Creating the blueprint layout script

The blueprint layout script must include a function that generates the entities in your workflow. You can name this function whatever you like. AWS Glue uses the configuration file to determine the fully qualified name of the function.

Your layout function does the following:

• (Optional) Instantiates the Job class to create Job objects, and passes arguments such as Command and Role. These are job properties that you would specify if you were creating the job using the AWS Glue console or API.

• (Optional) Instantiates the Crawler class to create Crawler objects, and passes name, role, and target arguments.

• To indicate dependencies between the objects (workflow entities), passes the DependsOn and WaitForDependencies additional arguments to Job() and Crawler(). These arguments are explained later in this section.

• Instantiates the Workflow class to create the workflow object that is returned to AWS Glue, passing a Name argument, an Entities argument, and an optional OnSchedule argument. The Entities argument specifies all of the jobs and crawlers to include in the workflow. To see how to construct an Entities object, see the sample project later in this section.

• Returns the Workflow object.

For definitions of the Job, Crawler, and Workflow classes, see AWS Glue blueprint classes reference.

The layout function must accept the following input arguments.

Argument	Description
user_params	Python dictionary of blueprint parameter names and values. For more information, see Specifying blueprint parameters.
system_params	Python dictionary containing two properties: region and accountId.

Here is a sample layout generator script in a file named Layout.py:

import argparse
import sys
import os
import json
from awsglue.blueprint.workflow import *
from awsglue.blueprint.job import *
from awsglue.blueprint.crawler import *


def generate_layout(user_params, system_params):

    etl_job = Job(Name="{}_etl_job".format(user_params['WorkflowName']),
                  Command={
                      "Name": "glueetl",
                      "ScriptLocation": user_params['ScriptLocation'],
                      "PythonVersion": "2"
                  },
                  Role=user_params['PassRole'])
    post_process_job = Job(Name="{}_post_process".format(user_params['WorkflowName']),
                            Command={
                                "Name": "pythonshell",
                                "ScriptLocation": user_params['ScriptLocation'],
                                "PythonVersion": "2"
                            },
                            Role=user_params['PassRole'],
                            DependsOn={
                                etl_job: "SUCCEEDED"
                            },
                            WaitForDependencies="AND")
    sample_workflow = Workflow(Name=user_params['WorkflowName'],
                            Entities=Entities(Jobs=[etl_job, post_process_job]))
    return sample_workflow

The sample script imports the required blueprint libraries and includes a generate_layout function that generates a workflow with two jobs. This is a very simple script. A more complex script could employ additional logic and parameters to generate a workflow with many jobs and crawlers, or even a variable number of jobs and crawlers.

Using the DependsOn argument

The DependsOn argument is a dictionary representation of a dependency that this entity has on other entities within the workflow. It has the following form.

DependsOn = {dependency1 : state, dependency2 : state, ...}

The keys in this dictionary represent the object reference, not the name, of the entity, while the values are strings that correspond to the state to watch for. AWS Glue infers the proper triggers. For the valid states, see Condition Structure.

For example, a job might depend on the successful completion of a crawler. If you define a crawler object named crawler2 as follows:

crawler2 = Crawler(Name="my_crawler", ...)

Then an object depending on crawler2 would include a constructor argument such as:

DependsOn = {crawler2 : "SUCCEEDED"}

For example:

job1 = Job(Name="Job1", ..., DependsOn = {crawler2 : "SUCCEEDED", ...})

If DependsOn is omitted for an entity, that entity depends on the workflow start trigger.

Using the WaitForDependencies argument

The WaitForDependencies argument defines whether a job or crawler entity should wait until all entities on which it depends complete or until any completes.

The allowable values are "AND" or "ANY".

Using the OnSchedule argument

The OnSchedule argument for the Workflow class constructor is a cron expression that defines the starting trigger definition for a workflow.

If this argument is specified, AWS Glue creates a schedule trigger with the corresponding schedule. If it isn't specified, the starting trigger for the workflow is an on-demand trigger.