[EDP] Add Spark Shell Action job type

[EDP] Add Spark Shell Action job type


The EDP Shell action job type allows users to run arbitrary shell scripts on their cluster, providing a great deal of flexibility to extend EDP functionality without engine changes or direct cluster interface. This specification proposes the addition of this job type for the Spark engine.

A fuller explication of the benefits of this feature can be found in the edp-add-oozie-shell-action specification, which need not be repeated here.

Problem description

While the Oozie engine now supports Shell actions, Spark users do not presently have access to this job type. Its addition would allow the creation of cluster maintenance tools, pre- or post-processing jobs which might be cumbersome to implement in Spark itself, the retrieval of data from filesystems not supported as Sahara data sources, or any other use case possible from a shell command.

Proposed change

From an interface standpoint, the Spark Shell action implementation will follow the Oozie Shell action implementation almost precisely:

  • Shell jobs will require a single script binary in mains, which will be pushed to the cluster’s master node and executed.
  • Shell jobs will optionally permit any number of file binaries to be passed as libs, which will be placed in the script’s working directory and may be used by the script as it executes.
  • configs will be permitted to allow Sahara EDP-internal features (substitute_data_source_for_uuid and subsitute_data_source_for_name will be implemented for this job type, as they are for Oozie Shell actions.)
  • params key-value pairs will be passed to the script as environment variables (whether these are passed into a remote ssh client or injected into the script itself is left to the discretion of the implementer.)
  • args will be passed to the script as positional command-line arguments.
  • The Shell engine for Spark will store files as the main Spark engine does, creating a directory under /tmp/spark-edp/job_name/job_execution_id, which will contain all required files and the output of the execution.
  • The Spark Shell engine will reuse the launch_command.py script (as used by the main Spark engine at this time,) which will record childpid, stdout, and stderr from the subprocess for record-keeping purposes.

Spark Shell actions will differ in implementation from Oozie Shell actions in the following ways:

  • As Spark jobs and Shell actions which happen to be running on a Spark cluster differ quite entirely, the Spark plugin will be modified to contain two separate engines (provided via an extensible strategy pattern based on job type.) Sensible abstraction of these engines is left to the discretion of the implementer.
  • configs values which are not EDP-internal will not be passed to the script by any means (as there is no intermediary engine to act on them.)
  • Spark Shell actions will be run as the image’s registered user, as Spark jobs are themselves. As cluster and VM maintenance tasks are part of the intended use case of this feature, allowing sudo access to the VMs is desirable.


Do nothing.

Data model impact


REST API impact

No additional changes after merge of the Oozie Shell action job type implementation.

Other end user impact


Deployer impact


Developer impact


Sahara-image-elements impact


Sahara-dashboard / Horizon impact

No additional changes after merge of the Shell action job type UI implementation.



Primary assignee:
Other contributors:

Work Items

  • Add a Shell engine to the Spark plugin, and refactor this plugin to provide an appropriate engine branching on job type.
  • Add an integration test for Spark Shell jobs (as per previous plugin- specific Shell job tests).
  • Update the EDP documentation to specify that the Spark plugin supports the Shell job type.
  • Verify that the UI changes made for Oozie Shell jobs are sufficient to support the Shell job type in the Spark case (as is anticipated).


This change builds on the change [EDP] Add Oozie Shell Job Type.


  • Unit tests to cover the Spark Shell engine and appropriate engine selection within the plugin.
  • One integration test to cover running of a simple shell job through the Spark plugin.

Documentation Impact

The EDP sections of the documentation need to be updated.



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