Page tree

Versions Compared

Key

  • This line was added.
  • This line was removed.
  • Formatting was changed.
Comment: Published by Scroll Versions from space DEV and version next

...

This section provides an overview of sharing principles, limitations, and approaches.

Info

NOTE: You can share connections, too. See Share Connections below.

For more information on how to share a flow or send a copy of it, see Share Flow Dialog.

 

Collaborative Sharing

In the collaborative approach, two or more users can work on the same flow. When a flow is shared, all flow objects are shared, including:

  • Imported datasets

    Info

    NOTE: If a flow shared with you includes datasets with parameters, you can modify the parameters for those datasets.

  • Recipes
  • Job results
Info

NOTE: Sharing of data is managed at the flow level. You cannot share individual recipes or datasets from within a flow.

...

  • Datasets that are accessed through private connections cannot be shared.
  • Stricter permissions sets on the datastore can adversely affect users' ability to access shared flows.

 

Sharing samples: A flow's samples are not necessarily available to all users who have been shared the flow. In some cases, if a user who has been shared a flow does not have access to a recipe's sample, the user may have to collect a separate sample to view data or edit the recipe associated with the sample. To enable universal access to shared samples, you can use either of the following permissions schemes:

  1. The default output directories for any user can be accessed by any other user. This configuration must be managed in the base storage layer.
  2. When the sample is executed, an individual user must set his or her default output directory to a location that shared users of the flow can access.

...

 

  • Send Send a copy of the flow to another user

  • Send a copy of the flow to yourself

  • Remove access for yourself to the shared flow

...

Info

NOTE: If a dataset from a shared flow is referenced in another flow, when sharing access is removed from the flow, the referenced dataset is still available in the other flow.

...

Sending Copies

As needed, you can send a copy of a flow to one or more users. Each user with whom you send the flow has an independent version of the flow. Changes made in copies of flows do not affect the original flow, and vice-versa. Examples:

...

  • Flow definition
  • Recipes in the flow
  • Reference and output objects

  • The original imported dataset(s)
  • Samples

Limitations

  • When you open your flow, you must swap in imported datasets to replace any missing or inaccessible ones. See Flow View Page.

  • The source of the flow is written in the description of its copy. If that value is changed, you cannot determine through the GUI if the flow was sent or not. 
  • In the Edit History panel, all edits made prior to the flow being sent to the current user appear as a single edit.
Info

NOTE: When a flow containing parameters is copied, any changes to parameter values in the copied flow also affect parameters in the original flow.

 

Permissions

The users to whom copies are sent are owners of those copies. They have full permissions over the flow and its datasets. 

The new owner of the copied flow has full editing permissions on the recipes. They can share or send copies of the flow to other users as needed. 

Share Connections

When initially created, a connection is private. It is accessible only to the user who created. it.

...

Info

NOTE: Password values for credentials are always masked in the user interface.

...

 

For more information, see Connections Page.

...

For more information, see Flow View Page.