Source code for airflow.providers.amazon.aws.example_dags.example_glue

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from datetime import datetime
from os import getenv

from airflow import DAG
from airflow.decorators import task
from airflow.models.baseoperator import chain
from airflow.providers.amazon.aws.hooks.s3 import S3Hook
from airflow.providers.amazon.aws.operators.glue import GlueJobOperator
from airflow.providers.amazon.aws.operators.glue_crawler import GlueCrawlerOperator
from airflow.providers.amazon.aws.sensors.glue import GlueJobSensor
from airflow.providers.amazon.aws.sensors.glue_crawler import GlueCrawlerSensor


[docs]GLUE_DATABASE_NAME = getenv('GLUE_DATABASE_NAME', 'glue_database_name')


[docs]GLUE_EXAMPLE_S3_BUCKET = getenv('GLUE_EXAMPLE_S3_BUCKET', 'glue_example_s3_bucket')


# Role needs putobject/getobject access to the above bucket as well as the glue
# service role, see docs here: https://docs.aws.amazon.com/glue/latest/dg/create-an-iam-role.html

[docs]GLUE_CRAWLER_ROLE = getenv('GLUE_CRAWLER_ROLE', 'glue_crawler_role')


[docs]GLUE_CRAWLER_NAME = 'example_crawler'


[docs]GLUE_CRAWLER_CONFIG = {
    'Name': GLUE_CRAWLER_NAME,
    'Role': GLUE_CRAWLER_ROLE,
    'DatabaseName': GLUE_DATABASE_NAME,
    'Targets': {
        'S3Targets': [
            {
                'Path': f'{GLUE_EXAMPLE_S3_BUCKET}/input',

            }
        ]
    },
}

# Example csv data used as input to the example AWS Glue Job.

[docs]EXAMPLE_CSV = '''
apple,0.5
milk,2.5
bread,4.0
'''


# Example Spark script to operate on the above sample csv data.

[docs]EXAMPLE_SCRIPT = f'''
from pyspark.context import SparkContext
from awsglue.context import GlueContext

glueContext = GlueContext(SparkContext.getOrCreate())
datasource = glueContext.create_dynamic_frame.from_catalog(
             database='{GLUE_DATABASE_NAME}', table_name='input')
print('There are %s items in the table' % datasource.count())

datasource.toDF().write.format('csv').mode("append").save('s3://{GLUE_EXAMPLE_S3_BUCKET}/output')
'''



@task(task_id='setup__upload_artifacts_to_s3')

[docs]def upload_artifacts_to_s3():
    '''Upload example CSV input data and an example Spark script to be used by the Glue Job'''
    s3_hook = S3Hook()
    s3_load_kwargs = {"replace": True, "bucket_name": GLUE_EXAMPLE_S3_BUCKET}
    s3_hook.load_string(string_data=EXAMPLE_CSV, key='input/input.csv', **s3_load_kwargs)
    s3_hook.load_string(string_data=EXAMPLE_SCRIPT, key='etl_script.py', **s3_load_kwargs)



with DAG(
    dag_id='example_glue',
    schedule_interval=None,
    start_date=datetime(2021, 1, 1),
    tags=['example'],
    catchup=False,
) as glue_dag:


[docs]    setup_upload_artifacts_to_s3 = upload_artifacts_to_s3()


    # [START howto_operator_glue_crawler]
    crawl_s3 = GlueCrawlerOperator(
        task_id='crawl_s3',
        config=GLUE_CRAWLER_CONFIG,
        wait_for_completion=False,
    )
    # [END howto_operator_glue_crawler]

    # [START howto_sensor_glue_crawler]
    wait_for_crawl = GlueCrawlerSensor(task_id='wait_for_crawl', crawler_name=GLUE_CRAWLER_NAME)
    # [END howto_sensor_glue_crawler]

    # [START howto_operator_glue]
    job_name = 'example_glue_job'
    submit_glue_job = GlueJobOperator(
        task_id='submit_glue_job',
        job_name=job_name,
        wait_for_completion=False,
        script_location=f's3://{GLUE_EXAMPLE_S3_BUCKET}/etl_script.py',
        s3_bucket=GLUE_EXAMPLE_S3_BUCKET,
        iam_role_name=GLUE_CRAWLER_ROLE.split('/')[-1],
        create_job_kwargs={'GlueVersion': '3.0', 'NumberOfWorkers': 2, 'WorkerType': 'G.1X'},
    )
    # [END howto_operator_glue]

    # [START howto_sensor_glue]
    wait_for_job = GlueJobSensor(
        task_id='wait_for_job',
        job_name=job_name,
        # Job ID extracted from previous Glue Job Operator task
        run_id=submit_glue_job.output,
    )
    # [END howto_sensor_glue]

    chain(setup_upload_artifacts_to_s3, crawl_s3, wait_for_crawl, submit_glue_job, wait_for_job)

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