emr-helper 1.0.0

Library to manage AWS EMR clusters.

The EMR Helper library tries to help when setting up and managing an EMR cluster.

AWS EMR has three distinct objects:

• Cluster

• Fleet

• Step

This library collects some of the most common types of these elements and manages them at the python class level.

Dependencies

• Boto3

Classes

Step

There is a general class Step to wrap all subtypes of steps. Currently there are only CommandRunnerStep implemented to launch a Command Runner step.

You can create a step as follow:

import boto3
from emrhelper import CommandRunnerStep

step = CommandRunnerStep(
            name='StepName',
            args=process_arguments)

It can be added to a cluster before it starts (see Cluster) or append to a started cluster:

step.run_on_cluster(‘clusterID’)

If clusterID is None, step is added to any available cluster.

Fleet

The instance fleets configuration for a cluster contains instances information for computation capacity of cluster. As steps, there is a main class ‘Fleet’ and several subclasses: OnDemandFleet and SpotFleet, depending on whether you want to launch spot or on-demand instances.

You can create a fleet as follow:

from emrhelper import SpotFleet

fleet = SpotFleet(name='My Fleet', capacity=4, fleet_type='CORE')

fleet.add_instance_config(instance_type='r5d.xlarge', capacity=2)
fleet.add_instance_config(instance_type='r5d.2xlarge', capacity=4)

Cluster

You can create a cluster, add steps and fleets, and run it.

from emrhelper import Cluster

cluster = Cluster(
    name='my-cluster',
    key_pair='keypair',
    subnets='...',
    sg_master='...',
    sg_slave='...',
    sg_service='...',
    instance_profile='...',
    service_role='...',
    log_uri='...'
)

cluster.add_step(step)
cluster.add_fleet(fleet)

cluster.run_cluster()

You can add as many steps and fleets as you need.

Installation

pip install emrhelper