for the Airflow web interface, and the DAGs folder in Cloud Storage.

To view deployment information:

  1. In the GCP Console, go to the Environments page.

    Open the Environments page

  2. To view the Environment details page, click example-environment.

Creating a DAG

An Airflow DAG is a collection of organized tasks that you want to schedule and run. DAGs are defined in standard Python files.

The Python code in quickstart.py:

  1. Creates a DAG, composer_sample_dag. The DAG runs once per day.
  2. Executes one task, print_dag_run_conf. The task prints the DAG run's configuration by using the bash operator.

To create a DAG, create a copy of the quickstart.py file on your local machine.

import datetime

import airflow
from airflow.operators import bash_operator

YESTERDAY = datetime.datetime.now() - datetime.timedelta(days=1)

default_args = {
    'owner': 'Composer Example',
    'depends_on_past': False,
    'email': [''],
    'email_on_failure': False,
    'email_on_retry': False,
    'retries': 1,
    'retry_delay': datetime.timedelta(minutes=5),
    'start_date': YESTERDAY,
}

with airflow.DAG(
        'composer_sample_dag',
        'catchup=False',
        default_args=default_args,
        schedule_interval=datetime.timedelta(days=1)) as dag:

    # Print the dag_run id from the Airflow logs
    print_dag_run_conf = bash_operator.BashOperator(
        task_id='print_dag_run_conf', bash_command='echo {{ dag_run.id }}')

Uploading the DAG to Cloud Storage

Cloud Composer schedules only the DAGs that are in the DAGs folder in the environment's Cloud Storage bucket.

To schedule your DAG, move quickstart.py from your local machine to your environment's DAGs folder:

  1. In the GCP Console, go to the Environments page.

    Open the Environments page

  2. To open the /dags folder, click the DAGs folder link for example-environment.

  3. On the Bucket details page, click Upload files and then select your local copy of quickstart.py.

  4. To upload the file, click Open.

    After you upload your DAG, Cloud Composer adds the DAG to Airflow and schedules the DAG immediately. It might take a few minutes for the DAG to show up in the Airflow web interface.

Viewing the DAG in the Airflow web interface

Each Cloud Composer environment has a web server that runs the Airflow web interface that you can use to manage DAGs.

To view the DAG in the Airflow web interface:

  1. In the GCP Console, go to the Environments page.

    Open the Environments page

  2. To open the Airflow web interface, click the Airflow link for example-environment. The interface opens in a new browser window.

  3. In the Airflow toolbar, click DAGs.

  4. To open the DAG details page, click composer_sample_dag.

    The page for the DAG shows the Tree View, a graphical representation of the workflow's tasks and dependencies.

Viewing task instance details in the Airflow logs

The DAG that you scheduled includes the print_dag_run_conf task. The task prints the DAG run's configuration, which you can see in the Airflow logs for the task instance.

To view the task instance details:

  1. In the DAG's Tree View in the Airflow web interface, click Graph View.

    If you mouseover the graphic for the print_dag_run_conf task, its status displays. Note that the border around the task also indicates the status (light green border = running).

  2. Click print_dag_run_conf task.

    The Task Instance Context Menu displays. Here you can get metadata and perform some actions.

  3. In the Task Instance Context Menu, click View Log.

  4. In the Log, look for Running: ['bash' to see the output from the bash operator.

Clean up

To avoid incurring charges to your GCP account for the resources used in this quickstart:

  1. No Console do GCP, acesse a página "Projetos".

    Acessar a página Projetos

  2. Caso o projeto que você planeja excluir esteja vinculado a uma organização, selecione-a na lista suspensa Organização, no topo da página.
  3. Na lista de projetos, selecione um e clique em Excluir projeto.
  4. Na caixa de diálogo, digite o código do projeto e clique em Encerrar para excluí-lo.

Alternatively, you can delete the resources used in this tutorial:

  1. Delete the Cloud Composer environment.
  2. Delete the Cloud Storage bucket for the Cloud Composer environment. Deleting the Cloud Composer environment does not delete its bucket.
  3. Delete the Cloud Pub/Sub topics for the Cloud Composer environment (composer-agent and composer-backend). Deleting the Cloud Composer environment does not delete these topics.

What's next

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