Intro
Adrenaline DataFlows is an in-house built, high-scale, and high-performance data transformation tool for massive DataSets in Domo powered by the Adrenaline engine. It uses a SQL script-based transformation interface, similar to MySQL DataFlows. Adrenaline DataFlows allow you to rapidly summarize and aggregate massive DataSets into smaller, more performant outputs. Adrenaline DataFlows can deliver high-performance by leveraging architectural investments and performance improvements made to the Domo Adrenaline engine over time. We recommend Adrenaline DataFlows for the following use cases:- Building high-performance dashboards from massive DataSets. Instead of directly building cards off such large DataSets, we recommend using Adrenaline DataFlows to create summarized and aggregated smaller outputs which can then be used to power fast, high-performance dashboards. For cases where access to the full data is needed, we recommend setting up Drill Paths to the original DataSet from the visualizations built from the summarized DataFlow outputs. Learn about Drill Paths.
- Data transformations that require scanning the entire length of massive DataSets, for example, COUNT DISTINCT, SUM, and other aggregate operations.
Note:
Domo does not recommend using Adrenaline DataFlows for row-by-row transformations, where DataFlow outputs have similar row counts as input DataSets.
Note:
Adrenaline DataFlows is available by default for users on the Domo Consumption agreement.For non-consumption users, Adrenaline DataFlows is available
on demand
and
paid.To enable Adrenaline DataFlows, contact your Domo account team. You may need to complete training before you can use the feature.
Create an Adrenaline DataFlow
- In the navigation header, go to Data.
- From the rail, select DataFlows.
- In the Magic Transform menu, select SQL.
- From the options, choose Adrenaline.
- Enter a DataFlow Name & Description, select DataSets, Transforms, and Output DataSets.
- After selecting DataSets, click Choose DataSet. You can also Create New DataSets.
- To remove a DataSet from the flow, select the
and choose Delete. - After entering SQL for transforms and output DataSets, select Apply.
FAQs
At what input DataSet sizes should I consider Adrenaline Transformations versus other DataFlows?
At what input DataSet sizes should I consider Adrenaline Transformations versus other DataFlows?
We recommend using Adrenaline DataFlows when you want to operate with massive input DataSets, even in the Billions of rows of input data.
Are there any limits on executions for Adrenaline DataFlows?
Are there any limits on executions for Adrenaline DataFlows?
Yes, by default Adrenaline DataFlow executions are capped to a 30-min timeout. If your DataFlow is timing out, please review your dataflow transformations to remove joins on string data, filter to only the required data, and reduce the complexity of each transform. If your DataFlow requires additional time to complete, we can extend timeouts on a case-by-case basis. Please reach out via Support to increase execution time for your specific use case.
Are Adrenaline DataFlows available by default?
Are Adrenaline DataFlows available by default?
Adrenaline DataFlows are a Premium feature. Please reach out to your Domo account team to learn more about pricing plans, including a limited free trial to test out your use cases.
How do I track Adrenaline DataFlows usage?
How do I track Adrenaline DataFlows usage?
DomoStats for DataFlows will provide DataFlow execution stats for Adrenaline DataFlows.
How do I control access to Adrenaline DataFlows in my Domo instance?
How do I control access to Adrenaline DataFlows in my Domo instance?
You must either be an Admin or have a role with the “Edit Adrenaline DataFlow” grant enabled. For more information about roles and grants, see Managing Custom Roles.
Why isn’t my data sorted correctly when I preview in the designer?
Why isn’t my data sorted correctly when I preview in the designer?
In the designer, your data is optimized for rapid previewing so sorting is not applied. However, your data will be correctly sorted when your DataFlow executes.