airflow.providers.amazon.aws.hooks.emr

Classes

EmrHook

Interact with Amazon Elastic MapReduce Service (EMR).

EmrServerlessHook

Interact with Amazon EMR Serverless.

EmrContainerHook

Interact with Amazon EMR Containers (Amazon EMR on EKS).

Functions

is_connection_being_updated_exception(exception)

Module Contents

class airflow.providers.amazon.aws.hooks.emr.EmrHook(emr_conn_id=default_conn_name, *args, **kwargs)[source]

Bases: airflow.providers.amazon.aws.hooks.base_aws.AwsBaseHook

Interact with Amazon Elastic MapReduce Service (EMR).

Provide thick wrapper around boto3.client("emr").

Parameters:

emr_conn_id (str | None) – Amazon Elastic MapReduce Connection. This attribute is only necessary when using the airflow.providers.amazon.aws.hooks.emr.EmrHook.create_job_flow().

Additional arguments (such as aws_conn_id) may be specified and are passed down to the underlying AwsBaseHook.

See also

AwsBaseHook

conn_name_attr = 'emr_conn_id'[source]
default_conn_name = 'emr_default'[source]
conn_type = 'emr'[source]
hook_name = 'Amazon Elastic MapReduce'[source]
emr_conn_id = 'emr_default'[source]
get_cluster_id_by_name(emr_cluster_name, cluster_states)[source]

Fetch id of EMR cluster with given name and (optional) states; returns only if single id is found.

See also

Parameters:

  • emr_cluster_name (str) – Name of a cluster to find

  • cluster_states (list[str]) – State(s) of cluster to find

Returns:

id of the EMR cluster

Return type:

str | None

create_job_flow(job_flow_overrides)[source]

Create and start running a new cluster (job flow).

See also

This method uses EmrHook.emr_conn_id to receive the initial Amazon EMR cluster configuration. If EmrHook.emr_conn_id is empty or the connection does not exist, then an empty initial configuration is used.

Parameters:

job_flow_overrides (dict[str, Any]) – Is used to overwrite the parameters in the initial Amazon EMR configuration cluster. The resulting configuration will be used in the EMR.Client.run_job_flow().

See also

add_job_flow_steps(job_flow_id, steps=None, wait_for_completion=False, waiter_delay=None, waiter_max_attempts=None, execution_role_arn=None)[source]

Add new steps to a running cluster.

See also

Parameters:

  • job_flow_id (str) – The id of the job flow to which the steps are being added

  • steps (list[dict] | str | None) – A list of the steps to be executed by the job flow

  • wait_for_completion (bool) – If True, wait for the steps to be completed. Default is False

  • waiter_delay (int | None) – The amount of time in seconds to wait between attempts. Default is 5

  • waiter_max_attempts (int | None) – The maximum number of attempts to be made. Default is 100

  • execution_role_arn (str | None) – The ARN of the runtime role for a step on the cluster.

test_connection()[source]

Return failed state for test Amazon Elastic MapReduce Connection (untestable).

We need to overwrite this method because this hook is based on AwsGenericHook, otherwise it will try to test connection to AWS STS by using the default boto3 credential strategy.

classmethod get_ui_field_behaviour()[source]

Return custom UI field behaviour for Amazon Elastic MapReduce Connection.

class airflow.providers.amazon.aws.hooks.emr.EmrServerlessHook(*args, **kwargs)[source]

Bases: airflow.providers.amazon.aws.hooks.base_aws.AwsBaseHook

Interact with Amazon EMR Serverless.

Provide thin wrapper around boto3.client("emr-serverless").

Additional arguments (such as aws_conn_id) may be specified and are passed down to the underlying AwsBaseHook.

See also

JOB_INTERMEDIATE_STATES[source]
JOB_FAILURE_STATES[source]
JOB_SUCCESS_STATES[source]
JOB_TERMINAL_STATES[source]
APPLICATION_INTERMEDIATE_STATES[source]
APPLICATION_FAILURE_STATES[source]
APPLICATION_SUCCESS_STATES[source]
cancel_running_jobs(application_id, waiter_config=None, wait_for_completion=True)[source]

Cancel jobs in an intermediate state, and return the number of cancelled jobs.

If wait_for_completion is True, then the method will wait until all jobs are cancelled before returning.

Note: if new jobs are triggered while this operation is ongoing, it’s going to time out and return an error.

airflow.providers.amazon.aws.hooks.emr.is_connection_being_updated_exception(exception)[source]
class airflow.providers.amazon.aws.hooks.emr.EmrContainerHook(*args, virtual_cluster_id=None, **kwargs)[source]

Bases: airflow.providers.amazon.aws.hooks.base_aws.AwsBaseHook

Interact with Amazon EMR Containers (Amazon EMR on EKS).

Provide thick wrapper around boto3.client("emr-containers").

Parameters:

virtual_cluster_id (str | None) – Cluster ID of the EMR on EKS virtual cluster

Additional arguments (such as aws_conn_id) may be specified and are passed down to the underlying AwsBaseHook.

See also

INTERMEDIATE_STATES = ('PENDING', 'SUBMITTED', 'RUNNING')[source]
FAILURE_STATES = ('FAILED', 'CANCELLED', 'CANCEL_PENDING')[source]
SUCCESS_STATES = ('COMPLETED',)[source]
TERMINAL_STATES = ('COMPLETED', 'FAILED', 'CANCELLED', 'CANCEL_PENDING')[source]
virtual_cluster_id = None[source]
create_emr_on_eks_cluster(virtual_cluster_name, eks_cluster_name, eks_namespace, tags=None)[source]
submit_job(name, execution_role_arn, release_label, job_driver, configuration_overrides=None, client_request_token=None, tags=None, retry_max_attempts=None)[source]

Submit a job to the EMR Containers API and return the job ID.

A job run is a unit of work, such as a Spark jar, PySpark script, or SparkSQL query, that you submit to Amazon EMR on EKS.

See also

Parameters:

  • name (str) – The name of the job run.

  • execution_role_arn (str) – The IAM role ARN associated with the job run.

  • release_label (str) – The Amazon EMR release version to use for the job run.

  • job_driver (dict) – Job configuration details, e.g. the Spark job parameters.

  • configuration_overrides (dict | None) – The configuration overrides for the job run, specifically either application configuration or monitoring configuration.

  • client_request_token (str | None) – The client idempotency token of the job run request. Use this if you want to specify a unique ID to prevent two jobs from getting started.

  • tags (dict | None) – The tags assigned to job runs.

  • retry_max_attempts (int | None) – The maximum number of attempts on the job’s driver.

Returns:

The ID of the job run request.

Return type:

str

get_job_failure_reason(job_id)[source]

Fetch the reason for a job failure (e.g. error message). Returns None or reason string.

See also

Parameters:

job_id (str) – The ID of the job run request.

check_query_status(job_id)[source]

Fetch the status of submitted job run. Returns None or one of valid query states.

See also

Parameters:

job_id (str) – The ID of the job run request.

poll_query_status(job_id, poll_interval=30, max_polling_attempts=None)[source]

Poll the status of submitted job run until query state reaches final state; returns the final state.

Parameters:

  • job_id (str) – The ID of the job run request.

  • poll_interval (int) – Time (in seconds) to wait between calls to check query status on EMR

  • max_polling_attempts (int | None) – Number of times to poll for query state before function exits

stop_query(job_id)[source]

Cancel the submitted job_run.

See also

Parameters:

job_id (str) – The ID of the job run to cancel.

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