As we develop workflows, it is inevitable that we will need to make additional modifications downstream of our data. To see the updates, we need to run the workflow. Depending on the data, this can take a long time. Let’s be honest, even waiting a couple of minutes to re-run the workflow is too much time... Ain't nobody got time for that!
Alteryx 2018.3 is here to help, with a shiny new caching feature! With caching, you can drastically reduce the running time of a workflow. Now, you can make changes without waiting for every single tool on your canvas to re-run.
A cache is "a computer memory with very short access time, used for the storage of frequently or recently used instructions or data." In the context of an Alteryx workflow, this would be the data you're bringing into and modifying with Alteryx Designer.
There are many reasons you may want to use caching...
Some of the top questions we receive on caching are regarding how this feature works. So here’s a behind-the-scenes look!
Caching plugs into the temp file management system that is being used by Alteryx Designer for all sorts of things, including the ability to preview your results at any point of your workflow, bringing In-Database data in with the Data Stream Out tool, and of course, populating Browse tools with their data and reports. These temp files are used in-the-moment to support visualizing your data and previewing it while you build out the workflow. When the workflow is closed, or you close Alteryx Designer, these temp files are cleared out so they don't stick around and eat up space on your computer.
Here is what's going on when you click Cache and Run Workflow on the Download tool in the video above:
So, next time the workflow runs it will pick up from this temporary cache file instead of at the beginning. When you edit a tool that has been disabled in a cache, all of these changes revert and you're back to your regular workflow.
There are two rules for a tool being eligible for caching:
The reason for these limitations is really simple - to avoid accidentally caching data that you weren't expecting to cache. The last thing we want to do is crash your computer while trying to save a cache billions of records long!
For a deep dive into this limitation, check out @SydneyF's excellent article What Can't Be Cached?
That's all I got for now, so...
Special thanks to my talented colleague @MindiG, who co-authored this blog post and made the video demo.
Alex is acutely aware of all the sleep he's lost wrangling gigantic data-sets. But that's ok; now he gets to work with the Alteryx Community, spreading a new culture of analytics. Get it done quicker, automate that task, and have more time to think about the bigger picture. Also it's fun, so there's that.
Alex is acutely aware of all the sleep he's lost wrangling gigantic data-sets. But that's ok; now he gets to work with the Alteryx Community, spreading a new culture of analytics. Get it done quicker, automate that task, and have more time to think about the bigger picture. Also it's fun, so there's that.
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