Glue Data Processing

class GlueJobHook(AwsBaseHook):
    def __init__(self, job_name: str = None, desc: str = None, concurrent_run_limit: int = 1, script_location: str = None, retry_limit: int = 0, num_of_dpus: int = None, aws_conn_id: str = 'aws_default', region_name: str = None, s3_bucket: str = None, iam_role_name: str = None, create_job_kwargs: dict = None, **kwargs):
        """
        Initialize Glue Job Hook.
        
        Parameters:
        - job_name: Name of the Glue job
        - desc: Job description
        - concurrent_run_limit: Maximum concurrent runs
        - script_location: S3 location of job script
        - retry_limit: Number of retries on failure
        - num_of_dpus: Number of DPUs allocated to job
        - aws_conn_id: AWS connection ID
        - region_name: AWS region name
        - s3_bucket: S3 bucket for job artifacts
        - iam_role_name: IAM role for job execution
        - create_job_kwargs: Additional job creation parameters
        """

    def list_jobs(self) -> list:
        """
        List all Glue jobs.
        
        Returns:
        List of job names
        """

    def get_job_state(self, job_name: str, run_id: str) -> str:
        """
        Get state of specific Glue job run.
        
        Parameters:
        - job_name: Name of the Glue job
        - run_id: Job run ID
        
        Returns:
        Current job run state
        """

    def initialize_job(self, job_name: str, arguments: dict = None) -> dict:
        """
        Initialize and start Glue job.
        
        Parameters:
        - job_name: Name of the Glue job
        - arguments: Job arguments dictionary
        
        Returns:
        Job run information
        """

    def get_or_create_glue_job(self) -> str:
        """
        Get existing Glue job or create new one.
        
        Returns:
        Job name
        """

    def get_job_run(self, run_id: str, job_name: str) -> dict:
        """
        Get details of specific job run.
        
        Parameters:
        - run_id: Job run ID
        - job_name: Name of the Glue job
        
        Returns:
        Job run details
        """

class GlueCrawlerHook(AwsBaseHook):
    def __init__(self, crawler_name: str, aws_conn_id: str = 'aws_default', **kwargs):
        """
        Initialize Glue Crawler Hook.
        
        Parameters:
        - crawler_name: Name of the Glue crawler
        - aws_conn_id: AWS connection ID
        """

    def get_crawler(self, name: str) -> dict:
        """
        Get crawler configuration.
        
        Parameters:
        - name: Crawler name
        
        Returns:
        Crawler configuration and state
        """

    def start_crawler(self, name: str) -> dict:
        """
        Start Glue crawler.
        
        Parameters:
        - name: Crawler name
        
        Returns:
        Start crawler response
        """

    def stop_crawler(self, name: str) -> dict:
        """
        Stop running crawler.
        
        Parameters:
        - name: Crawler name
        
        Returns:
        Stop crawler response
        """

    def get_crawler_metrics(self, crawler_names: list = None) -> dict:
        """
        Get crawler metrics.
        
        Parameters:
        - crawler_names: List of crawler names
        
        Returns:
        Crawler metrics
        """

class GlueJobOperator(BaseOperator):
    def __init__(self, job_name: str = 'aws_glue_default_job', job_desc: str = 'AWS Glue Job with Airflow', script_location: str = None, concurrent_run_limit: int = 1, script_args: dict = None, retry_limit: int = 0, num_of_dpus: int = 10, aws_conn_id: str = 'aws_default', region_name: str = None, s3_bucket: str = None, iam_role_name: str = None, create_job_kwargs: dict = None, **kwargs):
        """
        Execute AWS Glue job.
        
        Parameters:
        - job_name: Name of the Glue job
        - job_desc: Job description
        - script_location: S3 location of job script
        - concurrent_run_limit: Maximum concurrent runs
        - script_args: Arguments passed to the job script
        - retry_limit: Number of retries on failure
        - num_of_dpus: Number of DPUs allocated to job
        - aws_conn_id: AWS connection ID
        - region_name: AWS region name
        - s3_bucket: S3 bucket for job artifacts
        - iam_role_name: IAM role for job execution
        - create_job_kwargs: Additional job creation parameters
        """

class GlueCrawlerOperator(BaseOperator):
    def __init__(self, crawler_name: str, aws_conn_id: str = 'aws_default', poll_interval: int = 5, **kwargs):
        """
        Run AWS Glue crawler.
        
        Parameters:
        - crawler_name: Name of the Glue crawler
        - aws_conn_id: AWS connection ID
        - poll_interval: Polling interval in seconds
        """

class GlueJobSensor(BaseSensorOperator):
    def __init__(self, job_name: str, run_id: str, aws_conn_id: str = 'aws_default', **kwargs):
        """
        Wait for Glue job completion.
        
        Parameters:
        - job_name: Name of the Glue job
        - run_id: Job run ID to monitor
        - aws_conn_id: AWS connection ID
        """

class GlueCrawlerSensor(BaseSensorOperator):
    def __init__(self, crawler_name: str, aws_conn_id: str = 'aws_default', **kwargs):
        """
        Wait for Glue crawler completion.
        
        Parameters:
        - crawler_name: Name of the Glue crawler
        - aws_conn_id: AWS connection ID
        """

class GlueJobTrigger(BaseTrigger):
    def __init__(self, job_name: str, run_id: str, aws_conn_id: str = 'aws_default', poll_interval: int = 60, **kwargs):
        """
        Asynchronous trigger for Glue job monitoring.
        
        Parameters:
        - job_name: Name of the Glue job
        - run_id: Job run ID to monitor
        - aws_conn_id: AWS connection ID
        - poll_interval: Polling interval in seconds
        """

from airflow import DAG
from airflow.providers.amazon.aws.operators.glue import GlueJobOperator
from airflow.providers.amazon.aws.sensors.glue import GlueJobSensor

dag = DAG('glue_etl_job', start_date=datetime(2023, 1, 1))

# Run Glue ETL job
run_glue_job = GlueJobOperator(
    task_id='run_etl_job',
    job_name='customer-data-processing',
    script_location='s3://my-glue-scripts/customer_etl.py',
    script_args={
        '--input_path': 's3://raw-data/customers/{{ ds }}/',
        '--output_path': 's3://processed-data/customers/{{ ds }}/',
        '--database_name': 'analytics_db',
        '--table_name': 'customer_dim'
    },
    retry_limit=2,
    num_of_dpus=10,
    aws_conn_id='aws_default',
    dag=dag
)

from airflow.providers.amazon.aws.operators.glue import GlueCrawlerOperator
from airflow.providers.amazon.aws.sensors.glue import GlueCrawlerSensor

# Run crawler to discover new data
discover_data = GlueCrawlerOperator(
    task_id='discover_new_data',
    crawler_name='s3-data-crawler',
    aws_conn_id='aws_default',
    dag=dag
)

# Wait for crawler completion
wait_for_crawler = GlueCrawlerSensor(
    task_id='wait_for_discovery',
    crawler_name='s3-data-crawler',
    timeout=1800,  # 30 minutes
    dag=dag
)

discover_data >> wait_for_crawler

from airflow.providers.amazon.aws.operators.glue_databrew import GlueDataBrewStartJobRunOperator

# Data preparation with DataBrew
prepare_data = GlueDataBrewStartJobRunOperator(
    task_id='prepare_customer_data',
    job_name='customer-data-preparation',
    aws_conn_id='aws_default',
    dag=dag
)

# Process prepared data with Glue job
process_data = GlueJobOperator(
    task_id='process_prepared_data',
    job_name='customer-analytics-job',
    script_location='s3://my-glue-scripts/analytics.py',
    script_args={
        '--input_path': 's3://prepared-data/customers/{{ ds }}/',
        '--output_path': 's3://analytics-data/customers/{{ ds }}/'
    },
    dag=dag
)

prepare_data >> process_data

# Glue job states
class GlueJobState:
    STARTING = 'STARTING'
    RUNNING = 'RUNNING'
    STOPPING = 'STOPPING'
    STOPPED = 'STOPPED'
    SUCCEEDED = 'SUCCEEDED'
    FAILED = 'FAILED'
    TIMEOUT = 'TIMEOUT'

# Glue crawler states
class GlueCrawlerState:
    READY = 'READY'
    RUNNING = 'RUNNING'
    STOPPING = 'STOPPING'

# Glue job configuration
class GlueJobConfig:
    name: str
    description: str
    role: str
    command: dict
    default_arguments: dict = None
    connections: dict = None
    max_retries: int = 0
    allocated_capacity: int = None
    timeout: int = None
    max_capacity: float = None
    security_configuration: str = None
    tags: dict = None
    notification_property: dict = None
    glue_version: str = None
    number_of_workers: int = None
    worker_type: str = None
    code_gen_configuration_nodes: dict = None

# Glue crawler configuration
class GlueCrawlerConfig:
    name: str
    role: str
    database_name: str
    targets: dict
    description: str = None
    classifiers: list = None
    table_prefix: str = None
    schema_change_policy: dict = None
    recrawl_policy: dict = None
    lineage_configuration: dict = None
    lake_formation_configuration: dict = None
    configuration: str = None
    crawler_security_configuration: str = None
    tags: dict = None

# Worker types for Glue 2.0+
class GlueWorkerType:
    STANDARD = 'Standard'
    G_1X = 'G.1X'
    G_2X = 'G.2X'
    G_025X = 'G.025X'

# Glue versions
class GlueVersion:
    VERSION_1_0 = '1.0'
    VERSION_2_0 = '2.0'
    VERSION_3_0 = '3.0'
    VERSION_4_0 = '4.0'