Through the Flow View page, you can access and manage all objects in your flow. For each imported dataset, recipe, or other object in your flow, you can perform a variety of actions to effectively manage flow development and job execution through a single page.
If you have enabled deployment management, avoid making changes in Flow View on a Production instance of the platform.
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NOTE: If the displayed flow has been shared with you, some options are not available. |
Flow View page |
The imported datasets in the flow or reference datasets added to the flow are listed on the left side of the screen. Associated with each dataset can be one or more recipes, which are used to transform the source data.
NOTE: Objects marked with a red dot indicate a problem with the object's configuration. Please select the object to begin investigating the error. Error information may be displayed in the right panel. |
Datasets:
For any object, any objects on which it depends are displayed to the left of the object on one of the flowing lines leading from it.
Tip: When you run a job for a recipe, all of the recipes steps for the preceding datasets are executed as part of the job, and only the results of the terminal dataset are generated. |
In the above example, the POS-01
recipe is dependent on all of the objects in the flow.
The other datasets have been integrated with the POS-01
dataset and have not yet had a recipe created for them.
Recipes:
A recipe is a set of steps to transform source data into the results you desire.
For more information on these objects, see Object Overview.
Select an object from your flow to open an object-specific panel on the right side of the screen.
Tip: You can right-click any object in Flow View to see the list of available actions that appear when you select it and choose from the right panel. |
Tip: Double-click any recipe to edit it. See Transformer Page. |
Actions:
Rename: Select the name of the object to rename it within the platform. This rename does not apply to the source of the object, if it exists elsewhere.
Add Datasets: Add new datasets to the flow. Details are below.
Add Schedule: To add a scheduled execution of the recipes in your flow:
Share: Collaborate with others on the same flow.
You can also send a copy to other users for separate work.
NOTE: When a flow containing one or more connections is shared, its connections are also shared. By default, credentials are included. If the sharing of credentials has been disabled, the new users must provide their own credentials for the shared connection. See Configure Sharing. |
See Share Flow Dialog.
When a user is given access to a flow, all of the following actions are available to that user, except for editing details and deleting the flow.
Make a copy: Create a copy of the flow.NOTE: The copied flow is independent of the source flow, but the original source datasets are connected. |
Export: (Available to flow owner only) Export the flow for archive or transfer. For more information, see Export Flow.
Edit name and description: (Available to flow owner only) Change the name and description of the flow.
Delete: (Available to flow owner only) Delete the flow.
Deleting a flow removes all recipes that are contained in the flow. If copies of these objects exist in other flows, they are not touched. Imported datasets are not deleted by this action. |
From the Flow View page, you can add imported or reference datasets to your flow. These datasets are added as independent objects in the flow and can be joined, unioned, or referenced by other datasets in the flow.
Add datasets to current flow |
The dataset is added as a new object in flow view.
When you select an imported dataset, you can preview the data contained in it, replace the source object, and more from the right-side panel.
Imported Dataset view |
Key Fields:
Data Preview: In the Data Preview window, you can see a small section of the data that is contained in the imported dataset. This window can be useful for verifying that you are looking at the proper data.
Tip: Click the preview to open a larger dialog, where you can select and copy data. |
Location: Path to the location of the imported dataset.
enabled
- Data types have been applied to the dataset during import.disabled
- Data types were not globally applied to the dataset during import. However, some columns may have had overrides applied to them during the import process. See Import Data Page.For more information, see Configure Type Inference.
ConnectionName: If the data is accessed through a connection, you can click this link to review connection details in the right-side panel. See View for Connections below.
Actions:
Edit parameters: If your dataset contains parameters, you can change the parameters and their default values.
All dependent flows, outputs, and references are not removed from the flow. You can replace the source for these objects as needed.
NOTE: References to the deleted dataset in other flows remain broken until the dataset is replaced. |
Flow View for any flow containing a dataset with parameters has some variations.
In addition to the standard view of your flow, the Parameters panel contains information about the parameters that are applied to datasets in the flow.
Parameters Panel in Flow View |
Variable Overrides:
The above information is useful for reviewing parameters and specifying overrides at execution time.
For each variable, the default variable value or, if one is specified, the overriding value, is applied. A variable can have an empty value.
Variables are applied whenever:
a sample is collected
Tip: You can also apply variable override values when generating a new sample. See Samples Panel. |
To change the value that is applied when a job is executed, you can:
Hover over the entry for a specific variable. Click Edit and set the override value.
Tip: You can always revert to using the default value. |
When you select a dataset with parameters in Flow View, you can review the parameters that have been specified for the selected dataset in the right panel.
Parameters tab in Flow View |
Actions:
For each recipe, you can review or edit its steps or create new recipes altogether. You can also create references to the recipe, modify outputs, and create new recipes off of the recipe.
When you select a recipe:
Recipe view |
Actions:
Assign Target to Recipe: Create a target and assign it to this recipe. For more information, see Create Target.
Remove Target: Remove the currently assigned target from this recipe.
Change input: Change the input dataset associated with the recipe.
NOTE: This action substitutes only the primary input from a recipe, which does not include any datasets that are integrated from joins, unions, lookups, or other multi-dataset options. |
Tip: You can swap in dynamic datasets for static datasets, if needed.This feature may not be enabled in your environment. See Miscellaneous Configuration. |
Delete: Delete the recipe.
Tip: When a recipe is deleted, all samples associated with the recipe are also removed, which may significantly reduce the total volume of storage you are using. |
This step cannot be undone. |
Preview the first steps in the recipe.
Key Fields:
Preview the data as reflected by the recipe.
NOTE: To render this data preview, some of the data must be loaded, and all steps in the recipe must be executed to generate the preview. Some delays may be expected. |
Key Fields:
When a target has been assigned for this recipe, you can review its schema information in the Target tab. This tab appears only after a target has been assigned to the recipe.
To remove the current target, select Remove Target from the context menu.
Columns:
Associated with each recipe is one or more outputs, which are publishing destinations. Through outputs, you can execute and track jobs for the related recipe.
The Destinations tab contains all configured destinations associated with the recipe.
Scheduled destinations are populated whenever the flow's schedule is triggered and the destination's recipe is successfully executed.
Destinations tab |
Key Fields:
Environment: The running environment where the job is configured to be executed.
yes
.For more information, see Run Job Page .
Scheduled destinations:
If a schedule has been defined for the flow, these destinations are populated with results whenever the schedule is triggered and the associated recipe is successfully executed. If any input datasets are missing, the job is not run.
NOTE: Flow collaborators cannot modify publishing destinations. |
For more information, see Overview of Scheduling.
Actions:
Run Job: Click Run Job to queue for immediate execution a job for the manual destinations. You can track the progress and results of this task through the Jobs tab.
Removing an output does not remove the jobs associated with the output. You can continue working with those executed jobs.
See Jobs Page.
Edit: Click this link to modify the selected destination's properties.
Jobs tab |
Each entry in the Jobs tab identifies a job that has been queued for execution. You can track the progress, success, or failure of execution. When a job has finished execution you can review the results. Click the link to the job.
For more information, see Job Results Page.
Actions:
View Results: Click to view the results of your completed job.
For more information, see Job Results Page.
Export dependencies as Flow: For any job, you can export a snapshot of the flow, including all dependencies required to generate the job. This export can be useful for recording the state of the flow for job runs.
NOTE: An administrator may need to enable this feature in your environment. For more information, see Miscellaneous Configuration. |
Export Results: Click to export or publish the results from your completed job.
For more information, see Export Results Window.
Delete job: Delete the job from the platform.
Deleting a job cannot be undone. |
NOTE: This feature may not be enabled in your instance of the platform. For more information, please contact your |
Download Logs: Download the logs for the job. If the job is in progress, log information is likely to be incomplete.
When you select a recipe, you can choose to create a reference dataset off of that recipe. A reference dataset is a dataset that is a reference to the output generated from a recipe contained in another flow. Whenever the upstream recipe and its output data are changed, the results are automatically inherited through the reference to the reference dataset.
NOTE: You cannot select or use a reference dataset until a reference has been created in the source flow from the recipe to use. |
To create a reference dataset from a recipe, click the Paper Clip icon. The following options appear in the right panel.
Reference view |
Key Fields:
Actions:
Delete Reference Dataset: Remove the reference dataset from the flow.
Deleting a reference dataset in the source flow causes all references to it to be broken in the flows where it is referenced. These broken references should be fixed by swapping in new sources. |
A raw dataset is an imported dataset that does not contain any initial parsing steps. All parsing steps must be added through recipes that are applied to the dataset.
Tip: You can remove initial parsing during import or through the context menu for an imported dataset. See Initial Parsing Steps. |
Raw Dataset view |
Key Fields:
Data Preview: In the Data Preview window, you can see a small section of the data that is contained in the imported dataset. This window can be useful for verifying that you are looking at the proper data.
Tip: Click the preview to open a larger dialog, where you can select and copy data. |
Actions:
For flows that require connections to source data, you can review the details of the connection, whether you created it or it was shared with you.
Connections view |
Key Fields:
Private
- Connection is available for use only for specified users of the platform.Public
- Connection is available for all users.For more information, see Share Connection Window.
Actions:
Edit Connection: Select to modify the connection.
NOTE: For shared connections, you may only modify the username and password if they were not provided to you. All other fields are read-only. |
Share...: Click to share the connection with other users.
NOTE: You can share connections that have been shared with you. You cannot make these connections public or modify their properties. |
A reference dataset is a reference to a recipe's outputs that has been added to a flow other than the one where the recipe is located.
NOTE: A reference dataset is a read-only object in the flow where it is referenced. You cannot select or use a reference dataset until a reference has been created in the source flow from the recipe to use. See View for Recipes above. |
To add a reference dataset, you can:
View for referenced dataset in a new flow |
NOTE: Reference datasets marked with a red dot no longer have a source dataset for them in the other flow. These upstream dependencies should be fixed. See Fix Dependency Issues. |
When you select a reference dataset in flow view, the following are available in the right-hand panel.
Key Fields:
Actions: